Pharmaceutical companies are undergoing a digital transformation. By experimenting with new initiatives, they are positioned to play a role in the revolution of healthcare. This transformation is driven by data from internal and external sources, including both -omic data and that from digital devices. Bio-IT World WEST, part of Molecular Medicine Tri-Conference, brings together all the stakeholders involved in this transformation. Your registration includes the option to track-hop to the other programs at the Molecular Med TRI-CON as well as the Hackathon, plenary keynote, exhibit/poster hall, and more!

Machine learning, specifically for drug discovery and development, is highly data-intensive with disparate types of data being generated that have historically been trial-and-error processes. Deep learning, machine learning (ML) and artificial intelligence (AI), coupled with correct data, have the potential to make these processes less error-prone and increase the likelihood of success from drug discovery to the real-world setting. The AI-Enabled Drug Discovery and Development conference will discuss lessons learned from case studies as well as challenges that lay ahead.

Final Agenda

Monday, March 2

10:30 Conference Program Registration Open

KEYNOTE SESSION

(please see Keynotes page for details)

11:45 Organizer’s Opening Remarks

Cindy Crowninshield, RDN, LDN, HHC, Executive Event Director, Cambridge Healthtech Institute

11:50 Chairperson’s Remarks

Allison Proffitt, Editorial Director, Bio-IT World

11:55 Keynote Introduction, Benchling

Ashoka Rajendra, Head, Product, Registry, Inventory, Benchling

12:10 pm KEYNOTE PRESENTATION: The AI Bubble and the Emerging Thinking Economy

Pietro Michelucci, PhD, Director, Human Computation Institute

This presentation presents a realistic assessment of the “AI bubble” – where there is value, where there is hype, and how human-in-the-loop computing gives us futuristic AI capabilities today that co-evolve with AI technology and even help improve AI.

12:40 PANEL DISCUSSION: Data Quality in Human Computation Systems

Is today’s artificial intelligence fervor based on hype or is it happening? We’ve seen some amazing results from AI-based systems, fueled by increases in processing speed that render traditional applications finally practicable. At the same time, powerful new techniques are emerging including fruitful human/AI partnerships and recent successes based on combining crowdsourcing with machine learning. These new methods dovetail nicely with special challenges posed by precision medicine, often entailing complex interdependencies among data acquisition, analysis, privacy, and ethics. That said, they also introduce a new set of challenges as we navigate issues of transparency, trust, and reliability where automated systems are involved. This panel will discuss recent work in online collective systems that combine human and machine-based information processing in the biomedical space, how these systems could be applied to precision medicine, and how to avoid some of the potential pitfalls associated with these approaches. We also discuss an information processing ecosystem designed to accelerate precision medicine research while mitigating associated complexity and resource needs.

Moderator: Allison Proffitt, Editorial Director, Bio-IT World

Panelists: Jennifer Couch, PhD, Chief, Structural Biology and Molecular Applications Branch, Division of Cancer Biology and Citizen Science Coordinator, National Cancer Institute

Devin Krotman, Director, IBM Watson AI XPRIZE

Vani Mandava, Director, Data Science Outreach, Microsoft Research

Pietro Michelucci, PhD, Director, Human Computation Institute

Ginger Tsueng, PhD, Scientific Outreach Project Manager, Department of Integrative, Structural and Computational Biology, The Scripps Research Institute

1:30 Bio-IT World WEST Luncheon Presentation: Accelerating the Exchange of Data in Healthcare and Life Sciences

Fred Lee, MD, MPH, Head of Health Care, Life Sciences Business Development, AWS Data Exchange, AWS

Predictive models and algorithms in healthcare and life sciences (HCLS) have emerged from the combination of patient data and advanced analytics. With machine learning and AI technologies becoming commoditized, scalable access to patient data now throttles the build of such predictive analytics. We will discuss how the AWS Data Exchange, as a digital marketplace for data, addresses this ‘data bottleneck’ by accelerating data exchange in a regulatory compliant, economically sustainable, and cloud-native manner.

