Can Generative-Model-Based Drug Design Become a New Normal in Drug Discovery?
Abstract
It is still rare that AI application examples with full DMTA (Design, Make, Test, Analysis) outcomes are reported. A recent study highlights that a generative model could be applied in the drug discovery process through an example in which ideas generated by an AI generative model were confirmed by following wet-lab works.
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AI/ML-based generative models are being incorporated into realistic experimental settings despite initial limitations and criticisms.
“Progressively, and despite initial limitations and criticisms,160 AI/ML-based generative models are being incorporated into realistic experimental settings.”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [160]
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- Authors
- Chen, H.
- Affiliations
- Guangzhou Regenerative Medicine and Health Guangdong Laboratory (CN)
- Corresponding author
- Chen, Hongming
- ORCID
- Chen, Hongming
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-12-16
- Volume
- 65
- Issue
- 1
- Pages
- 100-102
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W4200240318
- Cited by
- 21
- References
- 8
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 8 · 2023: 9 · 2022: 1
- FWCI
- 2.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Medicinal Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative models, artificial intelligence in drug discovery, generative drug design, wet-lab validation
- MeSH terms
- Deep Learning, Artificial Intelligence, Humans, Drug Design, Neural Networks, Computer, Drug Discovery
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