Session 7: Commercial & Marketing
Linkage and Applications of Real-World Data with Insurance Claim, EHR, Whole Transcriptome Expression, Digital Pathology, etc., on 200K+ Prostate Cancer Patients
Seagle Liu
Seagle is the Director of Data Science
at Veracyte Inc. He leads a team of data scientists and data
engineers in large scale data analysis, machine learning and
data pipeline development. In the last 7 years working at
Veracyte, he led machine learning, bioinformatics, and data
development for three lab developed tests, as well as a
dozen research-use-only signatures. Many of these genomic
signatures are featured in publications on journals such as
Nature, Clinical Cancer Research, JAMA Oncology etc. His
team has also developed a fully scalable data processing
system that hosts over 100 signatures and over 200K whole
transcriptome genomic data. Recently, he led the data
linkage and analysis on whole-transcriptome genomic and
digital pathology data with real world data on over 200K
patients, which will be featured in today’s presentation.
Prior to joining Veracyte Inc, Seagle obtained his master
and PhD on statistics at UBC and worked as a data scientist
intern at Google.
Abstract:
From Data to Differentiation: The Tangible Impact of Generative AI and LLMs in Pharma Value Creation
Xiaoyan Wang
Dr. Xiaoyan Wang is a professor at
Department of Health Policy and Management of Tulane
University and Chief Scientist of IMO Health. She has
authored hundreds of research papers focused on transforming
healthcare and life sciences through AI innovation and has
held prominent leadership roles in AI advisory committees
and working groups across multiple scientific and
professional societies. She was recently VP of Healthcare
Analytics and Informatics and VP of Biopharma Solutions at
GeneDx Mount Sinai Genomics Inc. Before joining the
biopharma industry, she was a faculty member at the
University of Connecticut, UConn Health Center, and Mount
Sinai Health Systems bridging research, health services, and
teaching. She holds a Ph.D. in Biomedical Informatics and
NLP from Columbia University School of Medicine.
Abstract: The pharmaceutical industry is undergoing a transformation powered by generative AI and large language models (LLMs), creating unprecedented opportunities to leverage diverse real-world data and drive patient-centric value creation. This session delves into generative AI methodologies for unlocking actionable insights across three key areas: (1) social listening to capture and amplify patient voices, enabling the identification of unmet needs and preferences; (2) evidence synthesis from scientific literature to contextualize findings and inform decision-making; and (3) clinical data analysis from a physician’s perspective to validate real-world impact and outcomes. By integrating these AI-driven approaches into a cohesive intelligence framework, organizations can uncover actionable strategies that align commercial and marketing efforts with patient priorities. This session will highlight practical methodologies, showcase success stories, and explore how generative AI and LLMs can enhance innovation, differentiation, and value creation in the pharmaceutical sector, ultimately shaping a more patient-centered and data-driven future.