A Precedent-Guided Co-Scientist for Side-Effect-Aware Drug Redesign
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 25 references that are in the map. First posted on arXiv 3 Jul 2026.
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4 of 25 references.
References · 4
- 2025Qwen3 Technical Reportcited by 8,820
- 2018Junction Tree Variational Autoencoder for Molecular Graph Generationcited by 652
- 2024DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaborationcited by 44
- 2025LIDDIA: Language-based Intelligent Drug Discovery Agentcited by 24
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