T-cell-engager cytokine-release network
A cytokine-network QSP model coupling drug exposure to resting, activated, cytotoxic, and exhausted T cells and to IL-6, IL-10, IL-1beta, IFN-gamma, and TNF-alpha dynamics.
- Therapeutic
- Blinatumomab and comparator T-cell agonists
- Target
- CD19, CD3, CD28, IL-6R / CD126
- Disease
- Cytokine-release syndrome
Biological model
A cytokine-network QSP model coupling drug exposure to resting, activated, cytotoxic, and exhausted T cells and to IL-6, IL-10, IL-1beta, IFN-gamma, and TNF-alpha dynamics.
Intervention
Blinatumomab and comparator T-cell agonists
Biological focus
CD19, CD3, CD28, IL-6R / CD126
Context
Cytokine-release syndrome
Model details
A cytokine-network QSP model coupling drug exposure to resting, activated, cytotoxic, and exhausted T cells and to IL-6, IL-10, IL-1beta, IFN-gamma, and TNF-alpha dynamics.
Modeled states
- AUC IL6 pg h mlpg*h/mL
Modeled dynamic state for auc il6 pg h ml.
- Cdrug nMnM
Modeled dynamic state for cdrug nm.
- IFNg pg mlpg/mL
Modeled dynamic state for ifng pg ml.
- IL10 pg mlpg/mL
Modeled dynamic state for il10 pg ml.
- IL1b pg mlpg/mL
Modeled dynamic state for il1b pg ml.
- IL6 pg mlpg/mL
Modeled dynamic state for il6 pg ml.
- TNFa pg mlpg/mL
Modeled dynamic state for tnfa pg ml.
- Tact cells ulcell/uL
Modeled dynamic state for tact cells ul.
- Tcyt cells ulcell/uL
Modeled dynamic state for tcyt cells ul.
- Texh cells ulcell/uL
Modeled dynamic state for texh cells ul.
- Trest cells ulcell/uL
Modeled dynamic state for trest cells ul.
Key readouts
- T-cell agonist concentrationnM
Model-derived readout for t-cell agonist concentration.
- Activated T cellscell/uL
Model-derived readout for activated t cells.
- IL-6pg/mL
Model-derived readout for il-6.
- IFN-gammapg/mL
Model-derived readout for ifn-gamma.
- TNF-alphapg/mL
Model-derived readout for tnf-alpha.
Explore this model
Choose a starting point to view its result. Adjust key model inputs when you want to explore a different outcome.
blinatumomab 28 ug/day continuous infusion through day 28
How do drug exposure and immune feedback shape T-cell activation and the timing and magnitude of cytokine release? Explore this biological starting configuration through T-cell agonist concentration, Activated T cells, IL-6, IFN-gamma, TNF-alpha. This is a mechanistic product exploration, not a paper-result reproduction.
Questions to explore
- How do drug exposure and immune feedback shape T-cell activation and the timing and magnitude of cytokine release?
Starting result
This result reflects the starting settings. Run your changes to update it.
Model inputs
Five scientist-facing controls at most.
Compare a parameter
How does one model input change the response?
How do drug exposure and immune feedback shape T-cell activation and the timing and magnitude of cytokine release?
CL L h
Model parameter controlling cl l h.
Exploratory range around the default value.
5 evenly spaced values in L/hour. Other model inputs and the simulation window stay fixed.
Interpret with care
- Interpret trajectories as deterministic model behavior, not as a patient-specific prediction or dosing recommendation.
- Paper-result and exact-anchor checks remain in the private validation lane and are not part of this public scenario.
Review the server-confirmed fixed price before starting the comparison.
Comparative response
End-of-window response across the selected parameter values.
Choose an exploratory range around the default, review the fixed price, and run the comparison.
