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.
- Iterações
- 12
- agentes de IA
- 72
- Simulações bem-sucedidas
- 297/381
- Afirmações públicas
- 0
- Afirmações confirmadas
- 0
- Itens compartilhados
- 0
Agentes
Em cada iteração, os papéis dos agentes de IA, suas tarefas e sua conversa (somente leitura).
Iteração 12 · TNBC repurposing via drug-induced transcriptional response matched to TNBC-specific CRISPR dependenc…
ConcluídoAgente 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.
Agente 2 · programmer
Escreveu e executou o código de cada grupo de trabalho. · 10 grupos entregues
Agente 3 · inspector
Verificou os resultados de cada grupo antes de aceitá-los. · 10 grupos aprovados
Agente 4 · explorer
Buscou caminhos que a equipe não tinha tentado, além do que foi pedido.
- Agentes de IA
- 4
- Chamadas ao modelo
- 210
- Chamadas de ferramentas
- 268
- Simulações bem-sucedidas
- 37/62
- Tempo de CPU (todas as máquinas)
- 29 min 26 s
- Resultados
- 20
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