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10th annual World Medical Innovation Forum (WMIF) Monday, Sept. 23–Wednesday, Sept. 25 at the Encore Boston Harbor in Boston

Dr. Aviva Lev-Ari, PhD, RN, Founder

Leaders in Pharmaceutical Business Intelligence Group, LLC, Doing Business As LPBI Group, Newton, MA

will be in attendance

covering this event in REAL TIME for PharmaceuticalIntelligence.com and WMIF organizers

#WMIF2024

@Pharma_BI

@AVIVA1950

CLAIMER: Live coverage in REAL TIME on X.com for 9/23/2024

my two X.com accounts had exceeded tweeting volume capacity and were inactivated to verify if I am a person or a BOT. Account authentication reported SOmething went wrong, try later.

  • 9/23/2024 contacted Customer Services at X.com for reactivated these two accounts

 

For Speaker’s quotes on 9/23/2024 from 4PM EST to end on the day

  • see below on WordPress.com by Date, Time, Session Name and Speaker Name

For Speaker’s quotes on 9/24/2024 from 8AM to 5:30PM

  • see below on WordPress.com by Date, Time, Session Name and Speaker Name

For Speaker’s quotes on 9/25/2024 from 8AM to 12:35PM

  • see below on WordPress.com by Date, Time, Session Name and Speaker Name

UPDATE on reactivation of handles on X.com will be posted, here.

Usage of X.com will resume after Handle reactivation by X.com

 

UPDATED on 9/26/2024

Unmet Needs Panel

https://www.youtube.com/watch?v=e6hk7yavBzk

100+ Mass General Brigham Leading Experts Identify

Top Unmet Needs in Healthcare

Project from Harvard Medical School-affiliated clinicians and scientists in the Mass General Brigham healthcare system stimulates new consideration, urgency regarding

innovation in life sciences, healthcare

Top 10 List Announced at World Medical Innovation Forum

BOSTON, MA September 25, 2024 – Some of the most vexing challenges and transformational opportunities in healthcare are included in a new list, “Top Unmet Needs in Healthcare” released by leading experts at Mass General Brigham. Identified by more than 100 Harvard Medical School faculty at Mass General Brigham, the findings range from the need to expand and accelerate rare disease treatment, to the coming “gray tsunami” of aging patients and the implications for patient care, delivery, and technology. The project, revealed at the 10th annual World Medical Innovation Forum, is meant to stimulate new consideration and urgency regarding solving and advancing these issues for improved patient care.

Views from Leading Clinicians, Researchers, and Practitioners in Academic Medicine

The Top Unmet Needs emerge from structured one-on-one discussions with more than 100 Harvard faculty who practice medicine and conduct research at Mass General Brigham, the largest hospital system-based research enterprise in the U.S., with an annual research budget exceeding $2 billion, and five of the nation’s top hospitals according to US News & World Report.

Through one-on-one discussions with these key opinion leaders from diverse clinical and research fields, and subsequent analyses by internal teams of experts, Mass General Brigham has identified the following top 10 unmet clinical needs:

#1. Preparing for the ‘Gray Tsunami’

The need for better tools and therapies aimed at caring for geriatric populations and maintaining geriatric independence, with a particular focus on expanded hospital-at-home capabilities, and the need to better understand the pathways that lead to chronic and acute disease in geriatric patients to enable better and more proactive treatment.

#2. Defining and Maintaining Brain Health

The need for a model of brain health and neurological care that clearly defines not only what brain health is but also integrates our current understanding of the mechanisms and phases of neuroinflammatory and neurodegenerative diseases; enables better and earlier diagnoses and treatment; and propels the development of therapies that target these mechanisms and phases.

#3. A Paradigm Shift in Cancer Treatment

The need for a new framework for therapeutic development in cancer that is focused on improving curability as opposed to an exclusive focus on the development of drugs for metastatic disease. This

framework also requires effective tools for early-stage cancer detection across the board in all cancers, but especially in lung, ovarian, pancreatic, and GI cancers (esophagus, stomach and colon).

#4. Targeting Fibrosis, a Shared Culprit in Disease

The need for therapeutics that target fibrosis (tissue scarring), which is responsible for a significant percentage of deaths worldwide, representing diseases of the lung, liver, kidney, heart, and skin.

#5. New Approaches for Infectious Disease in a Changing World

The need for novel strategies for the rapid diagnoses, treatment, and even prevention of antibiotic-resistant infections, and the need for the next generation of globally deployable vaccines to enable pandemic preparedness.

#6. Striving for Equity in Healthcare

The need to radically rethink how, when, and where patients interact with healthcare services to optimize healthcare access and efficiency without diminishing its effectiveness, and to proactively meet the needs of currently underserved populations.

#7. Riding the Wave of Clinical Data

The need to expand the scope of available clinical data to include historically understudied populations (including women) and to model and implement a cohesive, dynamic data “stream,” which flows as patients do between the different phases of health and clinical care, enabling comparisons of patients to their previously healthy selves and the development of AI/ML approaches to harness these data to improve diagnosis, prognosis, and treatment.

#8. A Systems-Level View of Human Disease

The need to rethink how we understand and treat disease — not only from an organ-specific standpoint but from a whole-body, systems-level view — and to fully elucidate the roles that inflammation and immune pathways play in autoimmune and infectious diseases and their effects on chronic and acute diseases in diverse human systems, such as the cardiovascular/circulatory and nervous systems.

#9. A New Approach to Psychiatric Disease

The need for novel treatments for psychiatric disease, improved biomarkers and minimally invasive and ambulatory ways of measuring them, and more productive interactions with industry to advance new therapies to the clinic. This includes hybrid therapies (therapies that combine elements such as talk therapy, novel biomarkers, and pharmacological treatments) as well as new diagnostic and treatment modalities, such as psychedelic therapeutics and precision psychiatry.

#10. Charting a Course in Rare Disease Treatment

The need for viable treatments for the 7,000 identified rare diseases, especially the roughly 70% of such diseases that are genetic and the effects of which are first observed in early childhood.

The Unmet Needs list also include the following honorable mentions which rose to significant rankings in the analysis:

  • Driving Innovation in Chronic Disease: Improved Diagnosis, Treatment, and Prevention
  • A New Era of Obesity Medicine
  • A New Generation of Pain Treatments
  • Unlocking Novel Treatments for the Skin

Overarching Themes

Addressing unmet clinical needs involves solving a number of common challenges, including commercialization hurdles, regulatory considerations, and funding. The Mass General Brigham project identified overarching themes to help address these challenges and support innovation across multiple sectors. These include:

  • Taking a systems view of human disease and the practice of system-medicine
  • Developing a global view of infectious disease, including antimicrobial resistance
  • An expansion in high-quality, real-world data that closes gaps in current data (particularly for women and other underserved populations) and ensures that data sets are sufficiently enabling for AI/ML
  • Improving health and healthcare across key populations, including geriatrics and rare genetic disease
  • Addressing major diseases of the brain, including both neurodegenerative and neuropsychiatric conditions; these include Alzheimer’s disease, Parkinson’s disease, ALS, as well as psychiatric and mental health disorders
  • Opening an era of precision medicine across disease areas that includes early diagnosis, treating staged disease, and biomarker discovery and utilization

Panel co-chairs José Florez, Physician-in-Chief and Co-Chair of the MGB Department of Medicine and the Jackson Professor of Clinical Medicine at Harvard Medical School, and Bruce Levy, Physician-In-Chief and Co-Chair of the MGB Department of Medicine and the Parker B. Francis Professor of Medicine at Harvard Medical School, noted how the observations of a broad and representative set of faculty help illuminate the innovation landscape ahead.

“As a leader in patient care and healthcare innovation, our goal is to build on the legacy of research and discovery that has shaped the hospitals of the Mass General Brigham healthcare system for more than a hundred years, and continue to bring breakthroughs forward that can help solve pressing needs,” said Dr. Florez.

Dr. Levy added that “This is a roadmap for the future that can inform discussions happening throughout the healthcare and investment ecosystem regarding the future of medicine.”

More than 2000 decision-makers from healthcare, industry, finance and government attended the World Medical Innovation Forum this week in Boston. A premier global event, the Forum highlights leading innovations in medicine and transformative advancements in patient care.

###

About Mass General Brigham

Mass General Brigham is an integrated academic health care system, uniting great minds to solve the hardest problems in medicine for our communities and the world. Mass General Brigham connects a full continuum of care across a system of academic medical centers, community and specialty hospitals, a health insurance plan, physician networks, community health centers, home care, and long-term care services. Mass General Brigham is a nonprofit organization committed to patient care, research, teaching, and service to the community. In addition, Mass General Brigham is one of the nation’s leading biomedical research organizations with several Harvard Medical School teaching hospitals. For more information, please visit massgeneralbrigham.org.

Contact: Tracy Doyle Mass General Brigham Innovation

(262) 227-5514

Tdoyle5@mgb.org

SOURCE

From: “Doyle, Tracy” <tdoyle5@mgb.org>
Date: Thursday, September 26, 2024 at 10:19 AM
Cc: “Card, Matthew” <matthew.card@bofa.com>
Subject: Unmet Needs in Healthcare — Press Release and link to panel

 

@@@@@@@

Invitation as MEDIA

From: “Doyle, Tracy” <tdoyle5@mgb.org>
Date: Wednesday, August 14, 2024 at 4:04 PM
Cc: “Doyle, Tracy” <tdoyle5@mgb.org>, “Card, Matthew” <matthew.card@bofa.com>
Subject: Media Invite: World Medical Innovation Forum, Sept. 23-25, Boston — Hundreds of clinical experts, industry, investment leaders

 

Media Invite: World Medical Innovation Forum: Monday, Sept. 23—Wednesday, Sept. 25, Boston

At the intersection of innovation and investment in healthcare

Join Us!

Register Now: WMIF24 Media Registration

Mass General Brigham, one of the nation’s leading academic medical centers, is pleased to invite reporters to the 10th annual World Medical Innovation Forum (WMIF) Monday, Sept. 23–Wednesday, Sept. 25 at the Encore Boston Harbor in Boston. The event features expert discussions of scientific and investment trends for some of the hottest areas in healthcare, including

  • GLP-1s,
  • the cancer care revolution,
  • generative AI-enabled care paths,
  • xenotransplant,
  • community health,
  • hospital at home, and
  • therapeutic psychedelics, among many others.

 

The agenda includes nearly 175 executive speakers from healthcare, pharma, venture, start-ups, and the front lines of care, including many of Mass General Brigham’s Harvard Medical School-affiliated researchers and clinicians who this year will host 20+ focused sessions. Bank of America, presenting sponsor of the Forum, will provide additional expert insights on the investment landscape associated with healthcare innovation.

 

Forum highlights include:

 

1:1 and panel interviews with leading CEOs and government officials including:

  • Stéphane Bancel, CEO, Moderna
  • Albert Bourla, PhD, CEO, Pfizer
  • Marc Casper, CEO, Thermo Fisher
  • Deepak Chopra, MD, Founder, The Chopra Foundation
  • Scott Gottlieb, MD, PhD, Former Commissioner, FDA (2017-2019)
  • Maura Healey, Governor, Commonwealth of Massachusetts
  • David Hyman, MD, CMO, Eli Lilly
  • Haim Israel, Head of Global Thematic Investing Research, BofA Global Research
  • Reshma Kewalramani, MD, CEO, Vertex
  • Anne Klibanski, MD, President and CEO, Mass General Brigham
  • Peter Marks, MD, PhD, Director, Center for Biologics Evaluation and Research, FDA
  • Tadaaki Taniguchi, MD, PhD, Chief Medical Officer, Astellas Pharma
  • Christophe Weber, CEO, Takeda
  • Renee Wegrzyn, PhD, Director, ARPA-H

 

Expert panels including:

  • Oncology’s New Paradigm
  • Gene Therapies for Rare Diseases
  • Future of Metabolic Therapies
  • Digital Transformation
  • Biologic Revolution in Radiotherapies
  • Cell Therapies for Autoimmune Diseases
  • Hospital Venture Funds

 

Leading biotech and venture speakers from companies including:

  • Abata Therapeutics
  • Atlas Venture
  • Be Biopharma
  • Everly Health
  • Flagship Pioneering
  • Fractyl Health
  • MindMed
  • Mirador Therapeutics
  • Regor Therapeutics
  • RH Capital
  • Transcend Therapeutics


Exclusive programming:  

  • First Look – 15 rapid-fire presentations on the latest research from leading Mass General Brigham scientists
  • Un-Met Clinical Needs – 100+ key opinion leaders in healthcare weigh in on the top un-met clinical needs in medicine today
  • Emerging Tech Zone – Hands-on exploration of some of the latest digital and AI-based healthcare technologies

 

Our program keeps growing — explore the current Forum agenda and list of speakers.

FORUM AGENDA

SOURCE

https://2024.worldmedicalinnovation.org/agenda/

Monday, September 23, 2024

    • 7:00 AM – 8:30 AM

      Picasso Foyer

    • 7:00 AM – 5:00 PM

      Rotunda

    • 8:00 AM – 10:00 AM

      Picasso Ballroom

      First Look

      First Look: 14 rapid fire presentations

      Moderators

      Giles Boland, MD

      President, Brigham and Women’s Hospital and Brigham and Women’s Physicians Organization;

      Philip H. Cook Distinguished Professor of Radiology, Harvard Medical School

      Marcela del Carmen, MD

      President, Massachusetts General Hospital and Massachusetts General Physicians Organization (MGPO);

      Executive Vice President, Mass General Brigham;

      Professor of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School

      Presenters

      Natalie Artzi, PhD

      Associate Professor of Medicine, Brigham and Women’s Hospital & Harvard Medical School

      Yolonda Colson, MD, PhD

      Chief, Division of Thoracic Surgery, Massachusetts General Hospital;

      Hermes C. Grillo Professor of Surgery, Harvard Medical School

      Nobuhiko Hata, PhD

      Director, Surgical Navigation and Robotics Laboratory, Brigham and Women’s Hospital;

      Professor of Radiology, Harvard Medical School

      John Hanna, MD, PhD

      Associate Professor, Brigham and Women’s Hospital & Harvard Medical School

      Leigh Hochberg, MD, PhD

      Director of Neurotechnology and Neurorecovery, Massachusetts General Hospital;

      Senior Lecturer on Neurology, Harvard Medical School

      Daphne Holt, MD, PhD

      Director of the Resilience and Prevention Program, Massachusetts General Hospital;

      Associate Professor of Psychiatry, Harvard Medical School

      Ole Isacson, MD-PhD

      Founding Director, Neuroregeneration Research Institute, McLean Hospital;

      Professor of Neurology and Neuroscience, Harvard Medical School

      Farouc Jaffer, MD, PhD

      Director, Coronary Intervention, Massachusetts General Hospital;

      Associate Professor of Medicine, Harvard Medical School

      Albert Kim, MD

      Assistant Physician, Mass General Cancer Center;

      Assistant Professor, Harvard Medical School

      Vesela Kovacheva, MD, PhD

      Director of Translational and Clinical Research, Mass General Brigham;

      Assistant Professor of Anesthesia, Harvard Medical School

      Mark Poznansky, MD, PhD

      Director, Vaccine and Immunotherapy Center, Massachusetts General Hospital;

      Steve and Deborah Gorlin MGH Research Scholar;

      Professor of Medicine, Harvard Medical School

      Daniel Solomon, MD

      Matthew H. Liang Distinguished Chair in Arthritis and Population Health, Brigham and Women’s Hospital;

      Professor of Medicine, Harvard Medical School

      Scott Solomon, MD

      Director, Clinical Trials Outcomes Center;

      Edward D. Frohlich Distinguished Chair in Cardiovascular Pathophysiology, Brigham and Women’s Hospital;

      Professor of Medicine, Harvard Medical School

      Guillermo Tearney, MD, PhD

      Principal Investigator, Wellman Center for Photomedicine, Massachusetts General Hospital;

      Remondi Family Endowed MGH Research Institute Chair;

      Professor of Pathology, Harvard Medical School

      Raul Uppot, MD

      Interventional Radiologist, Massachusetts General Hospital;

      Associate Professor, Harvard Medical School

      David Walt, PhD

      Professor of Pathology, Brigham and Women’s Hospital;

      Hansjörg Wyss Professor of Biologically Inspired Engineering, Harvard Medical School

    • 10:00 AM – 10:20 AM

    • 10:20 AM – 10:30 AM

    • 10:30 AM – 10:55 AM

      Fireside

      Fireside Chat

      Moderator

      Keith Flaherty, MD

      Director of Clinical Research, Mass General Cancer Center;

      Professor of Medicine, Harvard Medical School

      Panelist

      Albert Bourla, PhD

      Chairman & CEO, Pfizer

    • 11:00 AM – 11:45 AM

Concurrent Events

  • 11:00 AM – 11:45 AM

    Oncology’s New Paradigm

    Moderators

    Keith Flaherty, MD

    Director of Clinical Research, Mass General Cancer Center;

    Professor of Medicine, Harvard Medical School

    Jason Zemansky, PhD

    SMid-Cap Biotech Analyst, BofA Global Research

    Panelists

    Jonathan Carlson, MD, PhD

    Director of Chemistry, Center for Systems Biology, Massachusetts General Hospital;

    Assistant Professor of Medicine, Harvard Medical School

    Gad Getz, PhD

    Director of Bioinformatics, Krantz Center for Cancer Research and Department of Pathology;

    Paul C. Zamecnik Chair in Cancer Research, Mass General Cancer Center;

    Professor of Pathology, Harvard Medical School

    Russell Jenkins, MD, PhD

    Krantz Family Center for Cancer Research, Massachusetts General Hospital;

    Mass General Cancer Center, Center for Melanoma;

    Assistant Professor of Medicine, Harvard Medical School

    Gregory Simon

    President, Simonovation

    Shannon Stott, PhD

    Associate Investigator, Krantz Family Center for Cancer Research and Mass General Cancer Center;

    d’Arbeloff Research Scholar, Massachusetts General Hospital;

    Associate Investigator, Krantz Family Center for Cancer Research Harvard Medical School

  • 11:00 AM – 11:45 AM

    GLP-1s: How Far Will They Go?

    Moderators

    Tazeen Ahmad

    SMid-Cap Biotech Analyst, BofA Global Research

    Fatima Cody Stanford, MD

    Obesity Medicine Physician Scientist, Massachusetts General Hospital;

    Associate Professor of Medicine and Pediatrics, Harvard Medical School

    Panelists

    Caroline Apovian, MD

    Co-Director, Center for Weight Management and Wellness, Brigham and Women’s Hospital;

    Professor of Medicine, Harvard Medical School

    Vanita Aroda, MD

    Director, Diabetes Clinical Research, Brigham and Women’s Hospital;

    Associate Professor, Harvard Medical School

    Paul LaViolette

    Managing Partner & COO, SV Health Investors

  • 11:00 AM – 11:45 AM

    Generative AI: Breakthrough Research and Limitations

    Moderators

    Adam Landman, MD

    Chief Information Officer & SVP, Digital, Mass General Brigham;

    Associate Professor of Emergency Medicine, Harvard Medical School

    Alec Stranahan, PhD

    SMid-Cap Biotech Analyst, BofA Global Research

    Panelists

    Katherine Andriole, PhD

    Director of Academic Research and Education, Mass General Brigham Data Science Office;

    Associate Professor, Harvard Medical School

    David Blumenthal, MD

    Professor of Practice of Public Health and Health Policy, Harvard TH Chan School of Public Health;

    Research Fellow, Harvard Kennedy School of Government;

    Samuel O. Thier Professor of Medicine, Emeritus, Harvard Medical School

    Faisal Mahmood, PhD

    Associate Professor, Brigham and Women’s Hospital & Harvard Medical School

    William Morris, MD

    Chief Medical Information Officer, Google Cloud

  • 11:00 AM – 11:45 AM

    Gene and Cell Therapy’s Unlimited Potential

    Moderators

    Roger Hajjar, MD

    Director, Gene & Cell Therapy Institute, Mass General Brigham

    Charlie Yang, PhD

    Large/SMid-Cap Biotech and Major Pharma Analyst, BofA Global Research

    Nathan Yozwiak, PhD

    Head of Research, Gene and Cell Therapy Institute, Mass General Brigham

    Panelists

    Samarth Kulkarni, PhD

    CEO, CRISPR Therapeutics

    Peter Marks, MD, PhD

    Director, Center for Biologics Evaluation and Research, FDA

    Marcela Maus, MD, PhD

    Director of Cellular Therapy and Paula O’Keeffe Chair in Cancer Research, Krantz Family Center for Cancer Research and Mass General Cancer Center;

    Associate Director, Gene and Cell Therapy Institute, Mass General Brigham;

    Associate Professor, Harvard Medical School

    Joanne Smith-Farrell, PhD

    CEO & Director, Be Biopharma

  • 11:00 AM – 11:45 AM

    Xenotransplant: Game Changing Organ Replacement

    Moderators

    Jason Gerberry

    Specialty Pharma and SMid-Cap Biotech Analyst, BofA Global Research

    Joren Madsen, MD, PhD

    Director, MGH Transplant Center;

    Paul S. Russell/Warner-Lambert Professor of Surgery, Harvard Medical School

    Panelists

    Tatsuo Kawai, MD, PhD

    Director of the Legorreta Center for Clinical Transplantation Tolerance,

    A.Benedict Cosimi Chair in Transplant Surgery, Massachusetts General Hospital;

    Professor of Surgery, Harvard Medical School

    Richard Pierson III, MD

    Scientific Director, Center for Transplantation Sciences, Massachusetts General Hospital;

    Professor of Surgery, Harvard Medical School

    Leonardo Riella, MD, PhD

    Medical Director of Kidney Transplantation, Massachusetts General Hospital;

    Harold and Ellen Danser Endowed Chair in Transplantation, Harvard Medical School

Concurrent Events

  • 12:00 PM – 12:45 PM

    Future of Cancer Care

    Moderator

    Alec Stranahan, PhD

    SMid-Cap Biotech Analyst, BofA Global Research

    Panelists

    Gerard Doherty, MD

    Surgeon-in-Chief, Mass General Brigham Cancer;

    Surgeon-in-Chief, Brigham and Women’s Hospital;

    Moseley Professor of Surgery, Harvard Medical School

    Daphne Haas-Kogan, MD

    Chief, Enterprise Radiation Oncology, Mass General Brigham;

    Professor, Harvard Medical School

    Benjamin Kann, MD

    Assistant Professor, Brigham and Women’s Hospital & Harvard Medical School

    David Ryan, MD

    Physician-in-Chief, Mass General Brigham Cancer;

    Professor of Medicine, Harvard Medical School

  • 12:00 PM – 12:45 PM

    Generative AI Enabled Care Paths

    Moderators

    Adam Ron

    Health Care Facilities and Managed Care Analyst, BofA Global Research

    Marc Succi, MD

    Executive Director, Mass General Brigham MESH Incubator;

    Associate Chair of Innovation & Commercialization, Mass General Brigham Radiology;

    Assistant Professor, Harvard Medical School

    Panelists

    Christopher Longhurst, MD

    Chief Medical & Digital Officer, UC San Diego Health

    Rebecca Mishuris, MD

    Chief Medical Information Officer, Mass General Brigham;

    Member of the Faculty, Harvard Medical School

    Shiv Rao, MD

    CEO & Founder, Abridge

    Alkesh Shah

    Head of US Equity Software Research, BofA Global Research

  • 12:00 PM – 12:45 PM

    Transforming Care in a Resource Limited Era

    Moderator

    Niyum Gandhi

    CFO & Treasurer, Mass General Brigham

    Panelists

    Fritz François, MD

    Executive Vice President and Vice Dean, Chief of Hospital Operations, NYU Langone Health

    Susan Huang, MD

    EVP, Chief Executive, Providence Clinical Network, Providence Southern CA

    Ron Walls, MD

    Chief Operating Officer, Mass General Brigham;

