Skip to main content


Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Fig. 3 | Journal of Translational Medicine

Fig. 3

From: Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm

Fig. 3

Fitting results of the model-simulated tumor size in the patients’ cohort (N = 54), with the clinically observed tumor sizes. a Each point shows the fitted versus the clinically measured sum of diameters (SOD) of a patient, at the time an imaging assessment took place in the clinic. The observed SOD on the reference line equals to the fitted values. The personalization parameter ranges used for the simulation are specified in Table 3, and the values of the other model parameters are summarized in Table 1. Numerical analyses and simulations were performed using the ode15s Runge–Kutta ODE solver of Matlab R2016a (The Mathsworks, UK). From the initial time of the simulation (t = 0) to the time of treatment initiation (t = t1), the model in Tsur et al. [39], was simulated, and from t1 until the end of the simulation period, the model in Eq. (1) was simulated. The effect of pembrolizumab on the immune system and tumor was implemented here by the parameters \({\text{a}}_{\text{pem}}\) and \({\text{b}}_{\text{pem}}\). b Fitted versus observed SOD on a log scale. Values of 0 were excluded from the dataset for calculation of R-squared

Back to article page