Cited by 265Computational Drug Discovery MethodsArtificial Intelligence in Healthcare and EducationMachine Learning in Materials Science

Assessing the impact of generative AI on medicinal chemistry

Walters, W. Patrick, Murcko, Mark·2020·Nature Biotechnology

Integrity signals

Registry

Crossref · 10.1038/s41587-020-0418-2

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Cites

Flagged first, then by citations

1 of the 23 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Walters, W. P., & Murcko, M.
Affiliations
Relay Therapeutics (United States) (US)
Corresponding author
Walters, W. Patrick
Venue
Nature Biotechnology
Published
2020-01-30
Volume
38
Issue
2
Pages
143-145
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W3003906593
Cited by
262
References
23
Citations by year
2026: 60 · 2025: 40 · 2024: 43 · 2023: 35 · 2022: 21 · 2021: 37 · 2020: 25 · 2019: 1
Type
dissertation
Language
en
Open access
closed
Locations
  • Nature Biotechnology (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 › Materials Science › Materials Chemistry › Machine Learning in Materials Science
Keywords
generative AI, medicinal chemistry, drug discovery, structure-based drug design, reinforcement learning, adenosine A2A receptor, AI impact assessment
MeSH terms
Artificial Intelligence, Chemistry, Pharmaceutical, Humans, Inhibitory Concentration 50, Quantitative Structure-Activity Relationship, Cell Line, Tumor, Protein Kinase Inhibitors, Drug Discovery

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review