Data sets are only continuing to grow larger as pharmaceutical companies generate and collect data from a number of sources, including R&D, clinical, translational, genomic, and health records, and these companies must effectively manage, integrate,
and analyze this data to enable more informed decision-making. Furthermore, ensuring this data is of a high quality, consistent, and correct is key to analyzing data and developing actionable insights. Track 10 explores the progress made in the integration
and analysis of complex data sets, generated both internally and externally, and real-world data to transform R&D and drive precision medicine.
Tuesday, May 15
7:00 am Workshop Registration Open (Commonwealth Hall) and Morning Coffee (Foyer)
8:00 – 11:30 Recommended Morning Pre-Conference Workshops*
W1. Data Management for Biologics: Registration and Beyond
12:30 – 4:00 pm Recommended Afternoon Pre-Conference Workshops*
W10. Digital Biomarkers in Pharma R&D: Technical Challenges and Strategies for Advancing Personalized Medicine
* Separate registration required.
2:00 – 6:30 Main Conference Registration Open (Commonwealth Hall)
4:00 PLENARY KEYNOTE SESSION (Amphitheater & Harborview 2)
5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing (Commonwealth Hall)
Wednesday, May 16
7:00 am Registration Open (Commonwealth Hall) and Morning Coffee (Foyer)
8:00 PLENARY KEYNOTE SESSION (Amphitheater & Harborview 2)
9:45 Coffee Break in the Exhibit Hall with Poster Viewing (Commonwealth Hall)
10:50 Chairperson’s Remarks
Yuriy Gankin, Vice President, Chief Life Science Officer, Life Sciences, EPAM Systems
11:00 R&D Informatics: Real-Time Data to Decisions
Anastasia Christianson, Vice President, R&D Operations IT, Oncology IT, Janssen
Pharma R&D needs to “democratize” data to make the right data available to the right audience at the right time to enable informed decision making. This starts with data management, standardization, and integration for easy access,
including easy import into advanced analytics tools and the output to decision support tools.
11:30 Cross-Departmental Collaboration: Driving Pharma R&D Informatics
Joseph Lehar, Executive Director, Computational Biology, Merck Research Labs
This talk discusses cross-team collaboration and an overview of themes in R&D informatics that are driving solutions, drug discovery, and translational research.
12:00 pm Making Heterogeneous Data Accessible and Actionable Using Natural Language Processing and Machine Learning
John Brimacombe, Executive Chairman, Linguamatics
AI in the form of NLP-based text mining has proved its value in life sciences. However, there is potential for much wider impact. In this talk we will show next generation approaches to put the power of NLP into the hands of a broad user base for
scientific knowledge discovery.
12:15 Creating a Connected Ecosystem to Gain Insights Across R&D
Kenneth Walker, PhD, Director, Research, Therapeutic Discovery, Amgen
Streamlining laboratory data exchange from molecular biology to preclinical remains a challenge. If an underlying platform is established to connect instruments and workflows, then it becomes possible to create a connected ecosystem. A connected ecosystem
allows for R&D organizations to share data, make informed decisions, and derive insights.
12:30 Session Break
12:40 Luncheon Presentation I: Unleashing Digital Innovation with a Graph-Based Semantic Layer
Jim LaPointe, Managing Director, Life Sciences & Healthcare, Sales, Cambridge Semantics Inc.
Insightful analyses of internal & external R&D data are helping transform innovative biopharmaceutical companies to maximize the benefit of their therapeutic products. Graph-based, semantics layer driven R&D data lakes, based on the
award winning Anzo Smart Data Lake® platform, rapidly integrates and harmonizes R&D data for immediate exploratory analytics at ‘big data’ scale.
1:10 Luncheon Presentation II: Celgene’s Journey to Become Information-Driven with Cognitive Search
Shefali Pathak, Global Search Service Owner, Search and Business Insights, Celgene
One of the biggest challenges facing pharmaceutical knowledge-workers is the information sprawl and limited availability of tools they can depend on to do their jobs and unify the information landscape. Learn how Celgene tackled these challenges with
Sinequa’s Cognitive Search & Analytics platform to generate new insights from vast scientific research & enterprise data and accelerate business and product innovation.
1:40 Session Break
1:50 Chairperson’s Remarks
Farida Kopti, PhD, Director, Chemistry/Pharmacology/HTS Informatics IT, Merck Research Labs, Merck & Co.
1:55 Next Generation R&D Data Science: The Takeda Data Science Institute
Eric Perakslis, PhD, Senior Vice President and Head, Takeda Data Science Institute; Strategy and Professional Affairs, Takeda Pharmaceuticals
Takeda R&D has developed a fully integrated Data Science Institute comprised of more than 170 diverse data science professionals that manage all aspects of R&D data science and that also serves as a center of excellence for all of Takeda.
