Pharmaceutical R&D Informatics

Pharmaceutical R&D departments are at a crossroads – we have more technology and data than ever before, priming us for novel discoveries, yet there are still many challenges informatics strategies must address. The digitalization of the lab is at the forefront, and it necessitates quality data as well as knowledge management strategies, especially in the search for effective, real-world uses of AI and machine learning. We must also address how these new technologies are transforming day-to-day workflow and knowledge exchange, and what change management, investment, and regulatory strategies must be employed to make them successful. The Pharmaceutical R&D Informatics track will explore real-world projects related to digitalization, FAIR data, knowledge management systems, and artificial intelligence development and implementation, and how such initiatives are driving precision medicine.

Tuesday, October 6

PLENARY KEYNOTE PROGRAM

10:00 am

Welcome Remarks

Cindy Crowninshield, Executive Event Director, Cambridge Healthtech Institute
Scott Parker, Director of Product Marketing, Marketing, Sinequa
10:15 am

NIH’s Strategic Vision for Data Science

Susan K. Gregurick, PhD, Associate Director, Data Science (ADDS) and Director, Office of Data Science Strategy (ODSS), National Institutes of Health
Rebecca Baker, PhD, Director, HEAL (Helping to End Addiction Long-term) Initiative, Office of the Director, National Institutes of Health
11:05 am

LIVE Q&A: Session Wrap-Up Panel Discussion

Panel Moderator:
Ari E Berman, PhD, CEO, BioTeam Inc
11:25 am Lunch Break - View Our Virtual Exhibit Hall
11:55 am Recommended Pre-Conference Workshops*
W1: Data Management for Biologics: Registration and Beyond
W2: A Crash Course in AI: 0-60 in Three
W3: Data Science Driving Better Informed Decisions

*Separate registration required. See workshop page for details.

1:55 pm Refresh Break - View Our Virtual Exhibit Hall
2:15 pm Recommended Pre-Conference Workshops*
W4: Digital Biomarkers and Wearables in Pharma R&D and Clinical Trials
W5: AI-Celerating R&D: Foundational Approaches to How Emerging Technologies Can Create Value
W6: Dealing with Instrument Data at Scale: Challenges and Solutions

*Separate registration required. See workshop page for details.

4:15 pm Close of Day

Wednesday, October 7

ENABLING DIGITAL TRANSFORMATION OF PHARMA R&D

9:00 am

Digital Transformation Driving Precision Medicine

Anastasia Christianson, Vice President, R&D Business Technology, Janssen Pharmaceuticals

Digital transformation is still a driving principle in pharma R&D with the ultimate goal being to streamline processes and enable precision medicine. This talk will showcase examples of digital technologies driving transformation and tangible results in R&D.

9:20 am

Enduring Value from Data-Centric Digital Transformation

Dana Vanderwall, PhD, Director, Biology & Preclinical Sciences IT, Research & Development IT, Bristol-Myers Squibb

Companies that have successfully transformed their business demonstrate the necessity of commensurate cultural change. Similarly, our ecosystem must embrace a data-centric design focus to deliver successful digital transformation and enduring value. Without implementing standards to deliver interoperable data with complete, consistent, standard contextual metadata, we will fail to transform the laboratory and data value chain. Continuing to generate data as a by-product of process and software underserves R&D objectives.

FAIR DATA DRIVING DECISION-MAKING

9:40 am

The Essentials of FAIR-ifying Data

Tom Plasterer, PhD, Director, Bioinformatics, Data Science & AI, Biopharmaceutical R&D, AstraZeneca

While the value of FAIR data has been established–as well as the costs of un-FAIR data–adoption lacks easy routes. The Pistoia Alliance FAIR data toolkit and Innovative Medicines Initiative (IMI) FAIRplus Cookbook offer frameworks to start. Key decisions on what to name things (e.g., identifiers) and their semantics (e.g., vocabularies) are critical at journey inception. Once established, FAIR knowledge graphs and FAIR analytic services become enterprise data-centric enablers.

