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.

Bio-IT World WEST is excited to return to San Francisco in 2020 with an expanded educational and networking program that promises to build on the success of our Boston-based 19th Annual Bio-IT World Conference & Expo. For the past 19 years, Bio-IT World Conference & Expo has established itself as a premier event focused on the innovative IT and informatics applications and enabling technologies that are driving the future of precision medicine. Bio-IT World Conference & Expo highlights the new frontiers in drug discovery & development, biomedical research, and clinical and healthcare initiatives made possible by these cutting-edge technologies. Join us at Bio-IT World WEST with an entirely new audience as we explore the Digitization of Pharma R&D, AI-Enabled Drug Discovery and Development, Emerging Technologies for Life Sciences, and Software Tools, Services, and Applications.

Final Agenda

Sunday, March 1

2:00 - 5:00 pm Afternoon Short Courses*

*Separate registration required

5:30 - 8:30 Dinner Short Courses*

*Separate registration required

Monday, March 2

8:00 - 11:00 am Morning Short Courses*

*Separate registration required

10:30 Conference Program Registration Open

KEYNOTE SESSION

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 Sponsor Introduction (Sponsorship Opportunity Available)


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

Pietro Michelucci, PhD, Director, Human Computation Institute

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

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, Global Learning XPRIZE and 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 (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

2:05 Session Break

INTERPRETABLE MACHINE LEARNING TECHNIQUES

2:20 Chairperson’s Remarks

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

2:25 Explainable Artificial Intelligence in Precision Medicine

Su-In Lee, Associate Professor, Paul G. Allen School of Computer Science & Engineering, University of Washington

I will briefly describe my group’s efforts to develop interpretable ML techniques for varied biological and medical applications, including treating cancer based on a patient’s own molecular profile, identifying therapeutic targets for Alzheimer’s, predicting kidney diseases, preventing complications during surgery, enabling pre-hospital diagnoses for trauma patients, and improving our understanding of pan-cancer biology and genome biology. My talk will focus in greater detail on: MERGE, which uses ML to identify molecular markers for chemotherapy drugs for acute myeloid leukemia in collaboration with UW medicine.

COMPUTER VISION APPLICATIONS FOR LIFE SCIENCE

2:55 ML-Based Productivity Tools for Cancer Treatment: The InnerEye Project

Aditya Nori, PhD, Healthcare Intelligence Lead, Senior Principal Researcher, Microsoft Research

Project InnerEye develops machine learning techniques for the automatic delineation of tumors as well as healthy anatomy in 3D radiological images. The InnerEye technology may enable: 1) extraction of targeted radiomics measurements for quantitative radiology; 2) efficient contouring for radiotherapy planning; and 3) precise surgery planning and navigation. In practice, Project InnerEye turns multi-dimensional radiological images into measuring devices.

3:25 Computer Vision for AI Augmented Medicine

Eric Oermann, MD, Instructor of Neurological Surgery, Mount Sinai Health System; Director, AISINAI

There are numerous applications of computer vision to augmenting medical care. We will discuss the latest advances in computer vision, and how they can be applied to making medical care faster, safer, and smarter.

3:55 Presentation to be Announced

4:25 Refreshment Break and Transition to Plenary Keynote


PLENARY KEYNOTE SESSION

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

8:00 Organizer’s Remarks

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

8:05 Chairperson’s Remarks

Sudeep Basu, PhD, Practice Leader, TechVision-Innovation Services, Frost & Sullivan

8:10 Keynote Sponsor Introduction (Sponsorship Opportunity Available)


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

Harsha K. Rajasimha, MS, PhD, Founder, Jeeva Informatics Solutions, Inc.; Founder, Organization for Rare Diseases India–USA (ORDIUSA); Co-Director, Rare Diseases Systems Biology Initiative, George Mason University

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

Moderator: Sudeep Basu, PhD, Practice Leader, TechVision-Innovation Services, Frost & Sullivan

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

Annastasiah Mhaka, PhD, President, The Alliance for Artificial Intelligence in Healthcare (AAIH)

Harsha K. Rajasimha, MS, PhD, Founder, Jeeva Informatics Solutions, Inc.; Founder, Organization for Rare Diseases India–USA (ORDIUSA); Co-Director, Rare Diseases Systems Biology Initiative, George Mason University

Christina Waters, PhD, President, CEO and Founder, RARE Science, Inc.

Additional Panelists to be Announced

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

KNOWLEDGE GRAPH APPLICATIONS

10:40 Chairperson’s Remarks

Casey Greene, PhD, Associate Professor, Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania

10:45 A Patient-Centered Analytic Learning Machine (PALM) for Learning Healthcare Systems

Parsa Mirhaji, MD, PhD, Associate Professor, Systems and Computational Biology, Chief Technology Officer, NY City Data Research Network, Director, Center for Health Data Innovations, Founder, Cognome, Inc.

PALM is a real-time system designed to scale advanced analytics and promote digital transformation of healthcare through analytically driven clinical decision support, patient experience, automation of operational processes and administrative support systems. PALM scales knowledge graphs to assimilate data from virtually any source and modality, and applies an ensemble of AI/ML/DL algorithms to generate predictive and prescriptive models to ultimately automate and drive patient care in complex healthcare systems environments.

