Healthcare analytics, AI solutions for biological big data, providing an AI platform for the biotech, life sciences, medical and pharmaceutical industries, as well as for related technological approaches, i.e., curation and text analysis with machine learning and other activities related to AI applications to these industries.
Tumor board Live… Molecular profiling great for identifying synthetic lethal combinations work very well… Many oncologist not accepting recommendations of molec tumor board
Tumor board Live . Oncologists don’t always accept tumor board recommendations based on molecular profiling… Dr Baptiste at first felt constrained to use single agent but WINTER combo trial with molec profiling better
Tumor board Live… Oncologist may give pushback when molecular therapeutic targets identified.. like when methylomics give a result and tumor board suggest temazolamide
Tumor board Live… Oncologist may give pushback when molecular therapeutic targets identified.. like when methylomics give a result and tumor board suggest temazolamide
Tumor board Live… Oncologist may give pushback when molecular therapeutic targets identified.. like when methylomics give a result and tumor board suggest temazolamide
Tumor board Live… Discussion of ovarian cancer case women first presented with CRC BRCA mut but failed PARP inhibitor board is looking at immunotherapy NGS IHC performed
Tumor board Live… Molecular profiling great for identifying synthetic lethal combinations work very well… Many oncologist not accepting recommendations of molec tumor board
APOE was marker for defining a long term survivor and short term survivor for ovarian cancer patients; the markers were in the stroma
there is spatial communication between tumor and underlying stroma
it is imperative to understand how your multiomics equipment images a tumor area before it laser captures and send to the MS system; can lose a lot of tissue and information based on differences in resolution
many of these multiomics systems are validated for the clinic in EU not US
multiomics spatial analysis allows you to image protein, metabolite, mRNA expression in the 3 dimensional environment of the tumor (tumor cells and stroma)
they are making a human tumor atlas
they say a patient who had tumor went home during COVID and took vaccine but got ill with vaccine; but came back to check tumor and tumor had greatly regressed because prevaccine the tumor was immunologically cold and post COVID vaccine any left over tumor showed great infiltration of immune cells
BD Bioscience multiomics platform is modular and can add more omics levels in the platorm
for example someone wanted to look at T cells
people have added CRISPR screens on the omics platform
most people are using single cell spatial omics
they have a FACS on their platform too so you can look at single cell spatial omics and sort different cellular populations
very comparative to 10X Genomics platform
their proteomics is another layer you can add on their platform however with proteomics you can high background notice with spatial proteomics or a limited panel of biomarkers
Their OMICS Protein One panels are optimized for biology and tumor type.
get high quality multiomics data and proteomics data but in a 3D spatial format
developed Cellismo Data Visualization software tool
4:55-5:10
Harsha Gowda, PhD, Senior Principal Scientist, Director, Research & Lab Operations, Signios Bio
Signios Biosciences (Signios Bio) is the US-based arm of MedGenome, a global leader in genetic testing services, genomics research, and drug discovery solutions.
Signios Bio is a multiomics and bioinformatics company dedicated to revealing the intricate signals within biological data. We leverage the power of multiomics—integrating data from genomics, transcriptomics, proteomics, epigenomics, metabolomics, and microbiomics—to gain a comprehensive understanding of disease biology. Our AI-powered bioinformatics platform allows us to efficiently analyze these complex datasets, uncovering hidden patterns and accelerating the development of new therapies and diagnostics.
Through the integration of cutting-edge multiomics technologies, advanced bioinformatics, and the expertise of world-class scientists, we enable researchers and clinicians with comprehensive, end-to-end solutions to improve drug discovery and development and advance precision medicine.
As part of MedGenome, we have access to real-world evidence (RWE) from global research networks across the US, Europe, Asia, Africa, Middle East, and Latin America. This access enables us to work with our partners to uncover insights that can lead to new biomarkers and drug targets, ensuring that precision medicine is inclusive and effective for all.
Dr. El-Diery welcomes all to this joint symposium with Advancing Precision Medicine and the Win Consortium, which he is currently the head of. More in the WIN Consortium: (Worldwide Innovation Network Consortium in Precision Oncology). The WIN Network is involved in setting up internationalclinical tumor board collaboration
WIN was formed on the premise that we can accomplish more together than each organization can achieve working alone. We aim to improve cancer patients’ survival and quality of life. View WIN’s history and unique attributes:
WIN members collaboratively design and carry out global studies designed to achieve breakthroughs for patients worldwide. Our distinguished Scientific Advisory Board oversees WIN studies. Current trials include:
They guide WIN’s strategic, operational, and scientific direction.
OrganizationThe WIN Consortium is organized in the following groups who collectively work together to achieve WIN’s common goals
Nigel Russell, Founder and CEO, Advancing Precision Medicine
Christopher P. Molineaux, President & Chief Executive Officer, Life Science Pennsylvania
Life Sciences Pennsylvania (LSPA) is the statewide trade association for the commonwealth’s life sciences industry. Founded in 1989, LSPA works to ensure Pennsylvania has a business and public policy climate that makes the commonwealth the most attractive location to open and operate a life sciences company. Our membership is comprised of organizations statewide, representing the entire ecosystem of the life sciences: research institutions, biotechnology, medical device, diagnostic, pharmaceutical, and investment entities, along with service providers who support the industry. Together, we unify Pennsylvania’s innovators to make the Commonwealth a global life sciences leader.
As president & CEO of Life Sciences Pennsylvania, Christopher Molineaux serves as the chief advocate and spokesman for the life sciences industry that calls Pennsylvania home. Molineaux oversees the strategic direction for the association, assuring Life Sciences Pennsylvania continues to be the catalyst that makes Pennsylvania the top location for life sciences companies.
Molineaux brings to Life Sciences Pennsylvania more than 25 years of experience in the bio-pharmaceutical and health care industries, with front-line experience in developing and executing strategies to navigate a shifting economic and political environment.
9:00-9:40
Keynote Lecture – WIN Consortium
Targeting the Achilles’ Heel of Cancer: Synthetic Lethality and Hypoxia in Precision Oncology
William Kaelin was born in New York City. He studied chemistry and mathematics at Duke University in Durham, North Carolina, and received his doctor of medicine degree there in 1982. He then did his residency at Johns Hopkins University in Baltimore, Maryland. In 2002 he became a professor at Harvard Medical School in Cambridge, Massachusetts.
