ウェビナー動画：次世代のバイオ医薬品開発 – 自動開発適性評価とAI駆動型予測モデリングのための統合プラットフォーム

次世代のバイオ医薬品の開発においては、モダリティの複雑化に伴う凝集や製剤不安定性、発現性の低さといった後期段階の課題が、開発遅延やコスト増加の要因となっています。本講演では、GenedataのAIプラットフォームを活用し、SEC・DLS・DSF・質量分析などの多様なデータを統合・解析することで、創薬初期からCMCにいたるまで継続的に開発適性を評価し、リスクの早期特定と意思決定の高度化を実現するアプローチを紹介しています。

The development of next-generation biotherapeutics, including multispecific antibodies, antibody-drug conjugates (ADCs), and complex modalities like RNA lipid nanoparticles, introduces significant developability and manufacturability challenges. Late-stage liabilities such as aggregation, formulation instability, and poor expression yield frequently compress timelines, create downstream bottlenecks, and lead to costly failures.

In this webinar, Jana Hersch, Head of Science at Genedata, presents a scalable enterprise AI platform that enables continuous developability assessment from early discovery through Chemistry, Manufacturing, and Controls (CMC). The system automates the capture, standardization, and analysis of multi-parametric assay data, including SEC, DLS, DSF, and mass spectrometry. Building on this foundation, the platform enables data modeling and AI-driven analytics and connects molecular context, experimental results, and predictive insights across the developability lifecycle. Identification of risk patterns helps teams intervene early, ultimately improving both efficiency and decision quality throughout biotherapeutic development.