Filling the massive AI drug discovery data gap.

Mullard A

DOI: 10.1038/d41573-026-00137-y
Published: 2026 Nov
Container: Nature reviews. Drug discovery
Publisher: Not recorded
Open access: unknown

Credibility signals

limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1038/d41573-026-00137-y,
  title = {Filling the massive AI drug discovery data gap.},
  author = {Mullard A},
  year = {2026},
  journal = {Nature reviews. Drug discovery},
  doi = {10.1038/d41573-026-00137-y},
  url = {https://doi.org/10.1038/d41573-026-00137-y}
}

RIS

TY  - JOUR
TI  - Filling the massive AI drug discovery data gap.
AU  - Mullard A
PY  - 2026
JO  - Nature reviews. Drug discovery
DO  - 10.1038/d41573-026-00137-y
UR  - https://doi.org/10.1038/d41573-026-00137-y
ER  -

APA

A, M. (2026). Filling the massive AI drug discovery data gap.. Nature reviews. Drug discovery. https://doi.org/10.1038/d41573-026-00137-y

Source records

pubmed · retrieved 2026-11-10T19:14:35.412Z