AI's potential to accelerate drug discovery needs a reality check
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Unstructured data can also be used for subphenotyping, as shown by a recent study identifying three ADRD subtypes.
“Unstructured data can also be used for subphenotyping, as shown in the identification of three ADRD subtypes in a recent study.131”
From Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias (2026) · cites this paper as [131]
Our copy discusses AI in drug discovery, including candidate molecules and clinical trials (Abstract and section F; page numbers unavailable). Searches for ADRD subtypes, subphenotyping, and unstructured patient data found no passage addressing the claimed identification of three subtypes. (LLM, conf=0.75)
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Cites
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- Venue
- Nature
- Published
- 2023-10-10
- Volume
- 622
- Issue
- 7982
- Pages
- 217-217
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W4387473803
- Cited by
- 42
- References
- 4
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, drug discovery, drug development, clinical trials, independent verification
- MeSH terms
- Artificial Intelligence, Clinical Trials as Topic, Humans, Reproducibility of Results, Uncertainty, Drug Discovery
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