10:00 am Coffee Break - View Our Virtual Exhibit Hall
10:20 am

A Journey to Build an Ecosystem of Data, Technology, and Culture for Insight Generation

Mark McCreary, Biomarker Data Management and Curation Lead, DevSci Informatics, Genentech

We aim to transform drug development and translational sciences by establishing the data and informatics ecosystem. Where do you even start when data are not readily accessible and are constantly evolving? How do you mobilize the organization to change the mindset for data sharing? This talk will share with you the journey we are on to revamp the data management practice and to build the end-to-end engine for FAIRification of our key data assets. We will share the challenges we have overcome and the successes leading to scientific impacts.

10:40 am

Making Drug Discovery Data FAIR: The Yawning Gap between Aspiration and Implementation

Christopher Southan, PhD, Principal Consultant, TW2Informatics

The FAIRification of data is gaining impetus. However, for drug discovery, the envisaged increased flow of structures and bioactivity into major public databases, such as PubChem, has not happened. Reasons will be reviewed, but a key impediment is that even when supplementary data from journal papers is submitted to open repositories, such as figshare, there is neither push nor pull into PubChem. Ways to ameliorate this major bottleneck will be discussed, including bypassing the entombment of chemistry in PDFs.

Andras Stracz, Head Developer, Drug Design Hub Development, ChemAxon

We will introduce ChemAxon’s platform for integration of a variety of data sources and services to augment real-time design. We cover 2 use cases:

1. How MMP analysis supports design out of hERG liability.

2. How a search on >500M molecules, from combined public databases, can be analyzed in seconds.

Ashoka Rajendra, Product Manager, Product, Benchling

High-quality data is a prerequisite for machine learning and high-throughput R&D. A first step is to ensure data is centralized and standardized. Learn how leading companies are using modern informatics to organize and structure R&D data - all the way from results-producing instruments to advanced analysis.

 

11:30 am LIVE Q&A:

Session Wrap-Up Panel Discussion

Panel Moderator:
Tom Plasterer, PhD, Director, Bioinformatics, Data Science & AI, Biopharmaceutical R&D, AstraZeneca
Panelists:
Anastasia Christianson, Vice President, R&D Business Technology, Janssen Pharmaceuticals
Dana Vanderwall, PhD, Director, Biology & Preclinical Sciences IT, Research & Development IT, Bristol-Myers Squibb
Mark McCreary, Biomarker Data Management and Curation Lead, DevSci Informatics, Genentech
Christopher Southan, PhD, Principal Consultant, TW2Informatics
Timothy Gardner, CEO, Riffyn
Ashoka Rajendra, Product Manager, Product, Benchling
Andras Stracz, Head Developer, Drug Design Hub Development, ChemAxon
11:50 am Lunch Break - View Our Virtual Exhibit Hall
11:55 am Interactive Breakout Discussions

Consider joining a breakout discussion group. These are informal, moderated discussions with brainstorming and interactive problem solving, allowing participants from diverse backgrounds to exchange ideas and experiences and develop future collaborations around a focused topic.

Michael Riener, President, RCH Solutions

Join us for a lively discussion among prominent pharma leaders, and learn:

Why, when & how to implement a public Cloud for your computing needs

Challenges and opportunities when setting and managing stakeholder expectations

Critical keys to success to realize the best outcomes

To learn more about RCH Solutions, visit our Virtual Booth

Joe Donahue, Managing Director, Life Sciences, Accenture

Hosted by Joe Donahue, Managing Director, Life Sciences, Accenture

 

Participants include: 

Andreas Matern, Head of Digital Translational Medicine, Sanofi

John Quackenbush, Professor of Computational Biology and Bioinformatics; Harvard T.H. Chan School of Public Health

Seungtaek Lee, VP, Strategic Partnerships and AI RWE Head of CoE; ConcertAI

Preston Keller, PhD, MBA, President & CCO, PercayAI

Philip Payne, PhD, Becker Professor and Chief Data Scientist, Washington University in St. Louis

 

Jeff Evernham, VP of Customer Solutions, Consulting, Sinequa

Most large scale analysis of clinical trial data only leverages part of the picture, ignoring unstructured data and limiting findability across all the information collected throughout multiple disparate data sources.  This roundtable will discuss leveraging a cognitive platform to combine all data from multiple sources into one unified view using a single entry point to the data.