11:15 Search Over Knowledge Graphs Predicts Cellular Mechanisms Underlying Statistical Associations

Casey Greene, PhD, Associate Professor, Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania

Knowledge graphs capture relationships between biomedical entities that can support drug repurposing, gene-disease association discovery, and other use cases. However, unsupervised analysis of paths across multiple node and edge types has been challenging because interpreting multi-edge scores depends significantly on node degrees. We developed an approach that provides well-calibrated estimates of the unexpectedness of a set of edges between a pair of entities given their node types and degrees. This can lay the groundwork for considering drug efficacy in the context of polypharmacology, identifying combinations of therapies that traverse different edges, predicting whether side effects arise from on-target or off-target binding events, and other efforts. Our proof-of-concept server implementing this methodology is available at https://het.io/search/.

11:45 Sponsored Presentation (Opportunity Available)

12:15 pm Session Break

12:20 Bio-IT World WEST Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

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

3:00 Transition to Conference Programs

IMAGING MODALITIES TO SOLVE HEALTHCARE PROBLEMS

3:15 Chairperson’s Remarks

Juan C. Caicedo, PhD, Schmidt Fellow, Principal Investigator, Broad Institute of MIT and Harvard

3:20 Image-Based Profiling for Phenotyping Variants of Unknown Significance

Juan C. Caicedo, PhD, Schmidt Fellow, Principal Investigator, Broad Institute of MIT and Harvard

We use Cell Painting for image-based profiling as a rapid and inexpensive method to systematically map chemical and genetic perturbations. Image-based profiling extracts single-cell measurements from microscopy images to compute signatures of treatments at high-throughput, which encode variations in cell state that are analyzed to identify correlations between treatments. We developed computational tools, including deep learning-based methods, to discern the functional impact of variants of unknown significance in lung cancer.

3:50 AI Approaches to Medical Imaging

Daniel L. Rubin, MD, MS, Professor of Biomedical Data Science, Radiology and Medicine, Director of Biomedical Informatics, Stanford Cancer Institute, Department of Biomedical Data Science, Stanford University

This talk will address several major challenges to developing robust and clinically useful AI models in medicine and some exciting frontiers to tackling them, specifically: 1) application for AI methods in making clinical predictions; 2) ways to leverage the large amounts of unlabeled data to build AI models using weak learning methods on text; and 3) federated computational methods to create AI models from multi-institutional data without data sharing.

4:20 Sponsored Presentation (Opportunity Available)

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

6:00 End of Day

6:30 - 9:30 Dinner Short Courses*

*Separate registration required

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)

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

KEYNOTE SESSION

8:00 Organizer’s Remarks

Edel O’Regan, PhD, Vice President, Production, Cambridge Healthtech Institute

8:05 Chairperson’s Remarks

Joseph Ferrara, CEO, Boston Healthcare

8:10 Keynote Sponsor Introduction (Sponsorship Opportunity Available)


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

Nicholas Schork, PhD, Deputy Director of Quantitative Sciences, Distinguished Professor of Quantitative Medicine, The Translational Genomics Research Institute (TGen)

Robert P. Sebra, PhD, Associate Professor, Director of Technology Development & Genomics Core Facility, Icahn Institute, Icahn School of Medicine, Mount Sinai

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

FUTURE APPLICATIONS: QUANTUM COMPUTING AND BLOCKCHAIN

10:40 Chairperson’s Remarks

Carl Dukatz, Digital Tech Arch Principal Director, Accenture

10:45 PANEL DISCUSSION: Quantum Computing in Life Sciences - Research and Applications

The tiny particles that make up our universe behave very differently at the sub-atomic scale. Actually, they behave in awesome ways. Companies are building computers that take advantage of these behaviors. This is called quantum computing and a sufficiently powerful quantum computer could change everything. Come learn from a distinguished panel of quantum software and hardware manufacturers about how this technology is changing the bio informatics space.

Moderator: Carl Dukatz, Digital Tech Arch Principal Director, Accenture

11:45 PANEL DISCUSSION: Enabled by Blockchain - Sharing Models

Decentralized privacy-preserving predictive modeling enables multiple institutions to learn a more generalizable model on healthcare or genomic data by sharing the partially trained models instead of patient-level data, while avoiding risks such as single point of control.

Moderator: Lucila Ohno-Machado, MD, PhD, Associate Dean, Informatics and Technology, University of California, San Diego Health

12:45 pm Session Break

12:50 Bio-IT World WEST Luncheon Presentation (Sponsorship Opportunity Available) or 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

Zhaoshi Jiang, PhD, Executive Director of Bioinformatics & Clinical Data Sciences, Gilead Sciences

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 Progress in Diagnosing Rare Disease Patients Leveraging NLP and Genomic Sequencing

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

Diagnosing patients with rare disease is challenging. Whole exome and whole genome sequencing have improved our diagnostic abilities but can still fall short due to our lack of understanding of which mutations are most likely to be the cause of disease. By combining phenotypic information automatically extracted from the patient’s EMR with a patient’s genome sequence, we have developed a system for prioritizing which mutations may be most significant and proposing possible diagnoses. Advances on this approach will be discussed.

3:05 Drug Targets with Genomic Support

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

3:35 Close of Conference