    Neskey Family Professor of Emergency Medicine, Harvard Medical School

  • 12:00 PM – 12:45 PM

    Cardiovascular Pipeline Renewal

    Moderators

    Jason Gerberry

    Specialty Pharma and SMid-Cap Biotech Analyst, BofA Global Research

    Calum MacRae, MD, PhD

    Vice Chair for Scientific Innovation, Department of Medicine, Brigham and Women’s Hospital;

    Professor of Medicine, Harvard Medical School

    Panelists

    Lotte Bjerre Knudsen, DMSc

    Chief Scientific Advisor, Novo Nordisk

    David Grayzel, MD

    Partner, Atlas Venture

    Christoph Westphal, MD, PhD

    General Partner, Longwood Fund

    Deborah Wexler, MD

    Chief, Diabetes Unit, Massachusetts General Hospital;

    Associate Professor of Medicine, Harvard Medical School

  • 12:45 PM – 1:00 PM

  • 1:00 PM – 1:20 PM

    Picasso Ballroom

    Opening Remarks

    Introducer

    Miceal Chamberlain

    President of Massachusetts, Bank of America

    Opening Remarks

    Maura Healey

    Governor of the Commonwealth of Massachusetts

  • 1:20 PM – 2:00 PM

    Picasso Ballroom

    Healthcare Innovation and Regional Competitiveness

    Panelists

    John Fish

    Chairman & CEO, Suffolk

    Reshma Kewalramani, MD

    CEO & President, Vertex Pharmaceuticals

    Jonathan Kraft

    President, The Kraft Group;

    Board Chair, Massachusetts General Hospital

  • 2:05 PM – 2:30 PM

    Picasso Ballroom

    Fireside

    Fireside Chat

    Moderators

    Tazeen Ahmad

    SMid-Cap Biotech Analyst, BofA Global Research

    Roger Hajjar, MD

    Director, Gene & Cell Therapy Institute, Mass General Brigham

    Panelist

    Reshma Kewalramani, MD

    CEO & President, Vertex Pharmaceuticals

  • 2:35 PM – 3:10 PM

    Picasso Ballroom

    Delivering Care: New Tools, Evolving Challenges, Bold Aspirations

    Moderator

    Andrew Bressler

    Washington Healthcare Policy Analyst, BofA Global Research

    Panelists

    Rod Hochman, MD

    President & CEO, Providence

    Anne Klibanski, MD

    President & CEO, Mass General Brigham;

    Laurie Carrol Guthart Professor of Medicine, Harvard Medical School

    Kevin Mahoney

    CEO, University of Pennsylvania Health System

  • 3:10 PM – 3:35 PM

    Picasso Ballroom

    Fireside

    Fireside Chat

    Moderators

    Caroline Sokol, MD, PhD

    Assistant Physician, Massachusetts General Hospital;

    Assistant Professor, Harvard Medical School

    Charlie Yang, PhD

    Large/SMid-Cap Biotech and Major Pharma Analyst, BofA Global Research

    Panelist

    Mark McKenna

    Chairman & CEO, Mirador Therapeutics

3:40 PM – 4:05 PM

Picasso Ballroom

RECORDING OF SPEAKERS’ QUOTES ON WordPress.com
 
STARTS HERE

Fireside

Fireside Chat

Moderators

Jason Gerberry

Specialty Pharma and SMid-Cap Biotech Analyst, BofA Global Research

Allan Goldstein, MD

Chief of Pediatric Surgery, Massachusetts General Hospital;

Surgeon-in-Chief, Mass General for Children;

Marshall K. Bartlett Professor of Surgery, Harvard Medical School

Panelist

Christophe Weber, President & CEO, Takeda

  • pipeline is very diverse at the R&D center in Boston

Phase III:

  • TAK-279 Psorisis
  • Neurocrine’s Takeda-Partnered Drug Candidate Aces Phase II Depression Study

The Markets for Takeda

  • US market is 40% of revenue, It is a difficult market but still the most important for Phama in the World
  • Japan is 8%
  • Growth by acquisitions and internal development like above, two Phase III drugs

Price control and policies:

  • negotiation
  • price war create tension

Team:

Public company traded in NYSE

  • Management team has 10 nationalities – Global company
  • AI is adopted as a digital companion

Recruiting Patients for Clinical Trial:

  • Very difficult

M&A

  • After acquisition of Shire – not many other opportunities are left

4:05 PM – 4:40 PM

Picasso Ballroom

The Innovation Gap: A Review of the Future of Viral Vector Manufacturing and the Delivery of Genetic Medicines

Moderators

Elizabeth Henske, MD, Director, Center for LAM Research and Clinical Care, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Alec Stranahan, PhD, SMid-Cap Biotech Analyst, BofA Global Research

Panelists

Peter Anastasiou, CEO, Capsida Biotherapeutics

  • Capsid technology for Liver disease, Parkinson’s
  • AV and CNS crossing BBB
  • One capsid for one disease
  • manufacture caspids
  • Challenges:  manufacturable after screening
  • IV delivery – brain disorder, blood flow would bring therapeutics to all brain tissue consistently vs localized
  • Partnership with Eli Lilly and with Crisper technologies with Abbvie

Steve Favaloro, Chairman & CEO, Genezen

  • 200 persons Team manufacture
  • Partnerships: synthetic plasma

Alexandria Forbes, PhD, CEO, MeiraGTx

  • Optimize promoters, control transcription expression by injection or by pill, control translation
  • improving potency of gene therapies capsule technology
  • cost hundred of $ not thousand of $
  • ALL manufacturing in house
  • 9 years of data can help to narrow down the parameters
  • time frame is shortened
  • company established 9 years ago
  • apply DNA expression – invented a technology
  • splicing control mRNA
  • control cell lines
  • give an injection or a pill and control antibodies, glucagon
  • control dosing for efficatious therapeutics
  • Potency
  • Ribozon is a delivery system
  • Partnership with J&J –

Fraser Wright, PhD, Chief Gene Therapy Officer, Kriya Therapeutics

  • manufacturing – changing in capsule design
  • manufacture viruses
  • cost of manufacturing – efficiency matters a lot
  • delivery of the gene in the tissue
  • Partnerships: basic vs applied Quality from research to manufacturing

4:45 PM – 5:20 PM

Picasso Ballroom

A Deep Dive on Genetic Modalities for Rare Disease: Genetic Medicines Are Here

Moderator

Tazeen Ahmad, SMid-Cap Biotech Analyst, BofA Global Research

  • Treat once or repeat therapy?

Patricia Musolino, MD, PhD, MGH

 

Panelists

Faraz Ali, Tenaya Therpeutics

  • genetic therapy for a genetic mutation – NOVEL approach
  • 400 mutation related to cardiomyopathy
  • 2018 – gene therapy was an innovation
  • genetic medicine Cardiology introducing opportunities wiht validation that did not exist
  • find novel targets Partnerships are a must to have
  • Viral therapies vs gene therapy

Lucas Harrington, PhD, Co-Founder & CSO, Mammoth Biosciences

  • How to turm Genome 2012 to therapy?
  • targeting: Taking risk Patient interaction with treatment
  • variation between Rare diseases some are very small some are not small – incentive to investors
  • The field will grow fast

Raju Prasad, PhD, Chief Financial Officer, CRISPR Therapeutics

  • various indications
  • FDA Approval
  • Gene editing technology for rare diseases
  • LPA for RNA therapy
  • incentive to investors
  • Important for investor to understand the siize of the market, CRISPR can be a technology for a large market size
  • Sickle cell disease – market is large and therapy can be made affordable

 

Sandi See Tai, MD, Chief Development Officer, Lexeo Therapeutics

  • cardiomyopathy
  • protective gene
  • Early genetic testing
  • Educating patients

5:20 PM – 6:30 PM

Picasso Terrace and Harborside Lawns 1 & 2

Tuesday, September 24, 2024

8:00 AM – 8:55 AM

Picasso Ballroom

The Transforming World

Introducer

Liz Everett Krisberg, Head of Bank of America Institute

  • Record attendance this year
  • Introduction to Haim

Panelist

Haim Israel

Head of Global Thematic Investing Research, BofA Global Research

  • Concept of the Future and for the Future: Short-term and long-term
  • Humanity achievements in Ten Year: Data, Processing power and BRAIN – Long-term becomes Short-term – Last 10 years: 2012, 2014 solar system, 2015 medicine, 2019 blackhole, 2023 core of sun – star was created hotter than core sun
  • 2022, 2024 – galaxy picture of the universe
  • Volume of data created every month in terrabyts every 18 month data is duplicating itself.
  • Olny 1% is used – imagine 2% or 3%
  • Processing power since Apollo 11 [one trillion] – getting cheaper – cost for calculation went down 16,000 fold since 1995
  • AMMOUNT of DATA goes up and Cost of COMPUTATION goes down – price per giga byte
  • Projections for the next 100 years
  • Negative for people and Negative for Companies who are concerned with quarterly financial data
  • Companies: Walmart, Alphabet, Home Depot – DATA larger that COuntries
  • Living in defining moment: started by iPhone revolution and 2023 by AI revolution – 6x outpaced Moore’s Law by GPT by 3000x
  • 18 months into AI revolution – GPT in use
  • The next 10 years:
  1. Aging population
  2. 2024 – birth rate low in US, Japan, CHina, S. Korea – Pension system will decline in size
  3. 2.2 millions new material were created by DeepMind at Alphabet by simulation of AI on molecule
  4. Microsoft in 80 hours identified 18 materials winners for Batteries using AI from 32 million material candidates
  5. AI- weather calculations in minutes 1,000x faster, cheaper and more accurate
  6. 2025 – GPT-6 AI surpass Human Brain
  7. China is a big player in AI
  8. Cyber CRIME is the 3rd largest economy in the World. Hackers are using ChatGPT to create fake pictures leading to ZERO privacy
  • PRIVACY: Deepfakes up 62x, social media
  • 2024 – Global Grid – needs much more energy because AI consumes so much energy
  • Metals shortages: Nickel, Copper,
  • Scarcity of water for 2/3 of the planet
  • data centers consume water more than Japan
  • 2025 – Genomics Data sequencing bigger that X.com or Youtube
  • 2027 – Peak oil demand: needed to be scalable, cheaper 25%
  • 2028 – 5G networks reaches full capacity, 6G will be needed
  • 2029 – 25x more satellites in Orbit than today
  • 2029 – Personalized AI medicines and treatments will manipulate death and revive LONGEVITY – AI will generate drugs and all treatments
  • 2030Generative AI:  re-skill 1 Billion people
  • 2035 – Fusion energy, known technology since the atomic bomb, how to keep it stable in plasma state of material – not yet achieved, it is clean, cheap: to Power the World – equivalent of 11 barrels of oil
  • Large cities: Cable diameter 17cm wide to power a large city
  • AI will change scarcity into abundance
  • 2037 – Artifitial SUPER Intelligence – AI to outsmart Life
  • Quantum computer – Consortium of NASA and other governmental agencies and Google on quantum computer design
  • 2024 the most interesting year in human history

 

Concurrent Events

  • 9:00 AM – 9:45 AM

    Current and Future States of Immunology

    Moderators

    Caroline Sokol, MD, PhD, Assistant Physician, Massachusetts General Hospital;, Assistant Professor, Harvard Medical School

    Alec Stranahan, PhD, SMid-Cap Biotech Analyst, BofA Global Research

    Panelists

    Dong Feng Chen, MD, PhD, Associate Scientist, Massachusetts Eye and Ear;, Associate Professor, Harvard Medical School

    Steven Grinspoon, MD, Chief, Metabolism Unit, Massachusetts General Hospital; Professor of Medicine, Harvard Medical School

    Alexandra-Chloé Villani, PhD, Investigator, Massachusetts General Hospital; Assistant Professor, Harvard Medical School

  • 9:00 AM – 9:45 AM

    Therapeutic Psychedelics – Opportunities and Impact

    Moderators

    Maurizio Fava, MD

    Chair, Department of Psychiatry, Massachusetts General Hospital;

    Slater Family Professor of Psychiatry, Harvard Medical School

    Jason Gerberry

    Specialty Pharma and SMid-Cap Biotech Analyst, BofA Global Research

    Kerry Ressler, MD, PhD

    Chief Scientific Officer, McLean Hospital;

    Professor of Psychiatry, Harvard Medical School

    Panelists

    Cristina Cusin, MD

    Director, MGH Ketamine Clinic and Psychiatrist, Depression Clinical and Research Program, Massachusetts General Hospital;

    Associate Professor in Psychiatry, Harvard Medical School

    Daniel Karlin, MD

    Chief Medical Officer, MindMed

    John Krystal, MD

    Chair, Department of Psychiatry, Yale School of Medicine

    Jennifer Warner-Schmidt, PhD

    Vice President, Scientific Affairs, Transcend Therapeutics

  • 9:00 AM – 9:45 AM

    Innovations Advancing Community Health Equity

    Moderators

    Allen Lutz

    Health Care Services Analyst, BofA Global Research

    Elsie Taveras, MD

    Chief Community Health & Health Equity Officer, Mass General Brigham;

    Conrad Taff Endowed Chair and Professor of Pediatrics, Harvard Medical School

    Panelists

    Rebecca Mishuris, MD

    Chief Medical Information Officer, Mass General Brigham;

    Member of the Faculty, Harvard Medical School

    Claire-Cecile Pierre, MD

    Vice President, Community Health Programs, Mass General Brigham;

    Instructor in Medicine, Harvard Medical School

    Jorge Rodriguez, MD

    Clinician-investigator, Brigham and Women’s Hospital;

    Assistant Professor, Harvard Medical School

    Prabhjot Singh, MD, PhD

    Senior Advisor, Strategic Initiatives Peterson Health Technology Institute

  • 9:00 AM – 9:45 AM

    Earliest Detection

    Moderators

    James Brink, MD

    Enterprise Chief, Radiology, Mass General Brigham;

    Juan M. Taveras Professor of Radiology, Harvard Medical School

    David Louis, MD

    Enterprise Chief, Pathology, Mass General Brigham

    Benjamin Castleman Professor of Pathology, Harvard Medical School

    Jason Zemansky, PhD

    SMid-Cap Biotech Analyst, BofA Global Research

    Panelists

    Jasmeer Chhatwal, MD, PhD

    Associate Neurologist, Massachusetts General Hospital;

    Associate Professor of Neurology, Harvard Medical School

    Pradeep Natarajan, MD

    Director of Preventive Cardiology, Paul & Phyllis Fireman Endowed Chair in Vascular Medicine, Massachusetts General Hospital;

    Associate Professor of Medicine, Harvard Medical School

    Yakeel Quiroz, PhD

    Director, Familial Dementia Neuroimaging Lab and Director, Multicultural Alzheimer’s Prevention Program, Massachusetts General Hospital;

    Paul B. and Sandra M. Edgerley MGH Research Scholar;

    Associate Professor, Harvard Medical School

    Heidi Rehm, PhD

    Chief Genomics Officer, Massachusetts General Hospital;

    Professor of Pathology, Harvard Medical School

  • 9:00 AM – 9:45 AM

    Women’s Health Technology Revolution

    Moderators

    Tazeen Ahmad

    SMid-Cap Biotech Analyst, BofA Global Research

    Hadine Joffe, MD

    Executive Director of the Connors Center for Women’s Health and Gender Biology;

    Interim Chair, Department of Psychiatry, Brigham and Women’s Hospital;

    Paula A. Johnson Professor of Psychiatry in the Field of Women’s Health, Harvard Medical School

    Panelists

    Keith Isaacson, MD

    Director of Minimally Invasive Gynecologic Surgery and Infertility, Newton Wellesley Hospital;

    Associate Professor of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School

    Nawal Nour, MD

    Chair, Department of Obstetrics and Gynecology, Brigham and Women’s Hospital;

    Associate Professor, Kate Macy Ladd Professorship, Harvard Medical School

    Kaveeta Vasisht, MD, PharmD

    Associate Commissioner, Women’s Health, U.S. Food and Drug Administration

    Alice Zheng, MD

    Principal, RH Capital

9:50 AM – 10:15 AM

Picasso Ballroom

Fireside

Fireside Chat

Moderator

David Brown, MD, President, Academic Medical Centers, Mass General Brigham; Mass General Trustees Professor of Emergency Medicine, Harvard Medical School

  • Hoe do you balance Private medicine with Public not for profit HealthCare
  • Healthcare delivery system can achieve that much in Human health
  • Resources for Equity: housing and services: Capacity and COst
  • Evolution of care close to home catalyst of the Pandemic – How government think about the right patient for the right care level
  • MGB 40-60 In-patients at Home – Largest Program in the State  – product needs to scale across all population though some do not have food security at home

Panelist

Kate Walsh, Secretary of Health and Human Services, State of Massachusetts

  • Stuart Bankrupcy – pstioents and providers involvement – structure challenges
  • Race and ethnicity – disparities, access and equity
  • Identify the challenge for Race and ethnicity
  • Focus to identify resources
  • Medicare & Medicaid – Human needs equity involve housing, food and home care – Public and Private sector cooperation
  • Pay for Performance
  • MA vs NYC – resources for welcoming new populations to the State of MA
  • Help finding Housing vs Shelter people
  • MA is the only State in the Union that is a Shelter State
  • People in our COuntry LEGALLY are in and out of shelters, new arrivals of skilled labor – temporary assistance to get jobs that we can’t find people to fill: CNA as example
  • MA has a community of shelters and medical center in the communities
  • Services for people that are at risk due to past life in home countries
  • Support for kids that do not speak English
  • Care and location: Keep care at home or SNF at home or in the community
  • Low income person at Home Hospital vs at MGB ?
  • Autist kids becoming Adult – how to care for ?

 

10:15 AM – 10:40 AM

Picasso Ballroom

Fireside

Fireside Chat

Moderators

Alec Stranahan, PhD, SMid-Cap Biotech Analyst, BofA Global Research

Teresa Gomez-Isla, MD, PhD, MGH, Neurology, Memory division

  • Altzheimer’s biomarkers
  • Clinical trials lessons on drug benefits

Panelist

David Hyman, MD, Chief Medical Officer, Eli Lilly and Company

  • Cardio-metabolic – medicines redefining disease by medicines benefit to patients
  • Investment in manufacturing medicines for Obesity, demand continue to expand
  • Oral small molecule and scaling focus on Sleep apnea, half of the population have metabolic disease and heart failure
  • Extension Program with sustained weigh loss in pre-diabetes progressing into maintained weigh loss
  • Invest in R&D in the cardio-metabolic
  • Listed to community feedback on experience how the drugs in AD affected patients in the Community – learning about challenges in delivery innovation in AD – irreversible neurodegenerative diseases – prevent not to loose the patients entirely – brain function
  • Targeted therapies, genetic therapies
  • Past life Oncologist – delivered innovations into Cancer patients – genetic medicines
  • AD medicines are not accessible even to people of means, Drug delivery using PET spinal injections
  • Ten years horizons at Eli Lilly is common
  • Obligation to provide scientific evidence from clinical trials
  • Inventory of patients qualification to participate in Clinical trials
  • Oncology: Interactions in biologics, cell therapies, conjucate compounds
  • Renewal of Targeting antigens
  • In Oncology: Proportions of patients get long term disease control by molecules developed in Academic Centers.
  • Eli Lilly acquired a BioPharma with manufacturing capabilities
  • Innovations are core vs discount cash-flow, strategy is to look at the science due to capacity to develop innovations

10:40 AM – 11:20 AM

Picasso Ballroom

Disruptors

The Disruptors: Metabolic Power…Need It…Want it

Moderator

Alec Stranahan, PhD, SMid-Cap Biotech Analyst, BofA Global Research

Caroline Apovian, MD, MGH, HMS

  • Last ten years, from metabolic lessons of Bariatric patients
  • Treat obesity before surgery
  • product composition
  • multidisciplinary approach to obesity needs to be like in Oncology – multiple dsciplines
  • Bariatric and weigh regain like stent stenosis after surgery
  • Obesity dysfunction inflammation Gut-Brain transfer of hormones from the gut do not reach the brain to carb hunger socieaty is not signaled in the Brain and eating continued to mitigate hunger
  • Insurance must cover
  • Obesity Medicine – training 25 new practitioners to treat Obesity – Standards of Care, life style change
  • Primary care providers do not have resources to treat Life style component of
  • To reduce mortality by 20% by Bariatric surgery – No reduce of mortality by stenting – THAT I DISAGREE with

 

Panelists

David Hyman, MD, Chief Medical Officer, Eli Lilly and Company

  • non-peptide agonist, bariatric level for obesity
  • peptide injecting device
  • hormones and peptids activan inhibitor
  • hundred of million of people – scaling up
  • Adolescence with obesity will develop CVD, NASH
  • Epidemic of obesity the medicines are combating the epidemic
  • Vials, differential pricing, orals vs injectables
  • Productivity of work force, coverage by employers health insurance vs Government to handle coverage
  • 10 additional drug

Xiayang Qiu, PhD, CEO, Regor Therapeutics

  • six years ago, great opportunity peptide and biologics for lifetime disease of obesity
  • cardiovascular favorably = affected by reduction in weigh
  • Medicines that works start early at age 35

Harith Rajagopalan, MD, PhD, CEO & Co-Founder, Fractyl Health

  • Diet & Life Style
  • Eli Lilly and Novo Nordik – have great drugs
  • Patients stop using them before they see the benefit
  • durable long term of mentainance long-tern to stay on the drug
  • Past life coronary cardiologist: PCI vs surgery choice of care angioplasty vs open heart surgery
  • Bariatric surgery vs great medicines
  • may be angioplasty for Bariatric patients
  • Obesity is different than CVD
  • BC-BS coverage of obesity drugs because weight is gained back vs Statins – continual use control cholestrol
  • maintenance drugs in the field of Obesity are needed
  • cost of drugs will come down
  • more evidence on obesity drugs will affect Formulary

 

11:20 AM – 12:00 PM

Picasso Ballroom

The Innovation Gap: The Broader Impact of Metabolic Drugs on Related Diseases

Moderator

Jason Zemansky, PhD, SMid-Cap Biotech Analyst, BofA Global Research

Patrick Ellinor, MD, PhD, MGH, HMS

Panelists

Craig Basson, MD, PhD, Chief Medical Officer, Bitterroot Bio

  • 17,000 patients obese no DM
  • prior CVD followed 3 yrs of treatment 6% mortality during the Trial
  • Death from CVD endpoint
  • weight at joining the trial, loss during the trial, benefir from the drug’
  • improve CVD not weigh loss
  • mechanism of Inflammation – drug, reduced atherosclerosis and reduced plaque and cytokins and inflammation improve CVD status
  • combination of life style and drugs GI axis systemic
  • cardiac artery disease: cholesterol, inhibit inflammatory signals plaque build on top of itself – approaches to remove debris macrophages in the plaque for artherosclerosis mechanism as CVD risk

Joshua Cohen, Co-CEO, Amylyx Pharmaceuticals

  • Bariatric surgery lower obesity
  • genetics, eating habits,
  • GLP-1 agonist developed

Punit Dhillon, CEO, Skye Bioscience

  • Phase II study combination therapy CVD and Obesity
  • optimize body composition – more productive on the body periphery
  • subtypes metabolic gains
  • Pharmacotherapy for obesity: mechanisms complementary life style change is a must have for long-term benefits
  • weight loss as a start before obesity treatment
  • co-morbidities of obesity

Justin Klee, Co-CEO, Amylyx Pharmaceuticals

  • Parkinson’s CNS peripheral Brain access therapies
  • revolution in metabolic disease treatment options, more studies for pathways to target the right patients for the right treatment
  • GLP-1 is energy regulator, Hypoglycemia is very dangerous

Rohan Palekar, CEO, 89bio

  • applications to obesity – data support
  • bariatric surgery intervention is not enough, NASH will not be impacted only by the surgery
  • NASH is a disease taking 25 years to develop
  • risk of fibrosis to set in Cirrhosis which is not curable

 

