armored-cart-design-agent
Design armored CAR-T cells with cytokine payloads and resistance mechanisms.
Maintainer FreedomIntelligence · Last updated April 1, 2026
Analyze drug response in patient-derived organoids for personalized therapy prediction.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/organoid-drug-response-agent
Skill Snapshot
Source Doc
Drug Response Analysis: Process organoid viability data to calculate IC50, AUC, and response metrics.
Patient-Organoid Concordance: Assess molecular fidelity between PDO and donor tumor.
Biomarker Discovery: Identify molecular features predicting drug sensitivity.
Combination Screening: Analyze drug synergy from combination matrices.
Clinical Translation: Project organoid findings to patient treatment recommendations.
Microenvironment Modeling: Analyze immune co-culture and CAF interactions.
| Feature | Organoids | Cell Lines | PDX |
|---|---|---|---|
| Patient fidelity | High | Low | High |
| Establishment rate | 60-90% | Variable | 30-50% |
| Turnaround | 4-8 weeks | Fast | 3-6 months |
| Throughput | Medium-high | Very high | Low |
| Microenvironment | Partial | None | Mouse |
| Cost | Medium | Low | High |
Input: Organoid drug screening data, organoid molecular profiles, patient tumor data.
QC: Assess organoid viability and growth metrics.
Response Calculation: Compute drug sensitivity metrics.
Concordance: Compare organoid to donor tumor molecular profiles.
Biomarker Analysis: Correlate sensitivity with molecular features.
Translation: Generate patient treatment recommendations.
Output: Drug rankings, biomarkers, recommended treatments.
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