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Model-Driven Hybrid AI Framework for End-to-End Autonomous Decision-Making in Drug Development

2026-02-06

Abstract excerpt

Decision-making in drug development spans heterogeneous stages from molecular design to clinical optimization, yet computer-aided workflows across stages remain fragmented, limiting traceability from evidence-derived clinical questions to simulation scenarios and decision endpoints. We present a model-driven hybrid AI framework for end-to-end decision support that treats PICO (Participants, Intervention, Compariso...

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Literature Corpus work
5f79a8d1-42cb-57ba-a4cc-513bee9784c6
DOI
10.64898/2026.02.03.703154
Open publication

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Model-Driven Hybrid AI Framework for End-to-End Autonomous Decision-Making in Drug DevelopmentDOI 10.64898/2026.02.03.703154
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