Concurrent Events

  • 12:15 PM – 1:00 PM

    ARPA-H: Opening New Frontiers in Health Innovations

    Panel of 5

    Glioblastoma Treatment Reinvented

    Moderators

    E. Antonio Chiocca, MD, PhD

    Chair, Department of Neurosurgery, Brigham and Women’s Hospital;

    Harvey W. Cushing Professor of Neurosurgery, Harvard Medical School

    Charlie Yang, PhD

    Large/SMid-Cap Biotech and Major Pharma Analyst, BofA Global Research

    Panelists

    Natalie Artzi, PhD

    Associate Professor of Medicine, Brigham and Women’s Hospital & Harvard Medical School

    Bryan Choi, MD, PhD

    Associate Director, Center for Brain Tumor Immunology and Immunotherapy, Massachusetts General Hospital;

    Assistant Professor of Neurosurgery, Harvard Medical School

    Alexandra Golby, MD

    Neurosurgeon;

    Director of Image-guided Neurosurgery, Brigham and Women’s Hospital;

    Professor of Neurosurgery, Professor of Radiology, Harvard Medical School

  • 12:15 PM – 1:00 PM

    Healthcare Corporate Venture

    Moderator

    Roger Kitterman

    Senior Vice President, Ventures and Business Development & Licensing, Mass General Brigham

    Managing Partner, Mass General Brigham Ventures

    Panelists

    Rahul Ballal, PhD

    CEO, Mediar Therapeutics

    Tim Luker, PhD

    VP, Ventures & West Coast Head, Eli Lilly

    James Mawson

    CEO, Global Corporate Venturing

  • 12:15 PM – 1:00 PM

    Inflammation Pathways

    Moderators

    Tazeen Ahmad

    SMid-Cap Biotech Analyst, BofA Global Research

    Katherine Liao, MD

    Associate Physician, Department of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital;

    Associate Professor of Medicine and Biomedical Informatics, Harvard Medical School

    Panelists

    Jessica Allegretti, MD

    Director, Crohn’s and Colitis Center, Brigham and Women’s Hospital;

    Associate Professor of Medicine, Harvard Medical School

    Andrew Luster, MD, PhD

    Chief, Division of Rheumatology, Allergy and Immunology;

    Director, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital;

    Persis, Cyrus and Marlow B. Harrison Professor of Medicine, Harvard Medical School

    Thorsten Mempel, MD, PhD

    Associate Director, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital;

    Professor of Medicine, Harvard Medical School

  • 12:15 PM – 1:00 PM

    Hospital at Home

    Moderators

    Joanna Gajuk

    Health Care Facilities and Managed Care Analyst, BofA Global Research

    Heather O’Sullivan, MS, RN, AGNP

    President, Mass General Brigham Healthcare at Home

    Panelists

    O’Neil Britton, MD

    Chief Integration Officer & Executive Vice President, Mass General Brigham

    Jatin Dave, MD

    Chief Medical Officer, MassHealth;

    Director of Clinical Affairs, UMass Chan Medical School

    Chemu Lang’at

    Chief Operating Officer, Best Buy Health

1:05 PM – 1:45 PM

Picasso Ballroom

Pioneering Digital Transformation

Moderator

Liz Kwo, MD, Chief Commercial Officer, Everly Health

  • Infrastructure
  • AI used for

Panelists

Anna Åsberg, Vice President, AstraZeneca Pharmaceuticals

  • Massive data bases organize
  •  AI to augment intelligence inside the data

Tyler Bryson, Corporate Vice President, US Health & Public Sector Industries, Microsoft Corporation

  • Do we have platforms to serve new problem
  • Regulatory changes require visiting use cases
  • Pharma has the research data, providers have EMR – Microsoft builds new models using that data
  • Tumor imaging data was processed and new pattern recognition done on data of these tumors. New patterns are now a subject for research, just identified inside the data
  • Trust in Healthcare
  • NYC and Microsoft developed a System for small businesses to access city resources
  • Works with Academic institutions: Programs at Harvard and Princeton to train students by Microsoft employees on MIcrosoft AI technologies that as they graduate there will be trained new AI-trained employees
  • collaborations

Aditya Bhasin, BofA

  • AI in Banking: Bias, security
  • AI virtual system analytics to provide insight for scaling

Jane Moran, MGH

  • Network, Data structure needs updates
  • technology to help clinicians
  • care team to work with Generative AI to assist in e-mail reading and problem solving
  • Healthcare equity – avoid Bias
  • AI is not an answer to every problem
  • innovate at scale: using Epic and Microsoft
  • Clinical data structure for LLM, AI to renovate administrative processes inside MGH
  • Data structure for transperancy
  • Digital Rounds like Medical ROunds audit problems
  • equity in data

1:45 PM – 2:25 PM

Picasso Ballroom

Capital Formation: Putting Money to Work – State of Affairs in Capital Markets

Moderators

John Bishai, PhD, BofA

  • valuations went down

Brendan Singleton, Healthcare Equity Capital Markets, BofA Securities

  • what impact Capital flow

Emma Somers-Roy, Chief Investment Officer, Mass General Brigham

Panelists

Chris Garabedian, Chairman & CEO, Xontogeny; Venture Portfolio Manager, Perceptive Advisors

  • Valuations done with comparables for IPO
  • Not quick to invest in companies, responsible behavior
  • Private rounds, Biotech and Pharma strategic partners
  • M&A stable requires are exciting valuation
  • foundations, institutional investors – level of interest is related to valuations number of years to exit
  • Peak sale, Public markets different than Private markets
  • Obesity is a crowd space, diferentiation is important
  • Exit tow ways: year for IPO natural acquirer – Who is he??
  • Cancer was a dominant now CNS, Cardio-metabolic, ophthalmology
  • size of market – Cancer was attractive, less in 2024
  • Early venture investor: 50-100MM valuation to 2Bil
  • CMS has discounting since profits are been realize at present time
  • Patents`
  • Presidential election
  • investors scarce pushed fewer mega rounds 100MM financing requires early clinical data
  • Hedge fund very conservative with valuations
  • Downsize in Biotech is over

Arjun Goyal, MD, Vida Ventures

  • Investment in private markets
  • 2019-2021 – IPOs on narratives and proof of concept, only only, no financials
  • M&A or Partnering – financial risk clinical data point
  • validation of team success
  • size of market is very important
  • Innovation matters always in Pharma, prospects for Biotech very bright
  • what is HOT in a moment
  • combination therapies
  • Life cycle: compound right gene, financing history, fundamentals
  • calibration of market valuations

 

2:25 PM – 2:50 PM

Picasso Ballroom

Fireside

Lessons Learned Shaping New Horizons: Visionary Change Agent Perspectives

Moderator

Yvonne Hao, Secretary of Economic Development, Commonwealth of Massachusetts

  • accelerate AI adoption by nurses, How do you do that??
  • Public private partnerships
  • If you have a blank slate – do it differently

Great impact of Cleveland Clinic

Panelists

Delos “Toby” Cosgrove, MD, Executive Advisor; former CEO & President, Cleveland Clinic

  • Housing, education, research beyond healthcare
  • Reduce cost in healthcare, call centers by AI: equipment to measure BP every 4 hours
  • Technology is approved 13 years to become standard of care
  • COST in healthcare requires SALVATION
  • mistakes by leadership
  • Regulators have their share in current situation of Healthcare
  •  Leadership in Health care must change

Marc Harrison, MD, Co-founder & CEO, Health Assurance Transformation Corp. (HATCo)

  • collaborate with competitors
  • AI is a tool not a solution
  • Streamline processes to reduce costs
  • Government should not solve the Healthcare problem
  • Residents are victims of leaders mistakes
  • Only healthcare industry sees the medical records of all the population
  • gene therapy, innovations to change healthcare and get financial solvency

2:50 PM – 3:15 PM

Picasso Ballroom

Fireside

Fireside Chat

Moderators

Andrew Bressler, Washington Healthcare Policy Analyst, BofA Global Research

  • What is coming up in the next two years
  • Are you growing and Hiring?

Yvonne Hao, Secretary of Economic Development, Commonwealth of Massachusetts

  • AI – what is the potential for Healthcare
  • MA to work with ARPA-H

Panelist

Renee Wegrzyn, PhD, Director, Advanced Research Projects Agency for Health – A Federal Governmental Agency

  • ARPA-H Model was introduce under the Advanced Research Projects Agency for Health
  • Hired 21 Program Managers to manage Health initiatives in research
  • Health is not a partizan affair
  • Bring young innovators, mantored by experiences healthcare professionals
  • cellular therapeutics is an example selected to advanced the field
  • Data driven – looking at +100 project approved by government agency
  • Governtment, Academia, Private sector – SOLICITATIONS for solving a research problem
  • Technical merit in judging applications
  • Value-baced pricing – data to influence policy FDA, NIH collaboration
  • FDA to finance projects spending
  • Pediatrics
  • President announced a program for ARPA-H to work on
  • Investors are welcome to review proof of concepts of ARPA-H
  • Return on Investment for all Americans’ Tax payers money
  • Yes, growing and hiring. $1.5 milion budget

 

 

3:15 PM – 3:20 PM

First Look

3:20 PM – 3:35 PM

Selector of Winner: Doug Marshall & Paul Anderson, MD, PhD

 

3:35 PM – 4:15 PM

Picasso Ballroom

Disruptors

The Disruptors: The Biologic Revolution in Radiotherapies

Moderator

John Bishai, PhD, Global Healthcare Investment Banking, BofA Securities

Umar Mahmood, MD, PhD, MGH, HMS

Panelists

Amos Hedt, Chief Business Strategy Officer, Perspective Therapeutics

  • imaging used to deliver the therapeutics before the drug touch the patient to calculate toxicity
  • PL-1 combined with radiotherapy synergistics results
  • immunogenic combination therapy, in presence of these agents, immune response reaction in the immune cells

Matthew Roden, PhD, President & CEO, Aktis Oncology

  • Conjugates – delivery direct to tumors
  • Opportunity two targets: (1) SSTA2 marker (2) xx
  • WHen agent inside the tumor, shrinkage and no emergence of cell nascent 
  •  optimization design
  • Treatment break for patients and families

Philip Kantoff, MD, Co-Founder & CEO, Convergent Therapeutics

  • Radio-pharmeceutics : 10 days half-life carrier not a target for small molecules Data on 120 patient, namo robust response synergy of antibody and molecule
  • image alphas
  • durable responses

Matt Vincent, PhD, AdvanCell Isotopes

  • ROS species generated in the tumor
  • peptides, protein binders
  • paradigm shift in delivery of oncology therapeutics directly to tumors

Lena Janes, PhD, Abdera Therapeutics

  • isotope will deliver the payload without damaging the DNA and healthy tissue
  • target different types of tumors, different half-life
  • Radiation therapy using isotopes id one of two modalities: tumor in and tumor out approach
  • screen for patient for the translational therapy
  • Next generation of products will come, now it is the beginning of these agents

4:20 PM – 4:45 PM

Picasso Ballroom

Fireside

Fireside Chat

Moderator

Michael Ryskin, Life Science Tools & Diagnostics Analyst, BofA Global Research

  • Precision Medicine was it a paradigm shift??
  • Acquisition of manufacturing capabilities
  • research, manufacturinf line blurred
  • WHat excites you the most

Panelist

Marc Casper, Chairman, President & CEO, Thermo Fisher Scientific

  • Enabling Life sceinces, Pharmaceutical industries $1.5Billion internal investment annually
  • AI increasing knowledge
  • How is Precision Medicine applied? Sequencing in Cancer accelerated the Genomics information in use for 24 hours response of the sequence – adopted around the World.
  • at MGH lung cancers are treated with genomic sequencing
  • identification of the patients suitability for a targeted treatment
  • treatment during pregnacy at home vs hospitalization
  • History of company: Tools first: Mass spectrometry, one year for one sequence, protein identification and carrying to Mass spectrometry
  • Interactions need understanding acquiring electro spectrometry allowing analytical chemistry on proteins
  • Broad range of products: Clinical research to meet regulatory requirements entry into Reagents products.
  • Clinical Trials made effective by Thermo Scientific Products
  • Capabilities in registries, patient safety in psoriasis
  • Large role in experimental medicine drives efficiency in LABS
  • SIze of customers: small Biotech and large Pharma
  • Manufacture medicines: work with partnersbuilt by acquisitions small molecules,
  • 100 engagements research, supply chain making medicines available at sites
  • Role for AI at Thermo Scientific:
  1. Productivity – Cost effective for processes in use by 120,000 employees
  2. Super customer interaction perfected by interogations with internal manuals to provide answers quickly
  3. Improvement of products
  • Excitement Points: Responsiveness to COVID pandemic
  • New medicine development

4:50 PM – 5:30 PM

Picasso Ballroom

The Reemergence of ADCs, Precision Medicine, T-cell engagers, and Bispecifics: Oncology at Its Finest

 

Moderators

John Bishai, PhD, BofA

  • Approach to AI
  • Strategy regarding clinical trial design, vs molecule design

Justin Gainor, MD, MGH, HMS

  • How strategies are developed and then modified?
  • immune therapies work better open new paradeigm

Panelists

Moitreyee Chatterjee-Kishore, PhD, Head of Development, Immuno-Oncology and Cancer Cell Therapy, Astellas Pharma Inc.

  • cancer – first line of treatment vs 2nd and 3rd
  • Precision medicine more precise
  • mix and match immunotherapy and other modalities
  • small molecule early on
  • molecule formulation is science and art
  • Stratify the patient population early on
  • Help needed to design better trials
  • Research is key for molecule design

Niall Martin, PhD, CEO, Artios Pharma

  • peptide chemistry
  • molecule design had options several are applied
  • biomarker driven event in development cycle
  • strategy of biomarkers – lack structure
  • effect of combination therapy on survival?

Chris Varma, PhD, Co-founder, Chairman & CEO, Frontier Medicines

 

5:30 PM – 8:30 PM

South Lawn Tent

Attendee Reception and Dinner

Moderator

Anne Oxrider

Senior Vice President, Benefits Executive, Bank of America

Panelist

Deepak Chopra, MD

Founder, The Chopra Foundation

Wednesday, September 25, 2024

8:30 AM – 8:55 AM

Picasso Ballroom

Fireside

Fireside Chat

Moderators

David Ting, MD, Associate Clinical Director for Innovation, Mass General Cancer Center; Associate Professor of Medicine, Harvard Medical School

  • Innovation is the foundation of the future
  • Creative thinking vs one agent and one target
  • Openness is much appreciated

Jason Zemansky, PhD, SMid-Cap Biotech Analyst, BofA Global Research

  • On WSJ article on M&A in Biotech attributing decline in M&A of Biotech companies due to LACK of Innovations
  • Q from audience: organizational structure and innovation
  • Vision on leveraging Partnerships

Panelist

Tadaaki Taniguchi, MD, PhD, Chief Medical Officer, Astellas Pharma

  • Pharma and Biotech heavy betting on new medicines in Oncology
  • Astellas Pharma is different than other Pharma companies
  • We focus on Oncology and in combination therapies as a priority
  • Investment pay attention to Leadership priorities
  • One product vs BEST combination therapy for best treatment and outcomes
  • Innovations come from anywhere
  • ADCs: Target, payload emerged recently by a partnership
  • Collaborations: several pathways, several modalities, several combinations therapies
  • Partnership requires greater flexibility
  • Created Small flexible Labs to enable to innovate with Partners, “we can’t innovate alone”

9:00 AM – 9:40 AM

Picasso Ballroom

Disruptors

The Disruptors: The Role of Pathway Inhibition in Inflammation and Inflammatory Diseases

Moderators

Tazeen Ahmad, SMid-Cap Biotech Analyst, BofA Global Research

  • Are you using AI
  • Neuroinflammation

Cynthia Lemere, PhD, BWH, HMS

  • What systems are primarily impacted by the Immunes system
  • Drug delivery for inflammation huge area
  • Getting antibodies to the Brain
  • Precision medicine, genetics,specific person with specific immune disease

Panelists

Jo Viney, PhD, Cofounder, President & CEO, Seismic Therapeutic

  • Pandemics highlighted the impact of the immune system
  • Targeting cytokines in specific locations – hew approach
  • Modalities on hand: protein degradation mediation by bringing two cells together
  • AI is used for Patient stratification
  • AI to be used in Pathways involved in disease process to identify Biologics, PROTAC,
  • AI and ML for training models from interaction between proteins
  • ChatGPT to predict interactions among proteins
  • Immune disease and remission bust the immune system to improve quality of life of patient undergoing interventions
  • T-cell engaggers – in cases of refractory – great approach for boosting the immune system: removal of antibidies, recycling antibodies,
  • Two ends: Cell depletion vs Early detection
  • Therapy is every 6 months, cell depletion takes 3 months to come back.
  • Target immune system in the periphery,
  • Immune system in neurodegenerative diseases: Parkinson’s local modulation to penetrate neurological system
  • Markers to cross the BBB or not cross in neurological diseases
  • Immune disease is POLYGENIC multiple o=etiologies, mutation, genetics, which cell and which pathway to target a therapeutics: Biologics
  • Patient stratification is key for Precision Medicine at the cell level
  • T-cell, B-cell, Cytokines and antibodies mediated disease
  • ADGs degradation

9:45 AM – 10:10 AM

Picasso Ballroom

H. Jeffrey Wilkins, MD, Abcuro
  • Inflammation play a role in activating the immune system
  • zin the days of Medical School: inhibition of cytokines
  • Today: specificity to target cells for depletion
  • Specific biomarkers for response to therapies
  • cell types by mutations and physiology and causality in the inflammation area: we know why they have inflammation we need to learn interventions for inflammation
  • Asthma in the 40s as an inflammatory disease
  • assess treatment of inflammation
  • Neuro-inflammation – not well understood
  • What is the cause that drive the disease: understanding encephalitis?
NiranJana Nagarajan, PhD, MGB Ventures
  • Biology is the driver not AI
  • depletion of cells in a certain stage
  • Translation from disease to other diseases in the case of cell therapy potential – active area companies are trying solutions
  • Inflammation is a huge challenge to treat

 

Fireside

Fireside Chat

Moderators

Daniel Kuritzkes, MD, Chief, Division of Infectious Diseases, Brigham and Women’s Hospital; Harriet Ryan Albee Professor of Medicine, Harvard Medical School

  • Pathways in vaccine design
  • How to educate population on Vaccines
  • other approaches than vaccines

Alec Stranahan, PhD, SMid-Cap Biotech Analyst, BofA Global Research

  • Vaccine approval
  • Next generation vaccines

Panelist

Stéphane Bancel, CEO, Moderna

  • Vaccine design: long term vaccines weakens in aged population
  • data on role of AVV in Multiple Sclerosis
  • working on in the US vs France, Netherland in Europe different approaches
  • Vaccine for HIV
  • Vaccine was approved last year for children, pharmacies shortage
  • Season of FLu three times more vaccines in use
  • Employees run vaccine clinics on site
  • Vaccines not related to COVID
  • Misinformation from COVID vaccine
  • 5% of COVID hospitalized were on the booster
  • Combination vaccines for high risk populations
  • Healthcare providers need to be involved in Education, many do not have an interest in the education on vaccines
  • Local stories from Vaccine manufectures and developer to be used in education in the communities
  • Individual DNA cancer celll signature of the cancer  – data over time for development of vaccine to cancer many more tumor types are needed
  • Checkpoints in early disease
  • biopsy are too expensive
  • Side effect studies going on
  • mono-therapy vs immunotherapy costs involved
  • Naive virus to get into the Liver two diseases – cassets for sose management
  • Recombinant antibodies technology from the 70s
  • PD-1
  • COVID – was nto in the plan for development – design in silicon in two weeks – no change after this design
  • 10:10 AM – 10:20 AM

10:20 AM – 11:00 AM

Picasso Ballroom

The Innovation Gap: Understanding the Role of Cell Therapies in Autoimmune Disease

Moderator

Charlie Yang, PhD

Large/SMid-Cap Biotech and Major Pharma Analyst, BofA Global Research

  • TCM
  • CAR-T
  • advantages of each cell type

Angele Shen, MGB Innovations

  • CAR-T
  • What would be a quick breakthrough?

Panelists

Jeff Bluestone, PhD, CEO & President, Sonoma Biotherapeutics

  • Cell therapy for cell depletion elimination of B-cells like its role in Multiple Sclerosis
  • Working with regulatory T-cells
  • Population of cells to study: T-cells master regulator in multiple ways – produce metabolic factors, infection tone in activation of other cells
  • Biology of cell: RNA, DNA
  • TCR – target antigens in tissues they are in in immune suppression
  • FInding the right peptide bindes to a certain MAC
  • CAR-T – recornize the cells in the local milieu like in patients with RA as an autoimmune disease
  • Clinical models ascertain cell types involvement leading to clinical trial insights then to therapies on a decision tree
  • recent data on CAR-T immune response in allogeneic for potential use in neurodegenerative diseases
  • patients and companies over react on immune therapy: Patients and Science vs hype
  • next generation: POC,
  • Gene therapy specificities vs Cell therapies – each approach will develop a different drug
  • FDA and NIH has in 11/2023 a meeting on Regulation of Cell therapy on stability and their approach to immune disease where there are already several drugs
  • approvals challenges companies
  • Price, too expensive a treatment is cell therapy

Chad Cowan, PhD, Executive Advisor, Century Therapeutics

  • use Natural Killer cells to elicit long-term immune response, T-cells,
  • active Beta cells]Regulatory monitoring use
  • DM – regulatory cells made from Stem cells
  • mission durable response
  • Clinical issues – not easy way for treatment wiht a cell line and bioreactors and modalities less similar to autologoous celles
  • CAR-T in oncology lessons now are transferred to Immune disease
  • Cell therapy requires technologies to mature multiple modalities and multiple drugs not one cell therapy for all immune diseases
  • Stability of the therapy vs rejection by immune system
  • FDA making cells is not as making drugs – higher level of scrutiny for cell therapy
  • SYNTHETIC BIOLOGY on B-cells for future breakthrough

Samantha Singer, President & CEO, Abata Therapeutics

  • Immune response involve many cell types in many diseases
  • Oncology the use of T-cells as tissue residents staying in tissue long time
  • Specific biology of the disease and regulatory cells receptors optimizing TCR presentation in pathology of tissue residents phyno types
  • activate in nervous system or in pancreas – intersection of cell biology with disease biology
  • Market feasibility – scaling, biology, pathology for reimbursement
  • antibody therapy may be appropriate than cell therapy is only a novel option
  • Cell manufacturing requires optimization of process, companies commercializing across all cell types
  • comprehensive approach for systemic immune suppression
  • : healthy tissue vs diseased tissue with cell theray implanted cells as residents in tissue
  • clinical data on product performance and on the biology reactions

11:00 AM – 11:40 AM

Picasso Ballroom

Unmet Clinical Needs: 100 Harvard KOLs Weigh In

Moderators

Jose Florez, MD, PhD, Physician-in-Chief and Chair, Department of Medicine, Massachusetts General Hospital; Professor, Harvard Medical School

  • 40 minutes to deal with big needs collected from 100 faculties at Harvard Medical School
  • The ten issues on one slide
  • How could we use compute to distill data

Bruce Levy, MD, Physician-In-Chief and Co-Chair, Department of Medicine, Brigham and Women’s Hospital; Parker B. Francis Professor of Medicine, Harvard Medical School

  • Transformation from the Present to the Future
  • identifying the needs
  • Infectious diseases: Rapid diagnostics need
  • resistance to antibiotics and metabolic reactions endogenous
  • Pandemics globally of diseases erradicated in the past: Pox, polio
  • Improving health in Geriatrics, not population growing but geriatric population growing. Beyong age 60 a citizen will use 1 or 2 physicians each
  • 7,000 diseases, Genetic diseases requires integration and innovations in therapy
  • Innovations in Home devices

Panelists

Rox Anderson, MD, Lancer Endowed Chair of Dermatology;, Director, Wellman Center for Photomedicine, MGH; Professor of Dermatology, HMS

  • Access to data across institutions

Nicole Davis, PhD, Biomedical Communications

  • We asked 104 expert practitioners, content collected was analyzed
  1. detection early
  2. keeping the Human brain healthy
  3. geriatrics Medicine, aging and compound effects on health system with aging and Health equity
  • Bias in Data

Jean-François Formela, MD, Partner, Atlas Venture

  • genetic information used in therapeutics design

Steven Greenberg, MD, Neurologist, Brigham and Women’s Hospital; Professor of Neurology, Harvard Medical School

  • Human genome completed in 1999, human genetic diseases were discovered learn about the disease at the tissue level with genomics and a system approach
  • Pathogenic drivers, systme integration by therapeutics approaches to pathways multiple cytokines in allergic reactions Pfizer had two biomarkers and therapies for systemic biology of disease
  • Pediatrics has its own challenges
  • Imaging medicine
  • Living longer at a lower cost  – HOW TO ACHIEVE THAT?
  • growth abnormality in children: Body growth and Skull shrink

John Lepore, MD, CEO, ProFound Therapeutics;, CEO-Partner, Flagship Pioneering

  • Pathway, targeting therapy to patients in a System biological approach
  • Database of systme biology has missing components not included in the Human genome project – completion of the Data
  • Definition of End points needs revisiting
  • Identifying specific populations vs getting quickly to market
  • Diseases of aging: Muscles diseases – how to promote improvement in muscle mass

CONCLUSIONS

  1. Gray Tsunami
  2. Brain health
  3. Cancer treatment paradigm shift
  4. Fibrosis in many diseases
  5. infectious disease in changing World
  6. Equity in HC
  7. Clinical Data is VAST
  8. Systemic view of Human disease
  9. New approaches to Psychaitry
  10. Rare disease treatment needs a charter

In addition,

  • new generation of pain treatment
  • skin treatment new drugs
  • Chronic disease: improve treatment and prevention.
  • Obesity medicine – new discipline in a new Era

11:45 AM – 12:30 PM

Picasso Ballroom

Fireside

Fireside Chat

Moderators

Tazeen Ahmad, SMid-Cap Biotech Analyst, BofA Global Research

  • FDA sets criteria  – How is that done?
  • Autoimmune disease therapies – What is in the horizon?

