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Tweets by @pharma_BI and @AVIVA1950 for #PMConf  at The 13th Annual Personalized Medicine Conference, From Concept to the Clinic, November 14–16, 2017, Joseph B. Martin Conference Center, Harvard Medical School, 77 Avenue Louis Pasteur Boston, MA 02115

Curator: Aviva Lev-Ari, PhD, RN

 

@pharma_BI

@AVIVA1950

 

All TWEETS from LPBI’s Twitter.com handles at #PMConf 

@pharma_BI

@AVIVA1950

  1. Aviva Lev-Ari Retweeted Gary An

    nice comment

    Aviva Lev-Ari added,

  2. Narrative plan unsupported by facts

  3. Robert C. Green, M.D., M.P.H., Director, Genomes2People Research Program, Professor of Medicine (Genetics), Brigham and Women’s Hospital, Broad Institute and Harvard Medical School pharmacogenomics can harm if odds are so low adherence will be lower

  4. Michael Snyder, Ph.D., Stanford W. Ascherman Professor, Chair, Department of Genetics, Director, Center of GenomiPersonalized Medicine, Stanford University School of Medicine Personal sequencing for multiple etiologies rich people are sequenced

  5. Tom Miller, M.S., Founder, Managing Partner, GreyBird Ventures LLC duty to call up therapies that will not work, balance addressed by PM – diagnostics in PM clinical utility from patient selection for the therapy the patient will respond to

  6. Sandro Galea, M.D., School of Public Health, Boston University US expense on Health care the highest in the World comes on the expense of housings, mental health, education – curative vs preventive care MDs are insentiviced to keep patients sick

  7. Robert C. Green, M.D., Broad Institute and HMS Platinum vs gold standard 59 genes will identify 80,000 will get the disease and 47,000 will never get the disease, is the technology the reason for investment vs Family history?

  8. Bryce Olson, Global Marketing Director, Health and Life Sciences Group, Intel Corporation Genome sequencing found his Pi3K Pathway – PIK3CA p.E54 – Anti Inhibitor for Pi3K = Precision Medicine

  9. Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA 21st Century – metastatic solid tumors – 900 patients: accommodated plan Lab developed Tests: new approach Efficiency, transparency

  10. innovation INFORMS at NIH Center of Excellence – data collection and analysis of multiple data types Biometric sensors collecting data on cancer patients collaboration with Academia, single arm vs randomized decentralized devices are collecting data

  11. FDA considers N of One, small samples, EGFR drug was approved in 2 1/2 years since Phase 1 of NDA New trial designs: reduce bias and alternative end points narrow criteria for participation, more personalized and more patient-centered innovation

  12. Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA Advances of technology of biomarkers, disease indication Accelerated approval by FDA a collaborative of speeding the process companion diagnosis assays

  13. Unmet need, commitment is there, innovation and connectivity drive access, collaboration not competition – helps Precision medicine in emerging nations. Access to PM anywhere in the world suggested Kristin Pothier, MS, Global Head, Life Sciences EY

  14. Stephen L. Eck, M.D., Ph.D., President, CEO, Aravive Biologics; Board Chairman, PMC Laxo – A molecular target to be found by diagnostics TEST — as a basis to develop a drug Pricing and value – dimensions of Value to society How PM is done today?

  15. Marc S. Williams, MD Geisinger Clinical Genomics vs Physician specialist (i.e.,hypercholestoralemia), both in same place – paper and EMR Outcomes – tracking patients over decades – systems in place to capture the data Virtual Cycle Clinical data

  16. Timothy Cannon, M.D., Inova Molecular Tumor Board, 5 hospital in VA, Precision Genomics Cancer Therapy Poor understanding of molecular results by MDs, Refractory Patients no Forum to discuss other options 220 patients presented beyond InovaOncologi

  17. Scott A. Beck, Mayo Clinic, MN, AZ PM, Genomics sequencing, BioEthics, IT, Translational Perspective in Epi-genomics, Discovery to Translation Applicattions Pharmacy- Formulary – EMR – Champions from Disease areas to practice environment Testing

  18. payment dominates delivery of care, future PM from Genomics cost to patients Transform acceptability of PM suggested Ronald A. Paulus, M.D., M.B.A., President, CEO, Mission Health, NC, ex-Geisinger, CIO

  19. Genomics based PM to be turned into Wellness Strategy – the path not yet knows said Jeffrey R. Balser, M.D., Ph.D., Dean, Vanderbilt University School of Medicine; President, CEO, Vanderbilt University Medical Center, Nashville, TN

  20. Millianlian Diabetics NOT on Medicare, Analytics: iPhone telling patient dishes to order since SYSTEM KNOWS BLOOD SUGER 24×7 – target care by Analytics Genomics paid by NIH PM Analytics is built at Vanderbilt University MC, Jeffrey R. Balser, CEO

  21. Survival of patient with mutation and targeted drug LIVE LONGER David B. Roth, M.D., Ph.D., Simon Flexner Professor Chair, Pathology and Laboratory Medicine, Perelman School of Medicine at University of Pennsylvania

  22. Lotte Steuten, Ph.D., School of Pharmacy at University of Washington, Seattle aggregate big data , models as evidence, has value to clinical, the model under development NGS Profile of Patient vs current standard of care.

  23. David B. Roth, M.D., Ph.D., UPenn Director, Penn Center for Precision Medicine 5000 patients underwent genome sequencing Interpretation is the issue that is hard Health IT are still in silos: Pharmacy data, financial data, EMR

  24. Michael Pellini, M.D., M.B.A., Chairman, Board of Directors, Foundation Medicine; Board Member, Personalized Medicine Coalition, we know there is value in PM we need to work together on the challenges — to prove the value in PM

  25. Andrea Stern Ferris, M.B.A., President, Chairman of the Board, LUNGevity Foundation – PATIENT to be included in the conversation patient after successful treatment have hope work pay taxes pay to health plans continue family life

  26. Molecular Era, NEJM, 2017, 377, 1813-1823, BRAF in Melanoma – 80% do not need additional therapy vs 20% benefitted in the Non-Molecular Era, data by Dane J. Dickson, CureOne (formerly MED-C); Oregon Health and Science University

  27. CURES – CAR-T are they cures??? A teen-ager’s Value-based Price: $475,000 x years lived suggests  Steven D. Pearson, M.D., M.Sc., Founder, President, Institute for Clinical and Economic Review (ICER)

  28. Of 134 drugs in development – 42 have the potential to become Personalized medicine therapies, said Stephen J. Ubl, President, CEO, PhRMA

  29. Transplantation vs enhancement – resistance to senescence and pathogens to be achieved by gene editing suggests George M. Church, Ph.D., Professor of Genetics

  30. Regulatory oversight on engineering embrios is coming, metric of success in recruitment of patients said Arthur L. Caplan, Ph.D., Drs. William F. and Virginia Connolly Mitty Chair, Director, Division of Medical Ethics, New York Univ

  31. CRISPR does not handle all mutation many require a different editing tool said George M. Church, Ph.D., Professor of Genetics, Health Sciences and Technology, Harvard-MIT Division of Health Sciences and Technology

  32. understand well enough  the gentic application where CRISPR will assist medicine: Retinal degeneration, two aspects one worked in Japan said Katrine Bosley, CEO, Editas Medicine

  33. Aviva Lev-Ari Retweeted Aviva Lev-Ari

    Amazing Power in hands of informed patients

    Aviva Lev-Ari added,

  34. Patients input and sophistication increased – IRB is not aware of the engagement of Patients and their challenging feedback say Deborah Schrag, M.D., M.P.H, Dana Farber

  35. Physicians needs interfaces, dashboard information delivered to MDs, data sits unused, new tools are needed for the data display by relevance to the MDs – clinicians needs decision support in their office

  36. Standards: Toxicity criteria – library of 882 symptoms, Patient reported outcomes by Patients, Resist criteria applied to imaging data criteria for brain tumors said Deborah Schrag, M.D., M.P.H., Chief Medical Oncology, Dana-Farber

  37. drafting document on Verify data integrity in clinical trials, detect discrepancies compromise the integrity of the data – audits by FDA said Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA

  38. pre-existing autoimmune disease – not indicated for them Immunotherapy even though patients wish to try said Deborah Schrag, M.D., M.P.H., Chief, Division of Population Sciences, Medical Oncology, Dana-Farber Cancer Institute

  39. Drug approved for one indication, provide new data for supplemental indications said Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA

  40. Eric G. Klein, Pharm.D, Eli Lilly Aggregate burden of disease, existence of co-morbidities Genomics: WHY is explained – precise tools data vs intelligence – interoperability Past clinical trial, replicate studies retrospective data

  41. linkages vs computational techniques we do not have consistent data, data structured Vital sign or WBC count – we have data standardization is evolving said Deborah Schrag, M.D., M.P.H., Chief, Dana-Farber Cancer Institute

  42. use data sets prospective vs retrospective studies asked Amy Abernethy, M.D., Ph.D., Chief Medical Officer, Chief Scientific Officer, Flatiron Health; Board Member, Personalized Medicine Coalition

  43. Clinical sense vs research context, FDA is more comfortable with other than oncology products beyond drugs, namely diagnostics, diagnostics company seeking partnership with many drug areas Thermo FIscher and Novartis partnership

  44. Cost of CT Scan vs an NGS Test – Genomic testing is much cheaper yet volume is still low said Jacob S. Van Naarden, Chief Business Officer, Loxo Oncology

  45. NGS – time results come back what the mutation mean? NOW results come in few days, data analysis assist the said Joydeep Goswami, Ph.D., M.B.A., M.S., President, Clinical Next-Generation Sequencing, Oncology, Thermo Fisher Scientifi

  46. 3D BioPrinting of Drugs and the innovation storm of agents — are both benefits, value based pricing, elasticities, is that price sufficient to support R&D, dynamic environment said Joshua Ofman, SVP, Global Value, Access, Amgen

  47. Awardee of Leadership in PM, Illumina, HC system not yet ready for Precision Medicine

  48. Amgen and Harvard Pilgrims interpretation of Values related to partnerships: Novartis

  49. at Illimina – Consumer Advocacy added to Technology breakthroughs in genome sequencing said Jay T. Flatley, M.S., Executive Chairman, Illumina

  50. National Genomic Service – Sequencing becoming STANDARD of Care, phynotypes, $10 million to be spent NIH said Jay T. Flatley, M.S., Executive Chairman, Illumina

  51. 13th Annual Leadership in Personalized Medicine Award AWARDEE | Jay T. Flatley, M.S., Executive Chairman, Illumina

  52. 13th Annual Leadership in PM Award to Jay T Flatlet, Illumina

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LIVE Day Two – 13th Annual Personalized Medicine Conference, From Concept to the Clinic, November 14–16, 2017, Joseph B. Martin Conference Center, Harvard Medical School, 77 Avenue Louis Pasteur Boston, MA 02115

 

JOSEPH B. MARTIN CONFERENCE CENTER

HARVARD MEDICAL SCHOOL, BOSTON, MA 02115

http://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/13th_Annual_PM_Conference37.pdf

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston

pharma_bi-background0238

will cover in REAL TIME the 13th Annual Personalized Medicine, From Concept to the Clinic, November 14–16, 2017, Joseph B. Martin Conference Center, Harvard Medical School, 77 Avenue Louis Pasteur Boston, MA 02115

In attendance, covering LIVE using Social Media

Aviva Lev-Ari, PhD, RN

Editor-in-Chief

http://pharmaceuticalintelligence.com

@pharma_BI

@AVIVA1950

#PMConf

Agenda · Part II  NOVEMBER 16, 2017 · CONFERENCE PROGRAM | AGENDA

7:00 am Registration and Breakfast

8:00 am Opening Remarks

SPEAKER | Stephen L. Eck, M.D., Ph.D., President, CEO, Aravive Biologics; Board Chairman, Personalized Medicine Coalition

  • 2005 at Pfizer new initiative on Personalized Medicine
  • Left to go to Lilly – not to give a drug to  Patients with KRAS mutation – beginning of PM
  • Laxo – A molecular target to be found by diagnostics TEST  — as a basis to develop a drug
  • Pricing and value – dimensions of Value to society
  • How PM is done today

8:10 am Clinical Adoption of Personalized Medicine: A Two-Part Discussion Pioneering health care providers have begun to explore the business models, operational processes, IT infrastructure and educational programs that are needed to catalyze the paradigm shift toward personalized medicine. This two-part session on clinical adoption will examine the strategic and day-to-day challenges clinical organizations face as they seek to integrate personalized medicine in clinical settings — and the solutions they employ to address those challenges.

SESSION CHAIR | Marcia A. Kean, M.B.A., Chairman, Strategic Initiatives, Feinstein Kean Healthcare

Discussion Part 1

8:15 am The Case for Personalized Medicine in the Clinic: The View From the Corner Office Inspiring an organizational commitment to a new way of practicing medicine requires visionary leadership. This fireside chat will highlight the viewpoints and approaches of leaders who are spearheading efforts to adopt personalized medicine at clinical institutions, with an eye on the value proposition for changing existing norms and practices.

MODERATOR | Howard L. McLeod, Pharm.D., Medical Director, The DeBartolo Family Personalized Medicine Institute, Chair, Department of Individualized Cancer Management, Senior Member, Division of Population Sciences, Moffitt Cancer Center; Board Member, Personalized Medicine Coalition

Jeffrey R. Balser, M.D., Ph.D., Dean, Vanderbilt University School of Medicine; President, CEO, Vanderbilt University Medical Center, Nashville, TN

  • Vanderbilt University Medical Center [$500 Million in Grants] is a HealthCare System, split from Vanderbilt University School of Medicine [1200 Medical Residents], now they are like Partners
  • BioMedical Informatics very strong at Vanderbilt University School of Medicine
  • Jeffrey R. Balser, M.D., Ph.D. was first student of Dan, A pioneer in Personalized Medicine
  • PM and Non-Oncology: PLAVIX – DSS when MD order drugs DSS trigger No PLAVIX to this patient, made second decision in real time by MDs
  • Nashville – four flagship hospitals, largest HMO not for profit in the country
  • PM at Vanderbilt University Medical Center – 25 drugs – given ONLY after Genomic sequencing
  • Millianlian Diabetics NOT on Medicare, Analytics: iPhone telling patient what dishes to order since SYSTEM KNOWS BLOOD SUGER 24×7 – target care by Analytics
  • Genomics paid by NIH
  • PM Analytics is built at Vanderbilt University Medical Center said Jeffrey R. Balser, M.D., Ph.D., Dean, Vanderbilt University School of Medicine; President, CEO, Vanderbilt University Medical Center
  • what is the economics benefit of Genomic sequencing: DSS on Drugs – Peterson is documenting drug class by economic benefit – bundle to show value
  • Genomics based PM is on drugs — polimorthism – this drug will not work
  • Disease counseling is harder than drug = wellness strategy is the Fututre
  • Genomics based PM to be turned into Wellness Strategy – the path not yet knows said Jeffrey R. Balser, M.D., Ph.D., Dean, Vanderbilt University School of Medicine; President, CEO, Vanderbilt University Medical Center, Nashville, TN
  • Research Investment is R&D, decisions made to guide all research and investment in PM initiative – not generating money. Pilot studies leads to grants. One study is on Economic benefit of PM

Ronald A. Paulus, M.D., M.B.A., President, CEO, Mission Health, NC, ex-Geisinger, CIO

  • 8 most western counties in NC
  • small group of Genetists:
  1. PM and Oncology and – Cancer therapy from a Genomics stand point
  2. PM and Non-Oncology – Drug-Drug interactions
  3. Clinicians needs actionable information
  4. Primary care practices to adopt PM – HOW, where, why? what will be out of pocket expense to the individual
  5. subsidization is a must
  6. payment dominates delivery of care, future PM from Genomics cost to patients
  7. Transform acceptability of PM suggested Ronald A. Paulus, M.D., M.B.A., President, CEO, Mission Health, NC, ex-Geisinger, CIO

Discussion Part 2

9:00 am Practicing Personalized Medicine: Lessons From the Front Lines To successfully integrate personalized medicine into a health system, administrators and clinicians must also design and implement new processes related to program infrastructure and informatics; help educate physicians and patients about the field; and inspire cultural change within the institution. During this panel discussion, a group of early adopters will share lessons learned from implementing pilot programs across the United States.

