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Ideas
AI-assisted central imaging reads to cut endpoint cost and variability

AI-assisted central imaging reads to cut endpoint cost and variability

Measuring tumours on scans for trials is slow, expensive and inconsistent between readers. Software that measures lesions and flags changes, checked by a radiologist, could make trial endpoints cheaper and more reliable.

Overview Key papers1 Connected11

Overview

Validated AI segmentation and lesion-tracking tools perform RECIST 1.1 measurements with radiologist adjudication only on flagged discordances, replacing dual blinded independent central review. Performance is locked and validated against historical BICR-adjudicated trial datasets before use; regulators accept the tool under a qualification pathway.

Hypothesis

AI-assisted central reads will match BICR progression dates within one assessment interval in more than 95 percent of cases, at less than half the cost and with lower inter-reader variance, without changing trial conclusions on re-analysis.

Rationale

Central imaging review is one of the largest fixed costs in phase 3 oncology trials and reader disagreement drives discordance between local and central PFS. Segmentation models now perform at expert level on common lesion types.

Proposed test

Re-read the imaging archives of three completed phase 3 trials with the AI-assisted workflow and compare PFS hazard ratios and progression dates with the original BICR.

Maturity

early clinical

Who acts

engineering

Cost to try

Medium ($1M to $50M)

Years to first evidence

3

Bottlenecks it attacks

Trial design, endpoints and cost · A phase 3 trial takes years and hundreds of millions of dollars, and often answers a question that has already moved on.
AI that is built but not validated or deployed · Thousands of cancer AI models are published; a handful are in clinical use, and fewer have shown they help patients.

Key papers

observationalBMJ 2017390 citations

Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by European Medicines Agency: retrospective cohort study of drug approvals 2009-13

Two bottleneck pages and 15 idea pages on OnCo cite this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing pages listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.

Connected

Similar pages

Idea
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Idea
No clinical claims for imaging-derived biomarkers without phantom and standards compliance
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Require a randomised phase 2 before any phase 3
Shares Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by European Medicines Agency: retrospective cohort study of drug approvals 2009-13, Progression-free survival (PFS), Trial design, endpoints and cost.
Technology
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Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI in radiology, CT (computed tomography).
Technology
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Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI in radiology, CT (computed tomography).

technologies

AI in radiology CT (computed tomography)

companies

terms

Progression-free survival (PFS)RECIST

roadmaps

AI in oncology roadmap: pattern readers → foundation models → agents in the workflow Trial modernisation roadmap: the randomised trial → platforms and adaptive designs → decentralised, pragmatic and always-on

bottlenecks

AI that is built but not validated or deployed Trial design, endpoints and cost

key papers

Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by European Medicines Agency: retrospective cohort study of drug approvals 2009-13

ProvenanceLast edited 2026-09-10 · Jude Gomila · Graph health · diff · file

Sources & links

Bottleneck evidence (Trial design, endpoints and cost): Davis et al., Availability of evidence of benefits on survival and quality of life of cancer drugs approved by EMA 2009-13 (BMJ 2017)

Data

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How review works

Technologies

CT (computed tomography)
AI in radiology

Companies

Aidoc
Lunit

Terms

RECIST
Progression-free survival (PFS)

Not yet reviewedNeeds expert (scientific) review. Review this page or see the review queue and roster.

Model panel commentary is coming to this page: machine commentary, not clinical review.

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