Work
Animals need oxygen for the conversion of food into useful energy. The importance of oxygen has been understood for centuries, but how cells adapt to changes in levels of oxygen has long been unknown. William Kaelin, Peter Ratcliffe, and Gregg Semenza discovered how cells can sense and adapt to changing oxygen availability. During the 1990s they identified a molecular machinery that regulates the activity of genes in response to varying levels of oxygen. The discoveries may lead to new treatments of anemia, cancer and many other diseases.
TRACK 1 204BC
WIN SYMPOSIUM
MULTI-OMICS
9:40 – 10:40
SESSION 1
From Base Pairs To Better Care:
AI and Omics in Precision Oncology
9:40-10:00
Multi-Omic Profiling and Clinical Decision Support in Precision Oncology
David Spetzler, PhD, MBA, MS, President, Caris Life Sciences
10:00-10:20
Integrating Omics and AI for Next-Gen Precision Oncology
Keith T. Flaherty, MD, FAACR, Director of Clinical Research,Massachusetts General Cancer Center; Professor of Medicine, Harvard Medical School; President-Elect: 2025-2026, American Association for Cancer Research (AACR)
10:20-10:40
Real-World Data and AI in Precision Oncology: Making Data Work for Patients – Q&A
MODERATOR: Jeff Elton, PhD, Vice Chairman, Founding CEO
ConcertAI
PANELISTS: David Spetzler, PhD, MBA, MS, President, Caris Life Sciences
Keith T. Flaherty, MD, FAACR, Director of Clinical Research,Massachusetts General Cancer Center; Professor of Medicine, Harvard Medical School; President-Elect: 2025-2026, American Association for Cancer Research (AACR)
Daryl Pritchard, PhD, Interim President, Personalized Medicine Coalition
Keith T. Flaherty, MD, FAACR, Director of Clinical Research,Massachusetts General Cancer Center; Professor of Medicine, Harvard Medical School; President-Elect: 2025-2026, American Association for Cancer Research (AACR)
SESSION 3
The Shifting Landscape:
Tumor Plasticity and Resistance
12:00-12:20
Mathematical and Evolutionary Modeling in Precision Radiation Oncology
Jacob Scott, MD, DPhil, Professor and Staff Physician-Scientist, CWRU School of Medicine and Cleveland Clinic
12:20-12:40
Plasticity and Persistence: The Role of EMT in Cancer Progression and Therapy Resistance
Sendurai A. Mani, PhD, Professor of Pathology and Laboratory Medicine, Brown University; Associate Director of Translational Oncology, Brown University Legorreta Cancer Center
12:40-1:00
Targeting Molecularly Defined Subsets: Challenges in Translational Oncology
Benedito A. Carneiro, MD, MS, Director, Clinical Research Director, Cancer Drug Development; Associate Director, Division of Hematology/Oncology
Legorreta Cancer Center, Brown University Health
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.
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.
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.
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
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.
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
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:
Speeding up target validation: now we can get through 300 molecules a day
Predicition like AlphaFold is doing; molecular simulations
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
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
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:
Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use
In this curation we wish to present two breaking through goals:
Goal 1:
Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer
Goal 2:
Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.
According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.
These eight subcellular pathologies can’t be measured at present time.
In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.
Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases
Glycation
Oxidative Stress
Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
Membrane instability
Inflammation in the gut [mucin layer and tight junctions]
Epigenetics/Methylation
Autophagy [AMPKbeta1 improvement in health span]
Diseases that are not Diseases: no drugs for them, only diet modification will help
Image source
Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease
These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:
Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL
In the Bioelecronics domain we are inspired by the work of the following three research sources:
Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia
THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC
PENDING
THE VOICE of Stephen J. Williams, PhD
Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes
25% of US children have fatty liver
Type II diabetes can be manifested from fatty live with 151 million people worldwide affected moving up to 568 million in 7 years
A common myth is diabetes due to overweight condition driving the metabolic disease
There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
Thirty percent of ‘obese’ people just have high subcutaneous fat. the visceral fat is more problematic
there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects. Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
At any BMI some patients are insulin sensitive while some resistant
Visceral fat accumulation may be more due to chronic stress condition
Fructose can decrease liver mitochondrial function
A methionine and choline deficient diet can lead to rapid NASH development
Acinetobacter baumannii bacteria that are resistant to important antibiotics called carbapenems. Acinetobacter baumannii are highly-drug resistant bacteria that can cause a range of infections for hospitalized patients, including pneumonia, wound, or blood infections.
Pseudomonas aeruginosa, which are resistant to carbapenems. Pseudomonas aeruginosa can cause skin rashes and ear infectious in healthy people but also severe blood infections and pneumonia when contracted by sick people in the hospital.
Enterobacteriaceae — a family of bacteria that live in the human gut — that are resistant to both carbepenems and another class of antibiotics, cephalosporins.
It has been designated critical need for development of antibiotics to these pathogens. Now researchers at Mcmaster University and others in the US had used artificial intelligence (AI) to screen libraries of over 7,000 chemicals to find a drug that could be repurposed to kill off the pathogen.
Liu et. Al. (1) published their results of an AI screen to narrow down potential chemicals that could work against Acinetobacter baumanii in Nature Chemical Biology recently.
Abstract
Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new antibacterial molecules. Here we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE. Moreover, abaucin could control an A. baumannii infection in a mouse wound model. This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen.
Schematic workflow for incorporation of AI for antibiotic drug discovery for A. baumannii from 1. Liu, G., Catacutan, D.B., Rathod, K. et al. Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii. Nat Chem Biol (2023). https://doi.org/10.1038/s41589-023-01349-8
Antibiotics kill bacteria. However, there has been a lack of new drugs for decades and bacteria are becoming harder to treat, as they evolve resistance to the ones we have.
More than a million people a year are estimated to die from infections that resist treatment with antibiotics.The researchers focused on one of the most problematic species of bacteria – Acinetobacter baumannii, which can infect wounds and cause pneumonia.
You may not have heard of it, but it is one of the three superbugs the World Health Organization has identified as a “critical” threat.
It is often able to shrug off multiple antibiotics and is a problem in hospitals and care homes, where it can survive on surfaces and medical equipment.
