Advancing clinical trials and translational research requires transforming biological insights and raw research data into clean, actionable data using innovative techniques for its integration, visualization and analysis. The Clinical Research & Translational
Informatics track explores new approaches to the integration, visualization, analysis, and application of biological and clinical trial data, including machine learning, artificial intelligence, big data analytics, and additional technologies with
case studies from across pharma and academia.
Final Agenda
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Tuesday, April 16
7:00 am Workshop Registration Open and Morning Coffee
8:00 – 11:30 Recommended Morning Pre-Conference Workshops*
12:30 – 4:00 pm Recommended Afternoon Pre-Conference Workshops*
* Separate registration required.
2:00 – 6:30 Main Conference Registration Open
4:00 PLENARY KEYNOTE SESSION
Amphitheater
5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing
Wednesday, April 17
7:30 am Registration Open and Morning Coffee
8:00 PLENARY KEYNOTE SESSION
Amphitheater
9:45 Coffee Break in the Exhibit Hall with Poster Viewing
10:50 Chairperson’s Remarks
Karla Feghali, Real World Evidence and Partnership Lead, ConvergeHEALTH Deloitte Consulting, LLP
11:00 Digital Health and Big Data for Drug Development
Ray Liu, PhD, Senior Director & Head, Statistical Innovation & Consultation, Takeda
Novel digital technology allows study subjects to be assessed with new metrics, monitored remotely and continuously, and deep phenotyped to reveal new patterns. Coupled with Big Data, digital technology has great potential to make the drug more efficient
and fulfill the promise of personalized medicine. The presentation is introductory in nature to help researchers understand the status of digital technology implementation in clinical trials. Challenges and opportunities for analytical development
will also be discussed.
11:30 How One Bold Data Hub Project Can Inspire an R&D Organization
Krista McKee, Director, Data and Analytics, Takeda Data Science Institute
Takeda’s R&D Data Hub was established to maximize the value of data by providing better access and better means to aggregate and analyze data efficiently. With its Platypus project, a winner of last year’s Bio-IT World Best Practices Awards,
Takeda aggressively and successfully pursued the Data Hub vision for a specific set of users. Along the way, multiple R&D functions were inspired to pursue more data-driven futures, enabled by the R&D Data Hub. From Clinical Science to Pharmacovigilance
to Translational Research, this presentation will focus on the Data Hub projects that emerged from Platypus and their impact on the organization. Specific projects include pursuing cross-portfolio, program-level analytics on clinical safety data;
piloting the utilization of machine learning algorithms/predictive analytics to monitor adverse event risk for an ongoing clinical trial; and igniting efforts within translational research to more broadly and systematically pursue data to inform and
influence program benchmarking and decision-making.
12:00 pm Leverage the Cancer Genome Atlas for Data Discovery in Oncology
Rob Rittberg, Global Marketing Manager, PerkinElmer
Patient stratification based on molecular profiles has shifted the paradigm, as evident in the field of Oncology. Combining large genomic datasets and sharing them is an important strategy for Oncology research to accelerate the comprehensive understanding
of cancer genetics. See how translational scientists can effectively access, integrate, and search the TCGA dataset for complex analytics.
12:15 Characterizing Targeted
Cancer Therapies via a Comprehensive Gene Fusion Database
Mark Kiel, MD, PhD Founder & Chief Science Officer, Genomenon
Possessing a comprehensive view of the research related to gene fusions can significantly accelerate the drug discovery and development process. This presentation demonstrates how a Gene Fusion Database allows researchers to find fusion pairs for any
disease of interest, identify targeted treatment strategies, and refine gene fusion breakpoint analysis.
12:30 Session Break
12:40 Luncheon Co-Presentation I: Building
an Enterprise-wide, API-first Platform to Conduct Analytics of Real World and Observational
Data
Vasu Chandransekran, PhD, Director of Data Sciences, Merck
Karla Feghali, Real World Evidence and Partnership Lead, ConvergeHEALTH Deloitte Consulting, LLP
The FDA recently created a strategic framework to advance the use of Real World Evidence (RWE) as well as issued final guidance on how manufacturers can communicate this evidence to our customers. Merck launched the development of the Real World Data
Exchange (RWDEx) platform to meet this need
1:10 Luncheon Presentation II: Barriers to Adopting
Real-world Data – a Roundtable Discussion
Patrick Bosco Global Alliances Director Sales InterSystems Corporation
Real time clinical data promises to accelerate clinical trial processes and efficiency. Despite widespread EMR adoption, life science companies encounter barriers to utilizing this data in critical clinical trial processes. In this round table discussion
we will explore the barriers to leveraging real world data and the opportunities to overcome them. This session is sponsored by InterSystems, a leading healthcare technology company supporting over 500 million patient records around the world.