MODERATOR | Daryl Pritchard, Ph.D., Senior Vice President, Science Policy, Personalized Medicine Coalition

Bonnie J. Addario, Founder, Chair, Bonnie J. Addario Lung Cancer Foundation; Board Member, Personalized Medicine Coalition; Lung Cancer Survivor

Scott A. Beck, M.B.A., Administrator, Center for Individualized Medicine, Mayo Clinic, MN, AZ

  • PM, Genomics sequencing, BioEthics, IT, Translational Perspective in Epi-genomics,
  • Discovery to Translation Applicattions
  • Pharmacy- Formulary – EMR – Champions from Disease areas to practice environment
  • Testing offering, approve value
  • 25 Projects: PharmacoGenomics Testing to patients, change drug before repeat endoscopy

Timothy Cannon, M.D., Clinical Director, Inova Schar Cancer Institute Molecular Tumor Board

  • 5 hospital in VA,
  • Precision Genomics Cancer Therapy
  • Poor understanding of molecular results by MDs, Refractory Patients – no Forum to discuss other options
  • Molecular Tumor Board for Inova Health System: 220 patients presented beyond Inova
  • Oncologists had concerned that patients are aware of drug that MD can’t deliver to client

Peter Hulick, M.D., M.M.Sc., Medical Director, Center for Personalized Medicine, NorthShore University HealthSystem

  • 4 hospitals – 950 MDs
  • PCP to get engaged
  • Neurology
  • Genetic Assessment tool DSS offers PCP option for electronic ordering of the Genetic Testing, Results appear in Patients’ charts
  • Proactive testing
  • 20,000 patients in the system to be tested for pharmaco-genomics testing

Marc S. Williams, M.D., F.A.A.P., F.A.C.M.G., F.A.C.M.I., Director, Genomic Medicine Institute, Geisinger – Central PA

  • 30% of providers are Geisinger the rest are not
  • Genomics: PM — Microbiome bank – broad user consent: recontact and return results
  • Genomics Medicine Institute – 2014 Partnership with Regeneron – genomics sequencing and profiling — all result to be used by Geisinger
  • 170,000 patient consented – 90% responded, 8,000 sequences available
  • 80 gene with potential actionability – interpretation by Scientists
  • Pathologic calls return results –
  • Clinical Genomics vs Physician specialist (i.e.,hypercholestoralemia), both in same place – paper and EMR
  • Outcomes – tracking patients over decades – systems in place to capture the data
  • Virtual Cycle Clinical data – dashboards were created to deliver results per week.
  • 1/2 people do not need criteria
  • Geisinger will disseminate internationally

10:15 am Networking Break (sponsored by Moffitt Cancer Center)

10:45 am Harvard Business School Case Study — Intermountain Healthcare: Pursuing Precision Medicine Intermountain has a long history of being at the forefront of health care quality improvement and the development of treatment protocols. In 2013, Intermountain Precision Genomics (IPG) was started with Dr. Lincoln Nadauld as its Executive Director. IPG focused on stage 4 cancer patients and performed three distinct functions: genomic sequencing, interpretation of sequencing results with recommendations for precision therapies, and drug acquisition and reimbursement. A paper published in February 2017 reported that in addition to having a higher quality of life, patients who received the targeted therapies had progression-free survival rates of almost twice as long as other patients. The purpose of our case discussion will be to assess these efforts, to consider their broader applicability and to review IPG’s plans for the future.

PRESENTER | Richard Hamermesh, D.B.A., Co-Faculty Chair, Harvard Business School Kraft Precision Medicine Accelerator

12:00 pm Overview of the International Landscape for Personalized Medicine

PRESENTER | Kristin Pothier, M.S., Global Head, Life Sciences, Parthenon-EY

  • Precision Medicine in the Globe – stackholder ecosystem
  • India
  • Latin America
  • USA
  • Africa
  • EU
  • APAC
  • Middle East

Regional Spotlight:

China – strength emerging 1.4 Billion people, 4.2 million annual incidence of Cancer – systemic challenges will limit access

Brazil – 440,000 cancer incidents a year, 207 Million Corporate, Hospital, Government, Academic research, collaboration vs competition, collaboration will win

Dubai – 28.5 Million population

Qatar

UAE – Initiative to sequence the entire population, 6,000 done

Saudi Arabia

Middle East – 0.4 oncologist for 100,000

Summary – Unmet need, commitment is there, innovation and connectivity drive access, collaboration not competition – helps Precision medicine in emerging nations. Access to PM anywhere in the world suggested Kristin Pothier, M.S., Global Head, Life Sciences, Parthenon-EY

12:30 pm Bag Lunch

1:30 pm Personalized Medicine at FDA: An Inside Look at the Agency’s Priorities for the Field

INTRODUCTION | Cynthia A. Bens, Vice President, Public Policy, Personalized Medicine Coalition

KEYNOTE | Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA

  • Advances of technology of biomarkers, disease indication
  • Accelerated approval by FDA a collaborative of speeding the process
  • companion diagnosis assays and drug or biologics
  • FDA considers N of One, small samples, EGFR drug was approved in 2 1/2 years since Phase 1 of NDA
  • New trial designs: reduce bias and alternative end points
  • narrow criteria for participation, more personalized and more patient-centered
  • innovation INFORMS at NIH Center of Excellence – data collection and analysis of multiple data types
  • Biometric sensors collecting data on cancer patients
  • collaboration with Academia, single arm vs randomized, decentralized
  • devices are collecting data in clinical trials
  • 21st Century – metastatic solid tumors – 900 patients: accommodated plan
  • Lab developed Tests: new approach
  • Efficiency, transparency

2:00 pm The Patient Perspective on Personalized Medicine

INTRODUCTION | Susan McClure, Founder, Publisher, Genome magazine; Board Member, Personalized Medicine Coalition

  • Precision medicine and relevant information for Patients
  • Genomic sequencing is the Opening Gate to PM

KEYNOTE | Bryce Olson, Global Marketing Director, Health and Life Sciences Group, Intel Corporation

  • genome sequencing found his Pi3K Pathway – PIK3CA p.E54 – Anti Inhibitor for Pi3K = Precision Medicine

2:30 pm Patient 2.0: Exploring the Future of Personalized Medicine Many observers speculate that the coming wave of gene editing, gene therapy, direct-to-consumer genetic tests and the personalized use of wearables will change the psychology, sociology, economy and efficacy of health care. Informed by the previous panel discussions, this conversation will examine the future of personalized medicine and the merits of these emerging trends.

MODERATOR | Robert C. Green, M.D., M.P.H., Director, Genomes2People Research Program, Professor of Medicine (Genetics), Brigham and Women’s Hospital, Broad Institute and Harvard Medical School

  • Neurologist first , Geneticist thereafter
  • Platinum vs gold standard
  • 59 genes will identify 80,000 will get the disease and 47,000 will never get the disease
  • is the technology the reason for investment vs Family history
  • pharmacogenomics can harm, if odds are so low than adherence will be lower

Sandro Galea, M.D., M.P.H., Dr.P.H., Dean, Robert A. Knox Professor, School of Public Health, Boston University

  • Skeptical of societal aspects: race, 50% of the country health getting better vs 50% getting worse but enthusiast on technology
  • US expense on Health care the highest in the World comes on the expense of housings, mental health, education – curative vs preventive care
  • MDs are insentiviced to keep patients sick
  • Folic Acid
  • Nudge behavior
  • invest in long livivng

Tom Miller, M.S., Founder, Managing Partner, GreyBird Ventures LLC

  • duty to call up therapies that will not work, balance addressed by PM – diagnostics in PM
  • clinical utility from patient selection for the therapy the patient will respond to
  • fantasy: Medical decision making to be made to avoid un neccesary care

Michael Snyder, Ph.D., Stanford W. Ascherman Professor, Chair, Department of Genetics, Director, Center of Genomics and Personalized Medicine, Stanford University School of Medicine

  • Personal sequencing for multiple etiologies
  • rich people come to get sequenced
  • libraries
  • Providers to be incentivized if patients are health

3:30 pm Closing Remarks

SPEAKER | Edward Abrahams, Ph.D., President, Personalized Medicine Coalition

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LIVE Day One – 13th Annual Personalized Medicine Conference, From Concept to the Clinic, November 14–16, 2017, Joseph B. Martin Conference Center, Harvard Medical School, 77 Avenue Louis Pasteur Boston, MA 02115

 

JOSEPH B. MARTIN CONFERENCE CENTER

HARVARD MEDICAL SCHOOL, BOSTON, MA 02115

http://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/13th_Annual_PM_Conference37.pdf

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston

pharma_bi-background0238

will cover in REAL TIME the 13th Annual Personalized Medicine, From Concept to the Clinic, November 14–16, 2017, Joseph B. Martin Conference Center, Harvard Medical School, 77 Avenue Louis Pasteur Boston, MA 02115

In attendance, covering LIVE using Social Media

Aviva Lev-Ari, PhD, RN

Editor-in-Chief

http://pharmaceuticalintelligence.com

@pharma_BI

@AVIVA1950

#PMConf

Agenda · Part I  NOVEMBER 15, 2017 · CONFERENCE PROGRAM | AGENDA

7:00 am Registration and Breakfast

8:00 am Opening Remarks SPEAKER | Edward Abrahams, Ph.D., President, Personalized Medicine Coalition

  • 13th Annual PM Conference at HMS
  • Paradigm shift from One medicine FITS ALL – 13 years ago was a promise in 2017 it is a REALITY
  • Liquid biopsies, read and write gene therapy
  • Value, Pricing, Access
  • Evidence for reimbursement and FDA directions
  • Introduction od PM to the Clinic
  • Case study on Value and Healthcare System
  • Future of PM Stanford, BU, Investor
  • Translation to Chinese, 50 guests from 20 countries and 21 from CA

 

8:10 am The State of Personalized Medicine

INTRODUCTION |

Steven D. Averbuch, M.D., Head, Precision Medicine Research & Development, Bristol-Myers Squibb; Board Member, Personalized Medicine Coalition

  • Known Tom for few decades, collecting tissue on lung cancer.
  • EGFR – discovered at HMS

KEYNOTE |

Thomas J. Lynch, Jr., M.D., Executive Vice President, Chief Scientific Officer, Research & Development, Bristol-Myers Squibb

  • Apply right drug to right patient
  • Gefitinig (AstraZeneca) vs Carboplatin/Paclitaxel – lung cancer – advanced NSCLC
  • Gene mutation – EGFR negative vs Positive – cost of sequencing inverse to Moore’s Law
  • Genome Sequenced at <$1,000
  • Lung Adenocarcinoma: 2016: PIK3CA, KRAS, BRAF
  • 2015NEJM – Design drugs: Resistance mutation vs. negative – no mutation EGFR
  • Immune -Biology of Cancer is Complex – Tumor, Effector Cells, Immune regulatory & APGs
  • NEXT opportunities: Novel I-O mechanisms, patient selection is key
  • Biomarkers: PDL-1, MSI – H Tumor mutation Burden (TMB) LAG-3
  • Future: Gene signature
  • Pembrolizumab Free survivsls – 50%
  • BMS – FoundationOne – calibration used by BMS: Mutational Burden: FoundationOne assey: Exploratory analysis: High TMB (Nivoluman vs Chemo, Nivo id bettervs LowTMB
  • Combination Drug Therapy: Nivo +Ipi
  • Assessment of TMB: coding regions of 21K genes: WES vs FoundationOne (F1)
  • TMB in Blood (bTMB) in 2L + NSCLC (POPLAR and OAK)
  • bTMB <16 vs bTMB >16
  • PM – molecular profiling of Hundreds of Cancers and PM of drug treatment driven by molecular profiles
  • F1 is promising

8:40 am 13th Annual Leadership in Personalized Medicine Award

AWARDEE | Jay T. Flatley, M.S., Executive Chairman, Illumina

  • Precision Medicine – still inpact is limited
  • Regulatory and Reimbursement are BARRIERS in the HealthCare system,
  • Kidney Cancer treated off-label – great
  • less 10% of tumors have been sequenced, sufficient tissue needed, physician voted not to sequence deeming it un-actionable
  • Cystic Fibrosis – only sequencing lead to FDA approval, POST marketing required significant resources
  • Translational researchers validated 200 genes
  • 400 genes at FoundationOne
  • DIagnostics companies – reimbursement process is TOO LONG
  • Regulatory – emerging diagnostics: Product in use in clinical trials
  • Risk models to be shared with Diagnostics companies – reimbursement at end of period when results are available
  • Blockchain technology is promising for handling data
  • Rare diseases in Cancer  – One milion genomes sequenced
  • National Genomic Service – Sequencing becoming STANDARD of Care, phynotypes, $10 million to be spent NIH said Jay T. Flatley, M.S., Executive Chairman, Illumina
  • at Illimina – Consumer Advocacy added to Technology breakthroughs in genome sequencing said Jay T. Flatley, M.S., Executive Chairman, Illumina

9:10 am Networking Break

9:35 am Progress in Partnerships: A Two-Part Discussion Aligning the constructs of the health system with the principles of personalized medicine will require stakeholders to scale the most promising cross-sector partnership models. This series of conversations will examine the potential of several of the most promising models that have emerged thus far.

Discussion

Part 1 9:35 am A Model for Risk-Sharing Agreements Between Payers and the Pharmaceutical Industry Many payers are reluctant to assume that covering personalized medicines will help mitigate costs associated with major medical events that require hospitalization. During this fireside chat, however, representatives from Amgen and Harvard Pilgrim Health Care will discuss the logic and implications of their groundbreaking agreement to share the financial risks of covering a targeted medicine based on that premise. Under the terms of the agreement, Amgen agreed to cover treatment costs for patients who have a heart attack or stroke while taking its personalized therapy for familial hypercholesterolemia.