Dr Jonathan Stokes, from McMaster University, describes the bug as “public enemy number one” as it’s “really common” to find cases where it is “resistant to nearly every antibiotic”.
Artificial intelligence
To find a new antibiotic, the researchers first had to train the AI. They took thousands of drugs where the precise chemical structure was known, and manually tested them on Acinetobacter baumannii to see which could slow it down or kill it.
This information was fed into the AI so it could learn the chemical features of drugs that could attack the problematic bacterium.
The AI was then unleashed on a list of 6,680 compounds whose effectiveness was unknown. The results – published in Nature Chemical Biology – showed it took the AI an hour and a half to produce a shortlist.
The researchers tested 240 in the laboratory, and found nine potential antibiotics. One of them was the incredibly potent antibiotic abaucin.
Laboratory experiments showed it could treat infected wounds in mice and was able to kill A. baumannii samples from patients.
However, Dr Stokes told me: “This is when the work starts.”
The next step is to perfect the drug in the laboratory and then perform clinical trials. He expects the first AI antibiotics could take until 2030 until they are available to be prescribed.
Curiously, this experimental antibiotic had no effect on other species of bacteria, and works only on A. baumannii.
Many antibiotics kill bacteria indiscriminately. The researchers believe the precision of abaucin will make it harder for drug-resistance to emerge, and could lead to fewer side-effects.
In principle, the AI could screen tens of millions of potential compounds – something that would be impractical to do manually.
“AI enhances the rate, and in a perfect world decreases the cost, with which we can discover these new classes of antibiotic that we desperately need,” Dr Stokes told me.
The researchers tested the principles of AI-aided antibiotic discovery in E. coli in 2020, but have now used that knowledge to focus on the big nasties. They plan to look at Staphylococcus aureus and Pseudomonas aeruginosa next.
“This finding further supports the premise that AI can significantly accelerate and expand our search for novel antibiotics,” said Prof James Collins, from the Massachusetts Institute of Technology.
He added: “I’m excited that this work shows that we can use AI to help combat problematic pathogens such as A. baumannii.”
Prof Dame Sally Davies, the former chief medical officer for England and government envoy on anti-microbial resistance, told Radio 4’s The World Tonight: “We’re onto a winner.”
She said the idea of using AI was “a big game-changer, I’m thrilled to see the work he (Dr Stokes) is doing, it will save lives”.
Other related articles and books published in this Online Scientific Journal include the following:
Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases, Reproductive Genomic Endocrinology
Science Has A Systemic Problem, Not an Innovation Problem
Curator:Stephen J. Williams, Ph.D.
A recent email, asking me to submit a survey, got me thinking about the malaise that scientists and industry professionals frequently bemoan: that innovation has been stymied for some reason and all sorts of convuluted processes must be altered to spur this mythical void of great new discoveries….. and it got me thinking about our current state of science, and what is the perceived issue… and if this desert of innovation actually exists or is more a fundamental problem which we have created.
The email was from an NIH committee asking for opinions on recreating the grant review process …. now this on the same day someone complained to me about a shoddy and perplexing grant review they received.
The following email, which was sent out to multiple researchers, involved in either NIH grant review on both sides, as well as those who had been involved in previous questionnaires and studies on grant review and bias. The email asked for researchers to fill out a survey on the grant review process, and how to best change it to increase innovation of ideas as well as inclusivity. In recent years, there have been multiple survey requests on these matters, with multiple confusing procedural changes to grant format and content requirements, adding more administrative burden to scientists.
The email from Center for Scientific Review (one of the divisions a grant will go to before review {they set up review study sections and decide what section a grant should be assigned to} was as follows:
Update on Simplifying Review Criteria: A Request for Information
NIH has issued a request for information (RFI) seeking feedback on revising and simplifying the peer review framework for research project grant applications. The goal of this effort is to facilitate the mission of scientific peer review – identification of the strongest, highest-impact research. The proposed changes will allow peer reviewers to focus on scientific merit by evaluating 1) the scientific impact, research rigor, and feasibility of the proposed research without the distraction of administrative questions and 2) whether or not appropriate expertise and resources are available to conduct the research, thus mitigating the undue influence of the reputation of the institution or investigator.
Currently, applications for research project grants (RPGs, such as R01s, R03s, R15s, R21s, R34s) are evaluated based on five scored criteria: Significance, Investigators, Innovation, Approach, and Environment (derived from NIH peer review regulations 42 C.F.R. Part 52h.8; see Definitions of Criteria and Considerations for Research Project Grant Critiques for more detail) and a number of additional review criteria such as Human Subject Protections.
NIH gathered input from the community to identify potential revisions to the review framework. Given longstanding and often-heard concerns from diverse groups, CSR decided to form two working groups to the CSR Advisory Council—one on non-clinical trials and one on clinical trials. To inform these groups, CSR published a Review Matters blog, which was cross-posted on the Office of Extramural Research blog, Open Mike. The blog received more than 9,000 views by unique individuals and over 400 comments. Interim recommendations were presented to the CSR Advisory Council in a public forum (March 2020 video, slides; March 2021 video, slides). Final recommendations from the CSRAC (report) were considered by the major extramural committees of the NIH that included leadership from across NIH institutes and centers. Additional background information can be found here. This process produced many modifications and the final proposal presented below. Discussions are underway to incorporate consideration of a Plan for Enhancing Diverse Perspectives (PEDP) and rigorous review of clinical trials RPGs (~10% of RPGs are clinical trials) within the proposed framework.
Simplified Review Criteria
NIH proposes to reorganize the five review criteria into three factors, with Factors 1 and 2 receiving a numerical score. Reviewers will be instructed to consider all three factors (Factors 1, 2 and 3) in arriving at their Overall Impact Score (scored 1-9), reflecting the overall scientific and technical merit of the application.
Factor 1: Importance of the Research (Significance, Innovation), numerical score (1-9)
Factor 2: Rigor and Feasibility (Approach), numerical score (1-9)
Factor 3: Expertise and Resources (Investigator, Environment), assessed and considered in the Overall Impact Score, but not individually scored
Within Factor 3 (Expertise and Resources), Investigator and Environment will be assessed in the context of the research proposed. Investigator(s) will be rated as “fully capable” or “additional expertise/capability needed”. Environment will be rated as “appropriate” or “additional resources needed.” If a need for additional expertise or resources is identified, written justification must be provided. Detailed descriptions of the three factors can be found here.
