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!

As the adoption of AI is flourishing in the life sciences, researcher are left wondering what specific applications can augment human intelligence in the most useful way in the next decade. Taking a holistic view of both commercial and academic progress allows for an honest assessment of the tools available today.  Join us at Emerging Technologies for Life Sciences as we showcase cutting edge research that helps to improve contextual data, real time analysis, and more to promote the digital transformation of this field.

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

(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 ProffittAllison 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

Michelucci_PietroPietro Michelucci, PhD, Director, Human Computation Institute


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

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


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


Krotman_DevinDevin Krotman, Director, IBM Watson AI XPRIZE


Mandavi_VaniVani Mandava, Director, Data Science Outreach, Microsoft Research


Michelucci_PietroPietro Michelucci, PhD, Director, Human Computation Institute


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


 

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

Fred Lee, MD, MPH, Head, 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

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

Lee-SunInSu-In Lee,PhD, 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 The InnerEye Project: Medical Imaging AI to Empower Clinicians

Nori_AdityaAditya 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

Oermann_EricEric 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 Talk Title to be Announced

Thomas Bengtsson, Global Head, PHC Imaging, Genentech

4:25 Refreshment Break and Transition to Plenary Keynote


PLENARY KEYNOTE SESSION

(please see Keynote pages 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 Chairperson’s Remarks

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

8:10 Keynote Sponsor Introduction

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

 

 

 

 


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

Rajasimhja_HarshaHarsha Rajasimha, MS, PhD, Founder, Jeeva Informatics Solutions, Inc.; Founder and Chairman, IndoUSrare; 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

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


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


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


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


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


 

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

Mirhaji_ParsaParsa 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

Greene_CaseyCasey 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/.

DATA MODELS

11:45 Data-Driven Modeling Platform

Corrado Priami, PhD, Founder and CSO, COSBI

A user-friendly graphical platform is presented to integrate different data types in a single framework and to abstract them into actionable models. The platform speeds up research and development process and promotes data sharing.

12:15 pm Session Break

CAS_New 12:20 BIO-IT WORLD WEST CO-LUNCHEON PRESENTATION I: Describing Chemistry to Algorithms: Why Scientific Expertise Improves Accuracy

Lee_AlphaAlpha Lee, PhD, Doctor, Physics, University of Cambridge


McBride_MatthewMatthew McBride, MS, Director, Science IP, CAS

If a picture is worth a thousand words, then a chemical structure is worth thousands of features.  Join Dr. Alpha Lee from the University of Cambridge to see how impactful descriptors are on predictions.  If your AI initiatives aren’t meeting expectations, see how better representations of chemistry structures improve algorithm performance.  CAS descriptors are derived from centuries of scientific knowledge and are proven to improve AI accuracy.

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

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.

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


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


Haussler_DavidDavid 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)


Worthey_LizElizabeth 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

 

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)

(please see Women in Science page for details)

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


Samuels_CamillePanelists: Camille Samuels, MBA, Partner, Venrock


Hastings_PaulPaul Hastings, President and CEO, Nkarta Therapeutics, Inc


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


alice-zhengAlice Zheng, MD, MPH, MBA, Engagement Manager and Women’s Health Practice Leader, Pharmaceuticals and Medical Device and Global Public Health Practices, McKinsey & Company


KEYNOTE SESSION

(please see Keynotes page for details)

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 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

Patt_DebraDebra 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)

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

IMAGING and  QUANTUM COMPUTING

10:40 Chairperson’s Remarks

Carl Dukatz, Digital Tech Arch Principal Director, Accenture

 

10:45 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.

11:15 Presentation to be Announced

11:45 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.

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


Martin_EricPanelists: Brian Martin, Head of AI in R&D Information Research, Senior Principal Data Scientist, AbbVie


Kam Chana, PhD, Director, Computational Platforms, Merck

Additional Panelists to be Announced

 

12:45 pm 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

VanderAuwera_GeraldineGeraldine 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

Defay_TomTom 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: 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.

 

3:35 Close of Conference