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Using OFF-X Data with In-House Information Sources to Build Artificial Intelligence Models

OFF-X is a translational safety intelligence portal built to help organizations identify toxicology and safety signals, mitigate safety liabilities, and de-risk early-stage assets. In this session, participants will learn how to use OFF-X API calls to integrate OFF-X translational safety data with in-house information sources. Attendees will then learn how to: build artificial intelligence models with high-quality curated data; assess potential safety liabilities to evaluate risk-benefit profiles; determine optimal secondary pharmacology drug screens to anticipate potential off-target toxicities; use reverse-pharmacology to identify the cause and mechanisms behind unexpected adverse events; and analyze biomedical literature to assess the potential safety signals identified in real-world evidence databases, such as FAERS (FDA Adverse Event Reporting System Electronic Submissions) or JADER (Japanese Adverse Drug Event Report). Please note: OFF-X is not licensed by the NIH Library, 

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