Now looking at some of the Comments were very illuminating:
I strongly support streamlining the five current main review criteria into three, and the present five additional criteria into two. This will bring clarity to applicants and reduce the workload on both applicants and reviewers. Blinding reviewers to the applicants’ identities and institutions would be a helpful next step, and would do much to reduce the “rich-getting-richer” / “good ole girls and good ole boys” / “big science” elitism that plagues the present review system, wherein pedigree and connections often outweigh substance and creativity.
I support the proposed changes. The shift away from “innovation” will help reduce the tendency to create hype around a proposed research direction. The shift away from Investigator and Environment assessments will help reduce bias toward already funded investigators in large well-known institutions.
As a reviewer for 5 years, I believe that the proposed changes are a step in the right direction, refocusing the review on whether the science SHOULD be done and whether it CAN BE DONE WELL, while eliminating burdensome and unhelpful sections of review that are better handled administratively. I particularly believe that the de-emphasis of innovation (which typically focuses on technical innovation) will improve evaluation of the overall science, and de-emphasis of review of minor technical details will, if implemented correctly, reduce the “downward pull” on scores for approach. The above comments reference blinded reviews, but I did not see this in the proposed recommendations. I do not believe this is a good idea for several reasons: 1) Blinding of the applicant and institution is not likely feasible for many of the reasons others have described (e.g., self-referencing of prior work), 2) Blinding would eliminate the potential to review investigators’ biosketches and budget justifications, which are critically important in review, 3) Making review blinded would make determination of conflicts of interest harder to identify and avoid, 4) Evaluation of “Investigator and Environment” would be nearly impossible.
Most of the Comments were in favor of the proposed changes, however many admitted that it adds additional confusion on top of many administrative changes to formats and content of grant sections.
Being a Stephen Covey devotee, and just have listened to The Four Principles of Execution, it became more apparent that issues that hinder many great ideas coming into fruition, especially in science, is a result of these systemic or problems in the process, not at the level of individual researchers or small companies trying to get their innovations funded or noticed. In summary, Dr. Covey states most issues related to the success of any initiative is NOT in the strategic planning, but in the failure to adhere to a few EXECUTION principles. Primary to these failures of strategic plans is lack of accounting of what Dr. Covey calls the ‘whirlwind’, or those important but recurring tasks that take us away from achieving the wildly important goals. In addition, lack of determining lead and lag measures of success hinder such plans.
In this case a lag measure in INNOVATION. It appears we have created such a whirlwind and focus on lag measures that we are incapable of translating great discoveries into INNOVATION.
In the following post, I will focus on issues relating to Open Access, publishing and dissemination of scientific discovery may be costing us TIME to INNOVATION. And it appears that there are systemic reasons why we appear stuck in a rut, so to speak.
The first indication is from a paper published by Johan Chu and James Evans in 2021 in PNAS:
Slowed canonical progress in large fields of science
Chu JSG, Evans JA. Slowed canonical progress in large fields of science. Proc Natl Acad Sci U S A. 2021 Oct 12;118(41):e2021636118. doi: 10.1073/pnas.2021636118. PMID: 34607941; PMCID: PMC8522281
Abstract
In many academic fields, the number of papers published each year has increased significantly over time. Policy measures aim to increase the quantity of scientists, research funding, and scientific output, which is measured by the number of papers produced. These quantitative metrics determine the career trajectories of scholars and evaluations of academic departments, institutions, and nations. Whether and how these increases in the numbers of scientists and papers translate into advances in knowledge is unclear, however. Here, we first lay out a theoretical argument for why too many papers published each year in a field can lead to stagnation rather than advance. The deluge of new papers may deprive reviewers and readers the cognitive slack required to fully recognize and understand novel ideas. Competition among many new ideas may prevent the gradual accumulation of focused attention on a promising new idea. Then, we show data supporting the predictions of this theory. When the number of papers published per year in a scientific field grows large, citations flow disproportionately to already well-cited papers; the list of most-cited papers ossifies; new papers are unlikely to ever become highly cited, and when they do, it is not through a gradual, cumulative process of attention gathering; and newly published papers become unlikely to disrupt existing work. These findings suggest that the progress of large scientific fields may be slowed, trapped in existing canon. Policy measures shifting how scientific work is produced, disseminated, consumed, and rewarded may be called for to push fields into new, more fertile areas of study.
So the Summary of this paper is
The authors examined 1.8 billion citations among 90 million papers over 241 subjects
found the corpus of papers do not lead to turnover of new ideas in a field, but rather the ossification or entrenchment of canonical (or older ideas)
this is mainly due to older paper cited more frequently than new papers with new ideas, potentially because authors are trying to get their own papers cited more frequently for funding and exposure purposes
The authors suggest that “fundamental progress may be stymied if quantitative growth of scientific endeavors is not balanced by structures fostering disruptive scholarship and focusing attention of novel ideas”
The authors note that, in most cases, science policy reinforces this “more is better” philosophy”, where metrics of publication productivity are either number of publications or impact measured by citation rankings. However, using an analysis of citation changes occurring in large versus smaller fields, it becomes apparent that this process is favoring the older, more established papers and a recirculating of older canonical ideas.
“Rather than resulting in faster turnover of field paradigms, the massive amounts of new publications entrenches the ideas of top-cited papers.” New ideas are pushed down to the bottom of the citation list and potentially lost in the literature. The authors suggest that this problem will intensify as the “annual mass” of new publications in each field grows, especially in large fields. This issue is exacerbated by the deluge on new online ‘open access’ journals, in which authors would focus on citing the more highly cited literature.
We maybe at a critical junction, where if many papers are published in a short time, new ideas will not be considered as carefully as the older ideas. In addition,
with proliferation of journals and the blurring of journal hierarchies due to online articles-level access can exacerbate this problem
As a counterpoint, the authors do note that even though many molecular biology highly cited articles were done in 1976, there has been extremely much innovation since then however it may take a lot more in experiments and money to gain the level of citations that those papers produced, and hence a lower scientific productivity.