Comprised of informaticians, biostatisticians, epidemiologists, medical outcomes experts, data architects and experts in molecular profiling and digital devices this team drives all aspects of modern biopharmaceutical data science for Takeda.
2:25 The Intersection of Data Sciences and Life Sciences in Rare Diseases
John Reynders, Vice President, Data Sciences, Genomics, and Bioinformatics, Alexion Pharmaceuticals, Inc.
Novel and non-obvious applications of data sciences in rare-disease research, strategy, and business development. Multiple case-studies and examples will be shared along with an overview of underlying capabilities and methods.
2:55 A Collaborative Ecosystem Can be the Answer
Misha Kapushesky, PhD, CEO, Genestack
With the cost of sequencing being driven down, the amount of omics data produced is increasing at an unfathomable rate. The challenges now faced by pharmaceutical organisations is not the need for more data, but better integration, management
and visualisation of all their data. The solution? A best of breed omics data ecosystem with flexible and modular architecture.
Co-Presentation: Breaking Down Data Silos and Leveraging External and Unstructured Data to Improve R&D Decisions
Richard Wendell, Founder & CEO, tellic
Ranjith Raghunath, Director, Head, Platform and Tools, Data Center of Excellence, GSK
Derek Marren, Director, Research IT, Biology Systems & Data Integration, Eli Lilly
Topics include: 1) How companies can harness the power of external and unstructured data 2) Engaging the C-suite to break down legacy data and organizational silo's and drive innovation 3) Best practices for how R&D IT can engage the business.
3:25 Refreshment Break in the Exhibit Hall with Poster Viewing (Commonwealth Hall)
4:00 Virtual Product Home
Etzard Stolte, PhD, Global Head Knowledge Management PTD, Pharma Technical Development, F. Hoffmann La Roche
During the last 3 years Roche Pharma Technical Development, a global organization of several thousand researchers, has implemented a one-stop-shop for product data and information. On the one hand, the underlying big data platform leverages
a state-of-the-art analytics to help in automated integration, searching, find an expert, and other functionality. On the other hand, a huge curatorial effort reviewed and migrated millions of documents to improve integration quality.
4:30 Things I Didn’t Know I Needed to Know before Attempting to Implement a Cloud-Based Genomics Data Environment
Enoch S. Huang, PhD, Executive Director, Head of Computational Sciences, Pfizer Worldwide Research and Development
This talk will describe the factors behind a major pharma’s effort to move genomics data processing and analysis to a public cloud environment in collaboration with a leading academic institution. I will discuss unanticipated challenges
associated with implementation, most of which were not technical or funding-related. Nevertheless, I am optimistic about the future of this platform, and will be sharing the reasons why I believe that this strategy will ultimately
produce sustainable solutions for pharma R&D.
4:40 Enabling the Integrated R&D Landscape: The Bayer Pharma R&D Integration Architecture Strategy Martin Sjöholm, Senior Enterprise Architect, Bayer Data is one of the most valuable assets of any R&D organization. The desired future state is to achieve “Data as an Asset”, unlocking the full potential of translating data into insights. Organizational and technical barriers often impede access to data assets, and effective access to them. So how can an R&D organization bridge those challenges? Our claim is that a well-defined strategy accompanied with clear guiding principles are key success criteria. The Bayer Pharma R&D Integration Architecture Strategy has a clear objective: to significantly increase the ability to quickly adapt the business by integrating processes and improving the accessibility of data assets. In this presentation we will share our experience from setting the strategy, and give advice to organizations looking for guidance on how to gradually evolve their ability to integrate processes and data.
5:00 Project Haystack: Universal Access to Corporate Research History
Andras Volford, Product Owner, JChem Engines, ChemAxon LLC
We present the results of an ongoing experimental project helping chemists and biologists discover information they don’t know exists: finding relevant data during design of drug candidates from idea to synthesis, universal,
domain agnostic, simple access to the complete research history, indexing arbitrary amount of data and running structure search in a distributed environment.
5:15 Leveraging Modern Software to Organize, Optimize, and Measure Biologics R&D
Sajith Wickramasekara, CEO & Co-Founder, Benchling
Scaling biologics infrastructure is an enormous challenge faced by R&D IT. Benchling is a biologics-native informatics platform used by over 100,000 scientists to configure biologics workflows and run day-to-day R&D. This presentation
will highlight how Benchling has helped leading biopharma companies organize, optimize, and measure their biologics R&D.
5:30 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing (Commonwealth Hall)
7:00 – 10:00 Bio-IT World After Hours @Lawn on D
Registration Required. Please bring your conference badge, wristband, and photo ID for entry.