MODERATOR | Meg Tirrell, M.S.J., Reporter, CNBC

Joshua Ofman, M.D., M.S.H.S., Senior Vice President, Global Value, Access and Policy, Amgen

  • Hyperlipidemia – Partnering, Amgen with Harvard Pilgrim Health Care
  • Arrangements: Patients who need the medication will get access to the medication
  • effective stuards: Co-Pay not too high, replacement of medication by generics
  • Medicare has requirements
  • Migraine medications are coming out from Amgen – novel payment
  • Combination drug therapy – Payment system not ready for it yet
  • 3D BioPrinting of Drugs and the innovation storm of agents — are both benefits, value based pricing, elasticities, is that price sufficient to support R&D, dynamic not linear environment said Joshua Ofman, M.D., M.S.H.S., Senior Vice President, Global Value, Access and Policy, Amgen

Michael Sherman, M.D., M.B.A., M.S., Chief Medical Officer, Senior Vice President, Harvard Pilgrim Health Care; Board Member, Personalized Medicine Coalition

  • complications,  cost, outcome work vs does not work
  • Gene therapies coming from Novartis and Partnership with Harvard Pilgrims
  • Value proposition for one drug and one cancer – to assure access Pharma and Payers Partnership
  • Drug and Outcome, high cost drug coming, very expensive, life saver for who needs them

Discussion

  • Pharma’s revenue stream is international, it is in the US that payers require Value

 

Part 2 10:05 am Models for the Development of Personalized Medicine Diagnostics Pharmaceutical and diagnostics companies have responded to a host of complex scientific, regulatory and reimbursement challenges partly by developing innovative partnership models around companion diagnostics. This panel discussion will feature representatives from the pharmaceutical and diagnostics industries, who will discuss the challenges partnerships have helped industry overcome as well as the obstacles that continue to inhibit the development of the diagnostic tools upon which personalized medicine depends. Agenda ·

 

MODERATOR | Alexander Vadas, Ph.D., Managing Director, L.E.K. Consulting

Joydeep Goswami, Ph.D., M.B.A., M.S., President, Clinical Next-Generation Sequencing, Oncology, Thermo Fisher Scientific

  • monitor disease , biopsy changes in 6 month and repeat is needed
  • NGS – results come back in a month what the mutation mean? NOW results come in few days, data analysis  assist the MDs for action in treatment said Joydeep Goswami, Ph.D., M.B.A., M.S., President, Clinical Next-Generation Sequencing, Oncology, Thermo Fisher Scientific
  • How to accelerate the need for safety and the avalangue of innovations
  • Clinical sense vs research context, FDA is more comfortable with other than oncology products beyond drugs, namely diagnostics

Jacob S. Van Naarden, Chief Business Officer, Loxo Oncology

  • Increase in need of drugs in NGS World, Tissue agnostics, ALL the drugs and all the tumors
  • reduction in cost with technology, can’t be too expensive,
  • LOXO drug development  – each testing addresses a focused medical issue  – cancer alterations  for ALL extremely aggressive cancer
  • DNA and RNA based events detected by tools
  • cost of test need to be low, Reference Labs need to collaborate to standarize technology and explain to the Payers
  • Cost of CT Scan vs an NGS Test – Genomic testing is much cheaper said Jacob S. Van Naarden, Chief Business Officer, Loxo Oncology
  • Educational

10:35 am Real-World Personalized Medicine: Examining the Role of Real-World Evidence in Personalizing Health Care FDA has offered a definition of real-world evidence, but the community continues to debate what is needed to fully integrate it into decision-making. This panel will explore what real-world evidence is, how it is being used and what regulatory requirements are needed to realize its potential.

MODERATOR | Amy Abernethy, M.D., Ph.D., Chief Medical Officer, Chief Scientific Officer, Flatiron Health; Board Member, Personalized Medicine Coalition

  • Collection of evidence to accelerate from lab to the Clinic
  • use data sets prospective vs retrospective studies asked Amy Abernethy, M.D., Ph.D., Chief Medical Officer, Chief Scientific Officer, Flatiron Health; Board Member, Personalized Medicine Coalition

Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA

  • 3/2017 established to have an integrative approach by FDA – real world dat ais important to FDA
  • Drug approved for one indication, provide new data for supplemental indications said Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA
  • co-morbidities cause EXCLUSION from clinical trials, i.e., HIV patients, experience of patients excluded to learn how differently they can be treated
  • drafting a document on Verify data integrity in clinical trials, detect discrepancies compromise the integrity of the data – audits by FDA said Sean Khozin, M.D., M.P.H., Associate Director (Acting), Oncology Center of Excellence, FDA
  • Validation of devices- FDA Innovation Initiative,

Eric G. Klein, Pharm.D., Senior Director, Oncology, Global Patient Outcomes and Real-World Evidence, Eli Lilly and Company

  • Aggregate burden of disease, existence of co-morbidities
  • Why it was occurring – Genomics: WHY is explained – precise tools
  • data vs intelligence – interoperability
  • Past clinical trial – replicate studies with retrospective data
  • finding the responding patients – pragmatic trial, not randomized, collect end point – very expensive and requires statisticians
  • end pint definition changed

Eleanor M. Perfetto, Ph.D., M.S., Senior Vice President, Strategic Initiatives, National Health Council

  • How patients  wish to see usage of their experience – how side effect information can be used.
  • New indication
  • reimbursement
  • improved used of existing drug higher rating vs new indications
  • clinical trial design gets input from patients, Patient can announce, dropping participation if a change is not made

Deborah Schrag, M.D., M.P.H., Chief, Division of Population Sciences, Medical Oncology, Dana-Farber Cancer Institute

  • Major gene mutation and Drugs
  • Drug exposure correlate with evidence, Worldwide,
  • linkages vs computational techniques we do not have consistent data, data structured or not, respond to medication: symptoms, prospects vs Vital sign or WBC count – we have data standardization is evolving said Deborah Schrag, M.D., M.P.H., Chief, Division of Population Sciences, Medical Oncology, Dana-Farber Cancer Institute
  • clinical decision support what is structured is data upon admission, monitoring the drugs given in this period, turning to patients willing to offer feedback and cooperate
  • pre-existing autoimmune disease – not indicated for them Immunotherapy even though patients wish to try said Deborah Schrag, M.D., M.P.H., Chief, Division of Population Sciences, Medical Oncology, Dana-Farber Cancer Institute
  • Standards: Toxicity criteria – library of 882 symptoms, Patient reported outcomes by Patients, Resist  criteria applied to imaging data criteria for brain tumors said Deborah Schrag, M.D., M.P.H., Chief, Division of Population Sciences, Medical Oncology, Dana-Farber Cancer Institute
  • Physicians needs interfaces, dashboard information delivered to MDs, data sits unused, new tools are needed for the data display by relevance to the MDs
  • Patients input and sophistication increased – IRB is not aware of the engagement of Patients and their challenging feedback say Deborah Schrag, M.D., M.P.H, Dana Farber

11:50 am Luncheon

1:00 pm The Designer Genome: Exploring the Implications of Gene Editing and Gene Therapy for the Future of Medicine and Humanity Many scientists believe the clustered regularly interspaced short palindromic repeats (CRISPR) genetic engineering tool and recent developments in gene therapy will dramatically alter the trajectory of medicine, but the specific implications of these developments for health systems around the world remain unclear. During this session, a panel of experts will discuss the status of these new technologies and how the medical community and regulatory agencies may have to adapt to keep up with forthcoming developments.

MODERATOR | Kevin Davies, Ph.D., Co-Author, DNA: The Story of the Genetic Revolution (with Jim Watson and Andrew Berry); Executive Editor, The CRISPR Journal

Katrine Bosley, CEO, Editas Medicine

  • spectrum of ease to correct a mutation, some mutation are easier than others for editing,
  • understand well enough  the gentic application where CRISPR will assist medicine: Retinal degeneration, two aspects one worked in Japan said Katrine Bosley, CEO, Editas Medicine

Arthur L. Caplan, Ph.D., Drs. William F. and Virginia Connolly Mitty Chair, Director, Division of Medical Ethics, New York University Langone Medical Center

  • Bioethics, super babies, engineering embrios,
  • Regulatory oversight on engineering embrios is coming, metric of success in recruitment of patients said Arthur L. Caplan, Ph.D., Drs. William F. and Virginia Connolly Mitty Chair, Director, Division of Medical Ethics, New York University Langone Medical Center
  • cell repair is cheaper that transplantation,
  • clone of super person next door
  • Bioterrorism accomplished by gene engineering !!

George M. Church, Ph.D., Professor of Genetics, Health Sciences and Technology, Harvard-MIT Division of Health Sciences and Technology; Director, Harvard Medical School NHGRI-Center of Excellence in Genomic Science; Director, Harvard Medical School Personal Genome Project; Founding Member, Wyss Institute for Biologically Inspired Engineering at Harvard University

  • Delivery, more precise,
  • Longevity and aging – one blockbuster is needed
  • Engineered mutation, machine learning
  • CRISPR does not handle all mutation many require a different editing tool said George M. Church, Ph.D., Professor of Genetics, Health Sciences and Technology, Harvard-MIT Division of Health Sciences and Technology; Director, Harvard Medical School NHGRI-Center of Excellence in Genomic Science; Director, Harvard Medical School Personal Genome Project; Founding Member, Wyss Institute for Biologically Inspired Engineering at Harvard University
  • over regulation – Do not touch germ line – is not desired
  • Transplantation vs enhancement – resistance to senescence and pathogens to be achieved by gene editing suggests George M. Church, Ph.D., Professor of Genetics
  • Bringing back genes – elephants with fur

Jeffrey D. Marrazzo, M.B.A., M.P.A., CEO, Spark Therapeutics

  • Retina degeneration causes blindness, deliver drug to back of the retine, inject genetic material and achieved remarkable results, drug approval of genetic therapy in the US for a genetic disorder in Retina causing blindness
  • 21st Century schema of Payment and benefits

 

2:15 pm Pricing Personalized Medicines The increasing pressure on industry stakeholders to alter their drug pricing practices has particular significance for personalized medicines, which must recoup research and development costs from smaller patient populations. This conversation will explore the pharmaceutical industry’s strategies for facilitating sustainable access to these innovative therapies.

MODERATOR | Meg Tirrell, M.S.J., Reporter, CNBC

Stephen J. Ubl, President, CEO, PhRMA

  • minimum 10% invested in R&D at each Pharma
  • Of 134 drugs in development – 42 have the potential to become Personalized medicine therapies, said Stephen J. Ubl, President, CEO, PhRMA
  • Icer methodology – average patient aggregate data, value pricing is a better model: RA targeted to subset of patients
  • Price gauging is a problem – bring solutions to the table, Patients asks for incentives
  • amortizing costs like mortgage
  • Outcome-based arrangements: If money-based guaranteed it negate Medicaid negotiation power. If transportation is covered – it leads to locking product in use

2:45 pm Networking Break (sponsored by GreyBird Ventures)

3:15 pm Precision Valuation: A Discussion of How Value Assessment Frameworks Can Account for Personalized Medicine Payers control access to personalized medicine, and some have begun to take an interest in findings from value assessment frameworks that are challenged to account for developments in the field. In addition to exploring their potential impact on individualized care, this session will examine how value assessment frameworks can and should consider personalized medicine as part of their processes for evaluating therapeutic options.

MODERATOR | Jennifer Snow, M.P.H., Director, Health Policy, Xcenda, AmerisourceBergen

  • Quality Era moved to Value Era

 

Dane J. Dickson, M.D., CEO, Founder, CureOne (formerly MED-C); Director, Precision Medicine Policy and Registries, Knight Cancer Institute at Oregon Health and Science University

Molecular Era

  • NEJM, 2017, 377, 1813-1823
  • BRAF in Melanoma – 80% do not need additional therapy vs 20% benefitted in the Non-Molecular Era

data by Dane J. Dickson, M.D., CEO, Founder, CureOne (formerly MED-C); Director, Precision Medicine Policy and Registries, Knight Cancer Institute at Oregon Health and Science University

 

Robert Dubois, M.D., Ph.D., Executive Vice President, Chief Science Officer, National Pharmaceutical Council

  • Value Assessment and PM: ACC, ASCO, ICER< Memorial Sloan,
  • The patient: survival, QOL, Adverse events, Out of pocket cost, extra survival by disease, treatment burden,
  • PAYERS: One size does not fit all – AVERAGE is meaningless
  • MDs vs Patients – are different in preference

Andrea Stern Ferris, M.B.A., President, Chairman of the Board, LUNGevity Foundation

  • PATIENT to be included in the conversation

Steven D. Pearson, M.D., M.Sc., Founder, President, Institute for Clinical and Economic Review (ICER)

  • Precision Medicine vs Value Assessment
  • Novartis CAR-T Kymriah:  relapsed B-cell precursor ALL under 25 – 5 yr survival – 10%
  • Changes associated with Gene therapies: single arm trials, surrogate outcomes, less certainty safety and benefits
  • Gene therapy – >> innovations Kymriah – $475,000 price
  • Long term value for money vs Short term affordability

PRICE-based on Value – discount from prices after rebate to meet ICER value-based Price range

  • More targeted = higher value more favorable cost-effectiveness
  • Rare/ultra-rare populations: broader value range:
  1. Use EARLIER
  2. will it work for patients without genetic marker?
  • Years of Life weighted by an INDEX of quality of life (1=perfect health;  0=dead)
  • willingness to pay: WHO and ACC: 1-3x
  • individual x2 salary
  • Opportunity cost x1 per capita GDP in UK
  • Future of value assessment and precision medicine
  • CURES – CAR-T are they cures???
  • A teen-ager’s Value-based Price: $475,000 x years lived suggestsSteven D. Pearson, M.D., M.Sc., Founder, President, Institute for Clinical and Economic Review (ICER)

4:30 pm The Utility Proposition: An Analysis of Case Studies in the Economic Value of Personalized Medicine Although personalized medicine’s proponents contend that the field can deliver economic value by helping doctors avoid prescribing costly but ineffective therapies, the field lacks literature testing that hypothesis. This session will highlight recent studies on the clinical and economic value of personalized medicine, shedding light on what we know about personalized medicine’s clinical and economic utility — and what we don’t.

