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!
Data is being constantly produced, in many disparate forms, but can easily become silo’d and inaccessible. Join us at Software Tools, Services, and Applications, part of Bio-IT World West and the Molecular Medicine Tri-conference
as we discuss best practices to store, analyze and share biomedical data within and outside of your company.
Final Agenda
Day 1 | Day 2 | Day 3 | Download Brochure
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
(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, 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
2:20 Chairperson’s Remarks
Matthew Trunnell, Vice President and Chief Data Officer Director, Hutch Data Commonwealth
2:25 Establishing a Regional Data Commons
Matthew Trunnell, Vice President and Chief Data Officer Director, Hutch Data Commonwealth
The focus of the commons will be enabling discovery of and access to life sciences research data and healthcare data to advance research and innovation. That is, the principal initial stakeholders are life & health sciences researchers
and technology organizations looking to innovate in this space. We currently have three workstreams: one around data discovery; one around privacy-preserving technologies (differential privacy, synthetic data, etc.) to facilitate access
to clinical data; and a third around governance focused on streamlining the process of establishing data use agreements.
2:55 Turning WGS Genetic Testing into a Dialogue between Physicians and Labs with GenomeDiver
Christian Stolte, Consultant, Icahn School of Medicine, Mt. Sinai
Developed as part of the NYCKidSeq project, GenomeDiver fosters a dialogue between the clinician and genetic testing lab. The software leverages the physician’s knowledge of their patient by asking them to provide additional information
to the lab, which then forms the basis for reanalysis. It delivers understandable information about mutations in the entire genome, using knowledge about functional variants coming from an increasing number of public sources, in particular
the GTEx project.
3:25 NEW: Using Modern Frameworks to Process Genomic Data at Scale
Rajesh Mikkilineni, Lead Data Engineer, Data Engineering & Artificial Intelligence, Takeda
Using a generic framework like Hail and a scalable data procession framework like Apache Spark to processing big genetic data set to power scientific analysis. These frameworks enable us to perform quality control at sample and variant level,
apply VEP annotation, and run PheWas and other statistical analyses on genetics data at scale.
Presentation delivered via a live, interactive video conferencing platform.
3:55 Refreshment Break and Transition to Plenary Keynote
(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
Day 1 | Day 2 | Day 3 | Download Brochure
Tuesday, March 3
7:30 am Registration Open and Morning Coffee
(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
10:40 Chairperson’s Remarks
Ryan Leung, Vice President, Strategy & Corporate Development, Research to the People
10:45 Rare Diseases: Starting at the Beginning
Michael Liebman, PhD, Managing Director, IPQ Analytics, LLC
Rare diseases, typically pediatric, are notoriously heterogeneous; they are difficult to diagnose and manage except in limited cases. We are establishing a “knowledge network” involving clinicians and researchers, patients and
families, and implementing it within a platform that looks at the fetus and the effects of maternal lifestyle, environment and clinical history on the evolving stages of organ system development to evaluate where and how risk may develop
for (rare) diseases. This involves an international collaboration and is targeting the identification of biomarkers and behaviors that indicate risk and may enable early detection and even prevention/mitigation. The platform initially
examines lung development and disease risk, e.g., ARD and BPD, and will enable integration of existing studies and extension to other organ systems.
11:15 Accelerating Research in Rare Disease through Patient-Partnered Collaborations
Ryan Leung, Vice President, Strategy & Corporate Development, Research to the People
Patient-centricity is becoming increasingly important in all areas of healthcare, but this is particularly the case for rare diseases. With so few patients, it is critical that we make the most out of every patients' story and experience,
engaging them at every point of research, development, care, and treatment. At Research to the People, we partner with patients directly to help them access and understand their health data. Leveraging advances in -omics, bioinformatics,
deep learning and cloud computing, alongside a powerfully diverse community of physicians, scientists and patient advocates, we've created a uniquely collaborative platform for open-source rare disease research. With 5 successful collaborations
to date, we're incredibly excited by the future of patient-partnered healthcare.
11:45 Strategies to Study Rare Diseases with “Big Data”
Jaclyn N.
Taroni, PhD, Principal Data Scientist, Childhood Cancer Data Lab, Alex’s
Lemonade Stand Foundation
We sometimes speak of “big data” in biology. In most cases, these data are wide, and have many more features than examples. This is particularly pronounced in the case of rare diseases, where we may have tens of samples but tens
of thousands of measurements. I’ll discuss how we can use compendia of data with many training examples as a training dataset and then transfer the results of those analyses to rare disease datasets where the number of samples is
particularly limited. I’ll also discuss how this feature of data, even outside of rare diseases, affects deep learning methods in this domain.
12:15 pm Session Break
12:20 BIO-IT WORLD WEST CO-LUNCHEON PRESENTATION I: Describing Chemistry to Algorithms: Why Scientific Expertise Improves Accuracy
Alpha Lee, PhD, Doctor, Physics, University of Cambridge
Matthew 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: Towards the Digital Lab
Paul Denny Gouldson, Chief Digital Officer, Digital Solutions, Zifo RnD Solutions
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
(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
Day 1 | Day 2 | Day 3 | Download Brochure
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)
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
(please see Keynotes page for 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
10:40 Chairperson’s Remarks
Shanrong Zhao, PhD, Director, Computational Biology, Pfizer
10:45 From Development to Deployment: Lessons Learned from Application of Machine Learning in Oncology Decision Support
Zahra ‘Nasim’ Eftekhari, Senior Manager, Head of Applied AI and Data Science, City of Hope
11:15 Leverage Sage Data Lake for Translational Medicine Biomarker Analytics
Ying (Sherry) Li, PhD, Lead IT Business Partner – Precision Medicine, Translational Medicine IT, Bristol-Myers Squibb
Clinical biomarkers have shown great promise to improve drug development efficiency and to understand target engagement, drug efficacy, as well as clinical endpoint prediction. At Bristol-Myers Squibb (BMS), biomarker research is a routine
practice for our ongoing clinical trials. To make data findable, accessible, interpretable and reusable (FAIR), we process and manage hundreds of BMS clinical trials’ biomarker data into our Sage Data Lake and integrate that with
clinical information from Oracle Clinical and Rave databases. This information is fed into the SignalsTranslational (Signals) application (co-developed by BMS and Perkin Elmer) as well as Sage Clinical database. Using Sage Signals, our
scientists can track biomarker assays, analyze biomarker data cross studies/diseases, drill into platform specific concerns, which help clinical programs to make informed decisions. We will share some use cases in our presentation and
discuss how Sage Data Lake helps our biomarker research.
11:45 PANEL DISCUSSION: Cutting-Edge Algorithms for scRNAseq
Moderator: Shanrong Zhao, PhD, Director, Computational Biology, Pfizer
Panelists: Rob Patro, PhD, Assistant Professor, Department of Computer Science, Center for Bioinformatics and Computational Biology, University of Maryland
Jeffrey Rosenfeld, PhD, Manager, Biomedical Informatics Shared Resource, Assistant Professor of Pathology and Laboratory Medicine, Rutgers Cancer Institute of New Jersey
12:45 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
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
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