Translation

Area: definition. Apply the shared measurement protocol.

Estimated progress toward AI-managed drug discovery

20% 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 + 0 + 5 + 0 = 20/100, 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: Clinical phase-transition data provide measurable downstream progress. Heterogeneous cohorts and human-managed development prevent interpreting those rates as autonomous drug development. 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: Track inception cohorts by indication and modality; archive phase transitions and failures, define success consistently and use time-to-event methods. 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

Phase-transition success by indication and modality, using complete cohorts, explicit follow-up, and time-to-event methods for ongoing programs.

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: Measured descriptive clinical cohort. 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

2026 publication; cohort cutoff March 1, 2026: The study's cohort, with cutoff March 1, 2026, reports phase 1 and phase 2 success rates of 77.8% and 19.5%, respectively. AI-enabled clinical pipeline cohort study.

Interpretation and tracking value

Cross-sectional, heterogeneous AI-enabled assets are not a randomized comparison with conventional discovery. Definitions, pending outcomes and censoring prevent direct comparison with differently selected earlier cohorts.

Next comparable measurement

Track inception cohorts by indication and modality; archive phase transitions and failures, define success consistently and use time-to-event methods. Preserve this dated observation; append future results with their model/system version, denominator, budget and evidence level rather than overwriting it.