Track 12: Digitization of Clinical Development and Clinical Trials

Collect and Transform Raw Data into Actionable Insights to Accelerate and Improve Clinical Outcomes

May 4 - 5, 2022 ALL TIMES EDT

Data and digital technologies are changing traditional drug discovery and clinical development processes, and the pandemic has served to accelerate the digitization trend. Advancing clinical research and translational research requires transforming raw research data and biological insights into clean, actionable data for integration, visualization, and analysis. The Digitization of Clinical Development and Clinical Trials track explores new and innovative tools and techniques–digital health technologies, data analytics, machine learning, and artificial intelligence–and how they can be leveraged to address specific challenges faced across the drug discovery spectrum to accelerate the translation of scientific discoveries from the bench to medical care. Gain practical recommendations and real-world insights from case studies across pharma and academia.

Tuesday, May 3

7:00 am Registration Open (Plaza Level Lobby)
8:00 am Recommended Pre-Conference Workshops and Symposium*

On Tuesday, May 3, 2022 Cambridge Healthtech Institute is pleased to offer nine pre-conference workshops scheduled across three time slots (8:00-10:00 am, 10:30 am-12:30 pm, and 1:45-3:45 pm) and a Symposium from 8:25 am-3:45 pm. All 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 Wednesday-Thursday.

*Separate registration required. See Workshop page and Symposium page for details.

3:45 pm Session Break and Transition to Plenary Keynote

PLENARY KEYNOTE LOCATION: 210 (Overflow 208)

PLENARY KEYNOTE PROGRAM

4:00 pm

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
4:05 pm Innovative Practices Award
Mike Tarselli, PhD, Chief Scientific Officer, TetraScience
4:30 pm

Ask What IT Can Do for Bio...and What Bio Can Do for IT

George M. Church, PhD, Robert Winthrop Professor, Genetics, Harvard Medical School

IT for Bio: In May 2021, one haploid human genome (3.055 billion bp) was sequenced completely, but zero diploid. We have 7.7 billion diploid humans yet to be sequenced and correlated with their environments and traits in the Personal Genome Project. Plus, at least one genome from each of over 8.7 million eukaryotic species in the Earth Biogenome project. Plus, monitoring pathogenic and commensal bacteria, allergens, and viruses in the BioWeatherMap. Plus, ancient DNA. We are counting RNA molecules per cell in most (or all) cell types in humans, mice, and many other species throughout development and connectome (with imaging resolution up to 20 nm).   

Bio for IT: Reading and writing DNA has improved exponentially in cost (at least 60 million fold) and is increasingly used for storing non-biological data. The record for editing DNA in vivo is now 24,000 edits per cell and for storing data in vivo is about 1 terabyte per mouse. Enormous chemical and biological 'libraries' can perform 'Natural Computing' for tasks far beyond current von-Neumann silicon and quantum computers. The combination of these – machine learning + megalibraries (ML-ML) is already having commercial impact (e.g. Nabla, Manifold, Dyno, Patch). 

5:45 pm Welcome Reception in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)
7:00 pm Close of Day

Wednesday, May 4

7:00 am Registration Open and Morning Coffee (Plaza Level Lobby)

PLENARY KEYNOTE ROOM LOCATION: 210

PLENARY KEYNOTE PROGRAM

8:00 am

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
Zachary Powers, Chief Information Security Officer, Benchling
8:15 am

Accessing and Securing the Data that Drives Breakthroughs

Allison Proffitt, Editorial Director, Bio-IT World
Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago
Ari E. Berman, PhD, CEO, BioTeam, Inc.
Jonathan C. Silverstein, Chief Research Informatics Officer & Professor, Biomedical Informatics, University of Pittsburgh
Rebecca F. Rosen, PhD, Director, Office of Data Science and Sharing, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health

Life sciences research is generating massive amounts of data that should be accessible to collaborators and colleagues to enable breakthrough discoveries. However, ensuring sensitive data are shared securely in a manner that protects patient privacy and complies with myriad regulations is a daunting task, which often slows the pace of research. Our panel of leading practitioners will share insights on the challenges and best practices of managing protected research data.

9:30 am Coffee Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ROOM LOCATION: 203

DATA INFRASTRUCTURE AND PLATFORMS

10:15 am Organizer's Remarks
10:20 am

Chairperson's Remarks

Asha Mahesh, Director, Data & Analytics Engineering & Data Platforms, R&D Data Science, Janssen R&D
10:25 am

Beyond Data FAIRness in Collaborative Clinical Research

Alexander Sherman, Director, Center for Innovation and Bioinformatics, Massachusetts General Hospital

Collaboration among academia, non-profits, and industry are essential for the creation of disease-specific pre-competitive informational resources for applying AI/ML models in identification of disease biomarkers, patient subpopulations, and creating disease progression and disease staging models. To improve the Findability, Accessibility, Interoperability, and Reuse (FAIR) of digital knowledge, i.e. introduction of precision research, the clinical research community shall agree to operate under similar operational guidelines, from regulatory/legal, to patient identification, to data standards.

