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The Ethereal
A Precedent-Guided Co-Scientist for Side-Effect-Aware Drug Redesign
July 03, 2026 ยท Grace Period ยท ๐ the ICML 2026 Workshop on AI for Science
Authors
Yujin Kim, Charmgil Hong
arXiv ID
2607.02944
Category
cs.LG: Machine Learning
Cross-listed
cs.AI
Citations
0
Venue
the ICML 2026 Workshop on AI for Science
Abstract
We propose PRECEDE, a precedent-guided co-scientist for side-effect-aware drug redesign that revises a parent compound to mitigate a specified side effect while preserving therapeutic function. Rather than isolated molecular generation, PRECEDE frames redesign as evidence-grounded reasoning over drug--side-effect associations, biomedical knowledge graphs, and precedents of safety-driven optimization, coordinated by an LLM orchestrator with explicit policies and human-review checkpoints. We position PRECEDE as a human-supervised AI-for-science workflow in which hypotheses remain auditable, falsifiable, and bounded by prior pharmacology.
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