Fig. 1: Workflow: development of a mathematical model, integration with data by fitting the model to data, identifiability analysis on the estimated parameters. | npj Systems Biology and Applications

Fig. 1: Workflow: development of a mathematical model, integration with data by fitting the model to data, identifiability analysis on the estimated parameters.

From: Effective dose window for containing tumor burden under tolerable level

Fig. 1

Dynamical analysis of the model and the parameter estimates provide a ground for modulating dose depending on the patient-specific TTV (Ktol). Three different treatment strategies: continuous therapy with a dose belongs to EDW (defined in equation (4)), optimal dose continuous therapy (defined in equation (19)), and adaptive therapy (defined in equation (20)). S: drug-sensitive cell population (the green circle), R: drug-resistant cell population (the orange circle), negative control line between S and R indicates competitive stress on R by S. The vertical gray axis labeled S + R represents the tumor volume, while the horizontal axis shows the time. Solid black on the horizontal axis resembles treatment-on and the thin blue part resembles treatment-off. The orange horizontal solid line represents the TTV(Ktol) and the dashed line shows the growth of the tumor volume. Continuous therapy represses the competition due to the continuous reduction of the S cell population and ends up with a volume below the TTV(Ktol). The optimal therapy applies a dose that balances the competitive stress, the drug, and TTV(Ktol). Adaptive therapy utilizes treatment on and off which tilts the seesaw on each side between the drug and S to R inhibition during treatment on and off.

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