This issue is seen in the field of economics as well
Ellison, Glenn. “Is peer review in decline?” Economic Inquiry, vol. 49, no. 3, July 2011, pp. 635+. Gale Academic OneFile, link.gale.com/apps/doc/A261386330/AONE?u=temple_main&sid=bookmark-AONE&xid=f5891002. Accessed 12 Dec. 2022.
Abstract:
Over the past decade, there has been a decline in the fraction of papers in top economics journals written by economists from the highest-ranked economics departments. This paper documents this fact and uses additional data on publications and citations to assess various potential explanations. Several observations are consistent with the hypothesis that the Internet improves the ability of high-profile authors to disseminate their research without going through the traditional peer-review process. (JEL A14, 030)
The facts part of this paper documents two main facts:
1. Economists in top-ranked departments now publish very few papers in top field journals. There is a marked decline in such publications between the early 1990s and early 2000s.
2. Comparing the early 2000s with the early 1990s, there is a decline in both the absolute number of papers and the share of papers in the top general interest journals written by Harvard economics department faculty.
Although the second fact just concerns one department, I see it as potentially important to understanding what is happening because it comes at a time when Harvard is widely regarded (I believe correctly) as having ascended to the top position in the profession.
The “decline-of-peer-review” theory I allude to in the title is that the necessity of going through the peer-review process has lessened for high-status authors: in the old days peer-reviewed journals were by far the most effective means of reaching readers, whereas with the growth of the Internet high-status authors can now post papers online and exploit their reputation to attract readers.
Many alternate explanations are possible. I focus on four theories: the decline-in-peer-review theory and three alternatives.
1. The trends could be a consequence of top-school authors’ being crowded out of the top journals by other researchers. Several such stories have an optimistic message, for example, there is more talent entering the profession, old pro-elite biases are being broken down, more schools are encouraging faculty to do cutting-edge research, and the Internet is enabling more cutting-edge research by breaking down informational barriers that had hampered researchers outside the top schools. (2)
2. The trends could be a consequence of the growth of revisions at economics journals discussed in Ellison (2002a, 2002b). In this more pessimistic theory, highly productive researchers must abandon some projects and/or seek out faster outlets to conserve the time now required to publish their most important works.
3. The trends could simply reflect that field journals have declined in quality in some relative sense and become a less attractive place to publish. This theory is meant to encompass also the rise of new journals, which is not obviously desirable or undesirable.
The majority of this paper is devoted to examining various data sources that provide additional details about how economics publishing has changed over the past decade. These are intended both to sharpen understanding of the facts to be explained and to provide tests of auxiliary predictions of the theories. Two main sources of information are used: data on publications and data on citations. The publication data include department-level counts of publications in various additional journals, an individual-level dataset containing records of publications in a subset of journals for thousands of economists, and a very small dataset containing complete data on a few authors’ publication records. The citation data include citations at the paper level for 9,000 published papers and less well-matched data that is used to construct measures of citations to authors’ unpublished works, to departments as a whole, and to various journals.
Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship
Josh Angrist, Pierre Azoulay, Glenn Ellison, Ryan Hill, Susan Feng Lu. Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship.
JOURNAL OF ECONOMIC LITERATURE
Abstract
Does academic economic research produce material of general scientific value, or do academic economists write only for peers? Is economics scholarship uniquely insular? We address these questions by quantifying interactions between economics and other disciplines. Changes in the influence of economic scholarship are measured here by the frequency with which other disciplines cite papers in economics journals. We document a clear rise in the extramural influence of economic research, while also showing that economics is increasingly likely to reference other social sciences. A breakdown of extramural citations by economics fields shows broad field influence. Differentiating between theoretical and empirical papers classified using machine learning, we see that much of the rise in economics’ extramural influence reflects growth in citations to empirical work. This growth parallels an increase in the share of empirical cites within economics. At the same time, some disciplines that primarily cite economic theory have also recently increased citations of economics scholarship.
Citation
Angrist, Josh, Pierre Azoulay, Glenn Ellison, Ryan Hill, and Susan Feng Lu. 2020.“Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship.”Journal of Economic Literature, 58 (1): 3-52.DOI: 10.1257/jel.20181508
VOL. 58, NO. 1, MARCH 2020
(pp. 3-52)
So if innovation is there but it may be buried under the massive amount of heavily cited older literature, do we see evidence of this in other fields like medicine?
Why Isn’t Innovation Helping Reduce Health Care Costs?
National health care expenditures (NHEs) in the United States continue to grow at rates outpacing the broader economy: Inflation- and population-adjusted NHEs have increased 1.6 percent faster than the gross domestic product (GDP) between 1990 and 2018. US national health expenditure growth as a share of GDP far outpaces comparable nations in the Organization for Economic Cooperation and Development (17.2 versus 8.9 percent).
Multiple recent analyses have proposed that growth in the prices and intensity of US health care services—rather than in utilization rates or demographic characteristics—is responsible for the disproportionate increases in NHEs relative to global counterparts. The consequences of ever-rising costs amid ubiquitous underinsurance in the US include price-induced deferral of care leading to excess morbidity relative to comparable nations.
These patterns exist despite a robust innovation ecosystem in US health care—implying that novel technologies, in isolation, are insufficient to bend the health care cost curve. Indeed, studies have documented that novel technologies directly increase expenditure growth.
Why is our prolific innovation ecosystem not helping reduce costs? The core issue relates to its apparent failure to enhance net productivity—the relative output generated per unit resource required. In this post, we decompose the concept of innovation to highlight situations in which inventions may not increase net productivity. We begin by describing how this issue has taken on increased urgency amid resource constraints magnified by the COVID-19 pandemic. In turn, we describe incentives for the pervasiveness of productivity-diminishing innovations. Finally, we provide recommendations to promote opportunities for low-cost innovation.
Net Productivity During The COVID-19 Pandemic
The issue of productivity-enhancing innovation is timely, as health care systems have been overwhelmed by COVID-19. Hospitals in Italy, New York City, and elsewhere have lacked adequate capital resources to care for patients with the disease, sufficient liquidity to invest in sorely needed resources, and enough staff to perform all of the necessary tasks.
The critical constraint in these settings is not technology: In fact, the most advanced technology required to routinely treat COVID-19—the mechanical ventilator—was invented nearly 100 years ago in response to polio (the so-called iron lung). Rather, the bottleneck relates to the total financial and human resources required to use the technology—the denominator of net productivity. The clinical implementation of ventilators has been illustrative: Health care workers are still required to operate ventilators on a nearly one-to-one basis, just like in the mid-twentieth century.