10:55 am

Linking Targets, Substances, and Conditions with the Global Substance Registration System (GSRS) to Organize Preclinical and Clinical Trial Data

Lawrence Callahan, PhD, Chemist, Global Substance Registration System/Office of Health Informatics, Office of Data, Analytics and Research, FDA

Preclinical and clinical trial data form the foundation of biomedical and regulatory science.  Typically, invitro preclinical tests indicate the potential potency and metabolic stability of a given substance and potential drug-drug interactions that should be avoided in initial clinical trials. Over the past five years the FDA and NCATS/NIH developed the Global Substance Registration System (GSRS) which defines substances in compliance with ISO IDMP standard. The system links active substances to products, targets, preclinical data, and clinical trials.  The talk will focus on the role the GSRS can play in the digitization of regulatory information.

11:25 am

ML-Enabled Biomarkers for Clinical Trials: A Framework for Productization and Deployment

Asha Mahesh, Director, Data & Analytics Engineering & Data Platforms, R&D Data Science, Janssen R&D
Oscar Carrasco-Zevallos, PhD, Associate Director, Data Science Platforms, Janssen R&D

Precision medicine and rare diseases clinical trials require screening of large patient cohorts for low-prevalence conditions and genetic alterations. Current screening methods are costly and time-consuming, potentially prolonging trial timelines and delaying regulatory approval. Janssen R&D has developed a scalable artificial intelligence and digital health platform for deploying novel tools in clinical trials that can decrease screening failure rates, reduce cost associated with standard diagnostics, and accelerate clinical development.


Santanu Sen, Vice President, Business Consulting Healthcare and Lifesciences, Virtusa
Christian Strauch, Chairman, inhive Group

The success of clinical trials depends on a pharmaceutical company's ability to conduct biological specimen analysis properly. Join the session to discover how Virtusa's Sample Collection, Orchestration and Reconciliation (SCORE) solution can help address the common barriers in the process. We'll be uncovering our state-of-the-art approach to ensure bio-sample data visibility  from their collection at study sites, their processing and storage in labs to potential secondary use, and more.

12:25 pm

Meaning-Based Computing beyond NLP: Integration of Text-Based Information in Digital Business for Faster Knowledge Transfer

Cedric Berger, Specialist, Head of Knowledge Extraction and Integration, F. Hoffmann-La Roche AG

Although submission packages are mostly composed of documents, health authorities increasingly request access to structured data. We present here our “Meaning-based Computing” (MBC) initiative and related digital products that improve knowledge extraction and integration from multiple and heterogeneous sources. Fetching knowledge from regulatory and manufacturing artefacts, we identify, categorise, and expose key knowledge elements (GMP process deviations, expert skills, regulatory risks) and expose them to solve concrete problems and secondary uses. MBC uses state-of-the art AI/NLP technology and agile/scrum product development to FAIRify our digital environment to fasten and funnel knowledge flow where it is needed most.

12:55 pm Session Break and Transition to Luncheon Presentation
1:05 pm Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own
1:50 pm Refreshment Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ANALYTIC AND VISUALIZATION TOOLS AND TECHNIQUES FOR IMPROVED DATA INSIGHTS

2:35 pm

Chairperson's Remarks

Laszlo Vasko, Senior Director, Clinical Innovation R&D IT, Janssen Pharmaceuticals, Inc.
2:40 pm

Engaging Deep Data Mining and AI-Powered Research Engine to Accelerate Biomarker Discovery

Hong Liu, Senior Director, Checkmate Pharmaceuticals

The explosive growth of genomic-assisted clinical trials provides great opportunity to investigate the mechanism of drug response and for personalized medicine. However, challenges emerge due to the heterogeneity of patient population and complexity of patient data. The talk will discuss approaches on how we (1) dive into deep data mining to stratify patient population and (2) apply AI-powered research engine to build explainable prediction models, which leads to novel insights into drug response mechanisms.