 

Sasha Paegle, Life Science Business Development, Dell Technologies

Evaluating, optimizing and benchmarking of next generation sequencing (NGS) methods are essential for clinical, commercial and academic NGS pipelines. Optimizations for speed and accuracy often require making trade-offs relative to other constraints. Join this roundtable to discuss benchmarking strategies, trade-offs, and the value of benchmarking genomics tools and applications. 

Timothy Gardner, CEO, Riffyn

Faster therapeutic development demands a non-trivial array of software capabilities, including data automation, system flexibility, ease of use, global collaboration, and analytics-ready data. Nexus, the world’s first process data system, meets this need — supporting dynamic, modular biologics development and tech transfer activities with clean, connected data and real-time analytics

PLENARY KEYNOTE PROGRAM

Michael Schwartz, Head, Product Marketing, Marketing, Benchling

The life science industry has forged ahead with a new generation of therapeutics. A new R&D paradigm is required to develop scientific platforms, manage data complexity, and orchestrate progress across specialized teams. Digital solutions and data ecosystems are at the heart of this, but require both structure and adaptability to thrive in the modern life science R&D environment.

12:30 pm KEYNOTE PRESENTATION & PANEL DISCUSSION:

Game On: How AI, Citizen Science, and Human Computation Are Facilitating the Next Leap Forward

Allison Proffitt, Editorial Director, Bio-IT World

While the precision medicine movement augurs for better outcomes through targeted prevention and intervention, those ambitions entail a bold new set of data challenges. Various panomic and traditional data streams must be integrated if we are to develop a comprehensive basis for individualized care. However, deriving actionable information requires complex predictive models that depend on the acquisition and integration of patient data on a massive scale. This picture is further complicated by new data streams emerging from quantified self-tracking and health social networks, both of which are driven by experimentation-feedback loops. Tackling these issues may seem insurmountable, but recent advancements in human/AI partnerships and crowdsourcing science adds a new set of capabilities to our analytic toolkit. This session describes recent work in online collective systems that combine human and machine-based information processing to solve biomedical data problems that have been otherwise intractable, and an information processing ecosystem emerging from this work that could transform the landscape of precision medicine for all stakeholders. Pietro will open with a framing talk, followed by short presentations from each panelist, ending with a moderated Q&A discussion by Allison with speakers and attendees. 

Panelists:
Seth Cooper, PhD, Assistant Professor, Khoury College of Computer Sciences, Northeastern University
Lee Lancashire, PhD, CIO, Cohen Veterans Bioscience
Pietro Michelucci, PhD, Director, Human Computation Institute
Jérôme Waldispühl, PhD, Associate Professor, School of Computer Science, McGill University
1:55 pm Refresh Break - View Our Virtual Exhibit Hall

KNOWLEDGE MANAGEMENT AND EXPLORATION TOOLS FOR DRUG DISCOVERY AND DEVELOPMENT

2:10 pm

How to Hold on to Your Knowledge in an Agile World

Etzard Stolte, PhD, Global Head, Knowledge Management PTD, F. Hoffmann-La Roche

As pharma is embracing digital and agile, new challenges for the retention and sharing of information are emerging. While the information standards of a validated environment remain, ad hoc processes and distributed cloud solutions are creating new islands of knowledge. In this presentation, I will present a knowledge strategy based on automated discovery and integration for a development department of several thousand scientists at Roche.

2:30 pm

Powering Question-Driven Problem Solving to Improve the Chances of Finding New Medicines

Samiul Hasan, PhD, Director, Scientific Analytics and Visualization, Data and Computational Sciences, GlaxoSmithKline

Making true “molecule”-“mechanism”-“observation” relationship connections is a time-consuming, iterative and laborious process. In addition, it is very easy to miss critical information that affects key decisions or helps make plausible scientific connections. The current practice for deciphering such relationships frequently involves subject matter experts (SMEs) requesting resources from already constrained data science departments to refine and redo highly similar ad hoc searches. The result of this is impairment of both the pace and quality of scientific reviews. In this presentation, I show how semantic integration can be made to ultimately become part of an integrated learning framework for more informed scientific decision-making. I will take the audience through our pilot journey and highlight practical learnings that should inform subsequent endeavors.