High levels of resources required for implementation of health care technologies constrain the scalability of patient care—such as during respiratory disease outbreaks such as COVID-19. Thus, research to reduce health care costs is the same kind of research we urgently require to promote health care access for patients with COVID-19.
Types Of Innovation And Their Relationship To Expenditure Growth
The widespread use of novel medical technologies has been highlighted as a central driver of NHE growth in the US. We believe that the continued expansion of health care costs is largely the result of innovation that tends to have low productivity (exhibit 1). We argue that these archetypes—novel widgets tacked on to existing workflows to reinforce traditional care models—are exactly the wrong properties to reduce NHEs at the systemic level.
Exhibit 1: Relative productivity of innovation subtypes
These may be contrasted with process innovations, which address the organized sequences of activities that implement content. Classically, these include clinical pathways and protocols. They can address the delivery of care for acute conditions, such as central line infections, sepsis, or natural disasters. Alternatively, they can target chronic conditions through initiatives such as team-based management of hypertension and hospital-at-home models for geriatric care. Other processes include hiring staff, delegating labor, and supply chain management.
Performance-Enhancing Versus Cost-Reducing Innovation
Performance-enhancing innovations frequently create incremental outcome gains in diagnostic characteristics, such as sensitivity or specificity, or in therapeutic characteristics, such as biomarkers for disease status. Their performance gains often lead to higher prices compared to existing alternatives.
Performance-enhancing innovations can be compared to “non-inferior” innovations capable of achieving outcomes approximating those of existing alternatives, but at reduced cost. Industries outside of medicine, such as the computing industry, have relied heavily on the ability to reduce costs while retaining performance.
In health care though, this pattern of innovation is rare. Since passage of the 2010 “Biosimilars” Act aimed at stimulating non-inferior innovation and competition in therapeutics markets, only 17 agents have been approved, and only seven have made it to market. More than three-quarters of all drugs receiving new patents between 2005 and 2015 were “reissues,” meaning they had already been approved, and the new patent reflected changes to the previously approved formula. Meanwhile, the costs of approved drugs have increased over time, at rates between 4 percent and 7 percent annually.
Moreover, the preponderance of performance-enhancing diagnostic and therapeutic innovations tend to address narrow patient cohorts (such as rare diseases or cancer subtypes), with limited clear clinical utility in broader populations. For example, the recently approved eculizimab is a monoclonal antibody approved for paroxysmal nocturnal hemoglobinuria—which effects 1 in 10 million individuals. At the time of its launch, eculizimab was priced at more than $400,000 per year, making it the most expensive drug in modern history. For clinical populations with no available alternatives, drugs such as eculizimab may be cost-effective, pending society’s willingness to pay, and morally desirable, given a society’s values. But such drugs are certainly not cost-reducing.
Additive Versus Substitutive Innovation
Additive innovations are those that append to preexisting workflows, while substitutive innovations reconfigure preexisting workflows. In this way, additive innovations increase the use of precedent services, whereas substitutive innovations decrease precedent service use.
For example, previous analyses have found that novel imaging modalities are additive innovations, as they tend not to diminish use of preexisting modalities. Similarly, novel procedures tend to incompletely replace traditional procedures. In the case of therapeutics and devices, off-label uses in disease groups outside of the approved indication(s) can prompt innovation that is additive. This is especially true, given that off-label prescriptions classically occur after approved methods are exhausted.
Eculizimab once again provides an illustrative example. As of February 2019, the drug had been used for 39 indications (it had been approved for three of those, by that time), 69 percent of which lacked any form of evidence of real-world effectiveness. Meanwhile, the drug generated nearly $4 billion in sales in 2019. Again, these expenditures may be something for which society chooses to pay—but they are nonetheless additive, rather than substitutive.
Sustaining Versus Disruptive Innovation
Competitive market theory suggests that incumbents and disruptors innovate differently. Incumbents seek sustaining innovations capable of perpetuating their dominance, whereas disruptors pursue innovations capable of redefining traditional business models.
In health care, while disruptive innovations hold the potential to reduce overall health expenditures, often they run counter to the capabilities of market incumbents. For example, telemedicine can deliver care asynchronously, remotely, and virtually, but large-scale brick-and-mortar medical facilities invest enormous capital in the delivery of synchronous, in-house, in-person care (incentivized by facility fees).
The connection between incumbent business models and the innovation pipeline is particularly relevant given that 58 percent of total funding for biomedical research in the US is now derived from private entities, compared with 46 percent a decade prior. It follows that the growing influence of eminent private organizations may favor innovations supporting their market dominance—rather than innovations that are societally optimal.
Incentives And Repercussions Of High-Cost Innovation
Taken together, these observations suggest that innovation in health care is preferentially designed for revenue expansion rather than for cost reduction. While offering incremental improvements in patient outcomes, therefore creating theoretical value for society, these innovations rarely deliver incremental reductions in short- or long-term costs at the health system level.
For example, content-based, performance-enhancing, additive, sustaining innovations tend to add layers of complexity to the health care system—which in turn require additional administration to manage. The net result is employment growth in excess of outcome improvement, leading to productivity losses. This gap leads to continuously increasing overall expenditures in turn passed along to payers and consumers.
Nonetheless, high-cost innovations are incentivized across health care stakeholders (exhibit 2). From the supply side of innovation, for academic researchers, “breakthrough” and “groundbreaking” innovations constitute the basis for career advancement via funding and tenure. This is despite stakeholders’ frequent inability to generalize early successes to become cost-effective in the clinical setting. As previously discussed, the increasing influence of private entities in setting the medical research agenda is also likely to stimulate innovation benefitting single stakeholders rather than the system.
Source: Authors’ analysis adapted from Hofmann BM. Too much technology. BMJ. 2015 Feb 16.
From the demand side of innovation (providers and health systems), a combined allure (to provide “cutting-edge” patient care), imperative (to leave “no stone unturned” in patient care), and profit-motive (to amplify fee-for-service reimbursements) spur participation in a “technological arms-race.” The status quo thus remains as Clay Christensen has written: “Our major health care institutions…together overshoot the level of care actually needed or used by the vast majority of patients.”
