Precision medicine continues to be at the forefront in research centers and pharmaceutical companies alike, and the pharmaceutical industry has a key role to play in driving this new reality, which requires integrating, analyzing, and interpreting data
from a myriad of sources, across departments, organizations, and geographical regions. Integrated Pharma Informatics will discuss challenges related to data from clinical trials, imaging, sequencing, EMRs and new sources such as wearbles.
This conference will examine real-world projects related to data integration, analysis, and storage; translation research; and healthcare. Special attention will be paid to new developments in artificial intelligence and machine learning. Join informatics
experts from pharma, biotech, biomedical research, and data and patient communities to discuss these challenges and real-world examples of using informatics to enable translational research and precision medicine.
Monday, February 12
10:30 am Conference Program Registration Open
11:50 Chairperson’s Opening Remarks
Anastasia Christianson, Vice President, R&D Operations IT, Oncology IT, Janssen
12:00 pm “The Last Mile”: Driving Self-Serve Informatics
Scott Bean, Director, Analytics & Innovation, Amgen
Investment in data science and advanced analytics technology is fruitless without adoption strategies to help non-expert IS teams and end users understand and use them. Our focus on Data and Analytics “as a service” will streamline access
and empower more of our workers to create new insights for patient benefit.
12:30 Application of Machine Learning and Artificial Intelligence as a Driver of Productivity in Drug Discovery & Development
Morten Sogaard, Vice President, Genome Sciences & Technologies, Pfizer Worldwide R&D
Examples will be given of application of machine learning and artificial intelligence along the drug discovery and development process, and how these investments drive innovation and productivity.
1:00 Session Break
1:10 Luncheon Presentation: Present and Future Collaborative Drug Discovery Informatics Innovations
Whitney Smith, Ph.D., New Business Development, Collaborative Drug Discovery Inc.
Since 2004 - before “Cloud Was Cool” - Collaborative Drug Discovery (CDD) has been providing a secure and performant hosted informatics solution for scientists at a fraction of the cost of traditional systems. CDD’s Research Informatics
Group invents bleeding edge technologies for tomorrow’s needs.
2:10 Session Break
2:30 Chairperson’s Remarks
Anastasia Christianson, Vice President, R&D Operations IT, Oncology IT, Janssen
2:40 Drivers for Pharma Informatics Today
Anastasia Christianson, Vice President, R&D Operations IT, Oncology IT, Janssen
This talk will discuss some of the challenges that pharmaceutical companies face in research and development, and how informatics, big data, and advanced analytics can help solve these problems. Considerations for developing informatics tools in the future
will also be discussed.
3:10 Roche Data Commons Enabling Advanced Analytics
Juergen Hammer, Ph.D., MBA, Global Head Data Science, Pharma Research and Development Informatics, Roche Innovation Center New York
We will provide an update on the implementation of our multi-layer Data Commons Platform. This modular platform is based on a new set of principles that cope with the challenge of multiple high-dimensional data types. We will show Deep Learning applications
in drug discovery that have or will benefit from this new environment. We will also highlight examples and benefits of a rapidly increasing biomedical application landscape that is based on our Data Commons principles.
3:40 Integrated Omics Data Platform
Misha Kapushesky, CEO, Genestack
How can we benefit from vast amounts of data available from myriad sources? Can we reduce cost and increase efficiency by automating repetitive tasks? How can we make collaboration more efficient? What’s next?
4:10 Leveraging
Modern Software to Organize, Optimize, and Measure Biologics R&D
Sajith Wickramasekara, CEO and 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.
4:40 Refreshment Break and Transition to Plenary Session
5:00 Plenary Keynote Session (click here for more details)
6:00 Grand Opening Reception in the Exhibit Hall with Poster Viewing
7:30 Close of Day
Tuesday, February 13
7:30 am Registration Open and Morning Coffee
8:00 Plenary Keynote Session (click here for more details)
9:00 Refreshment Break in the Exhibit Hall with Poster Viewing
10:05 Chairperson’s Remarks
Randy Qin, Associate Director, Senior Architect, Data Platform, R&D IT Engineering, Merck & Co.
10:15 Data Integration and Analysis Solutions for Lead Discovery and High Throughput Screening
Frank Kloeck, IT Business Partner, BS-ITBPPH-RD-R, Bayer Business Services
This talk will provide an overview of SMOL Bayer Lead Discovery and the Screening Units. The presentation will also describe solutions and methods for data storage and analysis of Lead Discovery data. The challenges of handling historical data of
more than 15 years will be discussed.
10:45 Cloud and Paas for Research Data Integration
Randy Qin, Associate Director, Senior Architect, Data Platform, R&D IT Engineering, Merck & Co.
The integration of internal and external research data is a constant challenge in the life sciences. Although many approaches have been adopted from other industries with varying success, research data integration is confounded by the extreme variety
and rate of change. While not a panacea, moving data integration efforts to the cloud does offer a possible path to an information platform that is more accommodating of data variety and more resilient to rapid change. In this talk I will discuss
three generations of approaching high variety data integration at scale; from on premise infrastructure, through cloud IaaS, to managed PaaS. I will also discuss efforts around the development of “12-factor” cloud-native micro-service
applications and the benefits of a “micro-service harness”.
