@ShiruiPan
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Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials @geochurch
1. This review explores the transformative potential of Large Language Models (LLMs) in drug discovery and development, from understanding disease mechanisms to optimizing clinical trials.
2. LLMs, like Geneformer and Chemcrow, are enabling unprecedented advancements in disease modeling, identifying therapeutic targets, and automating complex chemistry experiments.
3. A major highlight is how LLMs can reduce the time and cost of drug discovery by automating processes like molecule generation, reaction prediction, and protein-ligand interaction analysis.
4. The study presents the future of clinical trials, where LLMs streamline patient-trial matching, design trial protocols, and even predict trial outcomes by analyzing electronic health records.
5. In silico applications of LLMs now enable the design of novel therapeutic molecules, advancing areas like gene therapy and personalized medicine.
6. The role of LLMs in functional genomics, protein design, and biomolecular interaction prediction is leading to breakthroughs in target identification and validation.
7. This comprehensive framework showcases the broad impact of LLMs in every stage of drug discovery, pushing the boundaries of AI integration in pharmaceutical sciences.
@huanyeekoh @ShiruiPan
๐Paper: arxiv.org/abs/2409.04481โฆView quoted post on X
