A method for optimization of pharmacokinetic models

The authors have developed a method for optimizing nonlinear physiologicall y based pharmacokinetic (PBPK) models using Lagrangian-based or genetic alg orithms. The optimization method is demonstrated using PBPK models for phar macokinetics of nicotine, in which parameters that are not well established can be systematically varied to obtain optimized solutions based on experi mental data. The method provides valuable guidance in the determination of these model parameters. The PBPK model for nicotine was developed in C and linked with the ordinary differential equation package, CVODE. The model ca n, be run either stand-alone or under the control of an optimization packag e. The optimization is performed using SuperCode, running either a Lagrangi an-based (VMCON) or a genetic algorithm-based (GALIB) optimizer. To reduce computational time, SuperCode can carry out the optimization in parallel, u tilizing the Parallel Virtual Machine (PVM) message-passing software. Both the VMCON and GALLS optimizing algorithms have been used to fit the model t o experimental data for humans and Sprague-Dawley rats with good results.