Monday, September 20
7:30 am Registration Open
8:00 am Recommended Pre-Conference Workshops*
Cambridge Healthtech Institute is pleased to offer morning and afternoon pre-conference workshops on Monday, September 20, 2021. They 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 Tuesday-Wednesday.
*Separate registration required. See Workshop page for details.
9:30 am Break
9:45 am Recommended Pre-Conference Workshops*
11:15 am Enjoy Lunch on Your Own
12:45 pm Recommended Pre-Conference Workshops*
2:15 pm Break
2:30 pm Recommended Pre-Conference Workshops*
4:00 pm Session Break and Transition to Plenary Keynote
4:15 pm Innovative Practices Awards – Winners Spotlight
4:20 pm PANEL DISCUSSION:
Pharma Executive Roundtable: Broadening the Data Ecosystem
Lita Sands, Head, Life Sciences, Amazon Web Services
The Bio-IT World community employed creativity, problem solving, and technical ingenuity to weather 2020 and never was the work more important. Meanwhile, digitization has been broadening the horizons of new possibilities and initiatives that are driving innovation in the life sciences sector. While over the past year many pharmaceutical companies have seen an acceleration of digital transformation, there are still many that are unsure what to expect going forward. Digital transformation is now a strategic imperative, not a buzzword. Join our Pharma Executive Roundtable to discover how biopharma companies are broadening their digital strategies and capabilities to develop products and services to scale, streamline operations, and drive innovation in life sciences R&D.
Ramesh V. Durvasula, PhD, Vice President & Information Officer, Research Labs, Eli Lilly & Co.
Michael Montello, Senior Vice President, R&D Tech, GlaxoSmithKline
Bryn Roberts, PhD, Senior Vice President & Global Head of Data Services, Roche
Holly Soares, PhD, Vice President & Head, Precision Medicine, Pfizer Inc.
Lihua Yu, Chief Data Officer, FogPharma
5:45 pm Welcome Reception in the Exhibit Hall with Poster Viewing
7:00 pm Close of Day
Tuesday, September 21
7:00 am Registration Open and Morning Coffee
Building a Federated Data Ecosystem for Computational Research
Albert Wang, MS, Senior Director, IT for Translational Medicine, Informatics & Predictive Sciences, Bristol-Myers Squibb Co.
Following a major acquisition, Bristol-Myers Squibb has access to a rich and complex variety of internal and external data sources to drive future therapeutic research and patient benefit. This talk will discuss challenges and opportunities as we rethink how we manage and provision this data to seamlessly enable computational research.
Evolving an Ecosystem for Advanced Translational Insights
Erik Koenig, Director, Insights and Analytics, Takeda Data Sciences Institute, Takeda Pharmaceuticals
Krista McKee, Head, Insights & Analytics, Takeda R&D Data Sciences Institute, Takeda Pharmaceuticals
The quest for a digital translational research partner is on for Takeda. In this session, leaders of this effort will tell the story of how the journey began, what questions have been answered so far, and what remains to be done to create a clinical/translational AI-empowered assistant to help make better decisions and enable Takeda to deliver transformative therapies faster than previously possible.
9:10 am Coffee Break in the Exhibit Hall with Poster Viewing
Multi-Omic Pharmacodynamics Insights: Biology and Analytics Driven Insights on Strategy for Clinical Design and Development
Rangaprasad Sarangarajan, PhD, Senior Vice President & CSO, Berg LLC
Advances in multi-omic profiling and ML/AI analytical tools provide the perfect opportunity for development of PK/PD strategies for data driven clinical development. The presentation will focus on PD-derived data analytics in support of indication selection, independent validation of outputs across clinical development spectrum laying the foundation for lean pivotal trial design.
Failure to enroll patients is one of the leading causes of clinical trial delays. As life science organizations adopt more data-driven approaches to determining trial feasibility and seek to improve operational performance, the use of machine learning and predictive models can accelerate cycle times, improve site selection, provide more accurate enrollment forecasts to base decisions on, and reduce manual effort involved in scenario modelling.
11:00 am Interactive Discussions
12:15 pm Refreshment Break in the Exhibit Hall with Poster Viewing
How Digital Evolution and an Attitudinal Revolution are Re-Shaping the Future of the Life Sciences Industry
Nimita Limaye, PhD, Research Vice President, Life Sciences R&D Strategy and Technology, IDC
The world has rapidly transitioned to a model of disaggregated care and decentralized clinical trials, with a heightened focus on patient-centricity. Digital resiliency has become the priority and discretionary spend on R&D platforms has been delayed. Federated-learning models are fueling co-innovation and GPU-powered transformer models are accelerating drug discovery. Technology is enabling access and equity. The borders between healthcare and life sciences are blurring and real-world data is being leveraged to drive a precision medicine strategy.
