Bayer Develops PRINCE Platform for Reliable Agentic AI in Drug Discovery
One of the most interesting projects my colleagues have done with LLMs has been building a system with Bayer to allow pharmaceutical researchers to query decades of information about studies buried in PDF reports. Sarang Sanjay Kulkarni describes its evolution from keyword-based search to an intelligent research assistant capable of answering complex questions and drafting regulatory documents. more…
Bayer AG, in collaboration with Thoughtworks, has developed the Preclinical Information Center (PRINCE), a cloud-hosted platform designed to address challenges in pharmaceutical drug development using agentic AI. PRINCE leverages Retrieval-Augmented Generation (RAG) and Text-to-SQL to integrate extensive safety study reports, transforming keyword-based search into an intelligent research assistant. The platform enhances data accessibility and research efficiency by enabling natural language querying and drafting regulatory documents. Key engineering decisions focused on context engineering and harness engineering for reliability and observability. PRINCE prioritizes trust through transparency, explainability, and human-in-the-loop integration, demonstrating AI's transformative potential in the pharmaceutical industry while ensuring compliance.
Bayer's PRINCE platform showcases the transformative potential of agentic AI in drug discovery, improving data accessibility and research efficiency while prioritizing trust and compliance.
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