Christensen’s observations have been validated during the COVID-19 epidemic, as treatment of the disease requires predominantly century-old technology. By continually adopting innovation that routinely overshoots the needs of most patients, layer by layer, health care institutions are accruing costs that quickly become the burden of society writ large.
Recommendations To Reduce The Costs Of Health Care Innovation
Henry Aaron wrote in 2002 that “…the forces that have driven up costs are, if anything, intensifying. The staggering fecundity of biomedical research is increasing…[and] always raises expenditures.” With NHEs spiraling ever-higher, urgency to “bend the cost curve” is mounting. Yet, since much biomedical innovation targets the “flat of the [productivity] curve,” alternative forms of innovation are necessary.
The shortcomings in net productivity revealed by the COVID-19 pandemic highlight the urgent need for redesign of health care delivery in this country, and reevaluation of the innovation needed to support it. Specifically, efforts supporting process redesign are critical to promote cost-reducing, substitutive innovations that can inaugurate new and disruptive business models.
Process redesign rarely involves novel gizmos, so much as rejiggering the wiring of, and connections between, existing gadgets. It targets operational changes capable of streamlining workflows, rather than technical advancements that complicate them. As described above, precisely these sorts of “frugal innovations” have led to productivity improvements yielding lower costs in other high-technology industries, such as the computing industry.
Shrank and colleagues recently estimated that nearly one-third of NHEs—almost $1 trillion—were due to preventable waste. Four of the six categories of waste enumerated by the authors—failure in care delivery, failure in care coordination, low-value care, and administrative complexity—represent ripe targets for process innovation, accounting for $610 billion in waste annually, according to Shrank.
Health systems adopting process redesign methods such as continuous improvement and value-based management have exhibited outcome enhancement and expense reduction simultaneously. Internal processes addressed have included supply chain reconfiguration, operational redesign, outlier reconciliation, and resource standardization.
Despite the potential of process innovation, focus on this area (often bundled into “health services” or “quality improvement” research) occupies only a minute fraction of wallet- or mind-share in the biomedical research landscape, accounting for 0.3 percent of research dollars in medicine. This may be due to a variety of barriers beyond minimal funding. One set of barriers is academic, relating to negative perceptions around rigor and a lack of outlets in which to publish quality improvement research. To achieve health care cost containment over the long term, this dimension of innovation must be destigmatized relative to more traditional manners of innovation by the funders and institutions determining the conditions of the research ecosystem.
Another set of barriers is financial: Innovations yielding cost reduction are less “reimbursable” than are innovations fashioned for revenue expansion. This is especially the case in a fee-for-service system where reimbursement is tethered to cost, which creates perverse incentives for health care institutions to overlook cost increases. However, institutions investing in low-cost innovation will be well-positioned in a rapidly approaching future of value-based care—in which the solvency of health care institutions will rely upon their ability to provide economically efficient care.
Innovating For Cost Control Necessitates Frugality Over Novelty
Restraining US NHEs represents a critical step toward health promotion. Innovation for innovation’s sake—that is content-based, incrementally effective, additive, and sustaining—is unlikely to constrain continually expanding NHEs.
In contrast, process innovation offers opportunities to reduce costs while maintaining high standards of patient care. As COVID-19 stress-tests health care systems across the world, the importance of cost control and productivity amplification for patient care has become apparent.
As such, frugality, rather than novelty, may hold the key to health care cost containment. Redesigning the innovation agenda to stem the tide of ever-rising NHEs is an essential strategy to promote widespread access to care—as well as high-value preventive care—in this country. In the words of investors across Silicon Valley: Cost-reducing innovation is no longer a “nice-to-have,” but a “need-to-have” for the future of health and overall well-being this country.
So Do We Need A New Way of Disseminating Scientific Information? Can Curation Help?
We had high hopes for Science 2.0, in particular the smashing of data and knowledge silos. However the digital age along with 2.0 platforms seemed to excaccerbate this somehow. We still are critically short on analysis!
Old Science 1.0 is still the backbone of all scientific discourse, built on the massive amount of experimental and review literature. However this literature was in analog format, and we moved to a more accesible digital open access format for both publications as well as raw data. However as there was a structure for 1.0, like the Dewey decimal system and indexing, 2.0 made science more accesible and easier to search due to the newer digital formats. Yet both needed an organizing structure; for 1.0 that was the scientific method of data and literature organization with libraries as the indexers. In 2.0 this relied on an army mostly of volunteers who did not have much in the way of incentivization to co-curate and organize the findings and massive literature.
The Intenet and the Web is rapidly adopting a new “Web 3.0” format, with decentralized networks, enhanced virtual experiences, and greater interconnection between people. Here we start the discussion what will the move from Science 2.0, where dissemination of scientific findings was revolutionized and piggybacking on Web 2.0 or social media, to a Science 3.0 format. And what will it involve or what paradigms will be turned upside down?
Biden will appoint Dr. Elizabeth Jaffee, Dr. Mitchel Berger and Dr. Carol Brown to the panel, which will advise him and the White House on how to use resources of the federal government to advance cancer research and reduce the burden of cancer in the United States.
Jaffee, who will serve as chair of the panel, is an expert in cancer immunology and pancreatic cancer, according to the White House. She is currently the deputy director of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University and previously led the American Association for Cancer Research.
In this Sept. 8, 2016, file photo, Dr. Elizabeth M. Jaffee of the Pancreatic Dream Team attends Stand Up To Cancer (SU2C), a program of the Entertainment Industry Foundation (EIF), in Hollywood, Calif.ABC Handout via Getty Images, FILE
Berger, a neurological surgeon, directs the University of California, San Francisco Brain Tumor Center and previously spent 23 years at the school as a professor of neurological surgery.
Brown, a gynecologic oncologist, is the senior vice president and chief health equity officer at Memorial Sloan Kettering Cancer Center in New York City. According to the White House, much of her career has been focused on eliminating cancer care disparities due to racial, ethnic, cultural or socioeconomic factors.
Additionally, First Lady Jill Biden, members of the Cabinet and other administration officials are holding a meeting Wednesday of the Cancer Cabinet, made up of officials across several governmental departments and agencies, the White House said.
