Case Study: Absci achieves faster, higher-quality AI-driven drug discovery with Benchling

Harnessing AI to create next-generation medicines

Absci is a Vancouver, Washington–based drug and target discovery company that combines deep‑learning AI and synthetic biology in its Integrated Drug Creation™ Platform to identify and develop next‑generation protein therapeutics. Rapid, cross‑team workflows and reliable, standardized data are essential to its AI models, but Absci was struggling with error‑prone spreadsheet handoffs, inconsistent data quality (duplicates/incompletes), and poor interoperability across systems.

By implementing Benchling, Absci established a machine‑readable request handoff model, a custom registry schema, and flexible APIs/data‑warehouse integrations that connect disparate datasets and automate metadata capture. The result was faster end‑to‑end screening, higher data quality and accessibility, increased operational efficiency, and more time for scientists to focus on research and model development.

Absci

Jonathan Eads

Vice President of Informatics