Track 9: Pharmaceutical R&D Informatics

Drive Precision Medicine through the Digitalization of Pharma R&D

May 4 - 5, 2022 ALL TIMES EDT

The fact that the pharma industry generates more data than ever before and needs an effective way to analyze and understand it is not new; however, the past two years have brought about an unprecedented sense of urgency around the need to generate, organize, analyze, and act upon data in order to push through new products at record-breaking speed or while working outside of a traditional office or clinical trial setting. The Pharmaceutical R&D Informatics track will explore challenges and solutions around developing and scaling key infrastructure, managing data generated via new technologies and services, and creating an effective informatics ecosystem while meeting scientific, business, and regulatory demands. We’ll explore the continued role FAIR data has in successful projects, strategies around developing analytics and visualization tools, and novel approaches to utilizing AI, NLP, and machine learning, and how these initiatives are driving innovation in R&D.

Tuesday, May 3

7:00 am Registration Open (Plaza Level Lobby)
8:00 am Recommended Pre-Conference Workshops and Symposium*

On Tuesday, May 3, 2022 Cambridge Healthtech Institute is pleased to offer nine pre-conference workshops scheduled across three time slots (8:00-10:00 am, 10:30 am-12:30 pm, and 1:45-3:45 pm) and a Symposium from 8:25 am-3:45 pm. All are designed to be instructional, interactive and provide in-depth information on a specific topic. They allow for one-on-one interaction and provide a great way to explain more technical aspects that would otherwise not be covered during the main conference tracks that take place Wednesday-Thursday.

*Separate registration required. See Workshop page and Symposium page for details.

3:45 pm Session Break and Transition to Plenary Keynote

PLENARY KEYNOTE LOCATION: 210 (Overflow 208)

PLENARY KEYNOTE PROGRAM

4:00 pm

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
4:05 pm Innovative Practices Award
Mike Tarselli, PhD, Chief Scientific Officer, TetraScience
4:30 pm

Ask What IT Can Do for Bio...and What Bio Can Do for IT

George M. Church, PhD, Robert Winthrop Professor, Genetics, Harvard Medical School

IT for Bio: In May 2021, one haploid human genome (3.055 billion bp) was sequenced completely, but zero diploid. We have 7.7 billion diploid humans yet to be sequenced and correlated with their environments and traits in the Personal Genome Project. Plus, at least one genome from each of over 8.7 million eukaryotic species in the Earth Biogenome project. Plus, monitoring pathogenic and commensal bacteria, allergens, and viruses in the BioWeatherMap. Plus, ancient DNA. We are counting RNA molecules per cell in most (or all) cell types in humans, mice, and many other species throughout development and connectome (with imaging resolution up to 20 nm).   

Bio for IT: Reading and writing DNA has improved exponentially in cost (at least 60 million fold) and is increasingly used for storing non-biological data. The record for editing DNA in vivo is now 24,000 edits per cell and for storing data in vivo is about 1 terabyte per mouse. Enormous chemical and biological 'libraries' can perform 'Natural Computing' for tasks far beyond current von-Neumann silicon and quantum computers. The combination of these – machine learning + megalibraries (ML-ML) is already having commercial impact (e.g. Nabla, Manifold, Dyno, Patch). 

5:45 pm Welcome Reception in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)
7:00 pm Close of Day

Wednesday, May 4

7:00 am Registration Open and Morning Coffee (Plaza Level Lobby)

PLENARY KEYNOTE ROOM LOCATION: 210

PLENARY KEYNOTE PROGRAM

8:00 am

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
Zachary Powers, Chief Information Security Officer, Benchling
8:15 am

Accessing and Securing the Data that Drives Breakthroughs

Allison Proffitt, Editorial Director, Bio-IT World
Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago
Ari E. Berman, PhD, CEO, BioTeam, Inc.
Jonathan C. Silverstein, Chief Research Informatics Officer & Professor, Biomedical Informatics, University of Pittsburgh
Rebecca F. Rosen, PhD, Director, Office of Data Science and Sharing, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health

Life sciences research is generating massive amounts of data that should be accessible to collaborators and colleagues to enable breakthrough discoveries. However, ensuring sensitive data are shared securely in a manner that protects patient privacy and complies with myriad regulations is a daunting task, which often slows the pace of research. Our panel of leading practitioners will share insights on the challenges and best practices of managing protected research data.