The Cabinet will introduce new members and discuss priorities in the battle against cancer including closing the screening gap, addressing potential environmental exposures, reducing the number of preventable cancer and expanding access to cancer research.MORE: Long Island school district found to have higher rates of cancer cases: Study
It is the second meeting of the cabinet since Biden relaunched the initiative in February, which he originally began in 2016 when he was vice president.
Both Jaffee and Berger were members of the Blue Ribbon Panel for the Cancer Moonshot Initiative led by Biden.
The initiative has personal meaning for Biden, whose son, Beau, died of glioblastoma — one of the most aggressive forms of brain cancer — in 2015.
“I committed to this fight when I was vice president,” Biden said at the time, during an event at the White House announcing the relaunch. “It’s one of the reasons why, quite frankly, I ran for president. Let there be no doubt, now that I am president, this is a presidential, White House priority. Period.”
The initiative has several priority actions including diagnosing cancer sooner; preventing cancer; addressing inequities; and supporting patients, caregivers and survivors.
In this June 14, 2016, file photo, Dr. Carol Brown, physician at Memorial Sloan Kettering Cancer Center, gives a presentation, at The White House Summit on The United State of Women, in Washington, D.C.NurPhoto via Getty Images, FILE
The White House has also issued a call to action to get cancer screenings back to pre-pandemic levels.
“We have to get cancer screenings back on track and make sure they’re accessible to all Americans,” Biden said at the time.
Since the first meeting of the Cancer Cabinet, the Centers for Disease Control and Prevention has issued more than $200 million in grants to cancer prevention programs, the Centers for Medicaid & Medicare Services implemented a new model to reduce the cost of cancer care, and the U.S. Patent and Trademark Office said it will fast-track applications for cancer immunotherapies.
ABC News’ Sasha Pezenik contributed to this report.
President Joe Biden is expected to pick cancer surgeon Monica Bertagnolli as the next director of the National Cancer Institute (NCI). Bertagnolli, a physician-scientist at Brigham and Women’s Hospital, the Dana-Farber Cancer Center, and Harvard Medical School, specializes in gastrointestinal cancers and is well known for her expertise in clinical trials. She will replace Ned Sharpless, who stepped down as NCI director in April after nearly 5 years.
The White House has not yet announced the selection, first reported by STAT, but several cancer research organizations closely watching for the nomination have issued statements supporting Bertagnolli’s expected selection. She is “a national leader” in clinical cancer research and “a great person to take the job,” Sharpless told ScienceInsider.
With a budget of $7 billion, NCI is the largest component of the National Institutes of Health (NIH) and the world’s largest funder of cancer research. Its director is the only NIH institute director selected by the president. Bertagnolli’s expected appointment, which does not require Senate confirmation, drew applause from the cancer research community
Margaret Foti, CEO of the American Association for Cancer Research, praised Bertagnolli’s “appreciation for … basic research” and “commitment to ensuring that such treatment innovations reach patients … across the United States.” Ellen Sigal, chair and founder of Friends of Cancer Research, says Bertagnolli “brings expertise the agency needs at a true inflection point for cancer research.”
Bertagnolli, 63, will be the first woman to lead NCI. Her lab research on tumor immunology and the role of a gene called APC in colorectal cancer led to a landmark trial she headed showing that an anti-inflammatory drug can help prevent this cancer. In 2007, she became the chief of surgery at the Dana-Farber Brigham Cancer Center.
She served as president of the American Society of Clinical Oncology in 2018 and currently chairs the Alliance for Clinical Trials in Oncology, which is funded by NCI’s National Clinical Trials Network. The network is a “complicated” program, and “Monica will have a lot of good ideas on how to make it work better,” Sharpless says.
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One of Bertagnolli’s first tasks will be to shape NCI’s role in Biden’s reignited Cancer Moonshot, which aims to slash the U.S. cancer death rate in half within 25 years. NCI’s new leader also needs to sort out how the agency will mesh with a new NIH component that will fund high-risk, goal-driven research, the Advanced Research Projects Agency for Health (ARPA-H).
Bertagnolli will also head NCI efforts already underway to boost grant funding rates, diversify the cancer research workplace, and reduce higher death rates for Black people with cancer.
The White House recently nominated applied physicist Arati Prabhakar to fill another high-level science position, director of the White House Office of Science and Technology Policy (OSTP). But still vacant is the NIH director slot, which Francis Collins, acting science adviser to the president, left in December 2021. And the administration hasn’t yet selected the inaugural director of ARPA-H.
Correction, 22 July, 9 a.m.: This story has been updated to reflect that Francis Collins is acting science adviser to the president, not acting director of the White House Office of Science and Technology Policy.
Infertility is a major reproductive health issue that affects about 12% of women of reproductive age in the United States. Aneuploidy in eggs accounts for a significant proportion of early miscarriage and in vitro fertilization failure. Recent studies have shown that genetic variants in several genes affect chromosome segregation fidelity and predispose women to a higher incidence of egg aneuploidy. However, the exact genetic causes of aneuploid egg production remain unclear, making it difficult to diagnose infertility based on individual genetic variants in mother’s genome. Although, age is a predictive factor for aneuploidy, it is not a highly accurate gauge because aneuploidy rates within individuals of the same age can vary dramatically.
Researchers described a technique combining genomic sequencing with machine-learning methods to predict the possibility a woman will undergo a miscarriage because of egg aneuploidy—a term describing a human egg with an abnormal number of chromosomes. The scientists were able to examine genetic samples of patients using a technique called “whole exome sequencing,” which allowed researchers to home in on the protein coding sections of the vast human genome. Then they created software using machine learning, an aspect of artificial intelligence in which programs can learn and make predictions without following specific instructions. To do so, the researchers developed algorithms and statistical models that analyzed and drew inferences from patterns in the genetic data.
As a result, the scientists were able to create a specific risk score based on a woman’s genome. The scientists also identified three genes—MCM5, FGGY and DDX60L—that when mutated and are highly associated with a risk of producing eggs with aneuploidy. So, the report demonstrated that sequencing data can be mined to predict patients’ aneuploidy risk thus improving clinical diagnosis. The candidate genes and pathways that were identified in the present study are promising targets for future aneuploidy studies. Identifying genetic variations with more predictive power will serve women and their treating clinicians with better information.
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