MODERATOR | Michael Pellini, M.D., M.B.A., Chairman, Board of Directors, Foundation Medicine; Board Member, Personalized Medicine Coalition

  • we know there is value in Personalized Medicine
  • we need to work together to acknowledge the challenges — to prove the value in PM

Lincoln Nadauld, M.D., Ph.D., Executive Director, Precision Medicine, Precision Genomics, Intermountain Healthcare

  • Interpretation by Medical Oncologists beyond: KRAS, BRAF
  • Measuring the value and presenting that to the payers and inside the organizations
  • 2013 –

David B. Roth, M.D., Ph.D., Simon Flexner Professor Chair, Pathology and Laboratory Medicine, Perelman School of Medicine at University of Pennsylvania; Director, Penn Center for Precision Medicine

  • 5000 patients underwent genome sequencing
  • Interpretation is the issue that is hard
  • Health IT are still in silos: Pharmacy data, financial data, EMR are not integrated yet
  • Survival of patient with mutation and targeted drug LIVE LONGER

Lotte Steuten, Ph.D., M.Sc., Associate Faculty Member, Hutchinson Institute for Cancer Outcomes Research (HICOR), Fred Hutchinson Cancer Research Center; Affiliate Associate Professor, Pharmaceutical Outcomes Research and Policy Program, School of Pharmacy at University of Washington, Seattle

  • aggregate big data , models as evidence, has value to clinical, the model under development NGS Profile of Patient vs current standard of care. Model Payer advisor committee, Oncologist Advisory Committee great benefit to PM on the cost side data is for targeting treatment using the promise of PM

5:45 pm Elements Café Cocktail Reception

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Image Source:Koch Institute

LIVE – OCTOBER 17 – DAY 2- Koch Institute Immune Engineering Symposium 2017, MIT, Kresge Auditorium

Koch Institute Immune Engineering Symposium 2017

http://kochinstituteevents.cvent.com/events/koch-institute-immune-engineering-symposium-2017/agenda-64e5d3f55b964ff2a0643bd320b8e60d.aspx

Image Source: Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Aviva Lev-Ari, PhD, RN will be in attendance covering the event in REAL TIME

@pharma_BI

@AVIVA1950

#IESYMPOSIUM

@KOCHINSTITUTE

  • The Immune System, Stress Signaling, Infectious Diseases and Therapeutic Implications: VOLUME 2: Infectious Diseases and Therapeutics and VOLUME 3: The Immune System and Therapeutics (Series D: BioMedicine & Immunology) Kindle Edition – on Amazon.com since September 4, 2017

https://www.amazon.com/dp/B075CXHY1B

SYMPOSIUM SCHEDULE

OCTOBER 17 – DAY 2

8:30 – 9:45 Session V
Moderator: Stefani Spranger | MIT, Koch Institute

K. Christopher Garcia – Stanford University
Exploiting T Cell and Cytokine Receptor Structure and Mechanism to Develop New Immunotherapeutic Strategies

  • T Cell Receptor, peptide-MHC, 10 to the power of 10 is combinatorics – Library for selection to determine enrichment possibilities
  • Ligand identification for orphan TCRs
  1. Industrializing process
  2. use pMHC
  • IL-2 – Receptor Signaling Complex
  • Effector cells (NK, T)
  • Engineered  T Cell – Tunable expansion, ligand-Receptor interface
  • Randomize IL-2RBeta interface: Orthogonal receptor vs wild type
  • In Vivo adoptive transfer model: to quantify orthogonality ratio
  • CD4, CD8, Treg,C57BL/6J
  • Ligand discovery
  • Orthogonal IL-2

Stefani Spranger – MIT, Koch Institute
Batf3-DC as Mediators of the T Cell-Inflamed Tumor Microenvironment

  • Melanoma – solid cancer and other types, Immune inhibitory regulatory pathway patient with Immune response present
  • T cell-inflamed Tumor vs Non-T cell-inflamed Tumor
  • identify oncogenic pathways differentially activated between T cell-inflamed and non-Tcell-inflamed infiltration
  • If on Tumor:
  1. Braf/PTEN
  2. Braf/CAT
  3. Braf/PTEN/CAT
  • The role of T cell priming – lack of initial
  • Beta-catenin-expressing tumors fail to prime 2C TCR-transgenic T cells
  • Deficiency in number of CD8+ and CD103+ dendritic cells
  • CD103+ DC are essential for T cell Priming and T cell-inflammation #StefaniSpranger
  • Adoptive transfer of effector 2C T cells fails to control Beta-catenin+ tumors
  • Vaccination induced anti-gen specific T cell memory fails to control Beta-catenin+ tumors
  • What cell type in tumor microenvironment effect monilization of T cell
  • CD103+ Dendritic cellsare source chymokine
  • Recruitment of effector T cells: Reconstitution od Beta-catenin-expressing SIY+
  • Are Batf3-DC within the tumor required for the recruitment of effector T cells?
  • Tumor-residing Batf3-drive CD103+ DC are required for the recruitment of effector T cells
  • Gene spore for correlation with recturment of effector cells
  • T cell Priming – CD103+ DC are essential for effector T cells

George Georgiou – University of Texas at Austin
The Human Circulating Antibody Repertoire in Infection, Vaccination or Cancer

  • Serological Antibody Repertoire: in blood or in secretions
  • Antibody in serum – is difficult sequence identity
  • Serum IgG – 7-17 mg/ml if less immune deficient if more hyper globular
  • antibodies produced in long lived plasma cells in the bone marrow — experimentally inaccessible
  • Discovery of antibodies from the serological repertoire – not B cells
  • BM-PCs
  • Serum antibodies function via Fc effector mechanism – complement activation
  • Ig-SEQ – BCR-SEQ
  • Repertoire-wide computational modelling of antibody structures
  • En masse analysis & Mining of the Human Native Antibody Repertoire
  • hypervariable – High-Throughput Single B Cell VH:VL (or TCRalpha, beta) sequencing
  • EBOV Vaccinee Peak ASCs (day 8) mining: Neutralization
  • Features of the Serum Antibody Repertoire to Vaccine ANtigens:The Serum IgG Repertoire is Highly Polarized
  • Each bar represents a distinct antibody lineage
  • Serum IgG Repertoire becomes increasingly polarized with AGE >50 – may be predictive of tumor development process
  • Human Norovirus – explosive Diarreha, chromically infected – HuNoV BNAb Discovery – Takeda 214 bivalent Vaccine – Binding antibodies binding to avccine antigen VLP
  • HuNoV causes 800 death in the US per year of immune deficient
  • Influenza Trivalent Vaccine: Antibodies to hemaggiutinin: H1, H3, and B COmponenet
  • Abundant H1 +H3 Serum IgGs do not neutralize but confer Protection toInfluenza challenge with Live Virus #GeorgeGeorgiou
  • Non-Neutralizing Antibodies: The role of Complement in Protection

9:45 – 10:15 Break

10:15 – 11:30 Session VI
Moderator: K. Dane Wittrup | MIT, Koch Institute

Harvey Lodish – Whitehead Institute and Koch Institute
Engineered Erythrocytes Covalently Linked to Antigenic Peptides Can Protect Against Autoimmune Disease

  • Modified Red blood cells are microparticles for introducing therapeutics & diagnostics into the human body
  • Bool transfusion is widely used therapeutics
  • Covalently linking unique functional modalities to mouse or human red cells produced in cell culture:
  • PRODUCTION OF HUMAN RED BLOD CELLS EXPRESSING A FOREIN PROTEIN: CD34+ stem/progenitor cells that generates normal enucleated RBC.
  • PPAR-alpha and glucocorticoticoid receptor
  • Norman morphology: Sortase A is a bactrial transpeptidase that covalently links a “donor”
  • Engineering Normal Human RBC biotin-LPETG
  • Covelantely – Glycophorin A with camelid VHHs specific for Botulinum toxin A or B
  • Generation of immuno tolerance: SOruggable Mature RBCs: CRISPR mice expressing Kell-LPETG
  • Ovalbumin as Model Antigens:
  1. OBI B,
  2. OTI CD8 T cells
  3. OTII CD4 T cells
  4. OT-1
  5. OT-2
  • RBC induced peptides challenged and experiences apoptosis
  • Type I Diabetes in NOD mice
  • RBCs bearing InsB9-23 – prevented development of diabetes

Multiple sclerosis

  • MOG – Myelin Oligodend

Sai Reddy – ETH Zurich
Molecular Convergence Patterns in Antibody Responses Predict Antigen Exposure

  • Clonal diversity – estimating the size of antibody repertoire: 10 to power of 18 or 10 to 13
  • Clonal selection in antibody repertoire
  • Convergent selection in antibody repertoire
  • Convergent selection in TCR repertoire complex have restriction with MCH interactions
  • How molecular abundance of convergence predicts antigen exposure identify antigen-associated clusters #SaiReddy
  • molecular convergence 0 gene expression analysis, immunization scheme molecular bar coding to correct errors
  • Recoding antibody repertoire sequence space: Cross correlation reveals different clusters
  • Building a classifier model based on cluster frequency: Clones from immunized mice
  • epitope specificity is driving antibody repertoire response
  • deep learning,

K. Dane Wittrup – MIT, Koch Institute
Temporal Programming of Synergistic Innate and Adaptive Immunotherapy

  • Innate effector functions of anti-tumor antibodies
  • Innate & adaptive Immunotherapy
  • Innate mAb –>> tumor cell; adaptive CD8+ T cells
  • Chemokines Antigens
  • Cytokines Chemokines – back and forth innate Adaptive –> <— neutrophils impact
  • AIPV vaccine:
  • How anti-TAA mAbs helping T cell Immune response
  • Anti-TAA mAbs drive vaccinal T cell responses: NK cells
  • antibody drives T cells responses: alpha-TAA mAbs potentiate T cell therapies: ACT +MSA-IL-2 vs alphaPD-1 + vaccine
  • CD8+ T cells required for alpha TAA mAb efficacy- In absence of T cells Treatment does not work
  • Anti-TAA mAb +Fc/IL-2 induces intramural cytokine storm #KDaneWittrup
  • How to simplify and improve AIPV? Hypothesis: ALign dose schedule
  • Immune response to infection follwos a temporal progression: Innate … Adaptive
  • Antigenic material kill cells: Chemo, cell death Antigen presentation, T cell priming, T cell recirculation, Lymphocyte tumor infiltrate, TCR
  • IFN alpha 2 dys after mAb +Il-2: Curative: days post tumor injection
  • Necessary components: CD8+ T cells & DC, Macrophages,
  • Optimal IFNalpha coincides with max innate response vs Mature DCs after antigen loading #KDaneWittrup
  • Optimal timing od agent administration effect on Therapy Outcome: IL-2, IFNalpha, TAAmAb
  • Cytkine timing can be better than protein engineering #KDaneWittrup

11:30 – 1:00 Lunch Break

1:00 – 2:15 Session VII
Moderator: Michael Birnbaum | MIT, Koch Institute

Kai Wucherpfennig – Dana-Farber Cancer Institute
Discovery of Novel Targets for Cancer Immunotherapy

  • POSITIVE STRESS SIGNAL during malignant Transformation
  • NKG2G=D Receptor: MICA/B Results in Immune escape – Proteolytic cleavage  shedding of MICA/B present in serum, indication of tumor progression
  • Shed MICA vs Surface MICA/B – restore NK cell cytotoxicity and IFNgamma Production
  • Human NK cells express NKG2D and Fc Receptors
  • Synergistic NKG2D and CD16 signaling enhances NK cell cytootxicity: Control IgG vs Anti NKG2D
  • MICA Antibody induces Immunity Against Lung Metastases
  • NK cells are required to inhibit Growth of metastases: Anti-CD8beta,
  • Contribution to Therapeutic Efficacy: NKG2D and CD16 Receptors #KaiWucherpfennig
  • Strategy to analyze Pulmonary NK cells: Activation and expression
  • Single cell RNA-seq of lung NK cells Revealed higher infiltration of activated NK cells: Isotype vs 7C6-migG2a
  • Cytokines and Chemokines produce NK cells
  • MICA/B increaces NK
  •  Induction of Tumor cell Apoptosis
  • Xenotransplant Model with Human Melanoma Cel Line A2058
  • Lung metastasis, liver metastasis
  • Inhibition of human melanoma Metastases in NSG Mice Reconstitute with Human NK
  • Liver metastases are controlled by Myeloid Cells that include Kupffer cells

Michael Birnbaum – MIT, Koch Institute
An Unbiased Determination of pMHC Repertoires for Better Antigen Prediction

  • Vaccines TCR gene therapy adoptive T cel therapy
  • Tumor genone – Tumor pMHC repertoire = Tumor TCR repertoire T cell repertoire
  • Neoantigen vaccines as a personalized anti-cancer therapy
  • Tumor procurement – Target selection – personal vaccine production – vaccine administration
  • Prediction of neoantigen-MHC Binding due to polimorphism affecting recognition, rare in MHC Allells #Michael Birnbaum
  • Antigenicity – Chaperones HLA-DM sculp the peptide binding repertoire of MHC
  • Identification of loaded peptide ligands: pMHC mass spectroscopy of tissue
  • TCR recognition, pMHC yeast display: Cleave peptide-MHC linker, catalyze peptide exchange
  • HLA-DR4 library design and selection to enrich HLA-DM: Amino Acid vs Peptide position: Depleted vs Enriched – relative to expected for NNK codon
  •  6852 _ predicted to bind vs 220 Non-binding peptides
  • HLA polymorphism: repertoire differences caused by
  • Antigen – T cell-driven antigen discovery: engaging Innate and Adaptive Immune response
  • Sorting TIL and select: FOcus of T cell-driven antigen discovery
  • T cell-driven antigen discovery: TCR

Jennifer R. Cochran – Stanford University
Innate and Adaptive Integrin-targeted Combination Immunotherapy

  • alpa-TAA
  • Targeting Integrin = universal target involved in binding to several receptors: brest, lung, pancreatic, brain tumors arising by mutations – used as a handle for binding to agents
  • NOD201 Peptide-Fc Fusion: A Psudo Ab
  • Handle the therapeutics: NOD201 + alphaPD1
  • NOD201 effectively combines with alphaPD-L1, alphaCTLA-4, and alpha4-1BB/CD137
  • Corresponding monotherapies vs ComboTherapy invoking Innate and Adaptive Immune System
  • Microphages, CD8+ are critical vs CD4+ Neutrophils, NK cells, B cells #JenniferR. Cochran
  • Macrophages activation is critical – Day 4, 4 and 5
  • NOD201 + alphaPD1 combo increases M1 macrophages
  • Who are the best responders to PD1 – genes that are differentially expressed
  • NOD201 deives T cells reaponses through a “vaccinal” effect
  • CAncer Immune CYcle
  • Integrin – localization
  • Prelim NOD201 toxicity studies: no significant effects
  • Targeting multiple integrins vs antibodies RJ9 – minimal effect
  • NOD201 – manufacturability – NEW AGENT in Preclinical stage

2:15 – 2:45 Break

2:45 – 3:35 Session VIII
Moderator: Jianzhu Chen | MIT, Koch Institute

Jennifer Wargo – MD Anderson Cancer Center
Understanding Responses to Cancer Therapy: The Tissue is the Issue, but the Scoop is in the Poop