2:50 pm Refresh Break - View Our Virtual Exhibit Hall
3:10 pm

Computational Efforts on Drug Repurposing for Rare Diseases

Bin Li, PhD, Director, Computational Biology & Translational Medicine, Data Science Institute, Millennium, The Takeda Oncology Co.

We conducted in silico screens trying to repurpose >100 compounds for ~4000 rare disease indications. Various data types were utilized (protein-protein interaction network, pathways, disease-driven genes, competitive intelligence, etc.), and different computational methods were implemented and evaluated. Some biologically interesting drug/disease pairs were observed.

Jens Hoefkens, Ph.D., Industry Principal Director, Accenture

The drug development value chain starts with target selection – missteps at this stage result in costly failures downstream.  We’ll discuss work with industry leaders on an AI-assisted approach that brings together patient genomics and real-world data with information from clinical trials and drug approvals to prioritize and predict high-value targets.

4:00 pm LIVE Q&A:

Session Wrap-Up Panel Discussion

Panel Moderator:
Etzard Stolte, PhD, Global Head, Knowledge Management PTD, F. Hoffmann-La Roche
Panelists:
Samiul Hasan, PhD, Director, Scientific Analytics and Visualization, Data and Computational Sciences, GlaxoSmithKline
Bin Li, PhD, Director, Computational Biology & Translational Medicine, Data Science Institute, Millennium, The Takeda Oncology Co.
Jens Hoefkens, Ph.D., Industry Principal Director, Accenture
4:20 pm Bio-IT Connects - View Our Virtual Exhibit Hall
5:00 pm Close of Day

Thursday, October 8

USING AI TO PROPEL THE DRUG DISCOVERY AND DEVELOPMENT PIPELINE

9:00 am

Real-World Data and AI Hype: Stimulating and Supporting Each Other

Dorothee Bartels, PhD, Global Head of RWE, UCB

The real world data hype caused high expectations, including RCTs might only play a minor role in future drug development. But  they are rather complementary to RCT data and cannot replace them. Artificial intelligence may change  drug development and time to market significantly, but will not replace past knowledge and experience. Real World Evidence generation can be enhanced by AI and is key for public health.

9:20 am

New Methods to Integrate and Leverage Genomic and Clinical Data to Improve Rare Disease Diagnostics

Tom Defay, Deputy Head, Diagnostics, Alexion Pharmaceuticals

Rare disease patients suffer too often from long diagnostic delays and misidentified diseases. This creates a significant burden, not just for patients, but for healthcare systems. We present in this talk examples of instances where we have collaborated with researchers and hospital systems to develop novel approaches for rare disease patient identification using tools like genomics, machine learning, and NLP.

9:40 am Coffee Break - View Our Virtual Exhibit Hall

USING AI TO PROPEL THE DRUG DISCOVERY AND DEVELOPMENT PIPELINE (CONT.)

10:00 am

Machine-Learned Molecular Models for Protein Structure, Networks, and Design

Mohammed AlQuraishi, PhD, Assistant Professor, Systems Biology, Columbia University
10:20 am

ChemDataExplorer: A Data Warehouse, Visualization and Machine Learning Platform for Small Molecules

Peter V. Henstock, PhD, Machine Learning & AI Lead, Software Engineering & Statistics & Visualization, Pfizer Inc.

 

This presentation describes a novel data warehouse solution that captures and integrates 8 major public datasets of small molecule data.  With a pharmacology focus, the data are available for search, visualization of compound space, and machine learning.  


Jelena Dowey, Gabriel Sanna, Max Shirvanifar, Sishir Yeety, Lu Wang, Nicolas Tejera, Nandini Patel, Ravi Shanker, Peter V. Henstock
Harvard Extension School and Pfizer Inc.
Jane Reed, Director, Life Science, Linguamatics, an IQVIA Company

Pharma teams need insights across drug development/commercialization from multiple data sources. NLP transforms unstructured RWD sources, like patient forums, social media, medical records, into structured data. Insights Hub dashboards and search portals enable users to navigate the knowledge landscape. We will present use cases from disease understanding to medical affairs.