 

Paul Anderson, MD, PhD, Chief Academic Officer, Mass General Brigham;

  • drug development
  • drug pricing in Europe
  • New book
  • RA needs more medicines

UNCONTROLLED SPREAD

In Uncontrolled Spread, a New York Times Best Seller, Dr. Scott Gottlieb identifies the reasons why the US was caught unprepared for the pandemic and how the country can improve its strategic planning to prepare for future viral threats.

Panelist

Scott Gottlieb, MD, Physician; Former Commissioner, Food and Drug Administration (2017-2019)

  • FDA approval 1st gene therapy in his tenure
  • Price of drugs: efficatious vs time to deveop
  • competitors in the marketplace are there for market share
  • New Book: Episodes in the FDA, appproval process at FDA, Gene therapy 1st in class approved – a special moment. Back in 1980s era translated to antibodies, to T-cell pioneering work.
  • Publisher worried it will not sell very well
  • FDA had concerns about manufacturing aspects
  • In 2024 we understand Biologics on novel platforms
  • Worries that Medicare will not reimbursement  and cover the new therapies: Cell therapy
  • Statins approval had a known very large market vs Cell therapy not known which Cancer patients will benefit???
  • Black box involved in Autoimmune, studies bring exciting results
  • In 2018 – needs arise for early approved of drugs in AD, amyloid plaque – change in thinking and is controversial
  • In early 2020, change in settings of clinical trials, placido no more the only way for Randomized trials
  • Approval for AD drug vs othe indication – the process is difference (DMD a case to think about)
  • AI & NLP: Train on data of 10,000 lesions
  • FDA choose not to regulate AI the physician is in the Middle
  • Who is wrong: CHatGPT or the clinician ?
  • Data set on gene may represents NEW biologies that Physicians had not seen before
  • Data validation on medical devices and their approval after regulating them
  • Diagnostics tests: Validation Panels are involved
  • Regulated on input data vs Output data and validate the input data
  • Platforms are needed for regulation of AI involvement in the drug discovery and the drug approval process
  • investment in this platforms will be done by Whom?? It will come
  • Framework for AI at FDA: Regulatory gray data for applications and standards for output – not a novel regulatory concept
  • If AI will be applied widely, I/O accuracy is a must have
  • may be achievable soon?
  • FDA is evolutionary organization in its decision process NOT a REVOLUTIONARY organization. Simulation work started in 2003, 40 people doing that then.
  • Recently, new team in Agency working of Safety with tools and technologies that are common in Science  – Approvals to drug labels and off labels that 20 years ago would not have happened
  • Tolerance for higher prices is to support Private sector that brings the innovating drugs to market

 

SPEAKERS

C-Suite Speakers

Faraz Ali

CEO, Tenaya Therapeutics

Peter Anastasiou

CEO, Capsida Biotherapeutics

Paul Anderson, MD, PhD

Chief Academic Officer, Mass General Brigham; K. Frank Austen Professor of Medicine, Harvard Medical School

Rahul Ballal, PhD

CEO, Mediar Therapeutics

Stéphane Bancel

CEO, Moderna

Craig Basson MD, PhD

Chief Medical Officer, Bitterroot Bio

Jeff Bluestone, PhD

CEO & President, Sonoma Biotherapeutics

Albert Bourla, PhD

Chairman & CEO, Pfizer

O’Neil Britton, MD

Chief Integration Officer & Executive Vice President, Mass General Brigham

Marc Casper

Chairman, President & CEO, Thermo Fisher Scientific

Joshua Cohen

Co-CEO, Amylyx Pharmaceuticals

Delos “Toby” Cosgrove, MD

Executive Advisor; former CEO & President, Cleveland Clinic

Jatin Dave, MD

Chief Medical Officer, MassHealth; Director of Clinical Affairs, UMass Chan Medical School

Punit Dhillon

CEO, Skye Bioscience

Steve Favaloro

Chairman & CEO, Genezen

John Fish

Chairman & CEO, Suffolk

Alexandria Forbes, PhD

CEO, MeiraGTx

Niyum Gandhi

CFO & Treasurer, Mass General Brigham

Chris Garabedian

Chairman & CEO, Xontogeny; Venture Portfolio Manager, Perceptive Advisors

Lucas Harrington, PhD

Co-Founder & CSO, Mammoth Biosciences

Marc Harrison, MD

Co-founder & CEO, Health Assurance Transformation Corp. (HATCo)

Amos Hedt

Chief Business Strategy Officer, Perspective Therapeutics

Rod Hochman, MD

President & CEO, Providence

David Hyman, MD

Chief Medical Officer, Eli Lilly and Company

Philip Kantoff, MD

Co-Founder & CEO, Convergent Therapeutics

Daniel Karlin, MD

Chief Medical Officer, MindMed

Reshma Kewalramani, MD

CEO & President, Vertex Pharmaceuticals

Justin Klee

Co-CEO, Amylyx Pharmaceuticals

Anne Klibanski, MD

President & CEO, Mass General Brigham; Laurie Carrol Guthart Professor of Medicine, Harvard Medical School

Samarth Kulkarni, PhD

CEO, CRISPR Therapeutics

Liz Kwo, MD

Chief Commercial Officer, Everly Health

Adam Landman, MD

Chief Information Officer & SVP, Digital, Mass General Brigham; Associate Professor of Emergency Medicine, Harvard Medical School

Chemu Lang’at

Chief Operating Officer, Best Buy Health

Paul LaViolette

Managing Partner & COO, SV Health Investors

John Lepore, MD

CEO, ProFound Therapeutics; CEO-Partner, Flagship Pioneering

Christopher Longhurst, MD

Chief Medical & Digital Officer, UC San Diego Health

Kevin Mahoney

CEO, University of Pennsylvania Health System

Niall Martin, PhD

CEO, Artios Pharma

James Mawson

CEO, Global Corporate Venturing

Mark McKenna

Chairman & CEO, Mirador Therapeutics

Jane Moran

Chief Information and Digital Officer, Mass General Brigham

William Morris, MD

Chief Medical Information Officer, Google Cloud

Rohan Palekar

CEO, 89bio

Raju Prasad, PhD

Chief Financial Officer, CRISPR Therapeutics

Xiayang Qiu, PhD

CEO, Regor Therapeutics

Harith Rajagopalan MD, PhD

CEO & Co-Founder, Fractyl Health

Shiv Rao, MD

CEO & Founder, Abridge

Kerry Ressler, MD, PhD

Chief Scientific Officer, McLean Hospital; Professor of Psychiatry, Harvard Medical School

Matthew Roden, PhD

President & CEO, Aktis Oncology

Sandi See Tai, MD

Chief Development Officer, Lexeo Therapeutics

Samantha Singer

President & CEO, Abata Therapeutics

Joanne Smith-Farrell, PhD

CEO & Director, Be Biopharma

Emma Somers-Roy

Chief Investment Officer, Mass General Brigham

Adam Steensberg, MD

President & CEO, Zealand Pharma

Tadaaki Taniguchi, MD, PhD

Chief Medical Officer, Astellas Pharma

Elsie Taveras, MD

Chief Community Health & Health Equity Officer, Mass General Brigham; Conrad Taff Endowed Chair and Professor of Pediatrics, Harvard Medical School

Jo Viney, PhD

Cofounder, President & CEO, Seismic Therapeutic

Ron Walls, MD

Chief Operating Officer, Mass General Brigham; Neskey Family Professor of Emergency Medicine, Harvard Medical School

Christophe Weber

President & CEO, Takeda

Fraser Wright, PhD

Chief Gene Therapy Officer, Kriya Therapeutics

Speakers

Anna Åsberg

Vice President, AstraZeneca Pharmaceuticals

Tazeen Ahmad

SMid-Cap Biotech Analyst, BofA Global Research

Jessica Allegretti, MD

Director, Crohn’s and Colitis Center, Brigham and Women’s Hospital; Associate Professor of Medicine, Harvard Medical School

Rox Anderson, MD

Lancer Endowed Chair of Dermatology; Director, Wellman Center for Photomedicine, MGH; Professor of Dermatology, HMS

Katherine Andriole, PhD

Director of Academic Research and Education, Mass General Brigham Data Science Office; Associate Professor, Harvard Medical School

Caroline Apovian, MD

Co-Director, Center for Weight Management and Wellness, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Vanita Aroda, MD

Director, Diabetes Clinical Research, Brigham and Women’s Hospital; Associate Professor, Harvard Medical School

Natalie Artzi, PhD

Associate Professor of Medicine, Brigham and Women’s Hospital & Harvard Medical School

John Bishai, PhD

Global Healthcare Investment Banking, BofA Securities

David Blumenthal, MD

Professor of Practice of Public Health and Health Policy, Harvard TH Chan School of Public Health; Research Fellow, Harvard Kennedy School of Government; Samuel O. Thier Professor of Medicine, Emeritus, Harvard Medical School

Giles Boland, MD

President, Brigham and Women’s Hospital and Brigham and Women’s Physicians Organization; Philip H. Cook Distinguished Professor of Radiology, Harvard Medical School

Andrew Bressler

Washington Healthcare Policy Analyst, BofA Global Research

James Brink, MD

Enterprise Chief, Radiology, Mass General Brigham; Juan M. Taveras Professor of Radiology, Harvard Medical School

David Brown, MD

President, Academic Medical Centers, Mass General Brigham; Mass General Trustees Professor of Emergency Medicine, Harvard Medical School

Tyler Bryson

Corporate Vice President, US Health & Public Sector Industries, Microsoft Corporation

Jonathan Carlson, MD, PhD

Director of Chemistry, Center for Systems Biology, Massachusetts General Hospital; Assistant Professor of Medicine, Harvard Medical School

Miceal Chamberlain

President of Massachusetts, Bank of America

Moitreyee Chatterjee-Kishore, PhD

Head of Development, Immuno-Oncology and Cancer Cell Therapy, Astellas Pharma Inc.

Dong Feng Chen, MD, PhD

Associate Scientist, Massachusetts Eye and Ear; Associate Professor, Harvard Medical School

Jasmeer Chhatwal, MD, PhD

Associate Neurologist, Massachusetts General Hospital; Associate Professor of Neurology, Harvard Medical School

E. Antonio Chiocca, MD, PhD

Chair, Department of Neurosurgery, Brigham and Women’s Hospital; Harvey W. Cushing Professor of Neurosurgery, Harvard Medical School

Bryan Choi, MD, PhD

Associate Director, Center for Brain Tumor Immunology and Immunotherapy, Massachusetts General Hospital; Assistant Professor of Neurosurgery, Harvard Medical School

Deepak Chopra, MD

Founder, The Chopra Foundation

Yolonda Colson, MD, PhD

Chief, Division of Thoracic Surgery, Massachusetts General Hospital; Hermes C. Grillo Professor of Surgery, Harvard Medical School

Chad Cowan, PhD

Executive Advisor, Century Therapeutics

Cristina Cusin, MD

Director, MGH Ketamine Clinic and Psychiatrist, Depression Clinical and Research Program, Massachusetts General Hospital; Associate Professor in Psychiatry, Harvard Medical School

Nicole Davis, PhD

Biomedical Communications

Marcela del Carmen, MD

President, Massachusetts General Hospital and Massachusetts General Physicians Organization (MGPO); Executive Vice President, Mass General Brigham; Professor of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School

Gerard Doherty, MD

Surgeon-in-Chief, Mass General Brigham Cancer; Surgeon-in-Chief, Brigham and Women’s Hospital; Moseley Professor of Surgery, Harvard Medical School

Liz Everett Krisberg

Head of Bank of America Institute

Maurizio Fava, MD

Chair, Department of Psychiatry, Massachusetts General Hospital; Slater Family Professor of Psychiatry, Harvard Medical School

Keith Flaherty, MD

Director of Clinical Research, Mass General Cancer Center; Professor of Medicine, Harvard Medical School

Jose Florez, MD, PhD

Physician-in-Chief and Chair, Department of Medicine, Massachusetts General Hospital; Professor, Harvard Medical School

Jean-François Formela, MD

Partner, Atlas Venture

Fritz François, MD

Executive Vice President and Vice Dean, Chief of Hospital Operations, NYU Langone Health

Joanna Gajuk

Health Care Facilities and Managed Care Analyst, BofA Global Research

Jason Gerberry

Specialty Pharma and SMid-Cap Biotech Analyst, BofA Global Research

Gad Getz, PhD

Director of Bioinformatics, Krantz Center for Cancer Research and Department of Pathology; Paul C. Zamecnik Chair in Cancer Research, Mass General Cancer Center; Professor of Pathology, Harvard Medical School

Alexandra Golby, MD

Neurosurgeon; Director of Image-guided Neurosurgery, Brigham and Women’s Hospital; Professor of Neurosurgery, Professor of Radiology, Harvard Medical School

Allan Goldstein, MD

Chief of Pediatric Surgery, Massachusetts General Hospital; Surgeon-in-Chief, Mass General for Children; Marshall K. Bartlett Professor of Surgery, Harvard Medical School

Scott Gottlieb, MD

Physician; Former Commissioner, Food and Drug Administration (2017-2019)

David Grayzel, MD

Partner, Atlas Venture

Steven Greenberg, MD

Neurologist, Brigham and Women’s Hospital; Professor of Neurology, Harvard Medical School

Steven Grinspoon, MD

Chief, Metabolism Unit, Massachusetts General Hospital; Professor of Medicine, Harvard Medical School

Daphne Haas-Kogan, MD

Chief, Enterprise Radiation Oncology, Mass General Brigham; Professor, Harvard Medical School

Roger Hajjar, MD

Director, Gene & Cell Therapy Institute, Mass General Brigham

John Hanna, MD, PhD

Associate Professor, Brigham and Women’s Hospital & Harvard Medical School

Yvonne Hao

Secretary of Economic Development, Commonwealth of Massachusetts

Nobuhiko Hata PhD

Director, Surgical Navigation and Robotics Laboratory, Brigham and Women’s Hospital; Professor of Radiology, Harvard Medical School

Maura Healey

Governor of the Commonwealth of Massachusetts

Elizabeth Henske, MD

Director, Center for LAM Research and Clinical Care, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Leigh Hochberg MD, PhD

Director of Neurotechnology and Neurorecovery, Massachusetts General Hospital; Senior Lecturer on Neurology, Harvard Medical School

Daphne Holt, MD, PhD

Director of the Resilience and Prevention Program, Massachusetts General Hospital; Associate Professor of Psychiatry, Harvard Medical School

Susan Huang, MD

EVP, Chief Executive, Providence Clinical Network, Providence Southern CA

Keith Isaacson, MD

Director of Minimally Invasive Gynecologic Surgery and Infertility, Newton Wellesley Hospital; Associate Professor of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School

Ole Isacson, MD-PhD

Founding Director, Neuroregeneration Research Institute, McLean Hospital; Professor of Neurology and Neuroscience, Harvard Medical School

Haim Israel

Head of Global Thematic Investing Research, BofA Global Research

Farouc Jaffer, MD, PhD

Director, Coronary Intervention, Massachusetts General Hospital; Associate Professor of Medicine, Harvard Medical School

Russell Jenkins, MD, PhD

Krantz Family Center for Cancer Research, Massachusetts General Hospital; Mass General Cancer Center, Center for Melanoma; Assistant Professor of Medicine, Harvard Medical School

Hadine Joffe, MD

Executive Director of the Connors Center for Women’s Health and Gender Biology; Interim Chair, Department of Psychiatry, Brigham and Women’s Hospital; Paula A. Johnson Professor of Psychiatry in the Field of Women’s Health, Harvard Medical School

Benjamin Kann, MD

Assistant Professor, Brigham and Women’s Hospital & Harvard Medical School

Tatsuo Kawai, MD, PhD

Director of the Legorreta Center for Clinical Transplantation Tolerance, A.Benedict Cosimi Chair in Transplant Surgery, Massachusetts General Hospital; Professor of Surgery, Harvard Medical School

Albert Kim, MD

Assistant Physician, Mass General Cancer Center; Assistant Professor, Harvard Medical School

Roger Kitterman

Senior Vice President, Ventures and Business Development & Licensing, Mass General Brigham Managing Partner, Mass General Brigham Ventures

Lotte Bjerre Knudsen, DMSc

Chief Scientific Advisor, Novo Nordisk

Vesela Kovacheva, MD, PhD

Director of Translational and Clinical Research, Mass General Brigham; Assistant Professor of Anesthesia, Harvard Medical School

Jonathan Kraft

President, The Kraft Group; Board Chair, Massachusetts General Hospital

John Krystal, MD

Chair, Department of Psychiatry, Yale School of Medicine

Daniel Kuritzkes, MD

Chief, Division of Infectious Diseases, Brigham and Women’s Hospital; Harriet Ryan Albee Professor of Medicine, Harvard Medical School

Bruce Levy, MD

Physician-In-Chief and Co-Chair, Department of Medicine, Brigham and Women’s Hospital; Parker B. Francis Professor of Medicine, Harvard Medical School

Katherine Liao, MD

Associate Physician, Department of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital; Associate Professor of Medicine and Biomedical Informatics, Harvard Medical School

David Louis, MD

Enterprise Chief, Pathology, Mass General Brigham Benjamin Castleman Professor of Pathology, Harvard Medical School

Tim Luker, PhD

VP, Ventures & West Coast Head, Eli Lilly

Andrew Luster, MD, PhD

Chief, Division of Rheumatology, Allergy and Immunology; Director, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital; Persis, Cyrus and Marlow B. Harrison Professor of Medicine, Harvard Medical School

Allen Lutz

Health Care Services Analyst, BofA Global Research

Calum MacRae MD, PhD

Vice Chair for Scientific Innovation, Department of Medicine, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Joren Madsen, MD, PhD

Director, MGH Transplant Center; Paul S. Russell/Warner-Lambert Professor of Surgery, Harvard Medical School

Faisal Mahmood, PhD

Associate Professor, Brigham and Women’s Hospital & Harvard Medical School

Peter Marks, MD, PhD

Director, Center for Biologics Evaluation and Research, FDA

Marcela Maus, MD, PhD

Director of Cellular Therapy and Paula O’Keeffe Chair in Cancer Research, Krantz Family Center for Cancer Research and Mass General Cancer Center; Associate Director, Gene and Cell Therapy Institute, Mass General Brigham; Associate Professor, Harvard Medical School

Thorsten Mempel, MD, PhD

Associate Director, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital; Professor of Medicine, Harvard Medical School

Rebecca Mishuris, MD

Chief Medical Information Officer, Mass General Brigham; Member of the Faculty, Harvard Medical School

Pradeep Natarajan, MD

Director of Preventive Cardiology, Paul & Phyllis Fireman Endowed Chair in Vascular Medicine, Massachusetts General Hospital; Associate Professor of Medicine, Harvard Medical School

Nawal Nour, MD

Chair, Department of Obstetrics and Gynecology, Brigham and Women’s Hospital; Associate Professor, Kate Macy Ladd Professorship, Harvard Medical School

Heather O’Sullivan, MS, RN, AGNP

President, Mass General Brigham Healthcare at Home

Anne Oxrider

Senior Vice President, Benefits Executive, Bank of America

Claire-Cecile Pierre, MD

Vice President, Community Health Programs, Mass General Brigham; Instructor in Medicine, Harvard Medical School

Richard Pierson III, MD

Scientific Director, Center for Transplantation Sciences, Massachusetts General Hospital; Professor of Surgery, Harvard Medical School

Mark Poznansky, MD, PhD

Director, Vaccine and Immunotherapy Center, Massachusetts General Hospital; Steve and Deborah Gorlin MGH Research Scholar; Professor of Medicine, Harvard Medical School

Yakeel Quiroz, PhD

Director, Familial Dementia Neuroimaging Lab and Director, Multicultural Alzheimer’s Prevention Program, Massachusetts General Hospital; Paul B. and Sandra M. Edgerley MGH Research Scholar; Associate Professor, Harvard Medical School

Heidi Rehm, PhD

Chief Genomics Officer, Massachusetts General Hospital; Professor of Pathology, Harvard Medical School

Leonardo Riella, MD, PhD

Medical Director of Kidney Transplantation, Massachusetts General Hospital; Harold and Ellen Danser Endowed Chair in Transplantation, Harvard Medical School

Jorge Rodriguez, MD

Clinician-investigator, Brigham and Women’s Hospital; Assistant Professor, Harvard Medical School

Adam Ron

Health Care Facilities and Managed Care Analyst, BofA Global Research

David Ryan, MD

Physician-in-Chief, Mass General Brigham Cancer; Professor of Medicine, Harvard Medical School

Michael Ryskin

Life Science Tools & Diagnostics Analyst, BofA Global Research

Alkesh Shah

Head of US Equity Software Research, BofA Global Research

Angela Shen, MD

Vice President, Strategic Innovation Leaders, Mass General Brigham Innovation

Gregory Simon

President, Simonovation

Prabhjot Singh, MD, PhD

Senior Advisor, Strategic Initiatives Peterson Health Technology Institute

Brendan Singleton

Healthcare Equity Capital Markets, BofA Securities

Caroline Sokol, MD, PhD

Assistant Physician, Massachusetts General Hospital; Assistant Professor, Harvard Medical School

Daniel Solomon, MD

Matthew H. Liang Distinguished Chair in Arthritis and Population Health, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Scott Solomon, MD

Director, Clinical Trials Outcomes Center; Edward D. Frohlich Distinguished Chair in Cardiovascular Pathophysiology, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School

Fatima Cody Stanford, MD

Obesity Medicine Physician Scientist, Massachusetts General Hospital; Associate Professor of Medicine and Pediatrics, Harvard Medical School

Shannon Stott, PhD

Associate Investigator, Krantz Family Center for Cancer Research and Mass General Cancer Center; d’Arbeloff Research Scholar, Massachusetts General Hospital; Associate Investigator, Krantz Family Center for Cancer Research Harvard Medical School

Alec Stranahan, PhD

SMid-Cap Biotech Analyst, BofA Global Research

Marc Succi, MD

Executive Director, Mass General Brigham MESH Incubator; Associate Chair of Innovation & Commercialization, Mass General Brigham Radiology; Assistant Professor, Harvard Medical School

Guillermo Tearney, MD, PhD

Principal Investigator, Wellman Center for Photomedicine, Massachusetts General Hospital; Remondi Family Endowed MGH Research Institute Chair; Professor of Pathology, Harvard Medical School

David Ting, MD

Associate Clinical Director for Innovation, Mass General Cancer Center; Associate Professor of Medicine, Harvard Medical School

Raul Uppot, MD

Interventional Radiologist, Massachusetts General Hospital; Associate Professor, Harvard Medical School

Chris Varma, PhD

Co-founder, Chairman & CEO, Frontier Medicines

Kaveeta Vasisht, MD, PharmD

Associate Commissioner, Women’s Health, U.S. Food and Drug Administration

Alexandra-Chloé Villani PhD

Investigator, Massachusetts General Hospital; Assistant Professor, Harvard Medical School

Kate Walsh

Secretary of Health and Human Services, State of Massachusetts

David Walt, PhD

Professor of Pathology, Brigham and Women’s Hospital; Hansjörg Wyss Professor of Biologically Inspired Engineering, Harvard Medical School

Jennifer Warner-Schmidt, PhD

Vice President, Scientific Affairs, Transcend Therapeutics

Renee Wegrzyn, PhD

Director, Advanced Research Projects Agency for Health

Christoph Westphal, MD, PhD

General Partner, Longwood Fund

Deborah Wexler, MD

Chief, Diabetes Unit, Massachusetts General Hospital; Associate Professor of Medicine, Harvard Medical School

Charlie Yang, PhD

Large/SMid-Cap Biotech and Major Pharma Analyst, BofA Global Research

Nathan Yozwiak, PhD

Head of Research, Gene and Cell Therapy Institute, Mass General Brigham

Jason Zemansky, PhD

SMid-Cap Biotech Analyst, BofA Global Research

Alice Zheng, MD

Principal, RH Capital

We continue to confirm more speakers. Please check back regularly for updates.