1:40 Session Break
1:50 Chairperson’s Remarks
Farhan (CJ) Hameed, MD, MS, Senior Director, Global Real World Evidence Center of Excellence, Patient & Health Impact, Pfizer, Inc.
1:55 Use of Real World Data for Evidence Generation through ML & AI
Farhan (CJ) Hameed, MD, MS, Senior Director, Global Real World Evidence Center of Excellence, Patient & Health Impact, Pfizer, Inc.
There is a growing regulatory application of RWE beyond safety and with a particular interest in using RWE to bridge the evidentiary gap between regulators, HTAs and payers enabled an increase in availability of real world data from traditional claims
and EHR data sources to patient generated data from mobile wearables/sensor devices and genomic data facilitated by advanced analytics such as AI, ML and NLP, for an end to end drug development across products life cycle.
2:25 Machine Learning/Deep Learning Applications in RWE
Alan Andryc, Senior Technology Manager, Real World Evidence, Janssen Pharmaceuticals, Inc.
With massive computing power resources at one’s fingertips, Deep Learning finally became a reality in understanding complex patterns in patient journey: how they have been diagnosed, how they have been treated and how disease progressed. Leveraging
cloud-based AI solutions, we can apply Deep Learning to Electronic Health Record and reveal hidden patterns in patient journey and better understanding the dynamics in the real-world setting. In this talk, we will be discussing technology enablers
with DL applications in RWE.
2:55 Handling Real World Data to Inform Healthcare Decisions: Case Study Diabetes
Meeta Pradhan, PhD, Senior Data Scientist, Indiana Biosciences Research Institute
Despite progress in treatment of Type 2 Diabetes (T2D), T2D remains a growing global health issue. In Indiana approximately 12.9% of adult population have diabetes. Due to the multiple factors driving the increase in T2D, there is a need for precision
approach to T2D that would enable better treatment to patients. This talk demonstrates the complexity of real-world data, how to prepare it for research, and its utility in understanding T2D leveraging different machine learning approaches to
support better decision making.
3:25 Refreshment Break in the Exhibit Hall with Poster Viewing, Meet the Experts: Bio-IT World Editorial Team, and Book Signing with Joseph Kvedar, MD, Author, The Internet of Healthy Things℠ (Book will be available for purchase
onsite)
4:00 FEATURED PRESENTATION: Expanding Access to Dynamic Clinical Biomarker Visualizations: Automation, Integration and Exploration of Data Lakes
Philip Ross, PhD, Head of Translational Bioinformatics Data Science, Translational Medicine, BMS
With biomarker samples from thousands of patients across multiple indications, how do we detect meaningful clinical biomarker results in a reasonable timeframe and at reasonable levels of effort? Dynamic visualizations with up-to-date data provide
evolving insights. We are automating the integration of clinical and biomarker results in data lakes and leveraging dynamic visualizations to give the best possible access and exploration of emerging clinical biomarker data signals and trends.
4:30 Universal Spotfire Template (UniSpoT) for Clinical Biomarker Discovery
Sittichoke Saisanit, PhD, Principal Scientist, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Innovation Center New York
UniSpoT is the Roche pRED standardized visual analytics platform for clinical biomarker data. Enabled by the underlying BRAVE data process, it addresses the increasing and unmet business need for near real-time access to biomarker data, integrated
with clinical data for exploratory analysis. It has been used for early clinical studies which have open-label design (e.g. phase 1b). Using UniSpoT, scientists can gain earlier and better understanding of biology, generate hypothesis, improve
biomarker strategy and quality of data collection.
5:00 CO-PRESENTATION: Addressing High Performance Analytics Needs with the RSVP Platform
Satish J. Murthy, IT Manager, Janssen R&D IT
Paulo Bargo, Scientific Director, Statistics and Decision Sciences, Janssen R&D
The use of R for statistical computing is growing quickly among statisticians in Janssen Research & Development. They need an environment where they can collaborate in real time with colleagues across the world, run simulations with High Performance
Computing (HPC), and deploy Shiny Applications to share their analyses. The Janssen R&D IT team developed and implemented the R as a Service for Visualization and Processing (RSVP) platform which combines Rstudio Server, Rshiny, cloud-bursted
HPC, and Rconnect to address the challenges that Janssen scientists presented them with. This talk will present the design and architecture of RSVP from the IT side, and present a use case from the R&D side of an application that runs
on the platform.