Raveen Sharma, Managing Director, Life Sciences and Healthcare, Deloitte Consulting LLP

Transformational change in R&D productivity is required to reverse declining trends in R&D returns across the biopharma industry. Efficiently generating insights and evidence from research, clinical trials, and real world data has become mission critical and plays a central role in this transformation. We will discuss trends, technologies, and experiences.

11:10 am LIVE Q&A:

Session Wrap-Up Panel Discussion

Panel Moderator:
Peter V. Henstock, PhD, Machine Learning & AI Lead, Software Engineering & Statistics & Visualization, Pfizer Inc.
Panelists:
Dorothee Bartels, PhD, Global Head of RWE, UCB
Tom Defay, Deputy Head, Diagnostics, Alexion Pharmaceuticals
Mohammed AlQuraishi, PhD, Assistant Professor, Systems Biology, Columbia University
Philip R.O. Payne, PhD, FACMI, FAMIA, Becker Professor and Chief Data Scientist, Washington University in St. Louis, School of Medicine
Raveen Sharma, Managing Director, Life Sciences and Healthcare, Deloitte Consulting LLP
Jane Reed, Director, Life Science, Linguamatics, an IQVIA Company
Lu Wang, Founder and CEO, Komodotech
11:30 am Lunch Break - View Our Virtual Exhibit Hall
11:35 am Interactive Breakout Discussions

Consider joining a breakout discussion group. These are informal, moderated discussions with brainstorming and interactive problem solving, allowing participants from diverse backgrounds to exchange ideas and experiences and develop future collaborations around a focused topic.

Timothy Gardner, CEO, Riffyn, Inc.

How do you use data / digitization today to drive scientific discovery / product development?

What are you greatest scientific pain points / gaps that are not being met by digitization?

What kinds of outcomes do you believe digital tools could help you achieve?

 

Scott Jeschonek, Principal Program Manager, Microsoft Azure

Welcome to this discussion group on the growth of demand for HPC in scientific research. We are looking forward to a lively forum. We'll start by looking at three related topics:

- What events trigger demand in your organization? How has the current pandemic impacted resources?

- What could make scale and collaboration more accessible to more researchers?

- Share a recent experience of shifting workloads to manage HPC capacity.

Greg DiFraia, General Manager, Americas, Executive Team, Scality
Shailesh Manjrekar, Head of AI and Strategic Alliances, Executive Team, WekaIO

In this session we’ll discuss how to provide researchers with performance and scale in genomics & research analytics, to drive results at a price point that’s economically viable on public & private cloud.

11:35 am

Breakout: NGS Pipeline Optimizations

Tristan J Lubinski, PhD, Sr Scientist, Next Generation Sequencing Informatics, AstraZeneca Pharmaceuticals; Co-organizer, Boston Computational Biology and Bioinformatics (BCBB)
Howard Marks, Technologist Extraordinary and Plenipotentiary, VAST Data

Storage solutions we’ve been using force bioinformaticists to make trade-offs between the capacity and low-cost of disk and the performance of flash. This results in complex tiering configurations that only deliver performance for a small slice of the data. In this session, we will review how advancements in technology enable VAST Data to revolutionize the cost of all-flash and allows bioinformatists faster analysis across larger datasets for deeper insights.

PLENARY KEYNOTE PROGRAM

12:00 pm

Welcome Remarks

Cindy Crowninshield, Executive Event Director, Cambridge Healthtech Institute
Juergen A. Klenk, PhD, Principal, Deloitte Consulting LLP
12:15 pm

Toward Preventive Genomics: Lessons from MedSeq and BabySeq

Robert C. Green, Professor & Director, G2P Research, Genetics & Medicine, Brigham & Womens Hospital
12:40 pm

AI in Pharma: Where We Are Today and How We Will Succeed in the Future

Natalija Z. Jovanovic, PhD, Chief Digital Officer, Sanofi
1:05 pm

LIVE Q&A: Session Wrap-Up Panel Discussion

Panel Moderator:
Vivien R. Bonazzi, PhD, Managing Director & Chief Biomedical Data Scientist, Deloitte Consulting LLP
Juergen A. Klenk, PhD, Principal, Deloitte Consulting LLP
1:25 pm Happy Hour - View Our Virtual Exhibit Hall
2:00 pm Close of Conference





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