2:05 Session Break

APPLYING AI TO PRECISION MEDICINE

2:20 Chairperson’s Remarks

Michael D. Miller, Head of Science Infrastructure, Roche

2:25 AI and Computer-Aided Drug Discovery: the Hype, the Myth, the Legend

José Duca, PhD, Global Head, Computer-Aided Drug Discovery, Novartis

3:10 PANEL DISCUSSION: AI in Genomics and Precision Medicine

The AI-Enabled Drug Discovery and Development conference assembles thought leaders who will discuss Genomics and Precision Medicine, taking data from multiple -omics sources, imaging, and lifestyle data and aligning it with clinical action. These can then be turned into clinical recommendations for disease prevention, prognosis, diagnostics, and therapeutics. Machine learning gives us the power to extract elusive indicators from the ever-increasing volume of heath information. This information also gives us the power to make patient clusters, well beyond single etiology or prognostic indicators, and the panelists will present the promise and application of these multifactorial approaches toward curing or treating diseases and cancers.

Moderator: Ben Busby, PhD, Principal Scientist, DNANexus, Mountain Genomics, consultant to Johns Hopkins University (opencravat project)

Panelists: Jenny Smith, MSc, MEd, Research Bioinformatician, Clinical Research Division, Fred Hutchinson Cancer Research Center

Lukasz Kidzinski, PhD, CTO, Saliency.ai, Researcher, Stanford University

Celeste Shelton, PhD, CGC, Clinical Variant Scientist & Genetic Counselor, Ariel Precision Medicine

4:25 Refreshment Break and Transition to Plenary Keynote

PLENARY KEYNOTE SESSION

(please see Keynotes page for details)

4:35 Welcome Remarks

Cindy Crowninshield, RDN, LDN, HHC, Executive Event Director, Cambridge Healthtech Institute

4:45 PLENARY KEYNOTE INTRODUCTION

Thomas Westerling-Bui, PhD, Senior Scientist, Regional Business Development, Aiforia

5:00 PLENARY KEYNOTE PRESENTATION: High-Performance Medicine

Eric Topol, MD, Founder and Director, Scripps Research Translational Institute (SRTI); Author, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

6:00 Grand Opening Reception in the Exhibit Hall with Poster Viewing, Speed Networking, Book Signing, and Meetup Group

7:30 End of Day

Tuesday, March 3

7:30 am Registration Open and Morning Coffee

KEYNOTE SESSION

(please see Keynotes page for details)

8:00 Organizer’s Remarks

Cindy Crowninshield, RDN, LDN, HHC, Executive Event Director, Cambridge Healthtech Institute

8:05 NEW: Chairperson’s Remarks

Annastasiah Mudiwa Mhaka, PhD, Founder and Principal, Mawambo Lifesciences; Co-Founder, Convenor and Former President, Alliance for AI in Healthcare (AAIH)

8:10 Keynote Sponsor Introduction

Vasu Rangadass, President, CEO, L7 Informatics, Inc.

8:25 KEYNOTE PRESENTATION: AI and Big Data Strategies in Accelerating Clinical Research for Faster Rare Disease Cures

Harsha Rajasimha, MS, PhD, Founder, Jeeva Informatics Solutions, Inc.; Founder and Chairman, IndoUSrare; Co-Director, Rare Diseases Systems Biology Initiative, George Mason University

After losing a child to a rare congenital disease, Dr. Rajasimha became determined to apply his clinical genomics data research experience to develop solutions to help accelerate clinical research leading to faster cures for rare disease. Dr. Rajasimha will discuss his efforts in fostering collaborative bridges between patient advocacy groups and researchers in the USA and their counterparts in India to help accelerate clinical research, trials, and therapy access across borders. The talk will include recent global initiatives to accelerate screening, diagnosis, and treatments of rare and undiagnosed diseases. He will also share work on the development of an AI-driven digital health platform to improve clinical trial operational efficiencies while significantly reducing costs and travel burden on patients.