  • Optimize Targeted Treatment response
  • Translational research in patients on targeted therapy revealed molecular and immune mechanisms of response and resistance
  • Molecular mechanisms – T cell infiltrate after one week of therapy
  • Role of tumor stroma in mediating resistance to targeted therapy
  • Tumor microenvironment
  • Intra-tumoral bacteria identified in patients with Pancreatic Cancer
  • Translational research in patients on immune checkpoint blockade revealed molecualr and immune mechanism of response and resistance
  • Biomarkers not found
  • SYstemic Immunity and environment (temperature) on response to checkpoint blockade – what is the role?
  • Role of mIcrobiome in shaping response to checkpoint blockade in Melanoma
  • Microbime and GI Cancer
  • Diversity of the gut microbiome is associated with differential outcomes in the setting of stem cell transplant in AML
  • Oral and gut fecal microbiome in large cohort patient with metastatic melanoma undergoing systemic therapy
  • Repeat oral & gut AFTER chemo
  • WGSeq – Diversity of microbiome and response (responders vs non-responders to anti PD-1 – High diversity of microbiome have prolonged survival to PD-1 blockade
  • Anti tumor Immunity and composition of gut microbiome in patient on anti-PD-1 favorable AND higher survival #JenniferWargo
  • Enhance therapeutic responses in lang and renal carcinoma: If on antibiotic – poorer survival
  • sharing data important across institutions

Jianzhu Chen – MIT, Koch Institute
Modulating Macrophages in Cancer Immunotherapy

  • Humanized mouth vs de novo human cancer
  • B cell hyperplasia
  • double hit lymphoma
  • AML
  • Overexpression of Bcl-2 & Myc in B cells leads to double-hit lymphoma
  • antiCD52 – CLL
  • Spleen, Bone marrow, Brain
  • Microphages are required to kill Ab-bound lymphoma cells in vivo #JianzhuChen
  • COmbinatorial chemo-Immunotherapy works for solid tumors: treating breast cancer in humanized mice
  • Infiltration of monocytic cells in the bone marrow
  • Cyclophosphophamide-antibody synergy extending to solid tumor and different antibodies #JianzhuChen
  • Polarization of macrophages it is dosage-dependent M1 and M2
  • Antibiotic induces expression of M1 polarizing supresses development and function of tumor-associated macrophages (TAM)
  • Antibiotic inhibits melanoma growth by activating macrophages in vivo #JianzhuChen

 

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Image Source:Koch Institute

 

LIVE – OCTOBER 16 – DAY 1- Koch Institute Immune Engineering Symposium 2017, MIT, Kresge Auditorium

Koch Institute Immune Engineering Symposium 2017

http://kochinstituteevents.cvent.com/events/koch-institute-immune-engineering-symposium-2017/agenda-64e5d3f55b964ff2a0643bd320b8e60d.aspx

 

#IESYMPOSIUM

 

Image Source: Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Aviva Lev-Ari, PhD, RN will be in attendance covering the event in REAL TIME

@pharma_BI

@AVIVA1950

#IESYMPOSIUM

@KOCHINSTITUTE

  • The Immune System, Stress Signaling, Infectious Diseases and Therapeutic Implications: VOLUME 2: Infectious Diseases and Therapeutics and VOLUME 3: The Immune System and Therapeutics (Series D: BioMedicine & Immunology) Kindle Edition – on Amazon.com since September 4, 2017

https://www.amazon.com/dp/B075CXHY1B

SYMPOSIUM SCHEDULE

OCTOBER 16 – DAY 1

7:00 – 8:15 Registration

8:15 – 8:30Introductory Remarks
Darrell Irvine | MIT, Koch Institute; HHMI

  • Stimulating the Immune system not only sustaining it for therapies

K. Dane Wittrup | MIT, Koch Institute

8:30 – 9:45Session I
Moderator: Douglas Lauffenburger | MIT, Biological Engineering and Koch Institute

Garry P. Nolan – Stanford University School of Medicine
Pathology from the Molecular Scale on Up

  • Intracellular molecules,
  • how molecules are organized to create tissue
  • Meaning from data Heterogeneity is an illusion: Order in Data ?? Cancer is heterogeneous, Cells in suspension – number of molecules
  • System-wide changes during Immune Response (IR)
  • Untreated, Ineffective therapy, effective therapy
  • Days 3-8 Tumor, Lymph node…
  • Variation is a Feature – not a bug: Effective therapy vs Ineffective – intercellular modules – virtual neighborhoods
  • ordered by connectivity: very high – CD4 T-cells, CD8 T-cels, moderate, not connected
  • Landmark nodes, Increase in responders
  • CODEX: Multiples epitome detection
  • Adaptable to proteins & mRNA
  • Rendering antibody staining via removal to neighborhood mapping
  • Human tonsil – 42 parameters: CD7, CD45, CD86,
  • Automated Annotations of tissues: F, P, V,
  • Normal BALBs
  • Marker expression defined by the niche: B220 vs CD79
  • Marker expression defines the niche
  • Learn neighborhoods and Trees
  • Improving Tissue Classification and staining – Ce3D – Tissue and Immune Cells in 3D
  • Molecular level cancer imaging
  • Proteomic Profiles: multi slice combine
  • Theory is formed to explain 3D nuclear images of cells – Composite Ion Image, DNA replication
  • Replication loci visualization on DNA backbone – nascent transcriptome – bar code of isotopes – 3D  600 slices
  • use CRISPR Cas9 for Epigenetics

Susan Napier Thomas – Georgia Institute of Technology
Transport Barriers in the Tumor Microenvironment: Drug Carrier Design for Therapeutic Delivery to Sentinel Lymph Nodes

  • Lymph Nodes important therapeutics target tissue
  • Lymphatic flow support passive and active antigen transport to lymph nodes
  • clearance of biomolecules and drug formulations: Interstitial transport barriers influence clearance: Arteriole to Venule –
  • Molecular tracers to analyze in vivo clearance mechanisms and vascular transport function
  • quantifying molecular clearance and biodistribution
  • Lymphatic transport increases tracer concentrations within dLN by orders of magnitude
  • Melanoma growth results in remodeled tumor vasculature
  • passive transport via lymphatic to dLN sustained in advanced tumors despite abrogated cell trafficking
  • Engineered biomaterial drug carriers to enhance sentinel lymph node-drug delivery: facilitated by exploiting lymphatic transport
  • TLR9 ligand therapeutic tumor in situ vaccination – Lymphatic-draining CpG-NP enhanced
  • Sturcutral and Cellular barriers: transport of particles is restriced by
  • Current drug delivery technology: lymph-node are undrugable
  • Multistage delivery platform to overcome barriers to lymphatic uptake and LN targeting
  • nano particles – OND – Oxanorbornade OND Time sensitive Linker synthesized large cargo – NP improve payload
  • OND release rate from nanoparticles changes retention in lymph nodes – Axilliary-Brachial delivery
  • Two-stage OND-NP delivery and release system dramatically – OND acumulate in lymphocyte
  •  delivers payload to previously undraggable lymphe tissue
  • improved drug bioactivity  – OND-NP eliminate LN LYMPHOMAS
  • Engineered Biomaterials

Douglas Lauffenburger – MIT, Biological Engineering and Koch Institute
Integrative Multi-Omic Analysis of Tissue Microenvironment in Inflammatory Pathophysiology

  • How to intervene, in predictive manner, in immunesystem-associated complex diseases
  • Understand cell communication beteen immune cells and other cells, i.e., tumor cells
  • Multi-Variate in Vivo – System Approach: Integrative Experiment & COmputational Analysis
  • Cell COmmunication & Signaling in CHronic inflammation – T-cell transfer model for colitis
  • COmparison of diffrential Regulation (Tcell transfer-elicited vs control) anong data types – relying solely on mRNA can be misleading
  • Diparities in differential responses to T cell transfer across data types yield insights concerning broader multi-organ interactions
  • T cell transfer can be ascertained and validated by successful experimental test
  • Cell COmmunication in Tumor MIcro-Environment — integration of single-cell transcriptomic data and protein interaction
  • Standard Cluster Elucidation – Classification of cell population on Full gene expression Profiles using Training sets: Decision Tree for Cell Classification
  • Wuantification of Pairwise Cell-Cell Receptor/Ligand Interactions: Cell type Pairs vs Receptor/Ligand Interaction
  • Pairwise Cell-Cell Receptor/Ligand Interactions
  • Calculate strength of interaction and its statistical significance
  • How the interaction is related to Phenotypic Behaviors – tumor growth rate, MDSC levels,
  • Correlated the Interactions translated to Phynotypic behavior for Therapeutic interventions (AXL via macrophage and fibroblasts)
  • Mouth model translation to Humans – New machine learning approach
  • Pathways, false negative, tumor negative expression
  • Molecular vs Phynotypical expression
  • Categories of inter-species translation
  • Semi-supervised Learning ALgorithms on Transcriptomic Data can ascertain Key Pathways/Processes in Human IBD from mapping mouse IBD

9:45 – 10:15 Break

10:15 – 11:30Session II
Moderator: Tyler Jacks | MIT, Koch Institute; HHMI

Tyler Jacks – MIT, Koch Institute; HHMI
Using Genetically Engineered Mouse Models to Probe Cancer-Immune Interactions

  • Utility of genetically-engineered mouse models of Cancer:
  1. Immune Response (IR),
  2. Tumor0immune microenvironment
  • Lung adenocarcinoma – KRAS mutation: Genetically-engineered model, applications: CRISPR, genetic interactions
  • Minimal Immune response to KP lung tumors: H&E, T cells (CD3), Bcells (B220) for Lenti-x 8 weeks
  • Exosome sequencing : Modeling loss-and gain-of-function mutations in Lung Cancer by CRISPR-Cas9 – germline – tolerance in mice, In vivo CRISPR-induced knockout of Msh2
  • Signatures of MMR deficient
  • Mutation burden and response to Immunotherapy (IT)
  • Programmed neoantigen expression – robust infiltration of T cells (evidence of IR)
  • Immunosuppression – T cell rendered ineffective
  • Lymphoid infiltration: Acute Treg depletion results in T cell infiltration — this depletion causes autoimmune response
  • Lung Treg from KP tumor-bearing mice have a distinct transcriptional heterogeneity through single cell mRNA sequencing
  • KP, FOXP3+, CD4
  • Treg from no existent to existance, Treg cells increase 20 fold =>>>  Treg activation and effectiveness
  • Single cells cluster by tissue and cell type: Treg, CD4+, CD8+, Tetramer-CD4+
  • ILrl1/II-33r unregulated in Treg at late time point
  • Treg-specific deletion of IL-33r results in fewer effector Tregs in Tumor-bearing lungs
  • CD8+ T cell infiltration
  • Tetramer-positive T cells cluster according to time point: All Lung CD8+ T cells
  • IR is not uniform functional differences – Clones show distinct transcriptional profiles
  • Different phynotypes Exhaustive signature
  • CRISPR-mediated modulation of CD8 T cell regulatory genes
  • Genetic dissection of the tumor-immune microenvironment
  • Single cell analysis, CRISPR – CRISPRa,i, – Drug development

Wendell Lim – University of California, San Francisco

Synthetic Immunology: Hacking Immune Cells

  • Precision Cell therapies – engineered by synthetic biology
  • Anti CD19 – drug approved
  • CAR-T cells still face major problems
  1. success limited to B cells cancers = blood vs solid tumors
  2. adverse effects
  3. OFF-TUMOR effects
  • Cell engineering for Cancer Therapy: User remote control (drug) – user control safety
  • Cell Engineering for TX
  1. new sensors – decision making for
  2. tumor recognition – safety,
  3. Cancer is a recognition issue
  • How do we avoid cross-reaction with bystader tissue (OFF TISSUE effect)
  • Tumor recognition: More receptors & integration
  • User Control
  • synthetic NOTCH receptors (different flavors of synNotch) – New Universal platform for cell-to -cell recognition: Target molecule: Extracellular antigen –>> transciptional instruction to cell
  • nextgen T cell: Engineer T cell recognition circuit that integrates multiple inputs: Two receptors – two antigen priming circuit
  • UNARMED: If antigen A THEN receptor A activates CAR
  • “Bystander” cell single antigen vs “tumor” drug antigen
  • Selective clearance of combinatorial tumor – Boulian formulation, canonical response
  • Cell response: Priming –>> Killing: Spatial & Temporal choreographed cell
  • CAR expression while removed from primed cells deminished
  • Solid Tumor: suppress cell microenvironment: Selected response vs non-natural response
  • Immune stimulator IR IL2, IL12, flagellin in the payload — Ourcome: Immune enhancement “vaccination”
  • Immune suppression –  block
  • Envision ideal situation: Unarmed cells
  • FUTURE: identify disease signatures and vulnerabilities – Precision Medicine using Synthetic Biology

Darrell Irvine – MIT, Koch Institute; HHMI
Engineering Enhanced Cancer Vaccines to Drive Combination Immunotherapies

  • Vaccine to drive IT
  • Intervening in the cancer-immunity cycle – Peptide Vaccines
  • poor physiology  of solute transport to tissue
  • endogenous albumin affinity – Lymphe Node dying
  • Designing Albumin-hitchhiking vaccines
  • Amphiphile-vaccine enhance uptake in lymph nodes in small and large animal models
  • soluble vaccine vs Amphiphile-vaccine
  • DIRECTING Vaccines to the Lymph nodes
  • amph-peptide antigen: Prime, booster, tetramer
  • albimin-mediated LN-targeting of both antigen and adjuvant maximizes IR
  • Immuno-supressed microenvironment will not be overcome by vaccines
  • Replacing adoptive T cell transfer with potent vaccine
  • exploiting albumin biology for mucosal vaccine delivery by amph-vaccines
  • Amph-peptides and -adjuvants show enhanced uptake/retention in lung tissue
  •  Enhancing adoptive T cell therapy: loss of T cell functionality, expand in vivo
  • boost in vivo enhanced adoptive T cell therapy
  • CAR-T cells: Enable T cells to target any cell surface protein
  • “Adaptor”-targeting CAR-T cells to deal with tumor cell heterogeneity
  • Lymph node-targeting Amph as CAR T booster vaccine: prining, production of cytokines
  • Boosting CAR T with amph-caccines: anti FITC CAR-T by DSPE=PEG-FITC coated
  • Targeting FITC to lymph node antigen presenting cells
  • Modulatory Macrophages
  • Amph-FITC expands FITC-CAR T cells in vivo – Adjuvant is needed
  • Hijacking albumin’s natural trafficking pathway

11:30 – 1:00  Lunch Break

1:00 – 2:15Session III
Moderator: Darrell Irvine | MIT, Koch Institute; HHMI

Nicholas P. Restifo – National Cancer Institute
Extracellular Potassium Regulates Epigenetics and Efficacy of Anti-Tumor T Cells

Why T cell do not kill Cancer cells?

  • co-inhibition
  • hostile tumor microenvironment

CAR T – does not treat solid tumors

Somatic mutation

  1. resistence of T cell based IT due to loss of function mutations
  2. Can other genes be lost?

