Claim · 2024-04-30 · publication · Stated in source · Supported

Jayatunga et al. (Drug Discovery Today, published online 30 April 2024) state that a growing number of drugs and vaccines have been discovered using AI and analyse the clinical pipelines of what they call AI-native biotech companies.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons → bears on → A drug candidate discovered or designed with AI has entered human clinical trials

Where it appears

AI in science →

Claim and evidence

How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessonsbears on ↓A drug candidate discovered or designed with AI has entered human clinical trials

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2024-04-30 · publication Records dated 2024 →
Role: Context
Register (kind of text): Nonfiction
Missing element: Names no specific candidate in the abstract read; the criterion requires a named candidate stated to have begun human testing.

Scope and limitsThe record documents what this text states, in its register; it is not evidence that the proposition is true and implies no influence on or from any other text. Read in the Europe PMC record of the abstract only; the companies and molecules in the analysis were not read.

The evidence 01

primary sourceSupports the claim

How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons

Europe PMC (record of the PubMed abstract; article in Drug Discovery Today) · 2024-04-30

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Paraphrase

the authors say that a growing number of drugs and vaccines have been discovered using AI, and that they analysed the clinical pipelines of AI-native biotech companies.

Location in source Abstract (Europe PMC record, abstractText), second and fourth sentences

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-30

Source details and check notes

Authors: Kp Jayatunga M; Ayers M; Bruens L; Jayanth D; Meier C
Version: Retrieved for the candidate pack on 2026-10-30 (SHA-256 6264b8f15122449d0b3f0b4ab0251f46bad1fffa3ae7dcf40c5d4bd01868de32). Europe PMC REST core record (JSON) with the abstract; the publisher page (doi.org redirect to Elsevier) returned no readable text.
Canonical address: Open the canonical source ↗
Accessed: 2026-10-30
Language: English (en)
Attribution: Kp Jayatunga M, Ayers M, Bruens L, Jayanth D, Meier C, “How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons”, 2024-04-30.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, AI in biology (research/ai-in-biology). The paraphrase is Selekoa’s, written from the text retrieved for the candidate pack on 2026-10-30; it is not a quotation and was not machine-matched. Locator corrected at admission: the pipeline analysis is in the fourth sentence (cross-family check, item B111). A cross-family machine check (2026-10-30, item B111) re-read the record’s sources and found full support; its corrections were applied at admission. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. A passage of the document bears on the proposition without meeting its criterion; the record names the missing element. It is not an articulation and implies no influence.

Date. Electronic publication date as given by Europe PMC.

Record ID aib-arg-p3-jayatunga-2024