8:55 PANEL DISCUSSION: Applications of AI Technologies in Pharmaceuticals: Facilitating Development of Therapeutics in Treating Rare Diseases

The complex research framework involving industry, academia, and government to discover and develop new therapeutic products makes drug discovery a laborious process. With rapid strides that life sciences companies are making in the fields of gene and cell therapies, -omics technologies, and smart molecule approaches, an urgent need exists for cost-effective, time-effective, and advanced technologies to analyze large databases of information to help develop novel therapies. Organizations are recognizing the value of AI-based platforms and tools to leverage data to find hidden drug-disease correlations. Also, structured and unstructured data can be derived from multiple sources as never before. This panel brings senior level experts in pharma, AI-based technology, and government to discuss the role of AI platforms and tools to establish a robust pipeline as part of drug discovery portfolio and address new therapeutic areas, including rare diseases.

NEW: Moderator: Annastasiah Mudiwa Mhaka, PhD, Founder and Principal, Mawambo Lifesciences; Co-Founder, Convenor and Former President, Alliance for AI in Healthcare (AAIH)

Panelists: Tom Defay, Senior Director, R&D Strategy and Alliances, SPMD, Strategy, Program Management and Data Sciences, Alexion

Harsha Rajasimha, MS, PhD, Founder, Jeeva Informatics Solutions, Inc.; Founder and Chairman, IndoUSrare; Co-Director, Rare Diseases Systems Biology Initiative, George Mason University

Vasu Rangadass, President, CEO, L7 Informatics, Inc.

9:40 Refreshment Break in the Exhibit Hall with Poster Viewing, Speed Networking, Book Signing, and Meetup Group

FEATURED SESSION: DATA-DRIVEN PRECISION MEDICINE

10:40 Chairperson’s Remarks

Keith L. Ligon, MD, PhD, Associate Professor, Pathology, Harvard Medical School; Associate Pathologist and Neuropathologist, Pathology; Director, DFCI Center for Patient Derived Models, Brigham and Women’s Hospital

10:45 Translating Ten Trillion Points of Data into Diagnostics, Therapies and New Insights in Health and Disease

Atul Butte, MD, PhD, Priscilla Chan and Mark Zuckerberg Distinguished Professor; Director, Bakar Computational Health Sciences Institute, University of California, San Francisco; Chief Data Scientist, University of California Health (UC Health)

We build and apply tools that convert trillions of points of molecular, clinical, and epidemiological data – measured by researchers and clinicians over the past decade and now commonly termed “big data” – into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a computer scientist and pediatrician, will highlight his center’s recent work on integrating electronic health records data across the entire University of California, and how analytics on this “real world data” can lead to new evidence for drug efficacy, new savings from better medication choices, and new methods to teach intelligence – real and artificial – to more precisely practice medicine.

11:15 Using Networks to Decode Cancer Risk

John Quackenbush, PhD, Professor and Chair, Biostatistics, Harvard TH Chan School of Public Health

Precision medicine is based on the idea that single mutations can inform our understanding of disease and response to therapy. But we know that cancer is multifactorial, with many genetic variants moderating disease and disease risk. By using network methods, we can better understand how and why cancer develops and assess disease risk.

11:45 Machine Learning-Based Patient Subgroup Identification for Precision Medicine

Jie Cheng, PhD, Director, Exploratory Statistics, Abbvie

Central to precision medicine is the ability to detect patient subgroups with differential treatment effects in clinical trial datasets. These patient subgroups are defined by clinical variables and biomarkers. We will provide a brief overview of existing methods for patient subgroup identification and then present our novel approach. The performance of our method is evaluated against other state-of-the-art methods using both simulation and real-world clinical trial dataset

12:15 pm Session Break

12:20 LUNCHEON PRESENTATION I: A Modern Molecular LIMS Built for Precision Medicine

Nabil Hafez, MS, Senior Director, Product Management, Precision Medicine, Sunquest Information Systems

1:20 Refreshment Break in the Exhibit Hall with Poster Viewing, Speed Networking, Book Signing, and Meetup Group

2:00 Breakout Discussions in the Exhibit Hall (please click here for details)

3:00 Transition to Keynote Session

KEYNOTE SESSION

(please see Keynotes page for details)