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Drug Development Process been Revolutionized by Artificial Intelligence (AI) Technologies

Curators: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

 

The Voice of Stephen J. Williams, PhD

LPBI Group, CSO

PENDING

The Voice of Aviva Lev-Ari, PhD, RN

1.0 LPBI Group and 2.0 LPBI Group, Founder

With the advent of AI in the last 5-7 years in our fields: Pharmaceutical, Life Sciences and Medicine, LPBI Group had launched several initiatives to advance the frontier of knowledge by using our own contents repositories of +8 giga bytes for experimenting with Machine Learning (ML) technologies for Medical Text Analysis.

These AI Technologies include

  • Natural Language Processing (NLP): Statistical ML and Deep Learning ML
  • ChatGPT and GPT-4
  • Generative AI
A quote by Brad Power, Co-founder and CEO, Cancer Patient Lab made in January 2024
LPBI Group is in the admirable position of sitting on a treasure trove of medical literature that would be useful input in the current environment of customized ChatGPTs looking for reliable medical content.

In the Drug Development (DD) field, AI technologies are been employed  chiefly, for these tasks:

(a) Generation of molecular information libraries

(b) Explorations and combinatorial experiments on protein structures, and

(c) measurements of biochemical interactions

The A.I. learns from patterns in the data to suggest possible useful drug candidates, as if matching chemical keys to the right protein locks.

Because A.I. for drug development is powered by precise scientific data, toxic “hallucinations” are far less likely than with more broadly trained chatbots. And any potential drug must undergo extensive testing in labs and in clinical trials before it is approved for patients.

“Generative A.I. is transforming the field, but the drug-development process is messy and very human,” said David Baker, a biochemist and director of the Institute for Protein Design at the University of Washington.

As of December 2023,

  • 24 AI-discovered molecules had completed Phase I trials, with 21 of them being successful. This success rate of 80–90% is higher than the historical industry average of 40–65%. 
  • In Phase II trials, the success rate is around 40%, which is similar to the historical average. 

SOURCE

AI Overview

https://www.google.com/search?q=A.I.-developed+drugs+are+in+clinical+trials&oq=A.I.-developed+drugs+are+in+clinical+trials&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQIRigATIHCAIQIRigATIHCAMQIRigAdIBCTIxNzZqMGoxNagCCLACAQ&sourceid=chrome&ie=UTF-8

 

Examples of drugs developed by AI technologies:

NCI definition of AI Drugs:

AI drug

A drug that blocks the activity of an enzyme called aromatase, which the body uses to make estrogen in the ovaries and other tissues. Blocking aromatase lowers the amount of estrogen made by the body, which may stop the growth of cancer cells that need estrogen to grow. AI drugs are used to treat some types of breast cancer or to keep it from coming back. They may also be used to help prevent breast cancer in some women who are at a high risk of developing it. Examples of AI drugs are anastrozole, letrozole, and exemestane. AI drugs are a type of hormone therapy. Also called aromatase inhibitor.
 

SOURCE

https://www.cancer.gov/publications/dictionaries/cancer-terms/def/ai-drug

 

More examples of AI Drugs, Drugs developed with AI technologies

#1: 

INS018_055
Developed by Insilico Medicine, a Hong Kong-based biotech startup, to treat idiopathic pulmonary fibrosis (IPF). IPF is a chronic lung disease that causes scarring and can be fatal if left untreated. In January 2023, Insilico Medicine announced positive results from a Phase I safety trial of INS018_055. In February 2023, the FDA granted breakthrough status to a small molecule inhibitor identified by Insilico Medicine’s AI platforms for the drug. As of November 2023, INS018_055 was in mid-stage trials in the US and China, with some results expected in early 2025.
 
The first fully A.I. -generated drug enters clinical trials in human patients. Insilico Medicine, a Hong Kong-based biotech startup with more than $400 million in funding, created the drug as a treatment for idiopathic pulmonary fibrosis, a chronic lung disease.Jun 29, 2023
 
  • Schrödinger’s AI-driven platform
    Uses predictive modeling to optimize the molecular structure of drugs. AI is expected to integrate more advanced simulation techniques, such as quantum computing, to more accurately predict molecular behavior.

Drug discovery software developer Schrodinger Inc. (NASDAQ: SDGR) stock has been trying to recover after plummeting over 80% off its all-time high of $117 in January 2021. Schrodinger’s artificial intelligence (AI) powered software technology platform utilizes physics-based modeling and sophisticated machine learning algorithms to help clients identify the suitable molecules to treat the desired ailments. Its programs can help predict the behavior of molecules and potential outcomes.

This entails finding suitable molecules that effectively target specific cells and proteins, transcend through cell walls, are absorbed and dissolved well without interfering with other drugs or producing bad reactions to other drugs, and are scalable.

Big Name Pharma Customers of Schrödinger, Inc.

Its technology platform allows for the faster and cheaper discovery of novel molecules with a higher success rate than traditional methods. Its clients include the top 20 pharmaceutical companies in the world, including Pfizer Inc. (NYSE: PFE)Merck & Co. Inc. (NYSE: MRK), Takeda, AstraZeneca PLC (NYSE: AZN), and GlaxoSmithKline plc  (NYSE: GSK). It closed new agreements with Eli Lilly & Co. (NYSE: LLY) and Otsuka Pharmaceuticals out of Tokyo, Japan.

SOURCE

Schrodinger is an AI-Powered Drug Discovery Developer to Watch

https://www.nasdaq.com/articles/schrodinger-is-an-ai-powered-drug-discovery-developer-to-watch

 

Schrodinger’s Pipelines include:

  • SGR-1505 (MALT1)

Hematologic Malignancies

DISCOVERYPRECLINICALPHASE 1
 
  • SGR-2921 (CDC7)

AML/MDS

DISCOVERYPRECLINICALPHASE 1
 
  • SGR-3515 (Wee1/Myt1)

Solid Tumors

DISCOVERYPRECLINICALPHASE 1
 
  • SOS1

Oncology

DISCOVERYPRECLINICALPHASE 1
 
  • PRMT5-MTA

Oncology

DISCOVERYPRECLINICALPHASE 1
 
  • EGFRC797S

Oncology

DISCOVERYPRECLINICALPHASE 1
 
  • NLRP3

Immunology

DISCOVERYPRECLINICALPHASE 1
 
  • LRRK2

Neurology

DISCOVERYPRECLINICALPHASE 1
 
  • Undisclosed Programs

Multiple Areas

SOURCE

https://www.schrodinger.com/pipeline/#Proprietary-Pipeline

 

In high-tech labs, workers are generating data to train A.I. algorithms to design better medicine, faster. But the transformation is just getting underway.

Terray Therapeutics campus in Monrovia, Calif., June 17, 2024

https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html?smid=nytcore-ios-share&referringSource=articleShare

 

Five AI drug discovery companies you should know about

  1. Atomwise 
  2. Cradle 
  3. Exscientia 
  4. Iktos 
  5. Insilico Medicine 

According to Grand View Research, the global AI in drug discovery market size was valued at $1.1 billion in 2022, and is expected to expand at a compound annual growth rate (CAGR) of 29.6% from 2023 to 2030. The report states that the growing demand for the discovery and development of novel drug therapies and increasing manufacturing capacities of the life science industry are driving the demand for AI-empowered solutions in the drug discovery processes. 

As this report suggests, AI for drug discovery is clearly a growing field within the biopharma industry. Inevitably, as it grows even larger, we will see more companies come to the forefront of the field, hoping to change the face of drug discovery – and also the biopharma industry as a whole – so that the entire drug development process can become faster, more consistent, more accurate, and more scalable.

SOURCE

https://www.labiotech.eu/best-biotech/ai-drug-discovery-companies/#:~:text=to%20%2433%20million.-,Exscientia,manner%20using%20its%20AI%20technology.

 

At LPBI Group, Of Note is our Journal PharmaceuticalIntelligence.com

it represents our commitment to AI technologies in the following research categories and How many articles have been written in each of these topics: 

  • A total of x articles have been categorized 511 times among the following Artificial Intelligence research categories

Artificial Intelligence – General

113

An executive’s guide to AI

9

Artificial Intelligence – Breakthroughs in Theories and Technologies

94

Artificial Intelligence Applications in Health Care

81

Artificial Intelligence in CANCER

29

Artificial Intelligence in Health Care – Tools & Innovations

55

Artificial Intelligence in Medicine – Application for Diagnosis

44

Artificial intelligence applications for cardiology

21

AI-assisted Cardiac MRI

9

Artificial Intelligence in Psychiatry

5

Artificial Intelligence in Medicine – Applications in Therapeutics

50

 

LPBI Group’s involvement in Conceptual Drug Development covers the following two areas:

DrugDiscovery @LPBI Group, 2016 – 2018

Synthetic Biology in Drug Discovery, 2021 – Present

 

Applications of Artificial Intelligence to Medicine

Artificial Intelligence: Genomics & Cancer, 2021 – Present

Medicine with GPT-4 & ChatGPT, 2023 – Present

 

LPBI Group commitment to Medical Text Analysis using Machine Learning

2021-2025 Medical Text Analysis (NLP), 2020 – Present

ChatGPT + Wolfram PlugIn, 2023 – Present

 

LPBI Group Team members published two books on Drug Delivery Technologies

We had covered drug delivery technologies in two of our books. See all the Books: 

https://www.amazon.com/s?k=Aviva+Lev-Ari&i=digital-text&rh=n%3A133140011&ref=nb_sb_noss

 

  • Series E, Volume Four 

Medical 3D BioPrinting – The Revolution in Medicine, Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices. 

https://www.amazon.com/dp/B078QVDV2W

and

  • Series C, Volume Two 

Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery (Series C Book 2).

http://www.amazon.com/dp/B071VQ6YYK

 

The Table of Contents of these two book can be found in our

Spanish-language Edition, as well

  • Serie E, Volumen 4

Bioimpresión médica en 3D: la revolución de la medicina: Tecnologías para una medicina centrada en el paciente: de la I+D en agentes biológicos a los nuevos … en el paciente nº 4) (Spanish Edition) 2023

(Spanish Edition) Kindle Edition

https://www.amazon.com/dp/B0BRNVDB1P $56

 

  • Serie C, Volumen 2

Tratamientos contra el cáncer: Metabólicos, genómicos, intervencionistas, inmunoterapia y nanotecnología para la administración de tratamientos (Serie … y la oncología nº 2) 2022

(Spanish Edition) Kindle Edition

http://www.amazon.com/dp/B0BQTM44SM $75

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Live Conference Coverage: International Dialogue in Gynecological Oncology, From Bench to Bedside, Ovarian Cancer

Reporter: Stephen J. Williams, Ph.D.

Join Live on Wednesday May 22, 2024 for an international discussion on the current state of ovarian cancer diagnostics and therapeutics, and potential therapies and biomarkers, and biotargets.  Topics including potential new molecular targets for development of ovarian therapeutics, current changes in ovarian cancer clinical treatment protocols, chemo-resistance, and the use of Artificial Intelligence (AI) in the diagnosis and treatment of cancer will be discussed.

International Dialogue in Gynecological Oncology, From Bench to Bedside, ovarian Cancer meeting flyer

To join by Zoom click the link below

https://temple.zoom.us/j/94458267823 

Agenda:

Introduction

  • 00/15.00 Professor Giordano and Professor Ercoli
  • 10/15.10 We Have Never Been Only Human: a new perspective to defeat ovarian cancer (C. Martinelli)

Molecular Section

  • 20/15.20 DNA Repair mechanisms: understanding their role in cancer development and chemoresistance (L. Alfano)
  • 35/15.35 Progranulins: a new target for oncological treatment (A. Morrione)
  • 50/15.50 Modulation of gene expression and its applications (M. Cuomo)
  • 10.05/16.05 Commanding the cell cycle: the role of CDKs (S.R. Burk
  • 10.20/16.20 Drug development from nature (M. D’Angelo

Clinical Section

  • 05/17.05 Core principles of Radiologic Diagnosis & Staging in Ovarian Cancer(A. Blandino)
  • 20/17.20 Key Indications for Nuclear Medicine in Ovarian Cancer (S. Baldari)
  • 35/17.35 Cutting Edge Decision: Understanding Surgical Indications and Outcomes in Ovarian Cancer (A. Ercoli)
  • 50/17.50 Gold Standard in Oncology for Ovarian Cancer (N. Silvestris)
  • 12.05/18.05 Role of Radiotherapy in Ovarian Cancer (S. Pergolizzi)

Conclusion

12.20/18.20 AI Applied to medical science (V. Carnevale)

Speakers

  • – Professor Alfredo Blandino: Professor Blandino holds the esteemed positions of Head of school of Radiology and director of the department of radiology at the University of Messina. He has made significant contributions to diagnostic imaging with over hundreds of publications to his name, Professor Blandino’s work exemplifies excellence and innovation in radiology.
  • – Professor Alfredo Ercoli, serves as the Director of the Department of Gynecology and Obstetrics at the “G. Martino” University Hospital in Messina. He is also head of school of gynecology and obstetrics at Messina University. Starting his research in France with studies on pelvic anatomy that became a cornerstone in medical literature, He is a pioneer in advanced gynecologic surgery, including laparoscopic and robotic procedures, having performed over thousands of surgical interventions. His research focuses on gynecologic oncology, advanced gynecologic surgery, and endometriosis, urogynecology. Professor Ercoli’s dedication to education and his numerous publications have significantly advanced the field of gynecology.
  • Professor Sergio Baldari, an eminent figure in nuclear medicine. Professor Baldari is the Director of the department of nuclear medicine and head of school of nuclear medicine at the  University of Messina. He has authored or co-authored over 500 publications, with a focus on diagnostic imaging and the use of PET and radiopharmaceuticals in cancer treatment. His leadership and expertise have been recognized through various prestigious positions and awards within the medical community.
  • – Professor Nicola Silvestris is the Director of UOC Oncologia Medica at the University of Messina. His extensive research in cancer, has led to over 360 peer-reviewed publications. Professor Silvestris has made significant contributions to translational research and the development of guidelines for managing complex oncological conditions. His work continues to shape the future of cancer treatment.
  • Professor Stefano Pergolizzi, a leading expert in radiation oncology. Professor Pergolizzi serves as the Director of the department of radiotherapy and head of the school of radiotherapya at the University of Messina. He is also the president of the Italian Association of Radiotherapy and Clinical Oncology (AIRO) His research focuses on advanced radiotherapy techniques for cancer treatment. With a career spanning several decades, Professor Pergolizzi has published numerous papers and has been instrumental in developing innovative therapeutic approaches. His dedication to patient care and education is exemplary.
  • Margherita D’angelo: Graduated in Molecular Biology with honors from the Federico II University of Naples.
    Third year intern in Food Science at the Luigi Vanvitelli University of Naples.
    Research intern in Molecular oncology with the project of developing novel drugs starting from food waste at the Sbarro Institute for Cancer Research and Molecular Medicine at Temple University, Philadelphia (USA), directed by Dr A. Giordano.
  • Vincenzo Carnevale, Ph.D.

Dr. Carnevale is an Associate Professor in the Institute for Computational Molecular Science in the College of Science & Technology, Temple University.  He holds multiple NIH RO1 and NSF grants. Vincenzo Carnevale received B.Sc. and M.Sc. degrees in Physics from the University of Pisa and a PhD from SISSA – Scuola Internazionale Superiore di Studi Avanzati in Trieste, Italy. The Carnevale research group uses statistical physics and machine learning approaches to investigate sequence-structure-function relations in proteins. A central theme of the group’s research is how interactions give rise to collective phenomena and complex emergent behaviors. At the level of genes, the group is interested in epistasis – the complex entanglement phenomenon that causes amino acids to evolve in a concerted fashion – and how this shapes molecular evolution. At the cellular level, the group investigates how intermolecular interactions drive biomolecules toward self-organization and pattern formation. A long-term goal of the group is understanding the molecular underpinnings of electrical signaling in excitable cells. Toward these goals, the group applies and actively develops an extensive arsenal of theoretical and computational approaches including statistical (mean)field theories, Monte Carlo and molecular dynamics simulations, statistical inference of generative models, and deep learning.

  • Professor Andrea Morrione, Ph.D: Research Associate Professor, CST Temple University; After his studies in Biochemistry at Universita’ degli Studi Milano, Milan Italy, Dr. Morrione moved to USA in 1993 and has been working in the field of cancer biology since his postdoctoral training at the Kimmel Cancer Institute, Thomas Jefferson University, Philadelphia, PA in the laboratory of Dr. Renato Baserga, one of the leading experts in IGF-IR oncogenic signaling. In 1997 Dr. Morrione joined the Faculty of Thomas Jefferson University in the Department of Microbiology. In 2002 after receiving an NIH/NIDDK Career Development Award Dr. Morrione joined the Department of Urology at Jefferson where from 2008 to 2018 serves as the Director for Urology Basic Science and Associate Professor. Dr. Morrione joined the Department of Biology and the Sbarro Institute for Cancer Research and Molecular Medicine and Center for Biotechnology as Associate Professor of Research, and he is currently professor of Research and Deputy Director of the Sbarro Institute for Cancer Research and Molecular Medicine and Center for Biotechnology. He is a full member of the AACR.

 

  • Canio Martinelli, M.D.: Dr. Marinelli received his MD from Catholic University of the Sacred Heart in Rome, Visiting researcher at SHRO Temple University in Philadelphia, PhD candidate in Translational Molecular Medicine and Surgery & GYN-OB resident at UNIME. He has published numerous clinical papers in gynecologic oncology, risk reduction, and therapy and, most recently investigating clinical utilities of generative AI in gynecologic oncology.
  • Sharon Burk, Sharon Burk is a PhD student with Professor Antonio Giordano at the University of Siena, Italy in the department of Medical Biotechnologies, studying the role of Cyclin Dependent Kinase 10 in Triple Negative Breast Cancer. She received her Bachelor’s of Arts Degree from the University of California, Berkeley with a double major in molecular and cell biology and Italian studies.   She is a member of AACR.

This conference is being sponsored by Sbarro Health Research Organization and the Department of Biology, College of Science & Technology, Temple University.

To join by Zoom click the link below

https://temple.zoom.us/j/94458267823 

A QR code will be supplied at conference start, in addition to Zoom chat, to allow for questions to be submitted.

This conference is free to join on Zoom and will be covered live on @pharmaBI 

and on

 

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Live Notes from JP Morgan Healthcare Conference Virtual Endpoints Preview: January 8-9 2024

Reporter: Stephen J. Williams, Ph.D.

Endpoints at #JPM24 | Primed to unlock biopharma’s next dealmaking wave
Endpoints at JP Morgan Healthcare Conference
January 8-9 | San Francisco, CA80 Mission St, San Francisco, CA

An oasis has emerged in the biopharma money desert as backers look to replenish capital — still, uncertainty remains on whether it’s a mirage or the much needed dealmaking bump the industry needs. Yet spirits run high as JPM24 marks the triumphant return of inking strategic alliances and peering into the industry crystal ball — while keeping an eye out for some major M&A.

We’re back live from San Francisco for JPM Monday and Tuesday — our calendar of can’t-miss panels and fireside chats will feature prominent biopharma leaders to watch. The Endpoints Hub provides the ultimate coworking space with everything you need — 1:1 and group meeting spots plus guest pass capabilities and more. Join us in-person at the Endpoints Hub or watch online to stay plugged into all the action.

8 JAN
Welcome remarks
8:05 AM – 8:25 AM PST
Pfizer vet Mikael Dolsten has some thoughts on Big Pharma R&D

Endpoints News founding editor John Carroll will sit down with longtime Pfizer CSO Mikael Dolsten to talk about Pfizer’s pipeline, what he’s learned on the job about preclinical research and development and what’s ahead for the pharma giant in drug development and deals.

Mikael Dolsten

Chief Scientific Officer, President, Pfizer Research & Development

Pfizer

Pfizer Mikael Dolsten: Pfizer produced a series of AI generated molecules with new properties. Sees rapid adoption of AI in the area of drug discovery and molecular design.

 
 
8:25 AM – 9:05 AM PST
What pharma wants: The industry’s dealmakers look ahead at 2024

The drug industry’s appetite for new assets hasn’t slowed down. Top business development execs will give their outlook on the year, what they’re looking for and how they see the market.

Glenn Hunzinger

Pharmaceutical & Life Sciences Consulting Solutions Leader

PwC US

Rachna Khosla

SVP, Head of Business Development

Amgen

James Sabry

Global Head of Pharma Partnering

Roche

Devang Bhuva

SVP, Corporate Development

Gilead Sciences, Inc.

Endpoints News

Dealmaking panel

Glenn Hunzinger: if you do not have a GLP1 will have a tough time getting a good market price for your company; capital markets are not where they want to be; sees a tough deal making climate like last year.  The problem with many biotech companies are they are coming earlier to the venture capital because of greater funding needs and so it is imperative that they articulate the potential of their company in scientific detail

Rachna Khosla:  Make sure your investors are not just CAPITAL PARTNERS but use their expertise and involve them in development issues you may have, especially ones that a young firm will face.  The problem is most investments assume what the future looks like (for example how antibody drug conjugates, once a field left for dead, has been rejuvenated because of advances in chemistry). 

James Sabry: noted that cardiac and metabolic drugs are now at the focus of many investors, especially with the new anti-obesity drugs on market

Devang Bhuva: Most deals we see start as collaborations or partnerships.  You want to involve an alliance management team early in the deal making process.  This process could take years.

 
9:05 AM – 9:20 AM PST
The IPO: How Apogee Therapeutics went public in the most challenging market in years

Not many biotechs went public in 2023. And of those that did, not many have had a great time of it. Apogee is the exception and our panel will offer a behind-the-scenes look at their decision to enter the market and what life is like as a young public company.