11:15 Extended Q&A with Session Speakers
11:45 Drug Target Identification As Seen in the Data
Richard K. Harrison, Ph.D., CSO, Clarivate Analytics
This talk will review the current drug target landscape as seen through the Clarivate Analytics databases. Trends over the last 5 years around target families, indications and organizations will be examined to highlight the current and future directions
in target identification. Finally, we will briefly introduce new analytical tools to rapidly triage targets to identify the most promising from both scientific and commercial perspectives.
12:15 pm Session Break
12:25 Luncheon Presentation: Leveraging Cloud-Based Platforms to Drive
Data Strategy for the Life Sciences
Alok Tayi, CEO, TetraScience
Life science companies want to accelerate drug discovery using data analytics and machine learning. Scientific data, however, is not centralized nor standardized: from instrumentation to CRO/CMOs to legacy software. Here, we will discuss how biopharma
companies are developing their data strategies and deploying new data platforms.
1:25 Refreshment Break in the Exhibit Hall with Poster Viewing
2:00 Chairperson’s Remarks
Morten Sogaard, Vice President, Genome Sciences & Technologies, Pfizer Worldwide R&D
2:10 Disease and Patient Registries for Research and Machine Learning
Ajay Shah, Director, Research Informatics, Office of the Chief Informatics Officer, Beckman Research Institute and City of Hope National Medical Center
City of Hope, a NCI designated Comprehensive Cancer Center has implemented a comprehensive Disease/Patient Registries application suite based on SPIRIT (Software Platform for Integrated Research Information and Transformation) platform that allows
integration of data from electronic medical records, ancillary healthcare systems, longer term follow-up and clinical research data using Enterprise Data Warehouse. The Registries are integrated with SPIRIT SA (Scientific Analytics, a machine
learning platform) deeper insights into diseases.
2:40 Using Clinical Terminology Standards to Curate Real World Evidence Data – Biogen’s Learning Health System for MS
Eunice Jung, Associate Director, Healthcare Data Standards, Value Based Medicine, Biogen
The Institute of Medicine put forth the idea of Learning Health System that creates a continuous feedback loop in which scientific evidence informs clinical practice while data gathered from clinical practice and administrative sources inform scientific
investigation. Biogen’s evidence-based LHS uses clinical terminology dictionaries to curate data to provide interoperable, meaningful, and systems-agnostic information for the advancement of clinical research and data-driven insights at
point of care for MS patients.
3:10 Changing the Landscape of Cancer Immunotherapy
Nikesh Kotecha, Ph.D., Vice President, Bioinformatics, Parker Institute for Cancer Immunotherapy
Recent advances in oncology are transforming the nature of healthcare and biotech with immunotherapy leading the charge. This talk will introduce the Parker Institute for Cancer Immunotherapy, its mission to accelerate the development of breakthrough
immune therapies, highlight the informatics opportunities and challenges presented in this space and our approaches to address them.
3:40 Creating a Connected Ecosystem to Gain Insights Across R&D
Marc Siladi, Product Manager, Data Analytics, Thermo Fisher Scientific
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.
4:10 Valentine’s Day Celebration in the Exhibit Hall with Poster Viewing
5:00 Breakout Discussions in the Exhibit Hall
These interactive discussion groups are open to all attendees, speakers, sponsors, & exhibitors. Participants choose a specific breakout discussion group to join. Each group has a moderator to ensure focused discussions around key issues within
the topic. This format allows participants to meet potential collaborators, share examples from their work, vet ideas with peers, and be part of a group problem-solving endeavor. The discussions provide an informal exchange of ideas and are not
meant to be a corporate or specific product discussion.
Challenges and Obstacles to Using AI in Pharma R&D
Morten Sogaard, Vice President, Genome Sciences & Technologies, Pfizer Worldwide R&D
- AI and machine learning at every stage of the pipeline: What projects are possible?
- Goals of AI: will this drive innovation and productivity?
- What problems does AI solve and what infrastructure, planning, and resources are needed to succeed?
Integrating RWE into Data Sets for Actionable Insight
Eunice Jung, Associate Director, Healthcare Data Standards, Value Based Medicine, Biogen
- What are the biggest challenges in terms of infrastructure, data standardization, and systems that need to be addressed to streamline RWE data integration?
- Once data is integrated, how do we develop algorithms and analysis for meaningful insight?
- What will be the biggest impact of RWE projects and where do we go next?