9:30 am Coffee Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ROOM LOCATION: 311

SEARCH & ANALYTICS WORKFLOW AND PROCESSES: ACCESSING KNOWLEDGE ACROSS SYSTEMS

10:15 am Organizer's Remarks
Jane Reed, Director, Life Sciences, IQVIA NLP
10:25 am

Activity Graphs to Automate Agile Processes

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

Agile workflows require transparency and easy-to-do sharing of ongoing activities across systems, processes, and departments. In this presentation I will talk about the learnings in a multi-year project to establish digital self-service processes of an analytics-heavy development function. Transparency for digital artefacts scattered across many islands-of-knowledge was achieved through an unusual combination of data insight services: data catalogue, knowledge graph, and Kanban boards.

10:55 am

Climbing the Ladder: The Challenge of Elevating Data to Knowledge and Insight to Impact

Brian Martin, Head of AI, R&D Information Research, Research Fellow, AbbVie, Inc.

While data platforms, data lakes, data swamps, and any other container for data you can think of seem to be the rage, we need to understand how to move upward on the ladder from swimming with data to powering a flight that is impactful on wings of knowledge and insight. In this presentation we’ll talk about mechanisms and techniques to learn, implement, and capture the process of climbing the ladder of inference in a knowledge-driven way to impact the drug discovery process.  We’ll look at examples of how capturing and codifying the process of knowledge extraction at scale allows the development of applications that yield rapid insights and how these tools free our scientists to leverage those insights to impact their work.

11:25 am

Virtual Product Home (VPH) – Holding on to Your Knowledge in an Agile World

Roman Engel, Head Agile Document Flow - "Virtual Product Home", Knowledge Management Expert, F. Hoffmann-La Roche

In an ever-changing IT landscape, it is a challenge to manage the core business knowledge. As systems change, data cannot be migrated/accessed easily, especially when a mix of validated/non-validated/on-premise and cloud systems are involved. How to provide a document management process that is flexible enough to follow the trend of moving data to cloud platforms, reflect organizational changes, and still retain the knowledge from proprietary systems? Roche Technical Development managed to find a structured home for millions of product-relevant documents, no matter where they are stored.

Chris L. Waller, Ph.D., VP, Chief Scientist, Life Sciences, EPAM Systems Inc.

The life sciences industry is undergoing a digital transformation. Or, is it? Much has been written about the promise of data and analytics and the dramatic impact that they would have on the drug discovery process if only we learned to embrace the changes required to effectively realize the potential. In this talk, we will explore the evolution of data, analytics, and some potential future scenarios for the digital transformation to come.

Jane Reed, PhD, Director, Life Sciences, IQVIA NLP

For years, healthcare and life science have been making good use of their structured data. However, the larger part of enterprise data, nearly 80 percent, is unstructured and has been much less accessible, locked in silos across the data ecosystem. Embedding natural language processing (NLP) is the key to unlocking a step change in insight generation, decision making and innovation. In this session, we will discuss how flexible deployment of NLP capabilities can enable organizations to transform processes, increase efficiencies and realize meaningful value. A focus on use cases in drug safety will be presented, showcasing recent developments for cloud-first strategies and end user review.

Jeff Evernham, Vice President Product Strategy, Product Marketing, Sinequa

FAIR is great for data...but what can be done to make text - fundamental research, scientific papers, lab notebooks, clinical results, and everything else that is text - FAIR? Learn how FAIR data principles also apply to unstructured content, using NLP and ML to turn unstructured text into structured information, and how search brings focus to the overwhelming sea of content. That's the key to innovation - connecting the right information with employees to accelerate innovation throughout the enterprise, including scientific discovery, development, clinical trials, or regulatory affairs. With an overview of the principles and several case studies, see how Sinequa is helping propel the life sciences into a new renaissance of information utility. 

12:55 pm Session Break and Transition to Luncheon Presentation
Mike Loos, Global Director, Solution Architecture, TetraScience
Mike Tarselli, Chief Scientific Officer, TetraScience

Scientific data have exploded in volume, complexity, and diversity of sources. Data management and integration solutions have failed to keep pace. To truly unlock the value of your scientific data you need a purpose-built, vendor-agnostic scientific data cloud. Break down silos and enable actionable insights in minutes to hours versus weeks to months by ensuring that your data are FAIR and future-proofed. Join us for an engaging discussion!

