The use of a modified Fedorov exchange algorithm to optimise sampling times for population pharmacokinetic experiments

The new algorithm based on the classical Fedorov exchange algorithm optimises the determinant of the population Fisher information matrix and performed better especially when dealing with complex designs at the expense of longer computing times.

Abstract

We propose a new algorithm for optimising sampling times for population pharmacokinetic experiments using D-optimality. The algorithm was used in conjunction with the population Fisher information matrix as implemented in MATLAB (PFIM 1.1 and 1.2) to evaluate population pharmacokinetic designs. The new algorithm based on the classical Fedorov exchange algorithm optimises the determinant of the population Fisher information matrix. The performance of the new algorithm has been compared with other existing algorithms including simplex, simulated annealing and adaptive random search. The new algorithm performed better especially when dealing with complex designs at the expense of longer computing times.