Michael Henderson

CEO

Apogee Therapeutics

Kyle LaHucik

MODERATOR

Senior Reporter

Endpoints News

Michael Henderson:  Not many biotech IPOs deals happened in 2023.  Michael feels it is because too many biotechs focused on building platforms, which was a hard sell in 2023.  He felt not many biotechs had clear milestones and investors wanted a clear primary validated target.  He said many biotech startups are in a funding crunch and most need at least $440M on their balance sheet to get to 2026.

9:50 AM – 10:10 AM PST
Top predictions for biotech in 2024

Catalent CEO Alessandro Maselli will be back at the big JPM healthcare confab to talk with Endpoints News founder John Carroll about their top predictions of what’s coming up for the biotech industry in 2024. The stakes couldn’t be higher as the industry grapples with headwinds and new opportunities in a gale of market forces. Two top observers share their thoughts on the year ahead.

Alessandro Maselli

President & CEO

Catalent

10:15 AM – 10:35 AM PST
Innovation at a crossroads: Keys to unlocking the value of science and technology

The industry has long discussed the promise of technology and the acceleration it provides in scientific advancement and across the industry value chain. However, the promise of its impact has yet to fully be realized. This discussion will outline the keys to unleashing this promise and the implications and actions to be taken by the biopharmaceutical companies across the industry.

Ray Pressburger

North America Life Sciences Industry Lead & Global Life Sciences Strategy Lead

Accenture

SPONSORED BY

10:35 AM – 11:05 AM PST
Activism and Investing: In conversation with Elliott Investment Management’s Marc Steinberg

Elliott has been behind many of 2023’s highest-profile healthcare investments, including multiple activist engagements and taking Syneos Health private. What has made large healthcare companies such interesting investment opportunities for firms like Elliott? What’s Elliott’s investing strategy in healthcare? And what should companies expect when an activist calls?

Marc Steinberg

Senior Portfolio Manager

Elliott Investment Management

Andrew Dunn

MODERATOR

Biopharma Correspondent

Endpoints News

11:05 AM – 11:35 AM PST
Creating ROI from AI

AI is predicted to transform the way drugs are made, from discovery to clinical trials to market. But beyond the initial hype and early adoption, where has AI made meaningful contributions to R&D? How does it help drug developers advance science? Endpoints publisher Arsalan Arif is convening a panel of leading experts to discuss the state of AI in the pharmaceutical landscape and the outlook for 2024. How does AI impact the drug pipeline, from the early steps of discovery to reducing trial failure rate?

Thomas Clozel

Co-Founder & CEO

Owkin

Venkat Sethuraman

SVP, Global Biometrics & Data Sciences

Bristol Myers Squibb

Frank O. Nestle

Global Head of Research & Chief Scientific Officer

Sanofi

Matthias Evers

Chief Business Officer

Evotec

Arsalan Arif

MODERATOR

Founder & Publisher

Endpoints News

SPONSORED BY

11:35 AM – 12:00 PM PST
Biopharma’s dealmaker: Behind the scenes with Centerview Partners co-president Eric Tokat

Almost every major biopharma deal in 2023 had Centerview’s name attached to it. And much of the time, Eric Tokat was the banker making those deals happen. Hear his outlook for 2024, how transactions are getting done and what’s placed his firm at the center of so much action.

E. Eric Tokat

Co-President, Investment Banking

Centerview Partners

CenterView Partners Eric Tokat feels dealmaking will improve in 2024, given the recent flurry of dealmaking at end of last year and right before main JPM Healthcare Conference.  He says Centerview wants to help the biotechs they invest in on their strategic path.  This may translate into buyers more actively involved (more than startups want) and buyers now are in the drivers seat as far as the timeline of deals and development.

Is the megamerger dead for this year?  He says it is very hard to see two major mergers happening but there will be many smaller and mid size biotech deals happening, but these deals will be more speculative in nature..  The focus for large pharma is top line growth.  Most of the buyers have an infrastructure and value is more of buying and dropping it in their business so there is now a huge emphasis on due diligence on whether synergies exist or not

 
12:00 PM – 12:30 PM PST
Founder, legend, leader: In conversation with Nobel laureate Carolyn Bertozzi

Carolyn Bertozzi’s discoveries around bioorthogonal chemistry won the Nobel Prize in Chemistry in 2022 and are at the heart of new therapies being tested in patients. Join us as we discuss what inspires her and where she sees the next big advances.

Carolyn Bertozzi

Prof. of Chemistry, Stanford University and Baker Family Director of Sarafan ChEM-H

Stanford University

Nicole DeFeudis

MODERATOR

Editor

Endpoints News

Bioorthogonal chemistry: class of high yielding chemical reactions that proceed rapidly and selectively in biological environments without side reactions toward endogenous functions.  This is also a type of ‘click chemistry’ in biological system where only specifically alter the biomolecule of interest.

Orthogonal: two chemicals not interacting with each other

Dr. Bertozzi noted she has started a new Antibody-Drug-Conjugate (ADC) company which involves designing with biorthogonal chemistry to make new functional molecules with varying properties

She noted hardly any biologists knew anything about glycobiology when she first started.  However now she feels pharma and academia are working very well with each other

Bioorthogonal and Click Chemistry
Curated by Prof. Carolyn R. Bertozzi, 2022 winner of the Nobel Prize in Chemistry

Source: https://pubs.acs.org/page/vi/bioorthogonal-click-chemistry

The 2022 Nobel Prize in Chemistry has been awarded jointly to ACS Central Science Editor-in-Chief, Carolyn R. Bertozzi of Stanford University, Morten Meldal of the University of Copenhagen, and K. Barry Sharpless of Scripps Research, for the development of click chemistry and bioorthogonal chemistry.

To celebrate this remarkable achievement, 2022 Nobel Prize winner Professor Carolyn R. Bertozzi has curated this Bioorthogonal and Click Chemistry Virtual Issue, highlighting papers published across ACS journals that have built upon the foundational work in this exciting area of chemistry.

From Mechanism to Mouse: A Tale of Two Bioorthogonal Reactions

Ellen M. Sletten and Carolyn R. Bertozzi* Acc. Chem. Res. 2011, 44, 9, 666-676 August 15, 2011

Abstract

Bioorthogonal reactions are chemical reactions that neither interact with nor interfere with a biological system. The participating functional groups must be inert to biological moieties, must selectively reactive with each other under biocompatible conditions, and, for in vivo applications, must be nontoxic to cells and organisms. Additionally, it is helpful if one reactive group is small and therefore minimally perturbing of a biomolecule into which it has been introduced either chemically or biosynthetically. Examples from the past decade suggest that a promising strategy for bioorthogonal reaction development begins with an analysis of functional group and reactivity space outside those defined by nature. Issues such as stability of reactants and products (particularly in water), kinetics, and unwanted side reactivity with biofunctionalities must be addressed, ideally guided by detailed mechanistic studies. Finally, the reaction must be tested in a variety of environments, escalating from aqueous media to biomolecule solutions to cultured cells and, for the most optimized transformations, to live organisms.

9 JAN

9:40 AM – 10:10 AM PST

Biotech downturn survival school

Our panelists have seen the worst, and made it through to the other side. Join us for downturn survival school as our panelists talk about what sets apart the ones who make it through tough times.

These panalists think it will be specialist capital year to shine while the general capital is still sitting on the sidelines

JJ Kang

CEO

Appia Bio

“2023 was a tough year while 2020 was a boon year to start a company.  We will continue to see these cycles; many of these new CEOs have never seen a biotech downturn yet and may not know how to preserve capital for the downturn”.

“Doing a partnership with Kite Pharmaceuticals early in our startp allowed us to get work done without risking a lot of capital, even if it means equity and asset dilution.  That makes sense. However even if you are small insist on being an equal partner.”

“There are many investors we talk to who do not want to invest in cell therapy.  Too risky now”

Carl Gordon

Managing Partner

OrbiMed Advisors

There are many macroeconomic factors affecting investment and capital today which will carry on through 2024.   Not raising money when you do not need money is a bad philosophy.  Always bbe raising captial.  This is especially true when you have to rely on hedge funds.  Parnerships howeve are sometimes the only way for small biotechs to leverage their strengths.

Joshua Boger

Executive Chair

Alkeus Pharmaceuticals, Inc.

Boger: Expect volatility for 2024.  This environment feels very different than past downturns.

Even in downturns there is still lots of capital; remember access to human capital is better in a downturn and is easier to access;  however it has become harder to get drug approvals

The panelists agree that access to capital and funding will be as tricky in 2024 than 2023.  They did

suggest that a new funding avenue, private credit, may be a source of capital.  This is discussed below:

When thinking about a private alternative investment asset class, the first thing that springs to mind is private equity. But there’s one more asset class with the word private in its name that has recently gained much attention. We’re talking about private credit

Indeed, this once little-known investment strategy is now growing rapidly in popularity, offering private investors worldwide an exciting opportunity to diversify their portfolio with, in theory, less risky investments that yield significant returns. 

  • Private credit investments refer to investors lending money to companies who then repay the loan at a given interest rate within the predetermined period.
  • The private credit market has grown significantly over the past years, rising from $875 million in 2020 to $1.4 trillion at the beginning of 2023. 

Please WATCH VIDEO BY GOLDMAN SACHS ON PRIVATE CREDIT

 

 

 

 

10:50 AM – 11:20 AM PST

The New Molecule: How breakthrough technologies are actually changing pharma R&D

Join us for a look at how AI, machine learning and generative technologies are actually being applied inside drugmakers’ labs. We’ll explore how new technologies are being used, their implications, how they intersect with regulatory and IP issues and how this fast-changing field is likely to evolve.

Kailash Swarna

Managing Director & Global Life Sciences Clinical Development Lead

Accenture

Artificial Intelligence is making impact in a grand way on biology in three aspects:

  1. Speeding up target validation: now we can get through 300 molecules a day
  2. Predicition like AlphaFold is doing; molecular simulations
  3. Document submission especially with regulatory and IND submissions

Pamela Carroll

COO

Isomorphic Labs formerly of AlphaFold

We were first with Novartis at last year JPM and was one year old but parnering with them in that initial year was very important for sealing the deal.

They are looking now at neurologic diseases like ALS.  She wondered whether ALS is actually multiple diseases and we need to stratify patients like we do in oncology trials.  Their main competion is the whole tech world like Amazon, Google and other Machine Learning companies so being a tech player in the biotech world means you are not just competing with other biotechs but large tech companies as well.

Jorge Conde

General Partner

Andreessen Horowitz

Need is still great for drug discovery; early adopters show AI tools can be used in big pharma. There are lots of applications of AI in managing care; a lot of back office applications including patient triaging.  He does not see big AI mergers with pharma companies –  this will be mainly partnerships not M&A deals

Alicyn Campbell

Chief Scientific Officer

Evinova, a Healthtech Subsidiary of the AstraZeneca Group

There is a need to turn AI for real world example.  For example AI tools were used in clinical trials to determine patient cohorts with pneumonitis.  At Evinova they are determining how AI can hel[p show clinical benefit with respect to efficacy and safety

Joshua Boger at #JPM24 (Brian Benton Photography)

  January 12, 2024 09:06 AM ESTUpdated 10:00 AM PeopleStartups

Vertex founder Joshua Boger on surviving downturns, ‘painful’ partnerships, and the importance of culture: #JPM24

Andrew Dunn

Biopharma Correspondent

Source: https://endpts.com/jpm24-vertex-founder-joshua-boger-on-surviving-downturns-painful-partnerships-and-the-importance-of-culture/

While the JP Morgan Healthcare Conference was full of voices of measured optimism, rooting for the market to bounce back in 2024, one longtime biotech leader warned against setting any firm expectations.

Instead of predicting when the downturn may end, Vertex Pharmaceuticals founder Joshua Boger said he advises biotech leaders to expect — and plan for — volatility. Speaking Tuesday on an Endpoints News panel alongside OrbiMed’s Carl Gordon and Appia Bio CEO JJ Kang, Boger shared lessons learned on surviving downturns, striking pharma deals, and the importance of keeping a company’s culture based on his two decades of founding and leading Vertex as CEO from 1989 to 2009. The 72-year-old is now serving as executive chairman of Alkeus Pharmaceuticals, a startup developing a rare disease drug.

“I never experienced a straight line up,” Boger said. “Everything had its cycles, and it was how you respond to the cycle, not by predicting when the end is going to be, but just by responding to the present situation.”

At Boger’s first appearance at the JP Morgan conference in 1991, he said the conference’s theme was the end of biotech financing. Just a few months later, Regeneron successfully went public, rapidly changing the outlook for the whole field.

“We had no idea we were ever going to take public money,” he said. “When Regeneron did their IPO, we went, ‘Whoa, there’s something happening here,’ and we pivoted quickly.”

Vertex went public later that year. Throughout his 20-year tenure, Boger said no pharma company ever made an acquisition offer for Vertex, which now commands a market value of $110 billion and recently won the first FDA approval for a CRISPR gene editing therapy.

“We had an uber corporate policy to always make ourselves more expensive than anyone would stomach,” Boger said.

However, Vertex did strike a range of partnerships with Big Pharmas, which Boger described as a painful but necessary part of running a biotech startup.

“It’s impossible for a partnership not to slow you down,” he said. “You can and should try as hard as you can not to do that, but just count on it. They’ll slow you down.”

Boger said startups should insist on being equal partners in pharma deals, at least making sure they have a seat at a partner’s development meetings.

“Realize they’re going to be painful, it’s going to be horrible, and you need to do it,” Boger said.

While Vertex suffered through layoffs, stock price plunges, and trial failures, Boger credited a focus on culture as key to its long-term success.

“It’s the most important ingredient for a successful company,” he said. “Technology is acquirable. Culture is not acquirable. There are 10 companies that will fail because of culture for every one that succeeds, and the successful companies in retrospect will almost always have special cultural aspects that kept them through those downtimes.”

JPM24 opens with ADCs the hottest ticket in San Francisco

By Annalee ArmstrongJan 8, 2024 6:30am

Source: https://www.fiercebiotech.com/biotech/jpm24-opens-adcs-hottest-ticket-san-francisco

The overall deal flow in biopharma tapered off in 2023 but the big companies sure know what they want (what they really, really want), according to a new report from J.P. Morgan.

And that’s antibody-drug conjugates, which drove a fourth-quarter spike in licensing deal proceeds and provided a glimmer of hope to an industry battered by outside forces and grim financing prospects.

J.P. Morgan’s annual 2023 Biopharma Licensing and Venture Report arrived on the eve of the firm’s famous conference, which is set to welcome thousands of attendees in San Francisco today—East Coast weather permitting.

2023 was tough, but clinical biotechs still had a lot of opportunities to wheel and deal, according to J.P. Morgan. While licensing deals, venture investments, M&A and IPOs were down overall in the fourth quarter, deal values stayed fairly high thanks to a flurry of late-stage tie ups.

Follow the Fierce team’s coverage of the 2024 J.P. Morgan Healthcare Conference here

Biopharma licensing partnerships accounted for $63 billion in total value during the fourth quarter from 108 deals. Just one deal—Merck’s ADC partnership with Daiichi Sankyo—accounted for $22 billion of that. Another huge one was another ADC bet, with Bristol Myers Squibb signing on to work with SystImmune for a total value of $8.4 billion. If you exclude the Merck deal, the total value of these partnerships is still higher than the previous quarter, which ended with $32.1 billion.

The total number of licensing deals compares to 149 in the same quarter a year earlier, 195 for Q4 2021 and 223 for Q4 2022.

As for venture investments, the year closed out with $17 billion total across 250 rounds, thanks to $3.5 billion earned through 79 rounds in the last quarter. Aiolos Bio snagged the title of largest venture round of the quarter with $245 million, which also proved to be the largest series A, too.

There was just one IPO in all of the fourth quarter—Cargo Therapeutics making the plunge for $300 million—and 13 overall for the year. It’s a far cry from the heyday of 2021 and experts are still unsure what 2024 will hold. J.P. Morgan reported $2.5 billion raised from 12 completed biopharma IPOs for the year on Nasdaq and NYSE. Nine out of the 12 companies had clinical programs when they took the leap to the public markets. As of December 13, five of the companies were trading above their IPO price.

As for M&A, December saw a rush of Big Pharmas snapping up companies around Christmas. J.P. Morgan tallied the fourth quarter at $37.6 billion and $128.8 billion across 112 total acquisitions for all of 2023.

AbbVie was the top buyer of the quarter with the two largest acquisitions thanks to the $10 billion outlay for ImmunoGen and $8.7 billion buy of Cerevel Therapeutics.

All of this adds up to 270 total deals in the fourth quarter total, which is lower than the third quarter which exceeded 300.

J.P. Morgan sees some big potential for smaller biopharmas looking for licensing partners, as Big Pharmas have been handing out larger upfront payments for the deals they really want.

Cancer was once again the most in-demand therapeutic areas, reaching a new height of $86.1 billion in 2023. Followed by $21.1 billion for neurological disorders.

For More Articles on Real Time Conference Coverage in this Open Access Scientific Journal see:

Part One: The Process of Real Time Coverage using Social Media

Part Two: List of BioTech Conferences 2013 to Present

https://worldmedicalinnovation.org/

https://pharmaceuticalintelligence.com/2022/05/01/2022-world-medical-innovation-forum-gene-cell-therapy-may-2-4-2022-boston-in-person/

 

https://event.technologyreview.com/emtech-digital-2022/agenda-overview

 

Read Full Post »

The Continued Impact and Possibilities of AI in Medical and Pharmaceutical Industry Practices

Reporter: Adam P. Tubman, MSc Biotechnology, Research Associate 3, Computer Graphics and AI in Drug Discovery

 

Researchers have been able to discover many ways to incorporate AI into the practices of healthcare, both in terms of medical healthcare and also in pharmaceutical drug development. For example, given the situation where a doctor provides an inaccurate diagnosis to a patient because the doctor had an incomplete or inaccurate medical record/history, AI presents a solution that has the potential to rapidly and correctly account for human error and predict the correct diagnosis based on the patterns identified in other patient’s medical history to disease diagnosis indication. In the pharmaceutical industry, companies are changing and expanding approaches to drug discovery and development given the possibilities that AI can offer. One company, Reverie Labs, located in Cambridge, MA, is a pharmaceutical company utilizing AI for application of machine learning and computational chemistry to discover new possible compounds to be used in the development of cancer treatments.

Today, AI uses have had many other applications in medicine including managing healthcare data and performing robotic surgery, both of which transform the in-person patient and doctor experience. AI has even been used to change in-person cancer patient experiences. For example, Freenome, a company in San Francisco, CA uses AI in initial screenings, blood tests and diagnostic tests when a patient is being initially tested for cancer. The hope is that this technology will aide in speeding up cancer diagnoses and lead to new treatment developments.

The future will continue to bring many possibilities of AI, provided an acceptable level of accuracy is still maintained by AI technologies and that the technology remains beneficial. If research continues to focus on diagnosing diseases at a faster rate given the potential human errors in having an inaccurate or incomplete medical record upon diagnosis, AI could provide an improved experience for patients given the quicker diagnosis and treatment combined with less time spent either treating the wrong underlying condition or not knowing what condition to treat when accounting for an incomplete medical record. If this technology is proven to be successful not just in theory, but in practice, technology would then be available and could be beneficially applied to all diagnoses and treatment plans, across the world.

However, the reality regarding AI development is that its evolution depends on how much human effort is involved in its development. Therefore, the world won’t know or see the full benefits of AI until it is developed and actively applied. Similarly, the impact that AI will have in medical and pharmaceutical practices won’t be known until scientists fully develop and apply the technologies. Many possibilities, including a possible drastic lowering of the cost for pharmaceutical drugs across the board once drugs are much more readily discovered and produced, may carry a profound benefit to patients who currently struggle to afford their own treatment plans. Additionally, unforeseen advances in the medicinal and pharmaceutical fields because of AI development will lead to unforeseen effects on the global economy and many other life changing variables for the entire world.

For more information on this topic, please check out the article below.

SOURCE

Daley, S. (2018). Artificial Intelligence in healthcare: 39 examples Improving the Future of Medicine. Built In. https://builtin.com/artificial-intelligence/artificial-intelligence-healthcare

Read Full Post »

The Use of ChatGPT in the World of BioInformatics and Cancer Research and Development of BioGPT by MIT

Curator: Stephen J. Williams, Ph.D.

Chatbots are being used in multiple interdisciplanary areas in research and medicine and so it was a natural progression to incorporate artificial intelligence (AI), natural language processing (NLP), and chatbot technology like ChatGPT into bioinformatic analysis.

“In domains like informatics, management and marketing, media and communication science, languages and philosophy, psychology and sociology, engineering, design, and human-computer interaction, the fast expanding body of chatbot study is clearly interdisciplinary.

The field of bioinformatics is a natural fit for incorporting this technology.  The curated information below shows some use examples of this technology in bioinformatics related to cancer research.

The text in this reference source was actually generated by ChatGPT (https://chat.openai.com/chat)

Source: https://omicstutorials.com/using-chatgpt-in-bioinformatics-and-biomedical-research/

How ChatGPT can be used in bioinformatics research?
ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) language model that was designed to generate human-like text in a conversational setting. It is not directly related to bioinformatics, which is the field of study that deals with the storage, retrieval, and analysis of biological data, particularly in the context of genetics and genomics. However, ChatGPT could potentially be used in a bioinformatics context as a tool for generating natural language descriptions of genetic or genomic data, or for generating responses to queries about such data.

For example, a researcher could use ChatGPT to generate descriptions of genetic variants or gene expression patterns based on input data. This could be useful for generating summaries of results for reports or papers, or for generating explanations of complex concepts for non-expert audiences. ChatGPT could also be used to generate responses to queries about genetic or genomic data, such as “What is the function of gene X?” or “What are the potential consequences of variant Y?”

It’s worth noting that ChatGPT is just one of many tools and techniques that can be used in bioinformatics, and it is unlikely to be the most suitable or effective option in every situation. There are many specialized tools and resources available for working with biological data, and it is often necessary to use a combination of these tools to fully analyze and understand the data.

Generating descriptions of genetic or genomic data: ChatGPT could be used to generate natural language descriptions of genetic or genomic data based on input data. For example, suppose a researcher has a dataset containing information about gene expression levels in different tissues. The researcher could use ChatGPT to generate a description of the data, such as:
“Gene X is highly expressed in the liver and kidney, with moderate expression in the brain and heart. Gene Y, on the other hand, shows low expression in all tissues except for the lung, where it is highly expressed.”

 

Thereby ChatGPT, at its simplest level, could be used to ask general questions like “What is the function of gene product X?” and a ChatGPT could give a reasonable response without the scientist having to browse through even highly curated databases lie GeneCards or UniProt or GenBank.  Or even “What are potential interactors of Gene X, validated by yeast two hybrid?” without even going to the curated InterActome databases or using expensive software like Genie.

Summarizing results: ChatGPT could be used to generate summaries of results from genetic or genomic studies. For example, a researcher might use ChatGPT to generate a summary of a study that found a association between a particular genetic variant and a particular disease. The summary might look something like this:
“Our study found that individuals with the variant form of gene X are more likely to develop disease Y. Further analysis revealed that this variant is associated with changes in gene expression that may contribute to the development of the disease.”

It’s worth noting that ChatGPT is just one tool that could potentially be used in these types of applications, and it is likely to be most effective when used in combination with other bioinformatics tools and resources. For example, a researcher might use ChatGPT to generate a summary of results, but would also need to use other tools to analyze the data and confirm the findings.

ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that is designed for open-domain conversation. It is not specifically designed for generating descriptions of genetic variants or gene expression patterns, but it can potentially be used for this purpose if you provide it with a sufficient amount of relevant training data and fine-tune it appropriately.

To use ChatGPT to generate descriptions of genetic variants or gene expression patterns, you would first need to obtain a large dataset of examples of descriptions of genetic variants or gene expression patterns. You could use this dataset to fine-tune the ChatGPT model on the task of generating descriptions of genetic variants or gene expression patterns.