CRISPR Cas9 – used to identify agents – GeCKOv2 Human library

Two cell-type (2CT) CRISPR assay system for genome-wide mutagenesis

  • work flow for genome-scale SRISPR mutagenesis profiling of genes essential for T cell mediate cytosis
  • sgRNA enrichment at the individual gene level by multiple methods:
  1. subunits of the MHC Class I complex
  2. CRISPR mutagenesis cut germline
  • Measutring the generalizability of resistance mechanism and mice in vivo validation
  • Validation of top gene candidates using libraries: MART-1
  • Checkpoint blockade: cells LOF causes tumor growth and immune escape
  • Weird genesL Large Ribisomal Subunit Proteins are nor all essential for cell survival
  • Bias in enrichment of 60S vs 40S
  • Novel elements of MHC class I antigen processing and presentation
  • Association of top CRISPR hits with response rates to IT – antiCTLA-4
  • CRISPR help identify novel regulators of T cells
  • Analyzed sgRNA – second rarest sgRNA for gene BIRC2 – encoded the Baculoviral Inhibitor
  • Drugs that inhibit BIRC2
  • How T cells can kill tumor cells more efficiently
  • p38kiaseas target for adoptive immunotherapy
  • FACS-based – Mapk14
  • Potent targets p38 – Blockade PD-1 or p38 ??
  • p38 signaling: Inhibition augments expansion and memory-marked human PBMC and TIL cells, N. P. Restifo
  • Tumor killing capacity of human CD19-specific, gene engineered T cells

Jennifer Elisseeff – Johns Hopkins University
The Adaptive Immune Response to Biomaterials and Tissue Repair

  • design scafolds, tissue-specific microenvironment
  • clinical translation of biosynthetic implants for soft tissue reconstruction
  • Local environment affects biomaterials: Epidermis, dermis
  • CD4+ T cells
  • Immune system – first reponders to materials: Natural or Synthetic
  • Biological (ECM) scaffolds to repair muscle injury
  • Which immune cells enter the WOUND?
  • ECM alters Macrophages: CD86, CD206
  • Adaptive system impact on Macrophages: CD86
  • mTOR signaling pathway M2 depend on Th2 Cells in regeneration of cell healing of surgical wounds
  • Systemic Immunological changes
  • Is the response antigen specific? – IL-4 expression in ILN,
  • Tissue reconstruction Clinical Trial: FDA ask to look at what cells infiltrate the scaffold
  • Trauma/biomaterial response – Injury induction of Senescence, anti apoptosis
  • Injury to skin or muscle
  • Is pro-regenerative environment (Th2/M2) pro-tumorigenic?
  • SYNTHETIC Materials for scafolds
  • Biomaterials and Immunology
  1. Immune response to bioscafolds
  2. environment modulate the immune system
  • Regenerative Immunetherapy

Marcela Maus – Massachusetts General Hospital

Engineering Better T Cells

  • Comparing CD19 CARs for Leukemia – anti-CD19- directed CAR T cells with r/r B-cell ALL – age 3-25 – FDA approved Novartis tisagenlecleucel – for pediatric r/r/ ALL
  • Phase II in diffuse large B cell lymphoma. Using T cells – increases prospects for cure
  • Vector retroviral – 30 day expression
  • measuring cytokines release syndrome: Common toxicity with CAR 19
  • neurological toxicity, B-cell aplagia
  • CART issues with heme malignancies
  1. decrease cytokine release
  2. avoid neurological toxicity – homing
  3. new targets address antigene escape variants – Resistance, CD19 is shaded, another target needed
  4. B Cell Maturation Antigen (BCMA) Target
  5. Bluebird Bio: Response duratio up to 54 weeks – Active dose cohort
  6. natural ligand CAR based on April
  7. activated in response to TACI+ target cells – APRIL-based CARs but not BCMA-CAR is able to kill TACI+ target cells
  • Hurdles for Solid Tumors
  1. Specific antigen targets
  2. tumor heterogeneity
  3. inhibitory microenvironment
  • CART in Glioblastoma
  1. rationale for EGFRvIII as therapeutic target
  2. Preclinical Studies & Phase 1: CAR t engraft, not as highly as CD19
  3. Upregulation of immunosuppression and Treg infiltrate in CART EGFRvIII as therapeutic target, Marcela Maus
  • What to do differently?

 

2:15 – 2:45 Break

2:45 – 4:00 Session IV
Moderator: Arup K. Chakraborty | MIT, IMES

Laura Walker – Adimab, LLC
Molecular Dissection of the Human Antibody Response to Respiratory Syncytial Virus

  • prophylactic antibody is available
  • Barriers for development of Vaccine
  • Prefusion and Postfusion RSV structures
  • Six major antigenic sites on RSV F
  • Blood samples Infants less 6 month of age and over 6 month: High abundance RSV F -specific memory B Cells are group  less 6 month

Arup K. Chakraborty – MIT, Institute for Medical Engineering & Science
How to Hit HIV Where it Hurts

  • antibody  – Model IN SILICO
  • Check affinity of each Ab for the Seaman panel of strain
  • Breadth of coverage
  • immmunize with cocktail of variant antigens
  • Mutations on Affinity Maturation: Molecular dynamics
  • bnAb eveolution: Hypothesis – mutations evolution make the antigen binding region more flexible,
  • Tested hypothesisi: carrying out affinity maturation – LOW GERMLINE AFFINITY TO CONSERVE RESIDUES IN 10,000 trials, acquire the mutation (generation 300)

William Schief – The Scripps Research Institute
HIV Vaccine Design Targeting the Human Naive B Cell Repertoire

  • HIV Envelope Trimer Glycan): the Target of neutralizing Antibodies (bnAbs)
  • Proof of principle for germline-targeting: VRC)!-class bnAbs
  • design of a nanoparticle
  • can germline -targeting innumogens prime low frequency precursors?
  • Day 14 day 42 vaccinate
  • Precursor frequency and affinity are limiting for germline center (GC) entry at day 8
  • Germline-targeting immunogens can elicit robust, high quality SHM under physiological conditions of precursor frequency and affinity at day 8, 16, 36
  • Germline-targeting immunogens can lead to production of memory B cells

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17th Annual EmTech @ Media Lab, MIT – November 7 – 8, 2017, Cambridge, MA – This Year’s Themes, Speakers and Agenda

MIT Media Lab
Building E14
75 Amherst Street 
(Corner of Ames and Amherst)

Themes:

  • Business Impact
  • Connectivity
  • Intelligent Machines
  • Rewriting Life
  • Sustainable Energy
  • Meet the Innovators Under 35

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston

pharma_bi-background0238

will cover in REAL TIME

The 17th annual EmTech MIT – A Place of Inspiration, November 7 – 8, 2017, Cambridge, MA

MIT Technology Review’s EmTech conference

In attendance, covering LIVE using Social Media

Aviva Lev-Ari, PhD, RN

Editor-in-Chief

http://pharmaceuticalintelligence.com

@pharma_BI

@AVIVA1950

#emtechmit

@techreview

 

https://events.technologyreview.com/emtech/17/?utm_medium=email&utm_source=press_list&utm_campaign=emtech2017&utm_term=conference&utm_content=press_credentials&discount=MEDIAM172B#section-about

AGENDA FOR TUESDAY, NOVEMBER 7, 2017

  • 8:00
    Registration & Breakfast
9:00
Opening Remarks – Elizabeth Bramson-Boudreau, MIT TR
  • In Media Lab – MIT and MIT Technology Review was established in 1899
  • EmTech 1999 – 100 years to MIT Technology Review
  • Innovations and pushing the boundaries
  • AI – potential and limitations
  • Climate change requires new technologies
  • Brain Technologies: Biology Vision
  • Tomorrow: emerging technologies: Cybercrime, role of technology
  • Automation and future of work
  • Partners: GE, Lamburghini
  • Lemelson-MIT
  • MITTR – Whova on AppleStore
9:15
The State of AI – Andrew Ng, CS.AI, Stanford University – was 2008 Young Innovator,
Founder, Deeplearning.ai; Adjunct Professor, Stanford University
  • Trends in AI – AI is the new Electricity
  • Deep Learning & Neural Networks (NN):
  1. Input a picture –>> output: Is it You?
  2. loan application outcome: will you repay (%)
  3. picture from car – Output GPS address –>> Supervised Learning
  4.  doing act in <1 sec of thinking
  5. training SMALL, Medium size very large NN
  6. Algorithm innovations:

Supervised Learning algorithm types:

  • Transfer Learning
  • Unsupervised learning
  • Reinforcement learning – hunger for data: i.e., robotic applications

Importance of Data accumulation for launch a Product –  Users — data growth

  • Shopping Mall + website is not equal an Internet company
  • Internet company:
  1. push data to CEOs
  2. A–B Testing
  3. Short cycle time
  4. Decisions made by PM and ERP

AI era

traditional company + NN not equal AI company

  • Strategic data acquisition
  • Unified data warehouse
  • NEW JOB DESCRIPTIONS
  • Precision automation
  • ORGANIZATION CHART to interface in a matrix with AI Teams – hire Ai in the Business Units
  • Scarce talent of AI

Discussion

  • Children MUST learn to code
  • Human-Computer communication will be by writing code
9:45
Meet the Innovators Under 35
  • Future of work
  • warranted reliant digital connectivity
10:30
Break & Networking
11:00
AI’s Next Leap Forward

Tomasso Poggio, MIT, CSAIL, BCS

  • Deep learning  – next step
  • Bet on Center Brain Mind Machines (CBMM)
  • Josh Tennenbaum at MIT
  • Autonomous Driving – Amnon Shaashua, MobilEye
  • 20 years @ MI AI: Dailmer and MIT — detection of pedestrans
  • Powerful computers and algorithms – Reinforcement Learning Networks (Brain Science), models of Vision and Deep Learning Networks – WHEN they work?
  • Building Jarvis – a buttler application in AI built by Marc Zukenberg
  • NeuroScience – MobilEye, AlphaGo
  • CBMM – NSF $50 Million in AI funding  – Science of Intelligence and Engineering of Intelligence
  • MIT & Harvard plus several organization
  • Business Partners: MS Soft, Google bought MobilEye,
  • Center for Visual Gaze – 200 msec of visual processing
  • ERGO SUM: toward symbols, Cognitive core, visual system, Brain OS – running routines
  • Breakthroughs: Theory: under which conditions,
  1. Learning theory
  2. optimization Approximation Theory: Deep vs Shallow networks
  3. Intelligence is greatest problem to solve it is like LIFE, Tomasso Poggio, MIT, CSAIL, BCS
  4. machine can help human to think better, long time horizon is needed,

Kris Hammond, Prof. Northtwestern University

  • Data analytics and Ideas
  • words vs language – past, present, future – uniquely HUMAN, now machine language is Human Partner
  • language vs Ideas
  • machines knows a lot
  • facts, dat move to narrative
  • Language is understanding
  • FIN information: Decisions about allocations,
  • Turbidity data on the beach in Chicago: Which Beach is the cleanest vs the dirtiest
  • NARRATIVE ANALYTICS: data that machine can tell us what it has as a story and presented as intelligent language,

    Cognitive Science application to autonomous driving – Yibio Zhau, Tennenbaum Lab @MIT, ISEE.AI, Computer vision, Cognitive Science

  •  interpulate and extrapulate data needed for autonomous driving
  • reasoning beyond the system: Human intelligence , intentional reasoning, pattern recognition,
  • Ali baba – funding building of a Robot for autonomous driving – understanding by imagining – causes for behavior by others
  • ISEE – Next generation of AI — driving drivessless ly for thousands of miles
  • Car to car communication is a sensoring issue, negotiation need to be taught to machines

Young Scientists 35 years old or less

Austin Olson, Luminar – object detection 99% accuracy,

Angella Schoellig — Roborts, Prof. University of Toronto, robots in predictable environments

Lorenz Meier — Vertical Technologies – Drones and safety – DB of flights

12:30
Lunch & Networking
2:00
Adapting to the reality of climate change

Lee Krevat, Sempra –

owns Wind Farms- managing a Grid with renewable energy. Variable – Wind technology wind is variable – if wind blows too much switch to diesel. 100% renewable for one hour on Islands

Growth area:
  1. 20 cents diesel, wind is 10 cents help the enviroment

mainland, not yet used, price diesel vs wind

Solar wind generation – next biggest Technology in Energy

and

Alex Tepper,Avetars

Robotics, Drones, AI and the Future of Energy – A start up incubator sponsored and funded by GE
  • RAIL – Predict derailments
  • OIL & GAS – corrosion is the enemy — knowledge of corosion progression – using AI algorithms

Growth area: Aviation

John Holdren – Harvard University – Government  Role in ENERGY and Climate Change – Obama’s advisor Presidential CSO on Climate and energy

  • mitigation
  • adaptation
  • suffering – shortcomings of mitigation and adaptation
  • harm of business as usual
  • Efficiency standards during Obama Administration, assistance to other countries led to the Agreement in Paris 195 countirs — agreement to reduce emission. China and US declare cooperation on emission of gases into the environment.
  • PRESIDENT TRUMPS CALLED CLIMATE CHANGE A HOAX  – proposed to cut energy R&D
  • All executive orders by Obama – were reverted by Trump
  • Innovations: Electricity from Solar increase and wind as well and batteries
  • Carbon capture and storage – technological challenge
  • Biofuel processing, liquid bio fuel
  • Nuclear innovations to nuclear waste
  • 2100 – 5% on defense and 2% on the environment – model under estimate the contribution of innovations for the long run.
  • 1000 businesses in deployment of technologies

Evelyn wang, MIT – Material Science – Sustainable energy – nano

  • material properties: superior properties of LOW DENSITIES
  • Light manipulation
  • membrane
  • CO2 capture
  • Technologies: Nnao, Thermoelectronics, energy and water
  • Solar 6% and wind 21%, biomass 5%voltaic
  • SOlar eneconversion
  • PHOVOLTAIC: SCALBALE, SOLID STATE, INTERMITTENT, PARTIAL SOLAR SPECTRUMrgy
  • Nanophotonics: Solar energy conversion: photo
  • Nano absorber – area ratio; Emitter: silicon and silicon  – spectral approach
  • potential STPVs
  • Transportation using energy with emission
  • Power consumed by HVAC
  • Thermal Battery for Electric Vehicle: Adsorption Heating and Cooling
  • Desorption vs Adsoption: cooling vs Heating mode
  • High capacity adsobents – Zeolite  MOF enhancing capacity heat and mass transport
  • Tmal Battery Prototype: Hybrid, electric, stationary domestic HVAC.
  • Water harvesting from Air – metal organic Frameworks: Adsorption – harvest water without need of additional electricity
  • Opportunities for Advanced Materials

Prof. David Keith, Harvard University

  • technologies to stop global changing
  • research program
  • stratospheric aerosol cool planet – pollution masking global warming
  • solar geo-engineering, vs emission cut 3x BAU vs business as usual
  • Annual maximal Temperatures, extreme precipitation,
  • carbon emission worm up vs climate risk in Time
  •  use of technology for climate change mitigation: carbon removal
  • Solar engineering is the solution
3:30
Break & Networking
4:00
Meet the Innovators Under 35

Next Generation Brain Interfaces

Andrew Schwartz, University of Pittsburg

  • Causality is obscure
5:30
Lemelson-MIT Prize Honors & Reception
Lemelson-MIT Prize Honors Feng Zhang, MIT with the Prize for contributions to CRISPR Applications as a therapeutics method in genomics

AGENDA FOR WEDNESDAY, NOVEMBER 8, 2017

  • 8:00
    Registration & Breakfast
9:00 Elizabeth Branson
9AM – 9:30AM Robots and AI in Everyday Life

