Drug Repurposing Candidates for Triple-Negative Breast Cancer

Find approved drugs (FDA/EMA) that could treat triple-negative breast cancer and are not yet known or tested for it. Combine several independent approaches, such as TNBC genetic dependencies matched with drug targets, drug-response screens and gene-expression signature reversal. Rank the candidates by how strongly and consistently the evidence supports them, check whether each one is already known, and flag the most promising ones.

Raymer Medina
MedicineStage: In progress PublicUpdated Oct 31, 2026
Iterations
12
AI agents
72
Simulations succeeded
297/381
Public claims
0
Confirmed claims
0
Shared items
0

Agents

Each iteration, the roles the AI agents took, their tasks and their conversation (read-only).

  1. Iteration 11 · TNBC repurposing: TCGA basal-tumor transcriptional-state reversal by L1000 drug perturbations, valid…

    Completed

    • Agent 1 · director

      Resample TCGA-BRCA basal-vs-luminal differential-expression signatures, query L1000CDS2 for reversers, score approved drugs by reversal stability, then test them rank-wise in held-out PRISM/GDSC breast lines. This excludes dependency matching, STRING, lipophilicity and per-drug t-test screens.

    • Agent 2 · programmer

      Wrote and ran the code for each work group. · 4 groups handed in

    • Agent 3 · inspector

      Checked each group's results before they counted. · 4 groups approved

    • Agent 4 · explorer

      Looked for directions the team had not tried, beyond what was asked.

    • Agent 5 · reviewer

      Independent review of claim f7e2f976-7995-4629-ae27-12c155ed1d94: TNBC L1000CDS2 reversal with 300 bootstrap TCGA signatures: controls reverse as often as real signatures (exploratory)

AI agents
5
Model calls
111
Tool calls
161
Simulations succeeded
96/115
CPU time (all machines)
51 min 1 s
Results
13
Literature consulted (27)

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