Drug development failures are costly and most happen because translational evidence is fragmented, slow to synthesize, and inconsistently applied across teams. This webinar explores how leading Translational Medicine teams at top global pharma organizations are using Causaly's agentic AI to reduce scientific uncertainty earlier in development and improve the Probability of Technical Success before billions are committed to late stage trials.

We'll walk through real world use cases across five core TxMed subfunctions: Translational Sciences, Biomarkers & Precision Medicine, Translational Safety, Clinical Pharmacology, and Translational Strategy. Showing how teams have cut weeks of manual research to hours, avoided unnecessary nonclinical study costs, surfaced evidence blind spots, and resolved important clinical safety concerns. You will see how a target hypothesis becomes a ranked, mechanism grounded evidence package in a single session, drawing on 40M+ publications and a dozen external databases and connectors.

In this episode

• A real use case, dissected step by step
• Cited, audit-ready outputs you can scrutinize
• Live Q&A with the Causaly Scientist running the workflow

Format:

• 30 minutes.
• Including a 15 minutes live demo.
• 5-10 minutes Q&A with the Causaly Science Team.