Daniela Rus, CSAIL, MIT – Robots: drones, 3D Printing

hosted by David Rotman, MIT TR

  • supply chain and transportation – city will benefit from a different business model
  • autonomous driving deployed in Singapore
  • all vehicles on wheels can be made autonomous
  • blind – camera on a belt assists in navigation
  • ML: Patterns and predictions
  • AI – reasoning
  • robots: motion
  • Machine read entire libraries
  • Radiology: Read by machines vs by Radiology: AI  + Human — 0.5% error
  • Rural area medicine
  • Machines – Better Lawyers: NLP – read precedents to cases, machines can’t write a briefing or defend a plaintif
  • Factory and Automation: Robots roles – enable mass OPTIMIZATION  not only mass production
  • Machines do not have common sense and do not have ability to reason
  • crunching data vs analysis
  • JOB Categories:Tasks vs Professions: Routine data processing and labor task — are ready for automation
  • NEW jobs: User experience designer, GPS enable taxi drivers to drive and drove pay scale down
  • GDP – decreased 1966 – 2016
  • KY school to train coal miners to do data processing to become CODERS
  • JFK – new machines brings man back to jos – new jobs
  • AI supports NEW jobs: CS/AI part of literacy
  • people and machines – in collaboration

discussion

  • Who to make the transition?
  • CODING is key – people must be active in keeping up and continue to train
  • make it easy to make machines, interactions Man-Machine easier,
  • YOU ARE WRONG SIGNAL IS recognized by EEG
  • AI and Future of Work Conference at MIT – anxiety related to job changing due to technology
  • Technology can’t solve all problems, Technology helps, Technology implications on Policy – technology as a unifier societal force not a dividers
  • Transportation as Utility

9:30 – 10:00 AI and the Future of Work

Iyad Rahwan, MIT Media Lab, Introduction by Elizabeth Woyke, TR

  • Physical Therapist — will not be replaced by computerisation
  • Probability of computerisation: Skilled cities are better at economics shocks
  • Adam Smith – simple operations
  • Differential Impact from Automation on Cities – the larger the city more resilient to automation
  • City size vs clusters of occupations — cluster grow with city size
  • Impact on Middle Class vs Lower and Upper: low paying jobs, middle and high
  • Skills in Occupations: mapping SkillScape correlations with Education
  • Skills in demand

discussion

  • Urbanization took place – 80% live in cities around the World
  • Outliers in CIties by size and Skills: Boulder, CO – small size very skilled labor, politics support start ups and high tech

 

10AM – 10:30AM

Meet the Innovators Under 35

  • Tracy Chou – ProjectInclude – diversity
  1. All about data

 

  • Olga Russakovsky – Princeton University – Computer vision
  • AI for education of under privileged high school
  1. IM-GENET – Data sets encode human biases
  2. AI is powered by Data
  3. AI learns societal  biases
  4. Researchers shape AI
  • 10:30

    Break & Networking

  • 11:00 – 11:30 What is Social Media Doing to Society?
 Yasmin Green, Jigsaw, Google
  • 300 million reach of Ads posted by Google in the Internet
  • Fake news
  • Network shape
  • Veracity and popularity personalized
Hosted by Martin Giles, TR
  • e 11:30 – 11:45 Meet the Innovators under 35
  • Phillipa Gill  – UMass CS – Project of Network measurement on censorship measurement platforms
  • Joshua Browder – DoNotPay

11:45 – 12:00 The Emerging Threat of Cybercriminal AI

Shuman Ghosemajumder, Shape Security

Hosted by Martin Gile

  • CyberCrime is evolving using AI – Imitation Game – Turing Test restricted Turing Tests
  • Computer vision, Solving CAPUTRE – Copletely Automated Turing  Tests
  • CAPTCHA by Google
  • Credential Stuffing Accounts Attacks – SONY was hacked and 93,000 Passwords stolen
  • Clip Farms at Google
  • BLACKFISH – identify Credential Stuffing Accounts Attacks, all invalid password are not valid to be used by cyber attackers again – that authentication is no longer valid
  • Multi Factors Authentications vs ease of use to Log In
  • Knowledge Basis – Probabilistic  SYmbols – BlackFISH – technological advantage – iPhone stores a math formulation of characteristics of the finger print not the image of the fingure
  •  12:00
    Lunch & Networking – Lamborghini -super sport car
1:30 – 2PM
Technology Spotlight: Mind-Controlled VR
Ramses Alcaide, Neurable
Hosted by Rachel Metz, TR
  • Killer Platforme ==>Killer Interaction ==>Killer application
  • Reactive ==> Proactive
  • Brain Computer Interaction (BCI) – maximum Privacy no voice involved like in SPeech
  • Voice, Motion Tracking, eye tracking
  • Human intentionality – a World without limitations
  • NASA is a client
  • consol technology for navigation, typing,
  • Problems: Add to glasses or as an Ear piece
  • the signal is ACTION POTENTIAL
  • latency differences between individuals
  • Non-invasive to invasive to capture signals

 

 
2:00 – 2:30 Capturing Our Imagination:: Evolution of Brain-Machine Interfaces
Mary Lou Jepsen, Openwater
Hosted by Antonio Ragalado, TR
  • Using functional MRI technology for a NEW device to scan emotions rather than medical diseases
  • HOLOGRAPHY of the Brain – liquid crystal display is like transistors on a chip
  • OPTICS – DISCONTINUITY of Moore’s law – high resolution like functional MRI
  • Holographic LCD – scattering material VOXEL detector – measure intensity of light, no resolution, consumer camera speed OK Inexpensive
  • Human body scattering
  • HAT and Bandage
2:30 – 3PM Future of Work – REWARD DISOBEDIENCE –
New Prize of $250,000  – Ethics and governance in AI at MIT Media lab
Reid Hoffman, Greylock Partners Founder LinkedIn
conversation with Joi Ito, MIT Media Lab
  • Tell the Truth
  • Media Lab — a Non-disciplinary place
  • Universities play a role in Social Justice
  • FEAR of AI:
  1. For profit will own it all
  2. stupid AI will govern
  3. displace work
  4. espionage
  5. catalytic institute that will make a contribution to OPENNESS vs technological dominance

Joi Ito, MIT Media Lab: AI problems –

  • MUST be democratized – Now it is in the hands of very FEW
  • RISK SCORES can’t be contested in court because they are IP of for profit companies
  • Joi Ito, MIT Media Lab at MIT do good to Society vs make the most of money which the majority are doing
  • AUTONOMICH vs autonomous agents, said Joi Ito, MIT Media Lab – Hoffman: Design goals more symbiotic: Scaling, more productive, Season 2 launched today
  • Design principle – LEARNING vs EDUCATION, Joi Ito, MIT Media Lab

Hoffman on AI Technologies

  • shaping it to avoid catastrophic negatives
  • provide a public good via participation
3:00
Break & Networking
3:30 – 4 Big Problems, Big Data Solutions
Deb Roy, MIT media Lab
  • Tweets and News, Washington Post – Tracking tweets from US on Politics related to the Elections
  • National memory on Guns, Immigrations
  • Debate brief from tweets and News rooms
  • topic classifier,  Campaign finance, SHARE OF COVERAGE IN NEWS, SHARED OF VOICE ON TWITTER
  • deep neural network training algorithms
  • Passion Gap: cut data on Twitter – Trump supporters exhibited x2 fold energy vs the Democratic candidate
  • How does Media flow: Sanders, Clinton, Trump – each is a Media Source
  • Truth, Trust, Attention  – Fact checking
  • If Trust the source then I believe it is True
  • Public Opinion: The Politics of Resentment in Rural WI – Katherine Cramer
  • Listening Networks: Human- Human Interaction: Media sharing network – change week by week – the MOST innovative methodology developed to date for Public Opinion – presentation by
    Deb Roy, MIT media Lab  – using deep Neural network training
  1. main stream
  2. conservative
  3. liberal activist
  • Health Indicators:
  • Shared attention
  • Shared Reality
  • Varied Perspective – surface under-heard voices
3:30 – 4
Meet the Innovators Under 35
1. Svenja Hinderer, Germany
  • Valve – development of Tissues, biochemical properties
  • signaling molecules
  • mechanical strength – physiological
  • Attrach stem cells – proper matrix formation
  • Functional implants
2. Viktor Adalsteinsson
  • Cancer Precision medicine – Liquid biopsy – tumor mutations
  • entire Cancer Genome – from blood biopsy
  • Scaling: Broad Institute 100 collaborators – 3,000 blood sample genomical analysis
2.Tallis Gomes, CEO Entrepreneur, Brazil
  • Easy Taxi
  • Fighting inequality
  • 15Billion – Beauty Market
3. Abidigani Diriye
  • IBM Research Africa – 300 million adults – lack of access to financial services
  • Univesities, Government  – start ups to scale ideas
Eyad Janneh
  • 5:00
    2017 Innovator Under 35 Awards & Reception
  1. Speakers
    • Viktor
      Adalsteinsson

      Group Leader, Broad Institute of MIT and Harvard

      2017 Innovator Under 35

    Gene
    Berdichevsky

    CEO, Sila Nano

    2017 Innovator Under 35

    • rechargeable battery
    • new class of materials charge and discharge in battery
    • store more energy
    • more better designed electronics: electrified flight, solar, car: Hybrid and electric
    • 21st Century belongs to electrification vs combustion in the 20th century,

      Gene
      Berdichevsky

      CEO, Sila Nano

    • Tracy
      Chou

      Founding Advisor, Project Include

      2017 Innovator Under 35

    • Adrienne
      Felt

      Software Engineer, Google

      2017 Innovator Under 35

    • Phillipa
      Gill

      Assistant Professor, University of Massachusetts, Amherst

      2017 Innovator Under 35

    • Tallis
      Gomes

      CEO, Singu

      2017 Innovator Under 35

    Kathy
    Gong

    CEO, WafaGames

    2017 Innovator Under 35

    • GAMING SWARD OF GLORY – EPIC NEW RTS EXPERIENCE – WAFA GAMES IN CHINA
    • Ian
      Goodfellow

      Staff Research Scientist, Google Brain, development occurred at OpenAI

      GAN’s – Generative Adversarial Network – from AI Optimization to Game Theory

      2017 Innovator Under 35

    • Yasmin
      Green

      Director of Research and Development, Jigsaw at Google

      Addressing Online Threats to Global Security

    • Kris
      Hammond

      Chief Scientist and Cofounder, Narrative Science

      AI’s Language Problem

    • Svenja
      Hinderer

      Scientist, Fraunhofer IGB

      2017 Innovator Under 35

    • Reid
      Hoffman

      Cofounder, LinkedIn; Partner, Greylock Partners

      The Future of Work

    • John
      Holdren

      Professor, Harvard University

      Climate Disruption: Technical Approaches to Mitigation and Adaptation

    • Joi
      Ito

      Director, MIT Media Lab

      The Future of Work

    • Mary Lou
      Jepsen

      Founder, Openwater

      Capturing Our Imagination: The Evolution of Brain-Machine Interfaces

    • David
      Keith

      Professor, Harvard University; Founder, Carbon Engineering

      The Growing Case for Geoengineering

    • Neha
      Narkhede

      Cofounder and CTO, Confluent

      2017 Innovator Under 35

    • Andrew
      Ng

      Founder, Deeplearning.ai; Adjunct Professor, Stanford University

      The State of AI

    • Tomaso
      Poggio

      Investigator, McGovern Institute; Eugene McDermott Professor, Brain and Cognitive Sciences, MIT

      Understanding Intelligence

    • Olga
      Russakovsky

      Assistant Professor, Princeton University

      2017 Innovator Under 35

    Michael
    Saliba

    Marie Curie Fellow, EPFL

    2017 Innovator Under 35

    • disruptive technology in the energy space
    • Gang
      Wang

      Chief Scientist, Alibaba

      2017 Innovator Under 35

    • Jianxiong
      Xiao

      Chief Executive Officer, AutoX, Inc.

      2017 Innovator Under 35

      CAMERA-first solution affordable self-driving

Read Full Post »


Lectures by The 2017 Award Recipients of Warren Alpert Foundation Prize in Cancer Immunology, October 5, 2017, HMS, 77 Louis Paster, Boston

Top, from left: James Allison and Lieping Chen. Bottom, from left: Gordon Freeman, Tasuku Honjo (NOT ATTENDED), Arlene Sharpe.

Aviva Lev-Ari, PhD, RN was in attendance and covered this event LIVE

 

The 2017 Warren Alpert Foundation Prize has been awarded to five scientists for transformative discoveries in the field of cancer immunology.

Collectively, their work has elucidated foundational mechanisms in cancer’s ability to evade immune recognition and, in doing so, has profoundly altered the understanding of disease development and treatment. Their discoveries have led to the development of effective immune therapies for several types of cancer.

