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name: 'cytokine-storm-analysis-agent' description: 'AI-powered cytokine release syndrome (CRS) and cytokine storm analysis for prediction, monitoring, and management in immunotherapy and infectious disease.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Cytokine Storm Analysis Agent

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.

When to Use This Skill

  • When monitoring CAR-T patients for cytokine release syndrome risk.
  • To predict CRS severity and timing post-immunotherapy.
  • For analyzing cytokine panels in sepsis and viral infections (COVID-19).
  • When guiding tocilizumab/siltuximab anti-IL-6 therapy decisions.
  • To distinguish CRS from ICANS, HLH, and other inflammatory syndromes.

Core Capabilities

  1. CRS Risk Prediction: ML models predict CRS development and severity from baseline factors (tumor burden, disease type, CAR-T product).

  2. Real-Time Monitoring: Track cytokine dynamics (IL-6, IFN-γ, IL-10, ferritin) with early warning alerts.

  3. Severity Grading: Automated ASTCT CRS grading using clinical parameters and biomarkers.

  4. Differential Diagnosis: Distinguish CRS from HLH/MAS, ICANS, infection, and tumor lysis syndrome.

  5. Treatment Guidance: AI-driven recommendations for tocilizumab, corticosteroids, and supportive care.

  6. Outcome Prediction: Model response to anti-cytokine therapy and overall outcomes.

Cytokine Panel Analysis

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

ASTCT CRS Grading (Automated)

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

Workflow

  1. Input: Cytokine levels, vital signs, laboratory values, treatment history.

  2. Risk Assessment: Baseline CRS risk stratification pre-therapy.

  3. Monitoring: Real-time cytokine tracking with trend analysis.

  4. Grading: Automated CRS grade assignment per ASTCT criteria.

  5. Differential: Rule out mimics (infection, HLH, ICANS).

  6. Treatment: Generate management recommendations.

  7. Output: CRS risk score, grade, differential diagnosis, treatment plan.

Example Usage

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

AI/ML Models

CRS Risk Prediction:

  • Features: tumor burden (LDH), lymphodepletion intensity, CAR-T dose, disease type
  • Model: Gradient boosting with SHAP interpretability
  • Performance: AUC 0.82-0.88 for severe CRS

Severity Trajectory:

  • Time-series modeling of cytokine dynamics
  • LSTM networks for temporal patterns
  • Early warning 24-48 hours before clinical deterioration

Treatment Response:

  • Tocilizumab response prediction
  • Corticosteroid escalation timing
  • ICU admission risk

Differential Diagnosis Decision Tree

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

Clinical Decision Support

Tocilizumab Indication:

  • Grade 2+ CRS
  • Rapidly rising cytokines
  • High-risk baseline features

Corticosteroid Indication:

  • Tocilizumab-refractory CRS
  • ICANS any grade
  • Grade 3+ CRS

Prerequisites

  • Python 3.10+
  • scikit-learn, XGBoost for ML
  • Time-series analysis libraries
  • FHIR client for EHR integration

Related Skills

  • CART_Design_Optimizer_Agent - For CAR-T design
  • TCell_Exhaustion_Analysis_Agent - For T-cell function
  • Clinical_NLP - For extracting symptoms from notes

Special Populations

  1. Pediatric: Different baseline cytokine ranges
  2. Post-COVID: Altered inflammatory responses
  3. Bridging Therapy: Impact on CRS risk
  4. Concurrent Infection: Confounding cytokine elevation

Author

AI Group - Biomedical AI Platform