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CONFERENCE PRESENTATION · SCDM 2023 Annual Conference
How Can Generative AI Transform Clinical Data Management?
- Session Type: Oral Presentation
- Topic: AI + Cognitive Tech
- Session Level: Intermediate
Overview
Clinical and scientific data collected from Electronic Data Capture (EDC) systems and third-party sources (e.g., lab data, biomarker, PK/PD data) during clinical trials involves intensive data exploration, visualization, and analysis for ensuring data quality and patient safety.
Current practices in clinical data management involve the complex process of data ingestion from multiple sources and often rely on data review tools. These tools require end users to navigate through numerous listings, reports, and dashboards to access the necessary insights. Unfortunately, creating these reports and dashboards demands significant time and effort for each study as they are integrated within study-specific data containers. Additionally, data cleansing involves extensive manual work, and gaining valuable insights from data using disparate analytics and visualization tools is challenging.
To address these challenges, generative AI technology emerges as a promising solution for revolutionizing clinical data management. By harnessing the power of generative AI in the analysis of clinical trial data, we can achieve more streamlined and accurate data ingestion, standardization, exploration, and analysis processes. Machine learning models empowered by generative AI can provide a faster setup of study data quality framework, automatic transformation of raw study data to data review models, identification of anomalies and discrepancies, generation of query texts, and automation of review and medical monitoring workflows.
In this session, we will provide an overview of Language Models (LLMs), which form the building blocks of generative AI. We'll explore how sponsors are leveraging Generative AI models in various use cases within clinical data management. This will include discussing the outcomes of different experiments and the insights gained from proof of concepts. Additionally, we'll examine how sponsors are strategizing to transition these use cases into production while addressing regulatory and data security requirements. The session will also offer an end-to-end system view, presenting the future state of clinical data management empowered by generative AI.
What You'll Learn
- Understand how clinical data management process efficiency can be improved through generative AI
- Sponsor experience in Selection and execution of Generative AI use cases in clinical data management
- Change management in people, process, and tools for implementing an AI based clinical data management solution
- Regulatory and compliance implications of generative AI based clinical data management solution
Meet the Presenters
Divya Doma
Abbvie
Divya Doma leads the Clinical Tech Strategy & Ops Teams for Oncology at AbbVie. In this role, Divya is responsible for Clinical Trial Database builds and manages Data Standardization for regulatory submissions. Divya has over 13 years’ of experience in the pharma industry. Prior to this role, Divya worked on various Clinical Technology solutions in the Data Management space across multiple AbbVie Therapeutic areas in Immunology, Neuroscience, and Women’s Health. Divya has an M.S. in Computer Science & Electrical Engineering from West Virginia University. Let’s Go…Mountaineers!
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Makesh Narasimhan
Senior Director, Product Management
Saama Technologies
Saama Technologies
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Sam Tomioka
Functional Director
Sam Tomioka has over 2 decades of experience in data science and technology in the pharmaceutical industry.
In his current role at Sunovion, he filed a U.S. patent application regarding a computational model and methods for selecting clinical trial subjects to reduce heterogeneity. Sam authored a technical paper on the novel computational model, and gave an invited talk at various conferences including Chelsea Innovation Lab regarding AI technology in clinical development. Additionally, Sam has developed an algorithm and a cloud-based application to generate patient narratives from structured clinical and safety data. Sam has given several talks on SDTM mapping and conversion, and natural language models for data standardization. Sam has managed clinical programmers and data scientists to support clinical development and provided guidance on approaches and methodologies on various projects.
Prior to Sunovion Pharmaceuticals, sam was a Senior Manager for Biostatistics and Data Management at Dainippon Sumitomo Pharma, where he led CDISC implementation and contributed to the psychometric validation of modified Toronto Clinical Neuropathy Score. Sam has given talks at Invivodata Electronic Patient Reported Outcomes Conference and CDISC Interchange Europe on Developing a Patient Reported Outcomes (PRO) strategy and strategy for CDISC SDTM conversion for FDA New Drug Application, respectively.
Sam Tomioka has over 2 decades of experience in data science and technology in the pharmaceutical industry.
In his current role at Sunovion, he filed a U.S. patent application regarding a computational model and methods for selecting clinical trial subjects to reduce heterogeneity. Sam authored a technical paper on the novel computational model, and gave an invited talk at various conferences including Chelsea Innovation Lab regarding AI technology in clinical development. Additionally, Sam has developed an algorithm and a cloud-based application to generate patient narratives from structured clinical and safety data. Sam has given several talks on SDTM mapping and conversion, and natural language models for data standardization. Sam has managed clinical programmers and data scientists to support clinical development and provided guidance on approaches and methodologies on various projects.
Prior to Sunovion Pharmaceuticals, sam was a Senior Manager for Biostatistics and Data Management at Dainippon Sumitomo Pharma, where he led CDISC implementation and contributed to the psychometric validation of modified Toronto Clinical Neuropathy Score. Sam has given talks at Invivodata Electronic Patient Reported Outcomes Conference and CDISC Interchange Europe on Developing a Patient Reported Outcomes (PRO) strategy and strategy for CDISC SDTM conversion for FDA New Drug Application, respectively.
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Prasanna Rao
Senior Director, Global Head of AI/ML, Pfizer and Chief
Pfizer
Prasanna Rao is an AI practitioner and Industry Thought Leader whose current role is Senior Director, Global Head of AI/ML for Data Management and Monitoring at Pfizer.He has over 30 years of experience in Information technology and Analytics, with 10+ years in Healthcare and Life Sciences.In his previous role as a Watson Solution Architect at IBM, he was instrumental in implementing many different AI systems from idea to implementation with various clients.In his current role, he works with various stakeholders, vendors, business SMEs, machine Learning developers, and data scientists to deliver innovation and drive adoption of AI.
Pfizer
Prasanna Rao is an AI practitioner and Industry Thought Leader whose current role is Senior Director, Global Head of AI/ML for Data Management and Monitoring at Pfizer.He has over 30 years of experience in Information technology and Analytics, with 10+ years in Healthcare and Life Sciences.In his previous role as a Watson Solution Architect at IBM, he was instrumental in implementing many different AI systems from idea to implementation with various clients.In his current role, he works with various stakeholders, vendors, business SMEs, machine Learning developers, and data scientists to deliver innovation and drive adoption of AI.
Earn CEUs
SCDM is authorized by IACET to offer 0.2 CEUs for this education program. Participants are eligible to receive CEUs upon successful completion of the digital assessment questionnaire linked to this session, within 30 days after the purchase of the conference session.
Price
SCDM members: $50
Non-members: $175
Not yet an SCDM member? Purchase this conference session and get a one-year membership with SCDM on us to enjoy all our educational programs and sessions at a discounted price.
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