Here’s an example of how you might use ChatGPT to generate a description of a genetic variant:

First, you would need to pre-process your dataset of descriptions of genetic variants to prepare it for use with ChatGPT. This might involve splitting the descriptions into individual sentences or phrases, and encoding them using a suitable natural language processing (NLP) library or tool.

Next, you would need to fine-tune the ChatGPT model on the task of generating descriptions of genetic variants. This could involve using a tool like Hugging Face’s Transformers library to load the ChatGPT model and your pre-processed dataset, and then training the model on the task of generating descriptions of genetic variants using an appropriate optimization algorithm.

Once the model has been fine-tuned, you can use it to generate descriptions of genetic variants by providing it with a prompt or seed text and asking it to generate a response. For example, you might provide the model with the prompt “Generate a description of a genetic variant associated with increased risk of breast cancer,” and ask it to generate a response. The model should then generate a description of a genetic variant that is associated with increased risk of breast cancer.

It’s worth noting that generating high-quality descriptions of genetic variants or gene expression patterns is a challenging task, and it may be difficult to achieve good results using a language model like ChatGPT without a large amount of relevant training data and careful fine-tuning.

 

To train a language model like chatGPT to extract information about specific genes or diseases from research papers, you would need to follow these steps:

Gather a large dataset of research papers that contain information about the specific genes or diseases you are interested in. This dataset should be diverse and representative of the types of papers you want the model to be able to extract information from.

Preprocess the text data in the research papers by tokenizing the text and creating a vocabulary. You may also want to consider lemmatizing or stemming the text to reduce the dimensionality of the dataset.

Train the language model on the preprocessed text data. You may want to fine-tune a pre-trained model such as chatGPT on your specific dataset, or you can train a new model from scratch.

ChatGPT could also be useful for sequence analysis

A few examples of sequence analysis a ChatGPT could be useful include:

  1. Protein structure
  2. Identifying functional regions of a protein
  3. Predicting protein-protein interactions
  4. Identifying protein homologs
  5. Generating Protein alignments

All this could be done without having access to UNIX servers or proprietary software or knowing GCG coding

ChatGPT in biomedical research
There are several potential ways that ChatGPT or other natural language processing (NLP) models could be applied in biomedical research:

Text summarization: ChatGPT or other NLP models could be used to summarize large amounts of text, such as research papers or clinical notes, in order to extract key information and insights more quickly.

Data extraction: ChatGPT or other NLP models could be used to extract structured data from unstructured text sources, such as research papers or clinical notes. For example, the model could be trained to extract information about specific genes or diseases from research papers, and then used to create a database of this information for further analysis.

Literature review: ChatGPT or other NLP models could be used to assist with literature review tasks, such as identifying relevant papers, extracting key information from papers, or summarizing the main findings of a group of papers.

Predictive modeling: ChatGPT or other NLP models could be used to build predictive models based on large amounts of text data, such as electronic health records or research papers. For example, the model could be trained to predict the likelihood of a patient developing a particular disease based on their medical history and other factors.

It’s worth noting that while NLP models like ChatGPT have the potential to be useful tools in biomedical research, they are only as good as the data they are trained on, and it is important to carefully evaluate the quality and reliability of any results generated by these models.

 

ChatGPT in text mining of biomedical data
ChatGPT could potentially be used for text mining in the biomedical field in a number of ways. Here are a few examples:

Extracting information from scientific papers: ChatGPT could be trained on a large dataset of scientific papers in the biomedical field, and then used to extract specific pieces of information from these papers, such as the names of compounds, their structures, and their potential uses.

Generating summaries of scientific papers: ChatGPT could be used to generate concise summaries of scientific papers in the biomedical field, highlighting the main findings and implications of the research.

Identifying trends and patterns in scientific literature: ChatGPT could be used to analyze large datasets of scientific papers in the biomedical field and identify trends and patterns in the data, such as emerging areas of research or common themes among different papers.

Generating questions for further research: ChatGPT could be used to suggest questions for further research in the biomedical field based on existing scientific literature, by identifying gaps in current knowledge or areas where further investigation is needed.

Generating hypotheses for scientific experiments: ChatGPT could be used to generate hypotheses for scientific experiments in the biomedical field based on existing scientific literature and data, by identifying potential relationships or associations that could be tested in future research.

 

PLEASE WATCH VIDEO

 

In this video, a bioinformatician describes the ways he uses ChatGPT to increase his productivity in writing bioinformatic code and conducting bioinformatic analyses.

He describes a series of uses of ChatGPT in his day to day work as a bioinformatian:

  1. Using ChatGPT as a search engine: He finds more useful and relevant search results than a standard Google or Yahoo search.  This saves time as one does not have to pour through multiple pages to find information.  However, a caveat is ChatGPT does NOT return sources, as highlighted in previous postings on this page.  This feature of ChatGPT is probably why Microsoft bought OpenAI in order to incorporate ChatGPT in their Bing search engine, as well as Office Suite programs

 

  1. ChatGPT to help with coding projects: Bioinformaticians will spend multiple hours searching for and altering open access available code in order to run certain function like determining the G/C content of DNA (although there are many UNIX based code that has already been established for these purposes). One can use ChatGPT to find such a code and then assist in debugging that code for any flaws

 

  1. ChatGPT to document and add coding comments: When writing code it is useful to add comments periodically to assist other users to determine how the code works and also how the program flow works as well, including returned variables.

 

One of the comments was interesting and directed one to use BIOGPT instead of ChatGPT

 

@tzvi7989

1 month ago (edited)

0:54 oh dear. You cannot use chatgpt like that in Bioinformatics as it is rn without double checking the info from it. You should be using biogpt instead for paper summarisation. ChatGPT goes for human-like responses over precise information recal. It is quite good for debugging though and automating boring awkward scripts

So what is BIOGPT?

BioGPT https://github.com/microsoft/BioGPT

 

The BioGPT model was proposed in BioGPT: generative pre-trained transformer for biomedical text generation and mining by Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon and Tie-Yan Liu. BioGPT is a domain-specific generative pre-trained Transformer language model for biomedical text generation and mining. BioGPT follows the Transformer language model backbone, and is pre-trained on 15M PubMed abstracts from scratch.

The abstract from the paper is the following:

Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e. BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the biomedical domain, such as BioBERT and PubMedBERT. While they have achieved great success on a variety of discriminative downstream biomedical tasks, the lack of generation ability constrains their application scope. In this paper, we propose BioGPT, a domain-specific generative Transformer language model pre-trained on large-scale biomedical literature. We evaluate BioGPT on six biomedical natural language processing tasks and demonstrate that our model outperforms previous models on most tasks. Especially, we get 44.98%, 38.42% and 40.76% F1 score on BC5CDR, KD-DTI and DDI end-to-end relation extraction tasks, respectively, and 78.2% accuracy on PubMedQA, creating a new record. Our case study on text generation further demonstrates the advantage of BioGPT on biomedical literature to generate fluent descriptions for biomedical terms.

Tips:

  • BioGPT is a model with absolute position embeddings so it’s usually advised to pad the inputs on the right rather than the left.
  • BioGPT was trained with a causal language modeling (CLM) objective and is therefore powerful at predicting the next token in a sequence. Leveraging this feature allows BioGPT to generate syntactically coherent text as it can be observed in the run_generation.py example script.
  • The model can take the past_key_values (for PyTorch) as input, which is the previously computed key/value attention pairs. Using this (past_key_values or past) value prevents the model from re-computing pre-computed values in the context of text generation. For PyTorch, see past_key_values argument of the BioGptForCausalLM.forward() method for more information on its usage.

This model was contributed by kamalkraj. The original code can be found here.

 

This repository contains the implementation of BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining, by Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon and Tie-Yan Liu. BioGPT is a github which is being developed by MIT in collaboration with Microsoft. It is based on Python.

License

BioGPT is MIT-licensed. The license applies to the pre-trained models as well.

Contributing

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As of right now this does not seem Open Access, however a sign up is required!

We provide our pre-trained BioGPT model checkpoints along with fine-tuned checkpoints for downstream tasks, available both through URL download as well as through the Hugging Face 🤗 Hub.

Model Description URL 🤗 Hub
BioGPT Pre-trained BioGPT model checkpoint link link
BioGPT-Large Pre-trained BioGPT-Large model checkpoint link link
BioGPT-QA-PubMedQA-BioGPT Fine-tuned BioGPT for question answering task on PubMedQA link
BioGPT-QA-PubMedQA-BioGPT-Large Fine-tuned BioGPT-Large for question answering task on PubMedQA link
BioGPT-RE-BC5CDR Fine-tuned BioGPT for relation extraction task on BC5CDR link
BioGPT-RE-DDI Fine-tuned BioGPT for relation extraction task on DDI link
BioGPT-RE-DTI Fine-tuned BioGPT for relation extraction task on KD-DTI link
BioGPT-DC-HoC Fine-tuned BioGPT for document classification task on HoC link

 

So far as to date (6/12/2023) there are three papers referencing BioGPT on PubMed (abstracts and links below)

 

BioGPT: generative pre-trained transformer for biomedical text generation and mining.

Luo R, Sun L, Xia Y, Qin T, Zhang S, Poon H, Liu TY.Brief Bioinform. 2022 Nov 19;23(6):bbac409. doi: 10.1093/bib/bbac409.PMID: 36156661

We evaluate BioGPT on six biomedical natural language processing tasks and demonstrate that our model outperforms previous models on most tasks. …Our case study on text generation further demonstrates the advantage of BioGPT on biomedical literature to generate fl …

Here they show the advantages of BioGPT over BioBERT and ChatGPT in an example of text extraction and question answer

Table 7. Example of generated text

Input                                           Model                 Text

Bicalutamide                               GPT-2                 Bicalutamide, a synthetic bicalutamide derivative, was found to increase the cellular proliferation

of C. elegans cells. This effect was not observed with the other synthetic bicalutamide derivatives. This is in line with our previous work which showed that bicalutamide increases the proliferation of C. elegans cells but not in the presence of synthetic bicalutamide.

BioGPT             Bicalutamide (Casodex) is an androgen receptor (AR) antagonist approved for the treatment of metastatic castration-resistant prostate cancer (mCRPC) in patients who have progressed on or are ineligible for docetaxel chemotherapy, as well as for the treatment of early-stage prostate cancer in men who have not progressed on or are ineligible for docetaxel chemotherapy, as well as for the treatment of metastatic castration-sensitive prostate cancer (mCSPC) in men who have not progressed on or are ineligible for docetaxel chemotherapy.

Janus kinase 3 (JAK-3)                 GPT-2               Janus kinase 3 (JAK-3) mediates the conversion of glucose to glycogen in skeletal muscle. The
increase in glucose uptake by skeletal muscle is believed to be associated with a reduction in muscle protein breakdown and with the release of ketone bodies, which contribute to the metabolism of glucose.

BioGPT             Janus kinase 3 (JAK-3) is a member of the Janus kinase (JAK) family of non-receptor tyrosine kinases and plays an important role in the regulation of cell proliferation, differentiation, survival, migration and angiogenesis.

Apricitabine                                 GPT-2               Apricitabine, duloxetine and citalopram) were investigated in patients with a history of
treatment-resistant depression (n = 10). We found that treatment with the three drugs significantly decreased depressive symptoms, but not depressive symptoms over the next 12 weeks. We conclude that antidepressant drugs that reduce depressive symptoms and reduce depressive symptoms over time may be beneficial in patients with recurrent depression.

BioGPT             Apricitabine is an oral prodrug of 5-aza-2 ’-deoxycytidine (5-aza-CdR), a DNA methyltransferase (DNMT) inhibitor, which has been approved by the US Food and Drug Administration (FDA) for the treatment of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) in combination with low-dose cytarabine (Ara-C) and granulocyte colony-stimulating factor (G-CSF) for patients with intermediate-2 or high-risk MDS or AML.

Xylazine                                      GPT-2               Xylazine, the ‘active ingredient’ in ‘bath salts’ (see above) has been linked to numerous deaths,
including those of former University of California, Berkeley, professor Andrew Anglin, who posted

a video of himself having a bath filled with it.

BioGPT             Xylazine is an alpha 2-adrenoceptor agonist which has been used as a sedative and analgesic in veterinary medicine for many years, but its effects on the cardiovascular system have not been extensively studied in the dog, and its effects on the central nervous system (CNS) have not been well characterized in the dog, despite the fact that xylazine has been widely used as a sedative and analgesic in veterinary medicine for more than 30 years.

Psoralen                                      GPT-2               Psoralen, the city of the spiritualist, and had been given to him by God, who wished to show him
the way of salvation, and to draw him back to the true life of Christ, and to bring him into communion with his fellow-man.

BioGPT             Psoralen photochemotherapy (PUVA) is a well-established treatment for psoriasis, but its use is limited by the risk of skin cancer, particularly squamous cell carcinoma (SCC) of the head and neck (H & N), which is the most common site of skin cancer in the United States (US)

CP-673451                                  GPT-2                 CP-673451) and 4-5-6-3-1-2-3-4-6-7-8-9-10-11-12-13-14-15-16-17-18-19-20-21-22-23-24-25-26-27-

28-29-30-31-32-33-34-35-36-37-38-39-40-41-42-43-44-45-46-47-48-49-50…

BioGPT             CP-673451 is a potent, selective, and orally active inhibitor of human neutrophil elastase (HNE) and human cathepsin G (CatG) with in vitro and in vivo anti-inflammatory activity in a variety of animal models of inflammation and in a model of acute lung injury (ALI) in the rat induced by intratracheal instillation of lipopolysaccharide (LPS) and tumor necrosis factor-alpha (TNF-alpha), a model of acute lung injury (ALI) in which neutrophils play an important role.

BIIB-021                                     GPT-2               BIIB-021A-2-1.pdf. Wright, C. (2002). ‘The War on Terror: A Legal Theory of Terrorist Attacks,’ in
L.E.R. Wright, S.R. Warrick and J.H. Rothman (Eds.), The War on Terror: Essays in Honor of Michael T. Klare (New York: Oxford University Press), 143-57.

BioGPT             BIIB-021 is a novel, orally active, non-peptide bradykinin B2 receptor antagonist with potent and long-lasting anti-inflammatory activity in animal models of acute and chronic inflammation and in a rat model of adjuvant-induced arthritis (AIA), an animal model of rheumatoid arthritis (RA) and in a rat model of collagen-induced arthritis (CIA), an animal model of collagen-induced arthritis (CIA), in which arthritis is induced by immunization with bovine type II collagen (CII).

Note how BioGPT is more descriptive and accurate!

EGFI: drug-drug interaction extraction and generation with fusion of enriched entity and sentence information.

Huang L, Lin J, Li X, Song L, Zheng Z, Wong KC.Brief Bioinform. 2022 Jan 17;23(1):bbab451. doi: 10.1093/bib/bbab451.PMID: 34791012

The rapid growth in literature accumulates diverse and yet comprehensive biomedical knowledge hidden to be mined such as drug interactions. However, it is difficult to extract the heterogeneous knowledge to retrieve or even discover the latest and novel knowledge in an efficient manner. To address such a problem, we propose EGFI for extracting and consolidating drug interactions from large-scale medical literature text data. Specifically, EGFI consists of two parts: classification and generation. In the classification part, EGFI encompasses the language model BioBERT which has been comprehensively pretrained on biomedical corpus. In particular, we propose the multihead self-attention mechanism and packed BiGRU to fuse multiple semantic information for rigorous context modeling. In the generation part, EGFI utilizes another pretrained language model BioGPT-2 where the generation sentences are selected based on filtering rules.

Results: We evaluated the classification part on ‘DDIs 2013’ dataset and ‘DTIs’ dataset, achieving the F1 scores of 0.842 and 0.720 respectively. Moreover, we applied the classification part to distinguish high-quality generated sentences and verified with the existing growth truth to confirm the filtered sentences. The generated sentences that are not recorded in DrugBank and DDIs 2013 dataset demonstrated the potential of EGFI to identify novel drug relationships.

Availability: Source code are publicly available at https://github.com/Layne-Huang/EGFI.

 

GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information.

Jin Q, Yang Y, Chen Q, Lu Z.ArXiv. 2023 May 16:arXiv:2304.09667v3. Preprint.PMID: 37131884 Free PMC article.

While large language models (LLMs) have been successfully applied to various tasks, they still face challenges with hallucinations. Augmenting LLMs with domain-specific tools such as database utilities can facilitate easier and more precise access to specialized knowledge. In this paper, we present GeneGPT, a novel method for teaching LLMs to use the Web APIs of the National Center for Biotechnology Information (NCBI) for answering genomics questions. Specifically, we prompt Codex to solve the GeneTuring tests with NCBI Web APIs by in-context learning and an augmented decoding algorithm that can detect and execute API calls. Experimental results show that GeneGPT achieves state-of-the-art performance on eight tasks in the GeneTuring benchmark with an average score of 0.83, largely surpassing retrieval-augmented LLMs such as the new Bing (0.44), biomedical LLMs such as BioMedLM (0.08) and BioGPT (0.04), as well as GPT-3 (0.16) and ChatGPT (0.12). Our further analyses suggest that: (1) API demonstrations have good cross-task generalizability and are more useful than documentations for in-context learning; (2) GeneGPT can generalize to longer chains of API calls and answer multi-hop questions in GeneHop, a novel dataset introduced in this work; (3) Different types of errors are enriched in different tasks, providing valuable insights for future improvements.

PLEASE WATCH THE FOLLOWING VIDEOS ON BIOGPT

This one entitled

Microsoft’s BioGPT Shows Promise as the Best Biomedical NLP

 

gives a good general description of this new MIT/Microsoft project and its usefullness in scanning 15 million articles on PubMed while returning ChatGPT like answers.

 

Please note one of the comments which is VERY IMPORTANT


@rufus9322

2 months ago

bioGPT is difficult for non-developers to use, and Microsoft researchers seem to default that all users are proficient in Python and ML.

 

Much like Microsoft Azure it seems this BioGPT is meant for developers who have advanced programming skill.  Seems odd then to be paying programmers multiK salaries when one or two Key Opinion Leaders from the medical field might suffice but I would be sure Microsoft will figure this out.

 

ALSO VIEW VIDEO

 

 

This is a talk from Microsoft on BioGPT

 

Other Relevant Articles on Natural Language Processing in BioInformatics, Healthcare and ChatGPT for Medicine on this Open Access Scientific Journal Include

Medicine with GPT-4 & ChatGPT
Explanation on “Results of Medical Text Analysis with Natural Language Processing (NLP) presented in LPBI Group’s NEW GENRE Edition: NLP” on Genomics content, standalone volume in Series B and NLP on Cancer content as Part B New Genre Volume 1 in Series C

Proposal for New e-Book Architecture: Bi-Lingual eTOCs, English & Spanish with NLP and Deep Learning results of Medical Text Analysis – Phase 1: six volumes

From High-Throughput Assay to Systems Biology: New Tools for Drug Discovery

Machine Learning (ML) in cancer prognosis prediction helps the researcher to identify multiple known as well as candidate cancer diver genes

 

20 articles in Natural Language Processing

142 articles in BioIT: BioInformatics

111 articles in BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics

 

Read Full Post »

Use of Systems Biology for Design of inhibitor of Galectins as Cancer Therapeutic – Strategy and Software

 

 

Curator: Stephen J. Williams, Ph.D.

Below is a slide representation of the overall mission 4 to produce a PROTAC to inhibit Galectins 1, 3, and 9.

 

Using A Priori Knowledge of Galectin Receptor Interaction to Create a BioModel of Galectin 3 Binding

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Now after collecting literature from PubMed on “galectin-3” AND “binding” to determine literature containing kinetic data we generate a WordCloud on the articles.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

This following file contains the articles needed for BioModels generation.

https://pharmaceuticalintelligence.com/wp-content/uploads/2022/12/Curating-Galectin-articles-for-Biomodels.docx

 

From the WordCloud we can see that these corpus of articles describe galectin binding to the CRD (carbohydrate recognition domain).  Interestingly there are many articles which describe van Der Waals interactions as well as electrostatic interactions.  Certain carbohydrate modifictions like Lac NAc and Gal 1,4 may be important.  Many articles describe the bonding as well as surface  interactions.  Many studies have been performed with galectin inhibitors like TDGs (thio-digalactosides) like TAZ TDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside).  This led to an interesting article

Dual thio-digalactoside-binding modes of human galectins as the structural basis for the design of potent and selective inhibitors

Affiliations 2016 Jul 15;6:29457.
 doi: 10.1038/srep29457. Free PMC article

Abstract

Human galectins are promising targets for cancer immunotherapeutic and fibrotic disease-related drugs. We report herein the binding interactions of three thio-digalactosides (TDGs) including TDG itself, TD139 (3,3′-deoxy-3,3′-bis-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside, recently approved for the treatment of idiopathic pulmonary fibrosis), and TAZTDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside) with human galectins-1, -3 and -7 as assessed by X-ray crystallography, isothermal titration calorimetry and NMR spectroscopy. Five binding subsites (A-E) make up the carbohydrate-recognition domains of these galectins. We identified novel interactions between an arginine within subsite E of the galectins and an arene group in the ligands. In addition to the interactions contributed by the galactosyl sugar residues bound at subsites C and D, the fluorophenyl group of TAZTDG preferentially bound to subsite B in galectin-3, whereas the same group favored binding at subsite E in galectins-1 and -7. The characterised dual binding modes demonstrate how binding potency, reported as decreased Kd values of the TDG inhibitors from μM to nM, is improved and also offer insights to development of selective inhibitors for individual galectins.

Figures

Figure 1
 
Figure 2
 
Figure 3

 

 

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Medical Startups – Artificial Intelligence (AI) Startups in Healthcare

Reporters: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN and Shraga Rottem, MD, DSc,

The motivation for this post is two fold:

First, we are presenting an application of AI, NLP, DL to our own medical text in the Genomics space. Here we present the first section of Part 1 in the following book. Part 1 has six subsections that yielded 12 plots. The entire Book is represented by 38 x 2 = 76 plots.

Second, we bring to the attention of the e-Reader the list of 276 Medical Startups – Artificial Intelligence (AI) Startups in Healthcare as a hot universe of R&D activity in Human Health.

Third, to highlight one academic center with an AI focus

ETH Logo
 
ETH AI Center - Header Image
 
 
Dear friends of the ETH AI Center,

We would like to provide you with some exciting updates from the ETH AI Center and its growing community.

We would like to provide you with some exciting updates from the ETH AI Center and its growing community. The ETH AI Center now comprises 110 research groups in the faculty, 20 corporate partners and has led to nine AI startups.

As the Covid-19 restrictions in Switzerland have recently been lifted, we would like to hear from you what kind of events you would like to see in 2022! Participate in the survey to suggest event formats and topics that you would enjoy being a part of. We are already excited to learn what we can achieve together this year.

We already have many interesting events coming up, we look forward to seeing you at our main and community events!

SOURCE

https://news.ethz.ch/html_mail.jsp?params=%2FUnFXUQJ%2FmiOP6akBq8eHxaXG%2BRdNmeoVa9gX5ArpTr6mX74xp5d78HhuIHTd9V6AHtAfRahyx%2BfRGrzVL1G8Jy5e3zykvr1WDtMoUC%2B7vILoHCGQ5p1rxaPzOsF94ID

 

 

LPBI Group is applying AI for Medical Text Analysis with Machine Learning and Natural Language Processing: Statistical and Deep Learning

Our Book 

Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology

Medical Text Analysis of this Books shows the following results obtained by Madison Davis by applying Wolfram NLP for Biological Languages on our own Text. See below an Example:

Part 1: Next Generation Sequencing (NGS)

 

1.1 The NGS Science

1.1.1 BioIT Aspect

 

Hypergraph Plot #1 and Tree Diagram Plot #1

for 1.1.1 based on 16 articles & on 12 keywords

protein, cancer, dna, genes, rna, survival, immune, tumor, patients, human, genome, expression

(more…)

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The Vibrant Philly Biotech Scene: Proteovant Therapeutics Using Artificial Intelligence and Machine Learning to Develop PROTACs

Reporter: Stephen J. Williams, Ph.D.

