Fig. 1.

Architecture of the method: in the pre-processing phase, sensitivity equations and Jacobians (both of the residuals and of the differential equations) are derived via symbolic manipulation, generating C code which is then linked to the initial value problem (IVP) solver, CVODES. The regularization scheme is selected according to the quality of the prior knowledge, and tuned following the procedure described in section “Tuning the regularization and prior knowledge”. Finally, global optimization with eSS2 is used to find the regularized estimate of the parameters. The resulting calibrated model can then be further evaluated using cross-validation, followed by additional post-regression and goodness-of-fit analysis