Candidate quality

Area: definition. Apply the shared measurement protocol.

Estimated progress toward AI-managed drug discovery

25% complete — judgment-based estimate as of November 7, 2026. Confidence: low. The scale starts at 0% before ChatGPT's public release in 2022 and ends at 100% when AI manages the field's continuing advancement without human participation. This rates the outcome's contribution to that transition, not the percentage of tasks solved, a measured fraction of the field, or time remaining.

The shared scoring rubric uses five equally weighted dimensions: execution, breadth, agenda-setting, validation, and sustained autonomous improvement. Points for this outcome are 10 + 5 + 5 + 5 + 0 = 25/100, in that order; each dimension has a maximum of 20. These component judgments make the estimate inspectable, but are not independently measured scores.

Reason for the estimate: One experimentally supported candidate demonstrates useful design assistance, but complete proposal-to-qualified-candidate rates and self-managed validation are unknown. The dated baseline below supplies the findings and source links used for this assessment. Unmeasured components receive no demonstrated-progress credit; missing evidence does not prove a missing capability.

What would move the score: Record all nominated candidates and prespecified assay thresholds; report each requirement and joint pass fraction, including failures. Higher autonomy scores additionally require AI to select worthwhile work, validate results and improve the process over repeated cycles without human research management, repair or adjudication. Lower the score if replication fails, quality regresses or previously hidden human assistance is found. Preserve this dated estimate when adding future assessments.

Measurement and acceptance rule

Fraction of candidates meeting prespecified potency, selectivity, exposure, and toxicity requirements in relevant assays.

Evidence requirements

Document exactly where AI contributed: target choice, molecular design, experiments, or trial operations. Compare matched programs and control for indication, modality, starting maturity, and selection bias. Use registered trial protocols, full outcome reporting, and independent analysis. Docking scores, animal responses, and biomarker changes must not be presented as established patient benefit.

Related milestones

See the area's proposed milestones. Proposed targets are distinct from the dated evidence below.

Baseline as of November 7 2026

Status: Validated candidate example; cohort pass fraction unknown. Sources accessed November 7, 2026. This is a documentary baseline, not an independent replication or an assertion of the worldwide best result. An unknown measurement is not zero.

Dated findings

2024 publication: AI-guided TNIK inhibitor INS018_055 showed drug-like properties and antifibrotic activity in preclinical models. TNIK inhibitor discovery, Nature Biotechnology.

Interpretation and tracking value

One selected candidate does not reveal the fraction of all proposals meeting potency, selectivity, exposure and toxicity thresholds. Sponsor participation and selection effects matter.

Next comparable measurement

Record all nominated candidates and prespecified assay thresholds; report each requirement and joint pass fraction, including failures. Preserve this dated observation; append future results with their model/system version, denominator, budget and evidence level rather than overwriting it.