ウェビナー動画：Sanofi社、バイオ医薬品のin vitro特性評価 - FAIRデータでAI時代に備える

Sanofi社では、NANOBODY^®創薬エンジンをExcelによる手作業のワークフローから、FAIRデータ原則に基づくAI駆動型のラボ環境へと進化させました。これにより、多様なNANOBODY^®フォーマットやターゲットに対応する高スループット解析を実現し、機械学習によるアッセイ最適化とリード選定への道を切り拓いています。

In this webinar, Pieter Kennis, Senior Principal Scientist Large Molecule Research at Sanofi, shares how the discovery engine for NANOBODY^® molecules evolved from fully manual workflows to a cutting-edge, AI-powered lab environment. Initially, screening and characterization campaigns relied heavily on human intervention and low-throughput data analysis using scattered spreadsheets and siloed data. Today, the team operates at the intersection of automation and artificial intelligence, guided by FAIR data principles and a commitment to scientific excellence. These are essential enablers for scalable, high-throughput analysis solutions that meet the growing complexity of NANOBODY^® formats and biological targets.

Pieter walks us through the phased integration of robotic and data workflows — from early semi-automated systems to fully integrated platforms, and from manual data entry to end-to-end automated data capture. This transformation has revolutionized how binding and functional assay data are generated, managed, and interpreted. The current systems support traceable, structured datasets and pave the way for machine learning models in assay optimization and lead candidate selection. Explore the challenges, breakthroughs, and strategic impact of embracing automation and FAIR data practices — key steps toward building the AI-powered lab of the future.