It has been a while since I have added to this series but there have been a plethora of exciting biotech startups in the Philadelphia area, and many new startups combining technology, biotech, and machine learning. One such exciting biotech is Proteovant Therapeutics, which is combining the new PROTAC (Proteolysis-Targeting Chimera) technology with their in house ability to utilize machine learning and artificial intelligence to design these types of compounds to multiple intracellular targets.

PROTACs (which actually is under a trademark name of Arvinus Operations, but is also refered to as Protein Degraders. These PROTACs take advantage of the cell protein homeostatic mechanism of ubiquitin-mediated protein degradation, which is a very specific targeted process which regulates protein levels of various transcription factors, protooncogenes, and receptors. In essence this regulated proteolyic process is needed for normal cellular function, and alterations in this process may lead to oncogenesis, or a proteotoxic crisis leading to mitophagy, autophagy and cellular death. The key to this technology is using chemical linkers to associate an E3 ligase with a protein target of interest. E3 ligases are the rate limiting step in marking the proteins bound for degradation by the proteosome with ubiquitin chains.

Model of PROTAC Ternarary Complex

A review of this process as well as PROTACs can be found elsewhere in articles (and future articles) on this Open Access Journal.

Protevant have made two important collaborations:

  1. Oncopia Therapeutics: came out of University of Michigan Innovation Hub and lab of Shaomeng Wang, who developed a library of BET and MDM2 based protein degraders. In 2020 was aquired by Riovant Sciences.
  2. Riovant Sciences: uses computer aided design of protein degraders

Proteovant Company Description:

Proteovant is a newly launched development-stage biotech company focusing on discovery and development of disease-modifying therapies by harnessing natural protein homeostasis processes. We have recently acquired numerous assets at discovery and development stages from Oncopia, a protein degradation company. Our lead program is on track to enter IND in 2021. Proteovant is building a strong drug discovery engine by combining deep drugging expertise with innovative platforms including Roivant’s AI capabilities to accelerate discovery and development of protein degraders to address unmet needs across all therapeutic areas. The company has recently secured $200M funding from SK Holdings in addition to investment from Roivant Sciences. Our current therapeutic focus includes but is not limited to oncology, immunology and neurology. We remain agnostic to therapeutic area and will expand therapeutic focus based on opportunity. Proteovant is expanding its discovery and development teams and has multiple positions in biology, chemistry, biochemistry, DMPK, bioinformatics and CMC at many levels. Our R&D organization is located close to major pharmaceutical companies in Eastern Pennsylvania with a second site close to biotech companies in Boston area.

Protein degradation

Source: Protevant

The ubiquitin proteasome system (UPS) is responsible for maintaining protein homeostasis. Targeted protein degradation by the UPS is a cellular process that involves marking proteins and guiding them to the proteasome for destruction. We leverage this physiological cellular machinery to target and destroy disease-causing proteins.

Unlike traditional small molecule inhibitors, our approach is not limited by the classic “active site” requirements. For example, we can target transcription factors and scaffold proteins that lack a catalytic pocket. These classes of proteins, historically, have been very difficult to drug. Further, we selectively degrade target proteins, rather than isozymes or paralogous proteins with high homology. Because of the catalytic nature of the interactions,  it is possible to achieve efficacy at lower doses with prolonged duration while decreasing dose-limiting toxicities.

Biological targets once deemed “undruggable” are now within reach.

About Riovant Sciences: from PRNewsWire https://www.prnewswire.com/news-releases/roivant-unveils-targeted-protein-degradation-platform-301186928.html

Roivant develops transformative medicines faster by building technologies and developing talent in creative ways, leveraging the Roivant platform to launch “Vants” – nimble and focused biopharmaceutical and health technology companies. These Vants include Proteovant but also Dermovant, ImmunoVant,as well as others.

Roivant’s drug discovery capabilities include the leading computational physics-based platform for in silico drug design and optimization as well as machine learning-based models for protein degradation.

The integration of our computational and experimental engines enables the rapid design of molecules with high precision and fidelity to address challenging targets for diseases with high unmet need.

Our current modalities include small molecules, heterobifunctionals and molecular glues.

Roivant Unveils Targeted Protein Degradation Platform

– First therapeutic candidate on track to enter clinical studies in 2021

– Computationally-designed degraders for six targets currently in preclinical development

– Acquisition of Oncopia Therapeutics and research collaboration with lab of Dr. Shaomeng Wang at the University of Michigan to add diverse pipeline of current and future compounds

Clinical-stage degraders will provide foundation for multiple new Vants in distinct disease areas

– Platform supported by $200 million strategic investment from SK Holdings

Other articles in this Vibrant Philly Biotech Scene on this Online Open Access Journal include:

The Vibrant Philly Biotech Scene: PCCI Meeting Announcement, BioDetego Presents Colon Cancer Diagnostic Tool

The Vibrant Philly Biotech Scene: Focus on KannaLife Sciences and the Discipline and Potential of Pharmacognosy

The Vibrant Philly Biotech Scene: Focus on Vaccines and Philimmune, LLC

The Vibrant Philly Biotech Scene: Focus on Computer-Aided Drug Design and Gfree Bio, LLC

Philly Biotech Scene: Biobots and 3D BioPrinting (Now called Allevi)

Philly Biotech Scene: November 2015 PCCI Meeting Showcasing ViFant (Penn Center For Innovation)

Spark Therapeutics’ $4.8Billion deal Confirmed as Biggest VC-backed Exit in Philadelphia

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The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

Curators: Dr. Stephen J. Williams and Aviva Lev-Ari, PhD, RN

UPDATED on 11/5/2021

Introducing Isomorphic Labs

I believe we are on the cusp of an incredible new era of biological and medical research. Last year DeepMind’s breakthrough AI system AlphaFold2 was recognised as a solution to the 50-year-old grand challenge of protein folding, capable of predicting the 3D structure of a protein directly from its amino acid sequence to atomic-level accuracy. This has been a watershed moment for computational and AI methods for biology.
Building on this advance, today, I’m thrilled to announce the creation of a new Alphabet company –  Isomorphic Labs – a commercial venture with the mission to reimagine the entire drug discovery process from the ground up with an AI-first approach and, ultimately, to model and understand some of the fundamental mechanisms of life.

For over a decade DeepMind has been in the vanguard of advancing the state-of-the-art in AI, often using games as a proving ground for developing general purpose learning systems, like AlphaGo, our program that beat the world champion at the complex game of Go. We are at an exciting moment in history now where these techniques and methods are becoming powerful and sophisticated enough to be applied to real-world problems including scientific discovery itself. One of the most important applications of AI that I can think of is in the field of biological and medical research, and it is an area I have been passionate about addressing for many years. Now the time is right to push this forward at pace, and with the dedicated focus and resources that Isomorphic Labs will bring.

An AI-first approach to drug discovery and biology
The pandemic has brought to the fore the vital work that brilliant scientists and clinicians do every day to understand and combat disease. We believe that the foundational use of cutting edge computational and AI methods can help scientists take their work to the next level, and massively accelerate the drug discovery process. AI methods will increasingly be used not just for analysing data, but to also build powerful predictive and generative models of complex biological phenomena. AlphaFold2 is an important first proof point of this, but there is so much more to come. 
At its most fundamental level, I think biology can be thought of as an information processing system, albeit an extraordinarily complex and dynamic one. Taking this perspective implies there may be a common underlying structure between biology and information science – an isomorphic mapping between the two – hence the name of the company. Biology is likely far too complex and messy to ever be encapsulated as a simple set of neat mathematical equations. But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI.

What’s next for Isomorphic Labs
This is just the beginning of what we hope will become a radical new approach to drug discovery, and I’m incredibly excited to get this ambitious new commercial venture off the ground and to partner with pharmaceutical and biomedical companies. I will serve as CEO for Isomorphic’s initial phase, while remaining as DeepMind CEO, partially to help facilitate collaboration between the two companies where relevant, and to set out the strategy, vision and culture of the new company. This will of course include the building of a world-class multidisciplinary team, with deep expertise in areas such as AI, biology, medicinal chemistry, biophysics, and engineering, brought together in a highly collaborative and innovative environment. (We are hiring!
As pioneers in the emerging field of ‘digital biology’, we look forward to helping usher in an amazingly productive new age of biomedical breakthroughs. Isomorphic’s mission could not be a more important one: to use AI to accelerate drug discovery, and ultimately, find cures for some of humanity’s most devastating diseases.

SOURCE

https://www.isomorphiclabs.com/blog

DeepMind creates ‘transformative’ map of human proteins drawn by artificial intelligence

DeepMind plans to release hundreds of millions of protein structures for free

James Vincent July 22, 2021 11:00 am

AI research lab DeepMind has created the most comprehensive map of human proteins to date using artificial intelligence. The company, a subsidiary of Google-parent Alphabet, is releasing the data for free, with some scientists comparing the potential impact of the work to that of the Human Genome Project, an international effort to map every human gene.

Proteins are long, complex molecules that perform numerous tasks in the body, from building tissue to fighting disease. Their purpose is dictated by their structure, which folds like origami into complex and irregular shapes. Understanding how a protein folds helps explain its function, which in turn helps scientists with a range of tasks — from pursuing fundamental research on how the body works, to designing new medicines and treatments.
 “the culmination of the entire 10-year-plus lifetime of DeepMind” 
Previously, determining the structure of a protein relied on expensive and time-consuming experiments. But last year DeepMind showed it can produce accurate predictions of a protein’s structure using AI software called AlphaFold. Now, the company is releasing hundreds of thousands of predictions made by the program to the public.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.”



Two examples of protein structures predicted by AlphaFold (in blue) compared with experimental results (in green). 
Image: DeepMind


There are currently around 180,000 protein structures available in the public domain, each produced by experimental methods and accessible through the Protein Data Bank. DeepMind is releasing predictions for the structure of some 350,000 proteins across 20 different organisms, including animals like mice and fruit flies, and bacteria like 
E. coli. (There is some overlap between DeepMind’s data and pre-existing protein structures, but exactly how much is difficult to quantify because of the nature of the models.) Most significantly, the release includes predictions for 98 percent of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. It isn’t the first public dataset of human proteins, but it is the most comprehensive and accurate.

If they want, scientists can download the entire human proteome for themselves, says AlphaFold’s technical lead John Jumper. “There is a HumanProteome.zip effectively, I think it’s about 50 gigabytes in size,” Jumper tells The Verge. “You can put it on a flash drive if you want, though it wouldn’t do you much good without a computer for analysis!”
 “anyone can use it for anything” 
After launching this first tranche of data, DeepMind plans to keep adding to the store of proteins, which will be maintained by Europe’s flagship life sciences lab, the European Molecular Biology Laboratory (EMBL). By the end of the year, DeepMind hopes to release predictions for 100 million protein structures, a dataset that will be “transformative for our understanding of how life works,” according to Edith Heard, director general of the EMBL.
The data will be free in perpetuity for both scientific and commercial researchers, says Hassabis. “Anyone can use it for anything,” the DeepMind CEO noted at a press briefing. “They just need to credit the people involved in the citation.”

The benefits of protein folding


Understanding a protein’s structure is useful for scientists across a range of fields. The information can help design new medicines, synthesize novel enzymes that break down waste materials, and create crops that are resistant to viruses or extreme weather. Already, DeepMind’s protein predictions are being used for medical research, including studying the workings of SARS-CoV-2, the virus that causes COVID-19.
 “it will definitely have a huge impact for the scientific community” 
New data will speed these efforts, but scientists note it will still take a lot of time to turn this information into real-world results. “I don’t think it’s going to be something that changes the way patients are treated within the year, but it will definitely have a huge impact for the scientific community,” Marcelo C. Sousa, a professor at the University of Colorado’s biochemistry department, told The Verge.
Scientists will have to get used to having such information at their fingertips, says DeepMind senior research scientist Kathryn Tunyasuvunakool. “As a biologist, I can confirm we have no playbook for looking at even 20,000 structures, so this [amount of data] is hugely unexpected,” Tunyasuvunakool told The Verge. “To be analyzing hundreds of thousands of structures — it’s crazy.”

Notably, though, DeepMind’s software produces predictions of protein structures rather than experimentally determined models, which means that in some cases further work will be needed to verify the structure. DeepMind says it spent a lot of time building accuracy metrics into its AlphaFold software, which ranks how confident it is for each prediction.

Example protein structures predicted by AlphaFold.
Image: DeepMind
Predictions of protein structures are still hugely useful, though. Determining a protein’s structure through experimental methods is expensive, time-consuming, and relies on a lot of trial and error. That means even a low-confidence prediction can save scientists years of work by pointing them in the right direction for research.
Helen Walden, a professor of structural biology at the University of Glasgow, tells The Verge that DeepMind’s data will “significantly ease” research bottlenecks, but that “the laborious, resource-draining work of doing the biochemistry and biological evaluation of, for example, drug functions” will remain.
Sousa, who has previously used data from AlphaFold in his work, says for scientists the impact will be felt immediately. “In our collaboration we had with DeepMind, we had a dataset with a protein sample we’d had for 10 years, and we’d never got to the point of developing a model that fit,” he says. “DeepMind agreed to provide us with a structure, and they were able to solve the problem in 15 minutes after we’d been sitting on it for 10 years.”

Why protein folding is so difficult

Proteins are constructed from chains of amino acids, which come in 20 different varieties in the human body. As any individual protein can be comprised of hundreds of individual amino acids, each of which can fold and twist in different directions, it means a molecule’s final structure has an incredibly large number of possible configurations. One estimate is that the typical protein can be folded in 10^300 ways — that’s a 1 followed by 300 zeroes.

 Protein folding has been a “grand challenge” of biology for decades 

Because proteins are too small to examine with microscopes, scientists have had to indirectly determine their structure using expensive and complicated methods like nuclear magnetic resonance and X-ray crystallography. The idea of determining the structure of a protein simply by reading a list of its constituent amino acids has been long theorized but difficult to achieve, leading many to describe it as a “grand challenge” of biology.
In recent years, though, computational methods — particularly those using artificial intelligence — have suggested such analysis is possible. With these techniques, AI systems are trained on datasets of known protein structures and use this information to create their own predictions.

DeepMind’s AlphaFold software has significantly increased the accuracy of computational protein-folding, as shown by its performance in the CASP competition. 
Image: DeepMind
Many groups have been working on this problem for years, but DeepMind’s deep bench of AI talent and access to computing resources allowed it to accelerate progress dramatically. Last year, the company competed in an international protein-folding competition known as CASP and blew away the competition. Its results were so accurate that computational biologist John Moult, one of CASP’s co-founders, said that “in some sense the problem [of protein folding] is solved.”

DeepMind’s AlphaFold program has been upgraded since last year’s CASP competition and is now 16 times faster. “We can fold an average protein in a matter of minutes, most cases seconds,” says Hassabis.

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The company also released the underlying code for AlphaFold last week as open-source, allowing others to build on its work in the future.

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Liam McGuffin, a professor at Reading University who developed some of the UK’s leading protein-folding software, praised the technical brilliance of AlphaFold, but also noted that the program’s success relied on decades of prior research and public data. “DeepMind has vast resources to keep this database up to date and they are better placed to do this than any single academic group,” McGuffin told The Verge. “I think academics would have got there in the end, but it would have been slower because we’re not as well resourced.”

Why does DeepMind care?

Many scientists The Verge spoke to noted the generosity of DeepMind in releasing this data for free. After all, the lab is owned by Google-parent Alphabet, which has been pouring huge amounts of resources into commercial healthcare projects. DeepMind itself loses a lot of money each year, and there have been numerous reports of tensions between the company and its parent firm over issues like research autonomy and commercial viability.

Hassabis, though, tells The Verge that the company always planned to make this information freely available, and that doing so is a fulfillment of DeepMind’s founding ethos. He stresses that DeepMind’s work is used in lots of places at Google — “almost anything you use, there’s some of our technology that’s part of that under the hood” — but that the company’s primary goal has always been fundamental research.
 “There’s many ways value can be attained.” 

“The agreement when we got acquired is that we are here primarily to advance the state of AGI and AI technologies and then use that to accelerate scientific breakthroughs,” says Hassabis. “[Alphabet] has plenty of divisions focused on making money,” he adds, noting that DeepMind’s focus on research “brings all sorts of benefits, in terms of prestige and goodwill for the scientific community. There’s many ways value can be attained.”
Hassabis predicts that AlphaFold is a sign of things to come — a project that shows the huge potential of artificial intelligence to handle messy problems like human biology.

“I think we’re at a really exciting moment,” he says. “In the next decade, we, and others in the AI field, are hoping to produce amazing breakthroughs that will genuinely accelerate solutions to the really big problems we have here on Earth.”


SOURCE

https://www.theverge.com/platform/amp/2021/7/22/22586578/deepmind-alphafold-ai-protein-folding-human-proteome-released-for-free?__twitter_impression=true

Potential Use of Protein Folding Predictions for Drug Discovery

PROTAC Technology: Opportunities and Challenges

  • Hongying Gao
  • Xiuyun Sun
  • Yu Rao*

Cite this: ACS Med. Chem. Lett. 2020, 11, 3, 237–240Publication Date:March 12, 2020https://doi.org/10.1021/acsmedchemlett.9b00597Copyright © 2020 American Chemical Society

Abstract

PROTACs-induced targeted protein degradation has emerged as a novel therapeutic strategy in drug development and attracted the favor of academic institutions, large pharmaceutical enterprises (e.g., AstraZeneca, Bayer, Novartis, Amgen, Pfizer, GlaxoSmithKline, Merck, and Boehringer Ingelheim, etc.), and biotechnology companies. PROTACs opened a new chapter for novel drug development. However, any new technology will face many new problems and challenges. Perspectives on the potential opportunities and challenges of PROTACs will contribute to the research and development of new protein degradation drugs and degrader tools.

Although PROTAC technology has a bright future in drug development, it also has many challenges as follows:
(1)
Until now, there is only one example of PROTAC reported for an “undruggable” target; (18) more cases are needed to prove the advantages of PROTAC in “undruggable” targets in the future.
(2)
“Molecular glue”, existing in nature, represents the mechanism of stabilized protein–protein interactions through small molecule modulators of E3 ligases. For instance, auxin, the plant hormone, binds to the ligase SCF-TIR1 to drive recruitment of Aux/IAA proteins and subsequently triggers its degradation. In addition, some small molecules that induce targeted protein degradation through “molecular glue” mode of action have been reported. (21,22) Furthermore, it has been recently reported that some PROTACs may actually achieve target protein degradation via a mechanism that includes “molecular glue” or via “molecular glue” alone. (23) How to distinguish between these two mechanisms and how to combine them to work together is one of the challenges for future research.
(3)
Since PROTAC acts in a catalytic mode, traditional methods cannot accurately evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) properties of PROTACs. Thus, more studies are urgently needed to establish PK and PD evaluation systems for PROTACs.
(4)
How to quickly and effectively screen for target protein ligands that can be used in PROTACs, especially those targeting protein–protein interactions, is another challenge.
(5)
How to understand the degradation activity, selectivity, and possible off-target effects (based on different targets, different cell lines, and different animal models) and how to rationally design PROTACs etc. are still unclear.
(6)
The human genome encodes more than 600 E3 ubiquitin ligases. However, there are only very few E3 ligases (VHL, CRBN, cIAPs, and MDM2) used in the design of PROTACs. How to expand E3 ubiquitin ligase scope is another challenge faced in this area.

PROTAC technology is rapidly developing, and with the joint efforts of the vast number of scientists in both academia and industry, these problems shall be solved in the near future.

PROTACs have opened a new chapter for the development of new drugs and novel chemical knockdown tools and brought unprecedented opportunities to the industry and academia, which are mainly reflected in the following aspects:
(1)
Overcoming drug resistance of cancer. In addition to traditional chemotherapy, kinase inhibitors have been developing rapidly in the past 20 years. (12) Although kinase inhibitors are very effective in cancer therapy, patients often develop drug resistance and disease recurrence, consequently. PROTACs showed greater advantages in drug resistant cancers through degrading the whole target protein. For example, ARCC-4 targeting androgen receptor could overcome enzalutamide-resistant prostate cancer (13) and L18I targeting BTK could overcome C481S mutation. (14)
(2)
Eliminating both the enzymatic and nonenzymatic functions of kinase. Traditional small molecule inhibitors usually inhibit the enzymatic activity of the target, while PROTACs affect not only the enzymatic activity of the protein but also nonenzymatic activity by degrading the entire protein. For example, FAK possesses the kinase dependent enzymatic functions and kinase independent scaffold functions, but regulating the kinase activity does not successfully inhibit all FAK function. In 2018, a highly effective and selective FAK PROTAC reported by Craig M. Crews’ group showed a far superior activity to clinical candidate drug in cell migration and invasion. (15) Therefore, PROTAC can expand the druggable space of the existing targets and regulate proteins that are difficult to control by traditional small molecule inhibitors.
(3)
Degrade the “undruggable” protein target. At present, only 20–25% of the known protein targets (include kinases, G protein-coupled receptors (GPCRs), nuclear hormone receptors, and iron channels) can be targeted by using conventional drug discovery technologies. (16,17) The proteins that lack catalytic activity and/or have catalytic independent functions are still regarded as “undruggable” targets. The involvement of Signal Transducer and Activator of Transcription 3 (STAT3) in the multiple signaling pathway makes it an attractive therapeutic target; however, the lack of an obviously druggable site on the surface of STAT3 limited the development of STAT3 inhibitors. Thus, there are still no effective drugs directly targeting STAT3 approved by the Food and Drug Administration (FDA). In November 2019, Shaomeng Wang’s group first reported a potent PROTAC targeting STAT3 with potent biological activities in vitro and in vivo. (18) This successful case confirms the key potential of PROTAC technology, especially in the field of “undruggable” targets, such as K-Ras, a tricky tumor target activated by multiple mutations as G12A, G12C, G12D, G12S, G12 V, G13C, and G13D in the clinic. (19)
(4)
Fast and reversible chemical knockdown strategy in vivo. Traditional genetic protein knockout technologies, zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), or CRISPR-Cas9, usually have a long cycle, irreversible mode of action, and high cost, which brings a lot of inconvenience for research, especially in nonhuman primates. In addition, these genetic animal models sometimes produce phenotypic misunderstanding due to potential gene compensation or gene mutation. More importantly, the traditional genetic method cannot be used to study the function of embryonic-lethal genes in vivo. Unlike DNA-based protein knockout technology, PROTACs knock down target proteins directly, rather than acting at the genome level, and are suitable for the functional study of embryonic-lethal proteins in adult organisms. In addition, PROTACs provide exquisite temporal control, allowing the knockdown of a target protein at specific time points and enabling the recovery of the target protein after withdrawal of drug treatment. As a new, rapid and reversible chemical knockdown method, PROTAC can be used as an effective supplement to the existing genetic tools. (20)

SOURCE

PROTAC Technology: Opportunities and Challenges
  • Hongying Gao
  • Xiuyun Sun
  • Yu Rao*

Cite this: ACS Med. Chem. Lett. 2020, 11, 3, 237–240

Goal in Drug Design: Eliminating both the enzymatic and nonenzymatic functions of kinase.

Work-in-Progress

Induction and Inhibition of Protein in Galectins Drug Design

Work-in-Progress

Screening Proteins in DeepMind’s AlphaFold DataBase

The company also released the underlying code for AlphaFold last week as open-source, allowing others to build on its work in the future.

Work-in-Progress

Other related research published in this Open Access Online Journal include the following:

Synthetic Biology in Drug Discovery

Peroxisome proliferator-activated receptor (PPAR-gamma) Receptors Activation: PPARγ transrepression  for Angiogenesis in Cardiovascular Disease and PPARγ transactivation for Treatment of Diabetes

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