5:30 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing
Thursday, April 18
7:30 am Registration Open and Morning Coffee
8:00 PLENARY KEYNOTE SESSION & AWARDS PROGRAM
Amphitheater
9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced
10:30 Chairperson’s Remarks
Gurpreet Kanwar, MBA, PMP, Senior Project Manager, NAV CANADA
10:40 CO-PRESENTATION: Implementation of Complex Innovative Designs (CID) at Janssen
Raj Malathker, Manager, Quantitative Sciences IT, Johnson & Johnson Pharmaceutical R&D
Vlad Dragalin, PhD, Vice President & Scientific Fellow, Global Quantitative Sciences, Janssen Pharmaceuticals R&D
Both the 21st Century Cures Act and the PDUFA VI legislations call for wider use and acceptance of complex innovative clinical trial designs with the goal of streamlining drug development and bringing needed new medicines to patients in a more
timely and efficient manner. We are the first PhRMA company to build an in-house platform, aptly named ACTIVE (Adaptive Clinical Trial’s Interactive Virtual Environment), for efficient implementation of such complex innovative designs.
11:10 Effectively Complete Your Projects
Gurpreet Kanwar, MBA, PMP, Senior Project Manager, NAV CANADA
Most organizations say they have too many projects on the go and are not able to manage with backlog still growing. They want to achieve a high throughput of successful projects, however many are unable or unwilling to allocate an appropriate
level of resourcing to approved initiatives. Methodologies to execute projects are not consistent and lacking standard processes. There is a need to manage project delivery expectations, satisfaction of business stakeholders and balance
the demand to help them achieve their strategic goal.
11:40 Increasing the Velocity of Team Data Science
Gregg TeHennepe, Program Manager, Computational Scientist, The Jackson Laboratory
Beena Kadakkuzha, PhD, Research Project Manager, The Jackson Laboratory
Learn how the Jackson Laboratory has leveraged concepts and processes from Agile and Scrum to significantly increase the effectiveness and pace of teams focusing on data science.
12:10 pm Enjoy Lunch on Your Own (Lunch Available for Purchase in the Exhibit Hall)
1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing
1:55 Chairperson’s Remarks
Jay Bergeron, Director, Translational Research Business Technologies, Pfizer
2:00 CASE STUDY: Cross-Industry Collaboration Evaluating How Blockchain Can Transform the Pharmaceutical and Healthcare Industry, Part of Emerging Trends & Technology PhUSE Workgroup
Disa Lee Choun, Director Head of Innovation, Global Clinical Sciences & Operations, UCB
Adama Ibrahim, Associate Director, Clinical Operations, Biogen
This presentation will cover an understanding of the landscape in the pharma and healthcare settings, explore the areas where blockchain could be used, and present two detailed used cases (a. Drug Supply Chain using Smart Contracts; b. Patient
Data Access/Transparency) to support future development and implementation for proof of concept.
3:00 Applying a Digital Rights Blockchain to Patient Data Exchange: Simulating Patient Trial Matching with the Bitmark Blockchain
Jay Bergeron, Director, Translational Research Business Technologies, Pfizer
The use of blockchains to enable complicated multiparty processes, pertinent to many patient use cases, generally requires blockchain customization or supplemental applications. A multiparty clinical trial matching simulation was implemented
using only the “Bitmark” digital rights blockchain. The simulation’s development inspired the design of other blockchain applications based on the digital rights model, including biomarker data management and processing.
3:30 Securing Clinical Trial and Biological Experiment Data with the Blockchain
Lu Yu, PhD, Instructor, Electrical and Computer Engineering, Clemson University
A bio-statistician survey found 31% of respondents active in medical research had knowingly committed fraud. The FDA mandates an inviolable audit trail, but when there are large financial stakes it is hard to believe this data will remain
unchanged. One approach is to secure this data using the blockchain, but blockchain discussions maintain that data is globally available and transparent. This is not desirable for HIPAA or proprietary information. This talk explains
how these issues are addressed by a prototype developed by Clemson University, University of Tennessee Chattanooga and the Medical University of South Carolina. We specifically address the differences between blockchain hype and reality.
4:00 Conference Adjourns
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