OnCo
ideasIdea

Automated combination discovery: patient-sample screens feeding Bayesian platform trials

There are far more possible drug combinations than can ever be tried in patients. Test thousands on living samples of real tumours, then feed only the winners into adaptive trials.

The combination space of approved and investigational cancer drugs is astronomically large; combinations reach the clinic through intuition and commercial convenience. Functional precision medicine (ex vivo drug testing on patient cells, EXALT trial in haematological malignancies) and high-throughput organoid screening make empirical combination discovery on patient material feasible. The proposal is an integrated pipeline: standardised ex vivo combination screens on fresh samples from trial participants, machine learning to prioritise synergistic and resistance-preventing pairs, and a standing Bayesian platform trial that adds and drops combination arms based on pipeline output.

Hypothesis
Pipeline-prioritised combinations achieve response rates in the platform at least double those of historically selected combinations in the same settings.
Rationale
Empirical screening beat rational design in antibiotics and in EXALT; connecting the screen directly to a trial closes the loop that has been missing.
What would test it
Run the pipeline in relapsed acute myeloid leukaemia and metastatic colorectal cancer for three years; compare platform response rates with contemporaneous conventional combination trials.
Maturity
preclinical evidence
Who has to act
research
Cost to try
Large (over $50M)
Years to first evidence
6
Bottlenecks it attacks

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