3:10 pm

The Future of Running Clinical Trials in Healthcare Systems

Laszlo Vasko, Senior Director, Clinical Innovation R&D IT, Janssen Pharmaceuticals, Inc.
Teddy Link, Implementation Director, Epic
Philip Lindemann, Vice President, Data and Analytics, Epic

Collecting clinical trial data vs. healthcare data primarily resided in parallel universes of Electronic Data Capture (EDC) and Electronic Health Records (EHR). Bridging the divide focused on secondary use of EHR data including EHR to EDC integration. What about the potential to run clinical trial research in EHR systems? This presentation will examine challenges and opportunities to fully run sponsored clinical research in EHRs from sponsor and EHR vendor perspectives.


3:40 pm

Social Media Listening for the Study of Dry Eye Disease

Lucia Schmidt, Postdoctoral Researcher, Roche

We made use of Social Media Listening to identify patient subpopulations with dry eye disease in a disease-specific forum. We also extracted the reported symptoms and preferred treatments to amplify the voice of the patient, supporting the discovery of potential problems with current treatments, the detection of unmet medical needs, and the deeper understanding of the disease burden and its effects on everyday life.

4:10 pm

Natural Language Generation for Clinical Study Reports

Jon Stevens, AI Language Capability Lead, AbbVie

Clinical study reports (CSRs) are long, detailed documents that combine study information contained in the clinical protocol with the data, results, and analyses from the study. In turn, CSRs serve as a basis for more concise manuscripts that eventually get submitted for publication in scientific journals. Both of these steps are time-consuming and expensive. We present two ongoing projects that leverage AI to guide and accelerate these steps.

4:40 pm Best of Show Awards Reception in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)
6:00 pm Close of Day

Thursday, May 5

7:30 am Registration Open and Morning Coffee (Plaza Level Lobby)

PLENARY KEYNOTE ROOM LOCATION: 210

PLENARY KEYNOTE PROGRAM

8:00 am

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World
Nate Raine, Director Data Custodians, Lifebit
8:15 am

Leveraging Large-Scale Human Data to Advance and Accelerate Drug Discovery

Shankar Subramaniam, PhD, Distinguished Professor of Bioengineering; Professor of Chemistry, Biochemistry and Nanotechnology; Adjunct Professor of Cellular & Molecular Medicine, University of California at San Diego

Advances in genomics technologies have led to generation of massive amounts of human data. This has catalyzed new insights into cellular processes in the normal and disease state and facilitated the search for safe and effective medicines. The UK Biobank, All of US and TopMed initiatives are exemplars of this approach. We highlight examples from our lab where meaningful insights have been obtained advancing our understanding of disease biology and its pharmacological application.

9:30 am Coffee Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ROOM LOCATION: 203

DIGITIZING CLINICAL RESEARCH WITH WEARABLES AND DIGITAL BIOMARKERS

10:15 am Organizer's Remarks
10:20 am

Chairperson's Remarks

Rama Rao, CEO & CoFounder, BLOQCUBE
10:25 am

Digital and Connected Healthcare

Anastasia Christianson, Vice President, R&D Business Technology, Janssen Pharmaceuticals

Physicians and scientists are increasingly leveraging digital health capabilities to enhance disease understanding, prevention, diagnosis, and treatment and to improve patient outcome through more targeted healthcare delivery. Likewise, patients are increasingly using digital health capabilities to 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.

10:55 am

Harnessing Digital Wearables and Biomarkers to Enable Decentralized Clinical Trial in Support of Biological Needs

Jordan Brayanov, PhD, Senior Director, R&D Digital Strategy, Takeda Pharmaceutical Co. Ltd.

There has been a substantial increase in the use of digital wearables and biomarkers in decentralized clinical trials (DCTs). DCTs may be more appealing to patients as they can decrease the need for travel to clinical sites, leading to improved recruitment and retention, and may also allow for clinical trials in indications previously thought to be unfeasible. Here we present a digitally-enabled DCT example along with technical and operational considerations.

11:25 am

Deploying Digital Technology in Clinical Development and Balancing the Site Burden

Aman Thukral, Director & Head, Clinical Systems & Digital Operations, AbbVie, Inc.

Pharmaceutical sponsors are deploying digital health tools in clinical development more than ever. These tools are incredibly helpful in acquiring real-time quality patient data. However, sites face an additional burden due to these technologies. The session will talk about the approach to balance the site burden.

11:55 am

Putting “Good” Back with “Night”: The Evaluation of Nocturnal Scratch and Sleep Digital Endpoints in Atopic Dermatitis

Carrie A. Northcott, PhD, Senior Director & Project Lead, Digital Medicine & Translational Imaging, Pfizer Inc.