The 2017 award recipients are:

  • James Allison, professor of immunology and chair of the Department of Immunology, The University of Texas MD Anderson Cancer Center – Immune checkpoint blockage in Cancer Therapystrictly Genomics based drug
  1. 2017 FDA approved a gemonics based drug
  2. and co-stimulatory signals
  3. CTLA-4 blockade, CD28, AntiCTLA-4 induceses regression of Transplantable Murine tumo
  4. enhance tumor-specific immune response
  5. Fully antibody human immune response in 10,000 patients – FDA approved 2011
  6. Metastatic melanoma – 3 years survival, programmed tumor death, PD-1, MHC-A1
  7. Ipi/Nivo vs. Ipi – combination – 60% survival vs Ipi alone
  8. Anti CTA4 va Anti-PD-1
  9. responsive T cell population – MC38 TILs
  10. MC38 Infiltrating T cell populations: Treg, CD4, Effector, CD8, NKT/gamma-delta
  11. Checkpoint blockage modulates infiltrating T cell population frequencies
  12. T reg correlated with Tumor growth
  13. Combination therapy lead to CURE survival at 80% rate vs CTAL-4 40% positive outcome

Not Attended — Tasuku Honjo, professor of immunology and genomic medicine, Kyoto University – Immune regulation of Cancer Therapy by PD-1 Blockade

 

  • Lieping Chen, United Technologies Corporation Professor in Cancer Research and Professor of immunobiology, of dermatology and of medicine, Yale University – Adoptive Resistance: Molecular Pathway t Cancer Therapy – focus on solid tumors
  1. Enhancement – Enhance normal immune system – Co-stimulation/Co-inhibition Treg, and Cytokines, adoptive cell therapy, Lymphoid organs stores
  2. Normalization – to correct defective immune system – normalizing tumor immunity, diverse tumor escape mechanisms
  3. Anti-PD therapy: regression of large solid tumors: normalizing tumor immunity targeting tumor microenvironment: Heterogeneity, functional modulation, cellular and molecular components – classification by LACK of inflamation, adaptive resistance, other inhibitory pathways, intrinsic induction
  4. avoid autoimmune toxicity,
  5. Resetting immune response (melanoma)
  6. Understad Resistance: Target missing resistance or Adaptive resistance Type II= acquired immunity
  • Gordon Freeman, professor of medicine, Dana-Farber Cancer Institute, Harvard Medical School – PD-L1/PD-1 Cancer Immunotherapy
  1. B7 antibody
  2. block pathway – checkpoint blockage, Expand the T cells after recognition of the disease. T cell receptor signal, activation, co -stimulatory: B71 molecule, B72 – survival signals and cytokine production,.Increased T cell proliferation,
  3. PDL-1 is a ligand of PD 1. How T cell die? genes – PD1 Gene was highly expressed,
  4. Interferon gamma upregulate PD-L1 expression
  5. Feedback loop Tumor – stimulating immune response, interferon turn off PD1
  6. PD-L1 and PD-L2 Expression: Interferom
  7. Trancefuctor MHC, B7-2
  8. PD-L! sisgnat inhibit T-cell activation: turn off Proliferation and cytokine production — Decreasing the immune response
  9. T cell DNA Content: No S-phase devided cell
  10. PD-L1 engagement of PD-1 results in activation : Pd-1 Pathway inhibits T Cell Actiivation – lyposite motility,
  11. Pd-L2 is a second ligand for PD-1 and inhibits T cell activation
  12. PDl-1 expression: BR CA, Ovarian, Colonol-rectal, tymus, endothelial
  13. Blockage of the Pathway – Immune response enhanced
  14. Dendritic cells express PD-L1, PD-L2 and combination of Two, Combination was best of all by increase of cytokine production, increasing the immune response.
  15. PD-L1 blockade enhanced the immune response , increase killing and increased production of cytokines,
  16. anti-tumor efficacy of anti-PD-1/Pd-L1
  17. Pancreatic and colono-rector — PD-L, PDL1, PDL2 — does not owrkd.
  18. In menaloma: PD-1 works better than CYLA-4
  19. Comparison of Targeted Therapy: BRAF TKI vs Chemo high % but short term
  20. Immunotherapy – applies several mechanism: pre-existing anti-therapy
  21. Immune desert: PD=L does not work for them
  22. COMBINATION THERAPY: BLOCK TUMOR INVASION THEN STIMULATE IMMUNE RESPONSE — IT WILL WORK
  23. PD blockage + nutrients and probiotic
  24. Tumor Genome Therapy
  25. Tumore Immuno-evasion Score
  26. Antigens for immune response – choose the ones
  27. 20PD-1 or PD-L1 drugs in development
  28. WHO WILL THE DRUG WORK FOR?

 

  • Arlene Sharpe, the George Fabyan Professor of Comparative Pathology, Harvard Medical School; senior scientist, department of pathology, Brigham and Women’s Hospital – Multi-faceted Functionsof the PD-1 Pathway
  1. function of the pathway: control T cell activation and function of maintain immune tolerance
  2. protect tissues from damage by immune response
  3. T cell dysfunction during cancer anf viral infection
  4. protection from autoimmunity, inflammation,
  5. Mechanism by which PD-1 pathway inhibits anti-tumor immunity
  6. regulation of memoryT cell responce of PD-1
  7. PD-1 signaling inhibit anti-tumor immunity
  8. Compare: Mice lacking CD8-Cre- (0/5) cleared vs PD-1-/-5/5 – PD-1 DELETION: PARTIAL AND TIMED: DELETION OF PD-1 ON HALF OG TILS STARTING AT DAY 7 POSTTUMOR IMPLANTATION OF BOTH PD-1 AND PD-1 TILS: – Tamoxifen days 7-11
  9. Transcription profile: analysis of CD8+ TILs reveal altered metabolism: Fatty Acid Metabolism vs Oxidative Phosphorylation
  10. DOes metabolic shift: WIld type mouth vs PD-1-/_ P14: analyze Tumor cell killingPD-1-/- enhanced FAO increases CD8+ T cell tocicity
  11. Summary: T cell memory development and PD-1: T effectors vs T cell memory: Primary vs Secondary infection: In the absent of PD-1, CD8+ T cels show increase expansion of T cells
  12. INFLUENZA INFECTION: PRIMARY more virus in lung in PD-1 is lacking
  13. Acute infection: PD-1 controls memory T cell differentiation vs PD-1 increase expansion during effector phase BUT impaired persistence during memory phase: impaired cytokine production post re-challenge
  14. PD-1 immunotherapy work for patients with tumor: Recall Response and Primary response
  15. TIL density Primary vs Long term survivor – 5 days post tumor implantation – rechallenged long term survival
  16. Hot tumor vs Cold tumor – Deletion of PD-1 impairs T memory cell development

 

Opening Remarks: George Q. Daley, MD, PhD, DEAN, HMS

  • Scientific collaboration check point – avoid the body attacking itself, sabotaging the immune system
  • 1987 – Vaccine for HepB
  • Eight of the awardees got the Nobel Prize

 

Moderated by Joan Brugge, PhD, HMS, Prof. of Cell Biology

  • Evolution of concepts of Immunotherapy: William Coley’s Toxin streptoccocus skin infection.
  • 20th century: Immuno-surveilence, Immune response – field was dead in 1978 replaced by Immunotherapy
  • Rosenberg at NIH, high dose of costimulatory molecule prevented tumor reappearanceantbody induce tumor immunity–>> immune theraphy by check point receptor blockade – incidence of tumor in immune compromised mice – transfer T cell
  • T cell defficient, not completely defficient, self recognition of tumor,
  • suppress immmune – immune evasion
  • Michael Atkins, MD, Detupy Director, Georgetown-Lombardi, Comprehensive Cancer Center Clinical applications of Checkpoint inhibitors: Progress and Promise
  1. Overwhelm the Immune system, hide, subvert, Shield, defend-deactivating tumor trgeting T cells that ATTACK the immune system
  2. Immune system to TREAT the cancer
  3. Monotherapy – anti PD1/PD-L1: Antagonist activity
  4. Evading immune response: prostate, colcn
  5. MMR deficiency
  6. Nivolumab in relaped/Refractory HODGKIN LYMPHOMAS – over expression of PD-L1 and PDL2in Lymphomas
  7. 18 month survival better with Duv in Lung cancer stage 3 – anti PD-1- adjuvant therapy with broad effectiveness
  8. Biomarkers for pD-L1 Blockage
  9. ORR higher in PD-L1
  10. Improve Biomarkers: Clonality of T cells in Tumors
  11. T-effector Myeloid Inflammation Low – vs Hogh:
  12. Biomarker Model: Neoantigen burden vs Gene expression vs CD8+
  13. Tissue DIagnostic Labs: Tumor microenveironmenr
  14. Microbiome
  15. Combination: Nivo vs Nivo+Ipi is superior: DETERMINE WHEN TO STOP TREATMENT
  16. 15/16 stopped treatment – Treatment FREE SURVIVAL
  17. Sequencing with Standard Therapies
  18. Brain metastasis – Immune Oncology Therapy – crosses the BBB
  19. Less Toxic regimen, better toxicity management,
  20. Use Immuno therapy TFS
  21. combination – survival must be justified
  22. Goal: to make Cancer a curable disease vs cancer becoming a CHronic disease

 

Closing Remarks: George Q. Daley, MD, PhD, DEAN, HMS

 

The honorees will share a $500,000 prize and will be recognized at a day-long symposium on Oct. 5 at Harvard Medical School.

The Warren Alpert Foundation, in association with Harvard Medical School, honors trailblazing scientists whose work has led to the understanding, prevention, treatment or cure of human disease. The award recognizes seminal discoveries that hold the promise to change our understanding of disease or our ability to treat it.

“The discoveries honored by the Warren Alpert Foundation over the years are remarkable in their scope and potential,” said George Q. Daley, dean of Harvard Medical School. “The work of this year’s recipients is nothing short of breathtaking in its profound impact on medicine. These discoveries have reshaped our understanding of the body’s response to cancer and propelled our ability to treat several forms of this recalcitrant disease.”

The Warren Alpert Foundation Prize is given internationally. To date, the foundation has awarded nearly $4 million to 59 scientists. Since the award’s inception, eight honorees have also received a Nobel Prize.

“We commend these five scientists. Allison, Chen, Freeman, Honjoand Sharpe are indisputable standouts in the field of cancer immunology,” said Bevin Kaplan, director of the Warren Alpert Foundation. “Collectively, they are helping to turn the tide in the global fight against cancer. We couldn’t honor more worthy recipients for the Warren Alpert Foundation Prize.”

The 2017 award: Unraveling the mysterious interplay between cancer and immunity

Understanding how tumor cells sabotage the body’s immune defenses stems from the collective work of many scientists over many years and across multiple institutions.

Each of the five honorees identified key pieces of the puzzle.

The notion that cancer and immunity are closely connected and that a person’s immune defenses can be turned against cancer is at least a century old. However, the definitive proof and demonstration of the steps in this process were outlined through findings made by the five 2017 Warren Alpert prize recipients.

Under normal conditions, so-called checkpoint inhibitor molecules rein in the immune system to ensure that it does not attack the body’s own cells, tissues and organs. Building on each other’s work, the five award recipients demonstrated how this normal self-defense mechanism can be hijacked by tumors as a way to evade immune surveillance and dodge an attack. Subverting this mechanism allows cancer cells to survive and thrive.

A foundational discovery made in the 1980s elucidated the role of a molecule on the surface of T cells, the body’s elite assassins trained to seek, spot and destroy invaders.

A protein called CTLA-4 emerged as a key regulator of T cell behavior—one that signals to T cells the need to retreat from an attack. Experiments in mice lacking CTLA-4 and use of CTLA-4 antibodies demonstrated that absence of CTLA-4 or blocking its activity could lead to T cell activation and tumor destruction.

Subsequent work identified a different protein on the surface of T cells—PD-1—as another key regulator of T cell response. Mice lacking this protein developed an autoimmune disease as a result of aberrant T cell activity and over-inflammation.

Later on, scientists identified a molecule, B7-H1, subsequently renamed PD-L1, which binds to PD-1, clicking like a key in a lock. This was followed by the discovery of a second partner for PD-1—the molecule PD-L2—which also appeared to tame T-cell activity by binding to PD-1.

The identification of these molecules led to a set of studies showing that their presence on human and mouse tumors rendered the tumors resistant to immune eradication.

A series of experiments further elucidated just how tumors exploit the interaction between PD-1 and PD-L1 to survive. Specifically, some tumor cells appeared to express PD-L1, essentially “wrapping” themselves in it to avoid immune recognition and destruction.

Additional work demonstrated that using antibodies to block this interaction disarmed the tumors, rendering them vulnerable to immune destruction.

Collectively, the five scientists’ findings laid the foundation for antibody-based therapies that modulate the function of these molecules as a way to unleash the immune system against cancer cells.

Antibody therapy that targets CTLA-4 is currently approved by the FDA for the treatment of melanoma. PD-1/PD-L1 inhibitors have already shown efficacy in a broad range of cancers and have been approved by the FDA for the treatment of melanoma; kidney; lung; head and neck cancer; bladder cancer; some forms of colorectal cancer; Hodgkin lymphoma and Merkel cell carcinoma.

In their own words

“I am humbled to be included among the illustrious scientists who have been honored by the Warren Alpert Foundation for their contributions to the treatment and cure of human disease in its 30+ year history.  It is also recognition of the many investigators who have labored for decades to realize the promise of the immune system in treating cancer.”
        -James Allison


“The award is a great honor and a wonderful recognition of our work.”
         Lieping Chen



I am thrilled to have made a difference in the lives of cancer patients and to be recognized by fellow scientists for my part in the discovery of the PD-1/PD-L1 and PD-L2 pathway and its role in tumor immune evasion.  I am deeply honored to be a recipient of the Alpert Award and to be recognized for my part in the work that has led to effective cancer immunotherapy. The success of immunotherapy has unleashed the energies of a multitude of scientists to further advance this novel strategy.”
                                        -Gordon Freeman


I am extremely honored to receive the Warren Alpert Foundation Prize. I am very happy that our discovery of PD-1 in 1992 and subsequent 10-year basic research on PD-1 led to its clinical application as a novel cancer immunotherapy. I hope this development will encourage many scientists working in the basic biomedical field.”
-Tasuku Honjo


“I am truly honored to be a recipient of the Alpert Award. It is especially meaningful to be recognized by my colleagues for discoveries that helped define the biology of the CTLA-4 and PD-1 pathways. The clinical translation of our fundamental understanding of these pathways illustrates the value of basic science research, and I hope this inspires other scientists.”
-Arlene Sharpe

Previous winners

Last year’s award went to five scientists who were instrumental in the discovery and development of the CRISPR bacterial defense mechanism as a tool for gene editing. They were RodolpheBarrangou of North Carolina State University, Philippe Horvath of DuPont in Dangé-Saint-Romain, France, Jennifer Doudna of the University of California, Berkeley, Emmanuelle Charpentier of the Max Planck Institute for Infection Biology in Berlin and Umeå University in Sweden, and Virginijus Siksnys of the Institute of Biotechnology at Vilnius University in Lithuania.

Other past recipients include:

  • Tu Youyou of the China Academy of Chinese Medical Science, who went on to receive the 2015 Nobel Prize in Physiology or Medicine with two others, and Ruth and Victor Nussenzweig, of NYU Langone Medical Center, for their pioneering discoveries in chemistry and parasitology of malaria and the translation of their work into the development of drug therapies and an anti-malarial vaccine.
  • Oleh Hornykiewicz of the Medical University of Vienna and the University of Toronto; Roger Nicoll of the University of California, San Francisco; and Solomon Snyder of the Johns Hopkins University School of Medicine for research into neurotransmission and neurodegeneration.
  • David Botstein of Princeton University and Ronald Davis and David Hogness of Stanford University School of Medicine for contributions to the concepts and methods of creating a human genetic map.
  • Alain Carpentier of Hôpital Européen Georges-Pompidou in Paris and Robert Langer of MIT for innovations in bioengineering.
  • Harald zur Hausen and Lutz Gissmann of the German Cancer Research Center in Heidelberg for work on the human papillomavirus (HPV) and cancer of the cervix. Zur Hausenand others were honored with the Nobel Prize in Physiology or Medicine in 2008.

The Warren Alpert Foundation

Each year the Warren Alpert Foundation receives between 30 and 50 nominations from scientific leaders worldwide. Prize recipients are selected by the foundation’s scientific advisory board, which is composed of distinguished biomedical scientists and chaired by the dean of Harvard Medical School.

Warren Alpert (1920-2007), a native of Chelsea, Mass., established the prize in 1987 after reading about the development of a vaccine for hepatitis B. Alpert decided on the spot that he would like to reward such breakthroughs, so he picked up the phone and told the vaccine’s creator, Kenneth Murray of the University of Edinburgh, that he had won a prize. Alpert then set about creating the foundation.

To award subsequent prizes, Alpert asked Daniel Tosteson (1925-2009), then dean of Harvard Medical School, to convene a panel of experts to identify scientists from around the world whose research has had a direct impact on the treatment of disease.

SOURCE

https://hms.harvard.edu/news/warren-alpert-foundation-honors-pioneers-cancer-immunology

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