3:15 Organizer’s Remarks

Christina Lingham, Executive Director, Conferences and Fellow, Cambridge Healthtech Institute

3:20 Keynote Introduction

Allison Mallory, PhD, Director, R&D Molecular Biology, Stilla Technologies

3:35 What Does the New Era of Genomic Medicine Look Like? Effects on Patient Care, Therapeutics, and Diagnostics

20 years after the completion of the first draft of the Human Genome Project, there is compelling evidence of genomics delivering the rich promise of precision medicine. There have been major advances in the throughput and affordability of genome sequencing, enhanced tools for genome analysis and interpretation, new paradigms for therapeutics and strong signs of clinical benefit using genome editing. But major challenges remain. In this special plenary roundtable, three established pioneers of genomic medicine – David Haussler, Stephen Kingsmore, and Liz Worthey – offer their insights on the extraordinary advances in genomic medicine over the past 1-2 decades and share their hopes and concerns for the future of our field.

Moderator: Kevin Davies, PhD, Executive Editor, The CRISPR Journal, Mary Ann Liebert, Inc.

Panelists: Stephen Kingsmore, MD, DSc, President/CEO, Rady Children’s Institute for Genomic Medicine

David Haussler, PhD, Investigator, Howard Hughes Medical Institute; Distinguished Professor, Biomolecular Engineering, University of California, Santa Cruz; Scientific Director, UC Santa Cruz Genomics Institute; Scientific Co-Director, California Institute for Quantitative Biosciences (QB3)

Elizabeth Worthey, PhD, Director, Genomic Medicine, University of Alabama, Birmingham School of Medicine

4:50 Spring Fling Celebration in the Exhibit Hall with Poster Viewing, Speed Networking, Book Signing, and Meetup Group

6:00 End of Day

Wednesday, March 4

6:45 am Registration Open

7:00 BREAKFAST PANEL DISCUSSION: The Time is NOW: Creating Meaningful Change for Women in the Workplace (Sponsorship Opportunity Available)

(please see Women in Science page for details)

Moderator: Robin Toft, Author of WE CAN, The Executive Woman’s Guide to Career Advancement; Founder and Chairman, Toft Group Executive Search

Panelists: Camille Samuels, MBA, Partner, Venrock

Paul Hastings, President and CEO, Nkarta Therapeutics, Inc

Teresa L. Wright, MD, Staff Physician, Medicine, San Francisco Veterans Administration

KEYNOTE SESSION

(please see Keynotes page xxxxxxxxxxxxxfor details)

8:00 Organizer’s Remarks

Mana Chandhok, Conference Producer, Cambridge Healthtech Institute

8:05 Chairperson’s Remarks

Joseph Ferrara, CEO, Boston Healthcare

8:10 Keynote Introduction

Fred Lee, MD, MPH, Head, Health Care, Life Sciences Business Development, AWS Data Exchange, AWS

8:25 KEYNOTE PRESENTATION: The Value and Application of Informatics in Cancer Care Delivery

Debra A. Patt, MD, Vice President, Public Policy & Academic Affairs, Medical Oncologist, Texas Oncology Cancer Center & Editor in Chief, Journal of Clinical Oncology-Clinical Cancer Informatics

8:55 KEYNOTE PANEL DISCUSSION: Pragmatic Use of Informatics in Cancer Care Delivery and Cancer Research: Big Data and AI Take on Cancer

Moderator: Joseph Ferrara, CEO, Boston Healthcare

Panelists: Mark Hulse, Chief Digital Officer, City of Hope

Debra A. Patt, MD, Vice President, Public Policy & Academic Affairs, Medical Oncologist, Texas Oncology Cancer Center & Editor in Chief, Journal of Clinical Oncology-Clinical Cancer Informatics

Kristin Beaumont, PhD, Assistant Professor, Assistant Director of Single Cell Genomics Technology Development Icahn Institute, Dept. of Genetics & Genomic Sciences, Icahn School

Ajay Shah, PhD, Executive Director & Head of IT for Translational Medicine, Bristol-Myers Squibb

Paul A. Rejto, PhD, Vice President, Head of Translational Research, Pfizer Oncology R&D