1:50 pm Refreshment Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

DATA STRATEGY: DRIVING BETTER DECISION-MAKING AND ORGANIZATION GROWTH

2:35 pm

Chairperson's Remarks

Sean Liu, PhD, Global Head Scientific Assets & Decision Support, R&D IT, Takeda California, Inc.
2:40 pm

How to Effectively Measure the Data Maturity of the Organization and Use the Outcomes to Drive the Data Transformation Journey

Raj Nimmagadda, Global Head, R&D Data Office, R&D Digital and Data Sciences, Sanofi US
Lucas Quarta, Partner & Associate Director, Boston Consulting Group

Organizations are investing and making data a strategic priority for organization growth, productivity, and innovation. In this session we will share how organizations measure data maturity in a standard way. The recent Boston Consulting Group’s (BCG) Data Capability Maturity (DACAMA) survey gives a detailed overview of more than 1,100 companies who participated worldwide, representing nine major industry clusters. These survey results help to validate the prioritization and funding of data initiatives in the organization transformation journey. We will share a use case on how one of the client organizations used these results to prioritize their data capabilities that add value to their organization growth.

3:10 pm

PrecisionFDA – A Collaborative Platform for Analysis of Biological, Clinical, and Chemical Datasets

Yulia Borodina, Chemist, Office of Data, Analytics, and Research, FDA

PrecisionFDA is a secure, cloud-based, high-performance platform implemented by the FDA for collaboration in the areas of biological, clinical and chemical informatics in order to advance precision medicine. It has expanded to assist the broader community of data scientists for analysis of clinical data and to host data-driven competitions that push the limits of tools and algorithms for large-scale data processing. PrecisionFDA has hosted 31 challenges and app-a-thons on topics including AI/ML development to identify COVID-19 risk factors and predict brain cancer patient outcomes and bioinformatics tool development and benchmarking for genetic variant calling and detection of microbial pathogens. The latest application of this platform provides analysis of chemical data sets, as well as benchmarking computational approaches to cheminformatics, drug discovery, and toxicology.

3:40 pm

Harmonizing Bioassay Data Management and Analytics – Takeda's Journey 

Nick Lynch, PhD, Founder & CTO, Curlew Research; Member, FAIRplus Consortium
Sean Liu, PhD, Global Head Scientific Assets & Decision Support, R&D IT, Takeda California, Inc.

We will present the journey at Takeda to transform the bioassay management and analytics platform. The key to the transformation is the development of a bioassay protocol management platform based upon the FAIR data principle.  This platform consists of an augmented BioAssay Ontology (BAO) with Takeda assay annotations, a Takeda minimum requirements for bioassay data annotation, a de facto industry standard of ontology management platform, and a newly developed assay protocol registration system. This platform will harmonize Takeda’s assay protocol registration and assay data management to significantly improve bioassay data’s searchability. 


Scott McClain, Advisory, Health and Life Sciences, SAS Institute, Inc
Douglas Last, Director, Integrated Technologies, BC Platforms AG

Goal of every BioIT attendee? To positively affect the broadest population possible with their therapy. To do so: You need every data form possible-genomic, omic, clinical, and more to form the ‘Whole Patient Digital Journey’. SAS and BCP have a roadmap and solutions including gold standard advanced analysis, ML, and AI tools to streamline regulatory submission work. Join BC Platforms & SAS in discussing a model indication-IBD-to see how to achieve this.

4:40 pm Best of Show Awards Reception in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)
6:00 pm Close of Day

Thursday, May 5

7:30 am Registration Open and Morning Coffee (Plaza Level Lobby)

PLENARY KEYNOTE ROOM LOCATION: 210

PLENARY KEYNOTE PROGRAM

8:00 am

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
Nate Raine, Director Data Custodians, Lifebit
8:15 am

Leveraging Large-Scale Human Data to Advance and Accelerate Drug Discovery

Shankar Subramaniam, PhD, Distinguished Professor of Bioengineering; Professor of Chemistry, Biochemistry and Nanotechnology; Adjunct Professor of Cellular & Molecular Medicine, University of California at San Diego

Advances in genomics technologies have led to generation of massive amounts of human data. This has catalyzed new insights into cellular processes in the normal and disease state and facilitated the search for safe and effective medicines. The UK Biobank, All of US and TopMed initiatives are exemplars of this approach. We highlight examples from our lab where meaningful insights have been obtained advancing our understanding of disease biology and its pharmacological application.

9:30 am Coffee Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ROOM LOCATION: 311

APPLYING AI TO PROPEL THE DRUG DISCOVERY AND DEVELOPMENT PIPELINE

10:15 am Organizer's Remarks
10:20 am

Chairperson's Remarks

Morten Sogaard, Vice President, Target Sciences & Technologies, External Sciences & Innovation, Worldwide R&D, Pfizer Inc.
10:25 am

NBS-WGS: Evaluating  Sensitivity and Specificity

Thomas Defay, Deputy Head, Diagnostic Strategy and Development, 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.