Thursday, May 17
7:30 am Registration Open (Commonwealth Hall) and Morning Coffee (Foyer)
8:00 PLENARY KEYNOTE SESSION & Awards program (Amphitheater & Harborview 2)
9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced (Commonwealth Hall)
10:30 Chairperson’s Remarks
Alok Tayi, CEO, TetraScience
10:40 The Promise and the Myth of AI in Transforming Biopharma
John Veytsman, Sr. Business Analyst, R&D Information Technology, Biogen
AI adoption has been mixed across biopharma. AI stands to transform how we work, how we research and how we discover new medicines. However, there is abundant confusion around what is AI, how does it work and what are the best use
cases. Biogen is seeking to implement AI in various forms at points of highest leverage to help improve how we collaborate and how our scientists conduct research. This talk will walk through some of the ways AI has been adopted
at Biogen and hopefully dispel some of the myths of what AI can do for biopharma.
11:10 Discovering Unknown Insights: How We Should Be Recycling Data, Not Just Our Trash
Derek Marren, Director, Research IT, Biology Results, Data Foundations, Laboratory Instrumentation Support Service & Neuroscience, Eli Lilly
As more data is collected and to achieve its maximum potential, there is value in semantically linking and connecting data sources to bring together public and proprietary/private data sources. Experience how Lilly and Open PHACTS
have collaboratively created an innovative solution to ingest data from disparate sources into an ecosystem using graph databases within an open source environment. Once integrated, viewing the behavior in the data will present
unforeseen and tease out new scientifically interesting insights that we desire to develop better understanding and support AI methods... the end game of driving toward better medicine and reuse of data connected and integrated
data, combined with data handling philosophy that all can ascribe to and benefit from academic and pharma scientist alike.
11:40 A Pre-Competitive Technology Platform for Pharma
Joseph Donahue, Managing Director, Accenture
12:10 pm Session Break
12:20 Luncheon Presentation I: Managing Biomedical Data and Metadata in Large Scale Collaborations
Georges Heiter, Founder, Databiology
Data Commons and new Population Scale Omics and Imaging Projects continue to multiply. We will discuss strategies and solutions to address collaboration and data integration in a world lacking universal standards and with a plethora
of regulatory frameworks. Join us together with leaders in large-scale biomedical collaborations to share insights about at some real world use cases.
12:50 Luncheon Presentation II: Zen and the Art of Data Science Maintenance
Jabe Wilson, PhD, Consulting Director, Text and Data Analytics, Elsevier, Inc.
You want insights from your Data: Use historic data for predictive modeling; Power virtualized R&D for data sharing; and, Mine Real World data to understand patients and markets. Is this an Art or a Science? Come learn how you
can use current technologies to integrate multiple data sources into a semantic infrastructure, enabling delivery of data for machine learning processes.
1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing (Commonwealth Hall)
1:55 Chairperson’s Remarks
Michael H. Elliott, CEO, Atrium Research and Consulting
2:00 R&D Data Hub – Connecting Data from Multiple Silos to Enable Analytics
Bryan Takasaki, PhD, Director, R&D Information US Lead, AstraZeneca
This talk will discuss AstraZeneca’s R&D data hub and how it is connecting data from multiple siloes to drive and enable operational dashboards and advanced analytics. We will examine the data warehouse approach, how data
was integrated, and what types of reports and analytics are available for R&D projects.
2:30 An Advanced Analytics Platform to Maximize the Value of Our Small Molecule Project Data Hub
Roman Affentranger, Head, Small Molecule Discovery Workflows, Roche
We present a strategic platform for advanced analytics to maximize the value of our recently updated drug discovery project data hub. We will discuss specialized analytics extensions for chemistry and PK/PD, intelligent small-molecule
building block search and filtering, integrated property prediction services, and broad data access to internal and external sources.
3:00 CO-PRESENTATION: Leveraging a R&D Data Hub Platform for Next Generation of Clinical Data Review
Krista McKee, Director, Data Analytics, Takeda
Raveen Sharma, Specialist Leader, Deloitte Consulting LLP
*Contributed work: Ramin Daron, Senior Director, Data Architecture, Takeda and Sunny Shahdadpuri, Senior Consultant, Deloitte Consulting LLP
The Data and Analytics Hub platform was conceived, designed, and built to address issues of data transparency, trust, and accessibility. This will support the efficient generation of insights for functions across R&D. In this presentation,
we will focus on a critical use case of the platform, clinical data review/medical monitoring that will ultimately allow for efficient cross-study and cross-compound analysis which will advance our ability to interact with the
4:00 Conference Adjourns