Cambridge Healthtech Institute's 5th Annual

Big Data Analytics, Machine Learning and Artificial Intelligence for Clinical Trials

Making Meaningful, Data-Driven Decisions in Clinical Trials

May 13-14, 2019


As new technology and increasing volumes of data becomes more accessible to the biopharmaceutical industry, how will the industry make meaningful, data-driven decisions aimed at improving the clinical trial process? CHI’s Big Data Analytics, Machine Learning and Artificial Intelligence for Clinical Trials conference gathers leaders across pharma, biotech and academia to explore the use of artificial intelligence, big data analytics, machine learning, and deep learning for improving the clinical trial process and harnessing existing clinical data for new insights. Discussions and case studies will address challenges and solutions in establishing big data analytic platforms and their use in making meaningful, data-driven decisions.

Final Agenda

Monday, May 13

7:25 am Conference Registration and Morning Coffee

Collecting, Utilizing, and Leveraging Real World Evidence

8:25 Chairperson’s Opening Remarks

8:30 CO-PRESENTATION: Collecting and Utilizing Real World Evidence Using Teva’s Digital Health Platform

Amir Kesten, Senior Director, Head of Digital Health Platform, Digital Health, Teva Pharmaceuticals

Lena Granovsky, Director, Analytics and Big Data, Teva Pharmaceuticals

As drug discovery is a complex process that requires integration of multiple data points, it is only natural that the pharmaceutical industry is turning to technology and big data analytics to streamline the process. Including digital sensors as a part of a clinical trial process allows for continuous and objective monitoring of disease symptoms, reducing errors caused by inconsistencies amongst physicians and subjective non-reliable self-reports of patients. Teva’s Digital Health Platform (DHP) is a global compliant patient connectivity and data research cloud platform, supporting development and commercialization of current and future medical devices, apps and innovative digital markers. Teva’s DHP is currently used for collection and sharing of patient medical device and sensor usage data globally, both in commercial settings and clinical studies. Future plans include improvement of efficiency and accuracy of clinical studies by integration with wearables and digital sensors, building a validated data backbone to support retrospective clinical studies based on Real World Evidence, and hosting patient-facing predictive algorithms.

9:30 Leveraging Real World Data through Evidence Generation for Clinical Trial Optimization

Farhan (CJ) Hameed, MD, MS, Senior Director, Global Real World Evidence Center of Excellence, Patient & Health Impact, Pfizer Inc.

Changing external environment such as passage of the 21st Century Cures Act has become a key driver for the industry to build an innovative operative model for regulatory grade evidence generation. An integrated approach to bring Randomized Clinical Trial (RCT) and evidence generated through Real World Data (RWD) together can provide the opportunities from identifying the trial population, recruitment, effectiveness prediction, trial optimization and several other growing Real World Evidence (RWE) opportunities to improve the clinical trials execution and value generation across the organization.

10:00 Networking Coffee Break

Managing Big Data Sets

10:30 Deeply-Phenotyped Individuals in Discovery and Clinical Research

Andrew Magis, PhD, Director, Research, Arivale

Response to pharmaceutical intervention in a clinical trial may be influenced by genetic predisposition, microbiome composition, and participant lifestyle, as well as other factors. Arivale has developed a platform to collect, ingest, and analyze longitudinal multi-omic data to support our research collaborations and ongoing clinical trials. We integrate genomics, clinical tests, gut microbiome sequencing, quantified-self data, metabolomics, proteomics, health history, diet, and lifestyle information within a single cohesive platform designed for data scientists.

11:00 Presentation to be Announced

IQVIA 11:30 Presentation to be Announced

12:00 pm Luncheon Presentation: Scaling Machine Learning for Practical Use in Clinical Trials

Luke Stewart, Senior Director, Product Management, Saama Technologies

Topics to be discussed include: 1) Current challenges in turning proofs-of-concept to production-ready implementations 2) The benefit of “Automated Machine Learning” (AutoML) for clinical trial analytics 3) Application of predictive analytics for operational risk mitigation and patient safety analytics.

12:45 Session Break

Managing Big Data Sets

1:25 Chairperson’s Opening Remarks

1:30 Blockchain Network Effect for Coding Adverse Events

Basker Gummadi, IT Strategy & Digital Transformation, Digital Innovation, Bayer U.S. LLC

Blockchain technology has the potential to positively impact clinical trial supply chains by improving the traceability of medications from active pharmaceutical ingredient (API) to patient. The chain between a clinical study sponsor, study patient, and site is long and involves the use of multiple IT systems. In a world where all parties are linked via a blockchain, it would be possible to leverage encryption and access control so that the members (trusted participants) could get confirmation of the receipt of the product without having access to protected patient information and, in turn, provide the ability to validate patient identity. The design of the blockchain has to take into consideration the nodes and participants of this blockchain: sponsor, distributor, site. Data elements to be stored in the blockchain: material number, substance name, provider, lot batch number, transaction date, time, etc.