10:55 am

Integrating Genetics and AI for Target Discovery and Validation

Morten Sogaard, Vice President, Target Sciences & Technologies, External Sciences & Innovation, Worldwide R&D, Pfizer Inc.

Human genetics is maturing w/ robust insights from both monogenic rare variant genetics and population genetics converging with the increased impact of population scale WES and WGS data sets. This talk will give an overview of drug discovery approaches and insights from large consortia and how genetic data can be integrated with transcriptomic, proteomic, epigenetic and imaging data to gain detailed mechanistic insights from genetic hits, as well as give some examples of how AI and Machine learning is used in the process.   

11:25 am

Digital Transformation and the Journey of AI-Enablement in Pharma

Reza Olfati-Saber, PhD, Global Head AI & Deep Analytics, Digital & Data Science R&D, Sanofi

We discuss the concept of deep digital transformation in pharma via data- and AI-enablement. Today, we are increasingly capable of integrating multiple modalities of data from clinical to omics and real-word evidence for drug discovery and development. How do we align our AI and digital strategies to produce value with end-to-end AI at scale. We determine ROI of AI in pharma with a real-life R&D use case in digital pathology. 

Raveen Sharma, Managing Director, Deloitte

There is an increasing sense of urgency to implement transformative change within Pharma R&D to improve Real-World outcomes for all patients. The availability of RWD sources continues to grow, but to date, these sources still lack critical information on social determinants of health and behavioral factors at scale that can help improve our understanding of how diversity impacts health care. We will share our experiences in solving for this data gap.

Eric Dawson, Bioinformatics Scientist, AI, Nvidia
Chris Botka, CTO, Healthcare and Life Sciences, Unstructured Data Solutions, Dell Technologies
GPU-based parallel processing of sequencing data is now addressing the myriad bottlenecks that occur across the computational workflow. With performance of up to 60x acceleration for state-of-the-art bioinformatics tools and complete end-to-end workflows in under 25 minutes, larger sequencing projects are becoming less expensive, easier to manage, and generating more useful insights than ever before.  We will discuss an accelerated analysis solution that includes IT infrastructure.

 

12:55 pm Session Break and Transition to Luncheon Presentation
Natalia Vassilieva, Director of Product, Machine Learning, Cerebras Systems
Jon Stevens, AI Language Capability Lead, AbbVie

NLP has tremendous potential for pharmaceutical companies. Domain-specific literature grows daily – scientific articles, clinical reports, healthcare records all in different languages. The domain knowledge hidden in these texts is crucial for biomedical R&D, and the ability to automate extraction of hidden insights is priceless. Extreme-scale NLP models can tackle this task but are expensive and hard to develop. Learn how we build NLP tools to address this biomedical research problem.

1:50 pm Refreshment Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

DATA INTEGRATION, INTEROPERABILTY, AND ADVANCED ANALYTICS

2:35 pm

Chairperson's Remarks

Tom Plasterer, PhD, Director, Bioinformatics, Data Science & AI, Biopharmaceutical R&D, AstraZeneca
2:40 pm

Data Centricity in Translational Medicine

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

Between discovery and clinical research lies translational, which advances science from laboratories to patients. We generate and consume heterogeneous pan-omics preclinical and clinical data from a multitude of internal and external sources, systems, and applications. To reach our goals requires wholistic data interoperability. We have adopted a data-centric approach that enables frictionless reuse of data across our systems, platforms, and applications. Key steps and lessons learned will be described.

3:10 pm

Identification of Genetic and Genomic Features for Exceptional Responders

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

We generated molecular profiling data for cancer exceptional responders from previous clinical trials, then conducted various computational analyses and identified key genetic/genomic features that could help to understand why some cancer patients responded very well for some drugs.


3:40 pm

Application of Artificial Intelligence Platforms to Tame Information Overload: Bridging Knowledge Gaps among Data Scientists, Industry, and Clinicians

Jennifer Ghith, Senior Director, Omnichannel Strategy and Innovations, Global Scientific Communications, Pfizer Oncology

The literature and clinical trial landscape is growing in complexity and with increasing speed. Applying and optimizing artificial intelligence to tame information overload can lead to speedier, more personalized, and advanced searches compared with traditional methods. This session will discuss practical insights into novel platforms as well as provide perspective on the importance of communications and how to bridge discussions amongst healthcare stakeholders.

4:10 pm Close of Conference





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