AI-powered cytokine release syndrome (CRS) and cytokine storm analysis for prediction, monitoring, and management in immunotherapy and infectious disease.
The Cytokine Storm Analysis Agent provides comprehensive AI-driven analysis of cytokine release syndrome (CRS) and hyperinflammatory states. It integrates cytokine profiling, clinical parameters, and immunological markers for early prediction, severity grading, and treatment guidance in CAR-T therapy, sepsis, and viral infections.
CRS Risk Prediction: ML models predict CRS development and severity from baseline factors (tumor burden, disease type, CAR-T product).
Real-Time Monitoring: Track cytokine dynamics (IL-6, IFN-γ, IL-10, ferritin) with early warning alerts.
Severity Grading: Automated ASTCT CRS grading using clinical parameters and biomarkers.
Differential Diagnosis: Distinguish CRS from HLH/MAS, ICANS, infection, and tumor lysis syndrome.
Treatment Guidance: AI-driven recommendations for tocilizumab, corticosteroids, and supportive care.
Outcome Prediction: Model response to anti-cytokine therapy and overall outcomes.
| Cytokine | Role in CRS | Kinetics | Therapeutic Target |
|---|---|---|---|
| IL-6 | Central mediator | Early peak | Tocilizumab, Siltuximab |
| IFN-γ | T-cell activation | Early | Emapalumab |
| IL-1β | Inflammasome | Early | Anakinra |
| IL-10 | Regulatory | Variable | - |
| TNF-α | Pro-inflammatory | Early | Infliximab (caution) |
| IL-2 | T-cell expansion | Early | - |
| GM-CSF | Myeloid activation | Sustained | Lenzilumab |
| Grade | Fever | Hypotension | Hypoxia |
|---|---|---|---|
| 1 | ≥38°C | None | None |
| 2 | ≥38°C | Responsive to fluids | Low-flow O2 |
| 3 | ≥38°C | One vasopressor | High-flow O2 |
| 4 | ≥38°C | Multiple vasopressors | Ventilation |
Input: Cytokine levels, vital signs, laboratory values, treatment history.
Risk Assessment: Baseline CRS risk stratification pre-therapy.
Monitoring: Real-time cytokine tracking with trend analysis.
Grading: Automated CRS grade assignment per ASTCT criteria.
Differential: Rule out mimics (infection, HLH, ICANS).
Treatment: Generate management recommendations.
Output: CRS risk score, grade, differential diagnosis, treatment plan.
User: "Monitor this CAR-T patient's cytokine levels and predict CRS severity."
Agent Action:
python3 Skills/Immunology_Vaccines/Cytokine_Storm_Analysis_Agent/crs_analyzer.py \
--patient_data demographics.json \
--cytokines cytokine_panel.csv \
--vitals vital_signs.csv \
--labs laboratory_values.csv \
--cart_product tisagenlecleucel \
--day_post_infusion 5 \
--model crs_predictor_v3 \
--output crs_report.json
CRS Risk Prediction:
Severity Trajectory:
Treatment Response:
Fever + Elevated Cytokines
|
CAR-T context?
/ \
Yes No
| |
Hypotension? Infection workup
| |
CRS Sepsis vs viral
|
Neuro symptoms?
|
ICANS vs CRS
|
Ferritin >10,000?
|
HLH/MAS evaluation
Tocilizumab Indication:
Corticosteroid Indication:
AI Group - Biomedical AI Platform