Speaker Profile
Ph.D., Advisory Board Member, Compass Bioinformatics
Biography
Scott Kahn joined the Board of Directors at Exagen after serving as the Chief Information and Privacy Officer at LunaPBC where he was responsible for all informatics and data science strategy. Through his work with the Helmsley Charitable Trust, Scott has worked on data privacy and data sharing policies for biomedical organizations globally, and he serves on the Board of Directors for Rady Childrens Institute of Genomic Medicine and is the Chairman of the Board for Blue Circle Health. Previously Scott spend 11 years as Illumina's first Chief Information Officer, and he also was an executive leader in Illumina's Enterprise Informatics Unit. He organized the Genome Informatics Alliance for five years to drive interdisciplinary thought leadership focused on the future of Next Generation Sequencing (NGS) and its role in precision medicine, healthcare, and other applied markets.Scott was a Fellow Commoner of Churchill College at the University of Cambridge in England.
Talk
AI, -OMICs, and Precision Medicine
Clinical interpretation of variants generated by NGS are the foundation of genome based diagnostics. With the advance of machine learning techniques, automated, accurate, and efficient interpretation of variants expands the utility of clinical sequencing for broader diagnostics and development of therapeutics. We present the evolution of the InheriNext platform to solve for the current opportunity.
AI and Data Sciences Showcase:
Compass Bioinformatics
COMPASS BIOINFORMATICS INC. was founded by a team of engineers, scientists, and medical professionals. The primary focus of our genomic analysis software is accuracy, and we deliver accuracy with scalability, efficiency and simplicity.
Session Abstract – PMWC 2025 Silicon Valley
The PMWC 2025 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