2:00 The Application of Intelligent Automation Technologies in Pharmacovigilance

Eileen Leonard, Executive Director, Global Pharmacovigilance and Epidemiology, Bristol-Myers Squibb

Given the wide variety of global regulatory requirements, managing the volume, variety and velocity of Pharmacovigilance data presents a significant challenge. Operations that are repetitive in nature and of relatively low business value are ripe for automation to gain efficiencies and reduce costs. TransCelerate’s newest Intelligent Automation initiative focuses on identifying how intelligent automation technologies can be used to better support execution of Pharmacovigilance activities/processes. By conducting an impact assessment and working with global health authorities to verify risks/issues with their use, this initiative will provide guidance, as appropriate, on applications of new technology in Pharmacovigilance practice.

2:30 Grand Opening Refreshment Break in the Exhibit Hall

3:15 Interactive Breakout Discussion Groups

Concurrent breakout discussion groups are interactive, guided discussions hosted by a facilitator or set of co-facilitators to discuss some of the key issues presented earlier in the day’s sessions. Delegates will join a table of interest and become an active part of the discussion at hand. To get the most out of this interactive session and format please come prepared to share examples from your work, vet some ideas with your peers, be a part of group interrogation and problem solving, and most importantly, participate in active idea sharing.

4:15 Welcome Reception in the Exhibit Hall

5:30 Close of Day

5:30 Dinner Short Course Registration

6:00-9:00 Recommended Dinner Short Course*

SC1: Central Monitoring Deconstructed from Raw Data to Monitoring Actions: An In-Depth Walk Through - Detailed Agenda


Tuesday, May 14

7:25 am Morning Coffee

AI & Data Analytics

7:55 Chairperson’s Opening Remarks

8:00 AI-Supported Clinical Trials

Ronald Dorenbos, PhD, Associate Director, Materials and Innovation, Takeda Pharmaceuticals

This presentation will discuss the use of AI in 1. shortening enrollment times, 2. improving patients’ adherence, and 3. new ways of monitoring & diagnosing patients.

8:30 CO-PRESENTATION: The Dark Side of Data in Clinical Trials

Pablo Gersberg, Head, Digital Solutions, BlackThorn Therapeutics

Kerensa Saljooqi, Associate Director, Clinical Operations, BlackThorn Therapeutics

BlackThorn’s data-driven approach to generating objective neuromarkers has allowed us to collect terabytes of data in our clinical trials. Keeping this data clean, organized, and accessible in a compliant manner is an obstacle we’re overcoming by implementing innovative technology solutions. This session will present BlackThorn’s lessons learned when awakening data from trials and our approach to develop a state-of-the-art, groundbreaking solution.

9:30 Sponsored Presentation (Opportunity Available)

10:00 Coffee Break in the Exhibit Hall

10:45 PLENARY KEYNOTE SESSION: Enabling Patient-Centric Clinical Trials

10:45 Chairperson Remarks: Patient-Centric Trials: How to Engage the Patients in a Clinical Study

Basker Gummadi, IT Strategy & Digital Transformation, Digital Innovation, Bayer U.S. LLC

Basker will share the results of the patients’ interaction and what is important to them and what keeps them engaged in a trial. He will also share his personal vision of how Digital technologies can help in this space.

10:55 KEYNOTE PRESENTATION: Patient-Centric Trials: Moving from What’s the Matter with Patients to What Matters to Patients

Lisa Shipley, Vice President, Global Digital Analytics, Merck

The overall percentage of potential patients that participate in clinical trial is very low. Engaging patients and removing barriers to patient participation in clinical trials is critically important to the development of new therapies to improve human health. Digital technologies are poised to improve patient participation and experience and shift from a site-centric to a patient-centric model. Pharmaceutical companies and CRO’s are exploring a number of different paradigms deploying technologies such as, telemedicine, wearables, and home-sampling.

11:15 KEYNOTE PANEL DISCUSSION: Going Virtual – Moving towards Patient-Centric, Site-Less Trials

Lisa Shipley, Vice President, Global Digital Analytics, Merck


Linnea Olson, Lung Cancer Patient Advocate


Laura Whitmore, Director, R&D Innovation, Corporate Projects, Otsuka


Basker Gummadi, IT Strategy & Digital Transformation, Digital Innovation, Bayer U.S. LLC


With the rise and integration of new technologies into clinical trials – mHealth, wearables, sensors, the internet of things – there is an unprecedented opportunity for revolutionizing how the industry performs clinical trials. New technology can help move clinical trials from sites directly into patient homes.

  • Virtual trials, decentralized trials, remote trials, site-less trials: What are we all talking about?
  • What are the latest successes and failures?
  • What are the barriers and challenges? How is the industry leveraging technology to make this a reality?
  • What are patients saying about their experience with virtual trials?
  • What does this mean for the future of clinical trials?

11:50 Keynote Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

12:35 pm Dessert Break in the Exhibit Hall

1:20 Close of Conference. Stay on to Attend Data & Tech Driven Clinical Trials.


Lee Yuan
(+1) 781-972-5404


(Companies A-O)
Ilana Quigley

(+1) 781-972-5457

(Companies P-Z)
Patty Rose
(+1) 781-972-1349


James Prudhomme
(+1) 781-972-5486