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Integrating AI and ADME Tools to Refine Early-Stage Drug Discovery

Drug discovery teams frequently face late-stage trial surprises due to a lack of human pharmacokinetic insight during the initial development phases. A new webinar aims to address this gap by demonstrating how integrated, AI-driven ADME workflows can refine compound prioritization and significantly reduce inefficient synthesis cycles.

Bio & NewsJuly 14, 2026486 reads0

The upcoming session, hosted by Xtalks, focuses on shifting human pharmacokinetic (PK) projection into the earliest stages of the discovery funnel. By utilizing a complete Tier 1 ADME panel combined with automated data generation, researchers can turn individual assay results into actionable endpoints. This approach is designed to support full-series evaluation, allowing teams to identify promising compounds before committing to costly synthesis cycles.

Experts Jonathan Grob from Ginkgo Bioworks, Alex Taylor of Inductive Bio, and Tangible Scientific co-founder Ted Peters will lead the presentation. They will examine how moving lead-optimization-quality data into the hit identification phase improves overall decision-making. The live broadcast is scheduled for Thursday, July 30, 2026, at 12pm EDT, providing a platform for discovery teams to learn how these novel tools can increase the likelihood of success in human trials.

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