All of Us Research Program – Seeking To Advance Precision Health for All Populations
Joshua Denny, MD, MS, CEO, All of Us Research Program, National Institutes of Health
The All of Us Research Program launched May 6, 2018 and currently has over 375,000 participants who have contributed biospecimens, health surveys, and a willingness to share their EHR. Participants are partners in the program and receive research results from data they contribute, including genetic ancestry and traits. In the future, participants will also receive health-related genomic results from whole genome sequencing. In May 2020, the program launched the beta version of the Researcher Workbench. Once researchers register and are approved to use the workbench, they can access individual-level data and a suite of tools to analyze these data. All of Us is committed to catalyzing a robust ecosystem of researchers and providing a rich dataset that drives discovery and improves health.
2:30 pm Refreshment Break in the Exhibit Hall with Poster Viewing
Standardization of Observational Health Data and the Criticality of Harmonized Infrastructure for Multi-Source Analysis
Alan Andryc, Associate Director, Observational Health Data Analytics, Janssen Pharmaceuticals Inc.
This session will dive into the importance and power of data standardization within the real-world data space. It will then touch on the benefits of transforming data into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), demonstrate how this approach can be scaled for multi-source network analyses, and address the need for infrastructure tuned for this type of work.
Translating FAIR and Data Readiness Principles to Enable AI for Clinical Applications
Kimberly Robasky, PhD, Head, Translational Science, Renaissance Computing Institute (RENCI)
Rebecca Boyles, Director and Senior Scientist, Research Systems and Data Management, RTI International
AI techniques simultaneously consider nonlinear clinical, biomolecular, environmental and social covariates for optimizing patient outcomes. The accuracy and applicability of these techniques improve with the size, breadth, and quality of the patient dataset used to train them. While FAIR principles (Findable, Accessible, Interoperable, and Reusable) are the standard for research data, there is little that addresses data quality. Data Readiness Levels does propose standards for data quality and we propose combining FAIR and Data Readiness Level with concepts on rigor and normalization to lay the foundation for application of AI and other advanced data science technologies in biomedical research.
4:05 pm Refreshment Break in the Exhibit Hall with Poster Viewing
The GPD-Insights Platform Data Lake: An Organizational Shift with Respect to Clinical Data Management and Exposure
Jay Bergeron, Director, Translational Research Business Technologies, Pfizer
Corporate analytic data systems were driven by traditional data warehousing models for the better part of two decades. Although effective, and cutting edge technologies for the time, change control inefficiencies and a greater need for ad hoc analytics led to the datalake paradigm, in which data is consolidated in, and used from, a largely unintegrated state. We describe an AWS-based datalake implementation that has been applied to, and is now an enterprise system for, clinical operations as well as emerging support for clinical trial analytics. Components enabling ingestion, cataloging, conformance and reporting will be reviewed.
6:35 pm Close of Day
Wednesday, September 22
7:30 am Registration Open
8:00 am Interactive Discussions (Sponsorship Opportunity) or Morning Coffee
Interactive Discussions are informal, moderated discussions, allowing participants to exchange ideas and experiences and develop future collaborations around a focused topic. Each discussion will be led by a facilitator who keeps the discussion on track and the group engaged. For in-person events, the facilitator will lead from the front of the room while attendees remain seated. For virtual attendees, the format will be in an online networking platform. To get the most out of this format, please come prepared to share examples from your work, be a part of a collective, problem-solving session, and participate in active idea sharing. Please visit the website's Interactive Discussions page for a complete listing of topics and descriptions.
- The opportunities and challenges of using AI in drug R&D
- Real-world use cases: successes, failures, and lessons learned
- How AI can unlock unstructured data for use alongside structured data
- Best practices for adopting intelligent technologies for drug discovery and development
- Looking ahead: using Insight Apps to accelerate the drug pipeline
9:00 am Coffee Break in the Exhibit Hall with Poster Viewing
Digital Transformation in Clinical Trials through Process Automation
Alan Rogerson, Principal Scientist, Research and Early Development Informatics, Roche Products Ltd.
Early phase clinical trials are governed by complex, concurrent and largely manual GCP processes. We have developed a platform to digitalize and automate these processes, to help study management teams to drive and manage their studies to completion with improved efficiency. The platform could help to transform the way that study teams work in the future.
Digital Health: Accelerating and Transforming Clinical Practice
Anastasia Christianson, Vice President, R&D Business Technology, Janssen Pharmaceuticals
Digital Health is a term used to describe a broad set of digital technologies and capabilities used in healthcare, including wearable devices, mobile health apps, telehealth and telemedicine, and software as a medical device. Physicians and scientists are increasingly leveraging digital health capabilities to enhance disease understanding, prevention, diagnosis, and treatment, with the goal of improving patient outcome through more targeted healthcare delivery. Likewise, patients are increasingly using digital health capabilities to track or manage their health and to make informed decisions about their healthcare options. This talk will provide examples of how digital technologies are evolving and transforming clinical research and practice to deliver precision medicine.