Atopic dermatitis is often accompanied by unrelenting nighttime pruritus/scratching and sleep disruptions. Quantitatively evaluating nighttime scratch and sleep via accelerometry using digital wearables to monitor patients passively and continuously would provide insight into the disease and effectiveness of treatments. Key aspects of providing value in these assessments are that the methods and devices are vetted and verified to detect clinically meaningful changes.

12:25 pm

OneSource Enables Automated EHR to eCRF Data Capture in Regulatory-Grade Clinical Trials (Innovative Practices Awards Winner)

Adam L. Asare, PhD, Chief Data Officer, Quantum Leap Healthcare Collaborative; Director Of Information Technology, University of California San Francisco Medical Center
Cal Collins, CEO & Co-Founder, OpenClinica

A major expense in clinical trials is the collection and abstraction of clinical data. This expense is further compounded by human errors that require additional investments in data cleaning/validation. Enhancements in the efficiency and accuracy of data capture are important advances in controlling the rising costs of clinical trials. In a project collaboration between OpenClinica and Quantum Leap Healthcare Collaborative/UCSF, we have established a flexible framework for integration and completion of Electronic Case Report Forms (eCRFs) through automated, direct capture from Electronic Health Record (EHR) systems. OneSource, launched within a participant’s EHR patient chart, automatically populates structured eCRFs by extracting data directly from the EHR, without need of manual abstraction. Deployed at 8 clinical sites in the multicenter, adaptive phase 2 I-SPY-COVID-19 platform trial, we demonstrate a time savings of 61% over sites using manual data abstraction. Furthermore, at sites using OneSource, data errors were eliminated, leading to additional downstream cost savings in cleaning/validation costs. OneSource has the additional benefits of low implementation costs and reusability across sites.

Tanina Cadwell, Solutions Architect, Vyasa
Ken Berta, Global Business Lead, Life Sciences, Unstructured Data Solutions, Dell Technologies

Drug discovery requires analyzing numerous data sources such as clinical trials, pharmacology reports, and small compounds. While rich in insight, up to 80% of data is unstructured requiring organizations to spend significant time, talent and financial investment to successfully analyze these data sources. Colleagues from Vyasa and Dell Technologies will discuss how advancements in deep learning combined with innovations in compute hardware address these challenges to accelerate the drug discovery process.

1:05 pm Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own
1:50 pm Refreshment Break in the Exhibit Hall with Poster Viewing (Auditorium/Hall C)

ROOM CHANGE: 207

PATHWAYS TO DIGITAL TWIN IN MEDICINE

2:35 pm

Co-Chairperson's Remarks

H. Kim Lyerly, MD, FACS, George Barth Geller Distinguished Prof, Surgical Sciences & Applied Therapeutics, Duke University; Chair of Executive Council, Open Health Systems Laboratory (OHSL)
Anil Srivastava, President, Open Health Systems Laboratory (OHSL)
Martin Deutsch, Open Health Systems Laboratory (OHSL)
4:10 pm Close of Conference
2:40 pm

Pathways to Digital Twin in Medicine

H. Kim Lyerly, MD, FACS, George Barth Geller Distinguished Prof, Surgical Sciences & Applied Therapeutics, Duke University; Chair of Executive Council, Open Health Systems Laboratory (OHSL)
Eric Stahlberg, PhD, Director, Cancer Data Science Initiatives, Frederick National Laboratory for Cancer Research
Ken Buetow, PhD, Director, Computational Sciences and Informatics Program for Complex Adaptive Systems, Arizona State University
Kunhiparambath P. Haresh, MD, Asst Professor, All India Institute of Medical Sciences
Nicholas Siebenlist, MD, PhD, Solutions Leader, Public Health, C3 AI
Jane Yu, MD, PhD, Digital Architect, High Performance Computing, US Federal, Microsoft
B. Jayaram, PhD, Professor, International Centre of Excellence for Computational and Biomedical Sciences
Prashant Shah, Global Head of Artificial Intelligence, Health and Life Sciences & Senior Principal Engineer, Intel Corporation

The cancer patient digital twin is a multi-institutional public-private technology initiative providing clinical decision support at the point of care to neuro oncology. The cancer patient digital twin is a physician-driven, precision medicine application delivering AI/ML insights within the clinician workflow. The application delivers value out of the box with previously integrated data sets and customized clinician’s dashboards. The application provides an end-to-end solution leveraging reusable data models for rapid integration of new sets, further strengthening AI/ML performance, and supporting equitable healthcare models. Delivering these oncology insights at the point of care enhances patient outcomes, saves physicians times, and reduces medical costs.

4:00 pm

Welcome by Conference Organizer

Allison Proffitt, Editorial Director, Bio-IT World





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