6:00 Close of Day
Wednesday, February 14
7:30 am Registration Open and Morning Coffee
8:00 Plenary Keynote Session (click here for more details)
10:00 Refreshment Break and Poster Competition Winner Announced in the Exhibit Hall
10:50 Chairperson’s Remarks
Ajay Shah, Director, Research Informatics, Office of the Chief Informatics Officer, Beckman Research Institute and City of Hope National Medical Center
11:00 Using Human Genetics to Drive Drug Discovery: The Industry Perspective
Anna Podgornaia, Ph.D., Associate Principal Scientist, Genetics and Pharmacogenomics, Translational Medicine, Merck
The Merck Genetics and Pharmacogenomics (GpGx) group uses human genetics and genomics across the entire drug development pipeline to make decisions anchored in human genetics. During the presentation, I will provide 3 vignettes about how we use human
genetics during the drug discovery process, including 1) Using human genetics to get inspiration for novel drug programs; 2) Using human genetics to gain insight into potential safety issues; 3) Pharmacogenomics. I will close with a section on
challenges and opportunities in using human genetics to drive drug discovery.
11:30 Immune-Mediated Dermatological Conditions: Target Identification
Deepak K. Rajpal, Senior Scientific Director, Computational Biology, Target Sciences, GSK
We share a framework for developing new therapeutic intervention strategies for such indications by utilizing publicly available clinical transcriptomics data sets. We propose a strategy based on developing disease signatures, and utilization of the
disease signatures conceptually for identifying potential drug repurposing opportunities and present novel target identification approaches. We anticipate that the conceptual methodology shared here or similar approaches will further support not
only biomarker discovery efforts but also the development of new drugs.
12:00 pm bStyle: A Graphical, Integrated and Modular Systems Biology Platform
Corrado Priami, Ph.D., President & CEO, COSBI
bStyle is a graphical platform to run systems biology analysis in the field of systems pharmacology. It handles multi-omics data to detect active networks and end-up performing in silico experiments for drug design
and development. All the mathematical technicalities are hidden behind the graphics and it is then easy to use even by a non-expert of modeling and data analysis.
12:30 Session Break
12:40 Enjoy Lunch on Your Own
1:10 Dessert Break in the Exhibit Hall and Last Chance for Poster Viewing
1:50 Chairperson’s Remarks
Michael N. Liebman, Ph.D., Managing Director, IPQ Analytics, LLC; Professor, Drexel College of Medicine; Professor, Wenzhou First University Medical School
2:00 Pharma and Physician Perspective - The Future of Drug Development and Health Care
Charles E. Barr, M.D., MPH, Group Medical Director & Head, RWE Strategy & External Relationships, US Medical Affairs, Genentech
Science advances the knowledge of disease mechanisms, enabling the creation of transformative therapies. However, both healthcare and drug development face serious challenges including unsustainable growth in costs. Feasible solutions will require
new ways for patients, physicians and researchers to leverage advanced technologies to accelerate both research and health care cost-effectively.
2:30 Healthcare Perspective – Limitations of Big Data Approaches and Clinical Needs
Hal Wolf, Director and Practice Leader for Information and Digital Health Strategy
Genomics has quickly become a wide and broad topic capturing both the academic and consumer medical/health models. But the access to meaning big data sets that can be turned into useful knowledge and the lack of clear medical needs has left many approaches
at a crossroads on how to proceed. Where will genomics set path and what are the dependencies to support its useful integration into the healthcare eco-system?
3:00 PANEL DISCUSSION
Moderator: Michael N. Liebman, Ph.D., Managing Director, IPQ Analytics, LLC; Professor, Drexel College of Medicine; Professor, Wenzhou First University Medical School
- Complexity of disease(s): Disease stratification; limitations in diagnosis
- Complexity of patients: Clinical history; co-morbidities; genomics
- Clinical guidelines: Quality of guidelines; compliance
- Trial populations vs. real world patients
- Translation of clinical trial results into clinical practice
- Unmet vs. unstated unmet clinical needs
3:30 Session Break
3:40 Chairperson’s Remarks
Lara Mangravite, Ph.D., President, Sage Bionetworks
3:45 Collaborative Ecosystems in Data-Intensive Science for Precision Medicine
Lara Mangravite, Ph.D., President, Sage Bionetworks
An advanced understanding of the dynamic nature of disease is necessary to meaningfully implement precision medicine but several barriers exist. In particular, approaches to understand dynamic fluctuations in disease are highly data intense and require
bioinformatic inquiry for which standard methodologies do not exist. These issues can be systematically addressed by combining resources, benchmarking methods, and establishing community consensus around well-supported research findings.
4:15 Novel Approaches to Participant Engagement in Genetic Research and Translating Big Data into Action
David Verbel, MPH, Director, Translational Data Science, Human Biology and Data Science, Eisai, Inc.
To identify the right medicines and patients to receive them, Eisai is exploring ways to identify individuals who carry genetic variants of interest. In two such studies, biological samples from genetically and clinically selected individuals
will be characterized to learn more about cellular and molecular consequences to changes in the function of particular genes. The first involves utilizing a novel research platform; the latter working with a leading academic center.
4:45 Scientific Informatics for Translational Oncology
Ronghua Chen, Director, Scientific Informatics, Global Research IT, R&D IT, Merck
The applications of molecular profiling technologies including next-generation sequencing in translational oncology offer unprecedented opportunities to discover new drug targets and biomarkers as well as to understand tumor biology. This
presentation will elaborate the complexities of oncology data sets and highlight an integrated scientific informatics approach in analyzing data and supporting translational research.
5:15 Close of Conference Program