Platformization of Clinical Research as Essential Element to Accelerate Discovery
Alexander Sherman, Director, Center for Innovation and Bioinformatics, Massachusetts General Hospital
Platformization is driving business acceleration. Platforms are ubiquitous in everyday lives. They are almost nonexistent in clinical research. Speed of protocol approval, patient identification and enrollment, heterogeneity of outcomes, and fragmentation of data ownership could be overcome with platformization of clinical trials, observational and patient-facing studies with plugable IRB-approved protocols and preexisting pools of patient population. Innovation accelerated through collaboration, pooled resources, from finances to data capture, faster startup/enrollment, information sharing/distribution.
Dimensions platform, powered by AI on full texts, allows you to quickly analyze raw full text data in a meaningful and custom way, generating insights that are impossible to gather using traditional search methods. To demonstrate the power of Dimensions in clinical research settings, Jenny Ghith will talk about a specific application of AI-based literature interrogation method that was utilized to identify biomarkers of scientific interest in oncology for further clinical development.
11:55 am Interactive Discussions
This discussion will cover common challenges in content management and provide guidance to improve the efficiency of clinical trials and reduce costs while remaining compliant and reducing risk.
The complexity of clinical trials is increasing faster than ever and collaboration must happen with many stakeholders globally.
Clinical operations need strict security and regulatory controls that don’t impede processes,
Clinical teams demand intuitive and cloud-based tools
1:10 pm Refreshment Break in the Exhibit Hall with Poster Viewing
2:05 pm Plenary Keynote Introduction (Sponsorship Opportunity Available)
2:10 pm PANEL DISCUSSION:
Trends from the Trenches
Kevin Davies, PhD, Executive Editor, The CRISPR Journal; Founding Editor, Bio-IT World
Since 2010, the “Trends from the Trenches” presentation, given by Chris Dagdigian, has been one of the most popular annual traditions on the Bio-IT Program. The intent of the talk is to deliver a candid (and occasionally blunt) assessment of the best, the worthwhile, and the most overhyped information technologies (IT) for life sciences. The presentation has helped scientists, leadership, and IT professionals understand the basic topics related to computing, storage, data transfer, networks, cloud, data science, and machine learning that are involved in supporting data-intensive science. In 2021, Chris will give the “Trends from the Trenches” presentation in its original “state-of-the-state address” followed by guest speakers giving podium talks on relevant topics. An interactive Q&A moderated discussion with the audience follows. Come prepared with your questions and commentary for this informative and lively session. To stay connected with Trends from the Trenches updates after today and all year, sign up for BioTeam's newsletter here: https://bit.ly/33uO0OY
Chris Dagdigian, Senior Director, BioTeam, Inc.
Fernanda S. Foertter, PhD, Director of Applications, NextSilicon
Karl Gutwin, PhD, Director, Software Engineering Services, BioTeam, Inc.
Adam Kraut, Director Infrastructure & Cloud Architecture, BioTeam, Inc.
3:30 pm Refreshment Break in the Exhibit Hall with Poster Viewing
Clinical Trial & Real-World Data (RWD) for Oncology Biomarker Discovery
Philip Ross, PhD, Director, Clinical Data Utilization, Knowledge Science Research, Bristol-Myers Squibb
Celine Han, Senior Scientist & Computational Biologist, Bristol Myers Squibb
Pharma faces challenges in drug development and has increasing needs for scientific exploration driven by clinical data and real-world data approaches. High quality data with automated QC and accelerated access are helpful, as well as integration of clinical trial data and real world data approaches for biomarker discovery. Machine Learning offers new insights in oncology biomarker discovery.
Increasing Trust in Real-World Evidence through Evaluation of Observational Data Quality
Clair Blacketer, Associate Director, Janssen
Advances in standardization of observational healthcare data have enabled methodological breakthroughs, rapid global collaboration, and generation of real-world evidence to improve patient outcomes. To ensure confidence in real-world evidence generated from the analysis of real-world data, one must first have confidence in the data itself. The Data Quality Dashboard is an open-source R package that reports potential quality issues in an OMOP CDM instance through the systematic execution and summarization of over 3,300 configurable data quality checks. Assessing and improving the quality of our data will inherently improve the quality of the evidence we generate.
Real-World Data and Analytics to Enable Real-World Evidence Generation
Yonghua Jing, Senior Director, Health Economics & Outcomes Research, AbbVie
In this presentation we will go over the concept of Real World Data (RWD) and Real World Evidence (RWE), current development status of RWD/RWE in key countries, key considerations and challenges of how to use RWE to inform drug development and support regulatory decision making. Recent European and American RWE case studies will be discussed in this session.
5:35 pm Close of Conference