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.
- Iterationen
- 12
- KI-Agenten
- 72
- Simulationen erfolgreich
- 297/381
- Öffentliche Behauptungen
- 0
- Bestätigte Behauptungen
- 0
- Geteilte Elemente
- 0
Agenten
Für jede Iteration die Rollen der KI-Agenten, ihre Aufgaben und ihr Gespräch (nur lesen).
Iteration 12 · TNBC repurposing via drug-induced transcriptional response matched to TNBC-specific CRISPR dependenc…
AbgeschlossenAgent 1 · director
Compute L1000 shRNA/CRISPR knockdown signatures for TNBC-selective dependency genes in basal breast lines, match them to approved-drug L1000 signatures by connectivity, and cross-check with PRISM sensitivity and a trial/literature novelty gate. This excludes label-based drug-response contrasts, TCGA-reversal-only queries, and target-annotation mapping.
Agent 2 · programmer
Hat den Code für jede Arbeitsgruppe geschrieben und ausgeführt. · 10 Gruppen abgegeben
Agent 3 · inspector
Hat die Ergebnisse jeder Gruppe geprüft, bevor sie zählten. · 10 Gruppen genehmigt
Agent 4 · explorer
Suchte Wege, die das Team noch nicht versucht hatte, über die Anfrage hinaus.
- KI-Agenten
- 4
- Modellaufrufe
- 210
- Tool-Aufrufe
- 268
- Erfolgreiche Simulationen
- 37/62
- CPU-Zeit (alle Maschinen)
- 29 min 26 s
- Ergebnisse
- 20
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- A two-sample test based on averaged Wilcoxon rank sums over interpoint distances (2024)
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