9:40 Refreshment Break in the Exhibit Hall with Poster Viewing, Speed Networking, Book Signing, and Meetup Group

    AI DRUG DISCOVERY USE CASE

10:40 Chairperson’s Remarks

Faisal Khan, PhD, Executive Director, Advanced Analytics and AI, AstraZeneca

10:45 NEW: On the Road to Genetically Validated Targets in Kidney Diseases: Computational Challenges

Thomas Tibbitts, PhD, Senior Vice President, Computational Discovery, Goldfinch Bio

Focal segmental glomerulosclerosis (FSGS) is scarring of the kidney that can lead to kidney failure. To discover genetic variants associated with FSGS, we built the Kidney Genome Atlas (KGA 1.0), which contains whole genomes (>30X) on 23000 individuals, including 2000 cases of FSGS and other proteinuric disorders. To efficiently process and analyze this large amount of genomic data we have implemented infrastructure and pipelines on AWS and launched a web portal to facilitate target discovery.

BUSINESS STRATEGY FOR PHARMA PIPELINES

Topics to be Discussed:

• Meeting expectations, what is good for both sides
• How we can facilitate the transformation of pharma R&D
• Best practices

Moderator: Annastasiah Mudiwa Mhaka, PhD, Founder and Principal, Mawambo Lifesciences; Co-Founder, Convenor and Former President, Alliance for AI in Healthcare (AAIH)

Panelists:

Joseph Szustakowski, PhD, Vice President of Translational Bioinformatics, Informatics & Predictive Sciences, Bristol-Myers Squibb 

Jonathan Allen, PhD, Computational Scientist, ATOM Consortium

Christopher Willis, PhD, Lead IT Business Partner, Precision Medicine, BMS

Gini Deshpande, PhD, Founder & CEO, NuMedii, Inc.

Given the massive expansion of Data Science and the consequent need for experts in this area across all industries, there is a massive competition to find and source the talent required. How can we identify, recruit and retain the best data scientists? What are the pitfalls and challenges to avoid and success stories we can learn from?

Moderator: Faisal Khan, PhD, Executive Director, Advanced Analytics and AI, AstraZeneca

Panelists: Mustaqhusain Kazi, Head of Personalized Healthcare, Pharma Informatics, Genetech

Zahra ‘Nasim’ Eftekhari, Senior Manager, Head of Applied AI and Data Science, City of Hope

José Duca, PhD, Global Head, Computer-Aided Drug Discovery, Novartis

12:15 pm Session Break

12:50 Enjoy Lunch on Your Own

1:20 Refreshment Break in the Exhibit Hall with Last Chance Poster Viewing, Speed Networking, Book Signing, and Meetup Group

FEATURED SESSION: DATA STRATEGIES FOR GENOMICS

2:00 Chairperson’s Remarks

Geraldine A. Van der Auwera, PhD, Director of Outreach and Communications, Data Sciences Platform, Broad Institute

2:05 Fake It ‘til You Make It (Reproducible): Synthetic Data Resources for Genomics

Geraldine A. Van der Auwera, PhD, Director of Outreach and Communications, Data Sciences Platform, Broad Institute

The computational reproducibility of published biomedical research is limited by data access restrictions, affecting not just researchers who wish to reuse published analysis code, but also tool developers and educators who lack suitable example data for testing and training. We present: 1) a prototype pipeline that wraps established open-source data simulation tools to generate publicly shareable synthetic sequence data at any scale; and 2) a plan to develop community resources.

2:35 Drug Targets with Genomic Support: A Genomics-based Strategic Framework for Improving Target Discovery and Accelerating Drug Development

Justin Wade Davis, PhD, ACOS Research Fellow, Director, Computational Genomics, Genomics Research Center (GRC), AbbVie

Despite strong vetting for disease activity, only 10% of candidate new molecular entities in Ph1 clinical trials are approved. Analyzing historical data, Nelson et al. 2015 concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. We extend this using updated data, test prospectively whether genetic evidence predicts future successes, and introduce statistical models adjusting for target and indication-level properties.

3:05 Close of Conference