Software for optimal design in population pharmacokinetics and pharmacodynamics: a comparison
F. Mentré (1), S. Duffull (2), I. Gueorguieva (3), A. Hooker (4), S. Leonov (5), K. Ogungbenro (6), S. Retout (1)
(1) INSERM, U738, Paris, France; Université Paris 7, Paris, France; AP-HP, Hôpital Bichat, Paris, France. (2) School of Pharmacy, University of Otago, Dunedin, NZ. (3) Global PK/PD, Lilly Research Centre, Windlesham, Surrey GU20 6PH, UK. (4) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. (5) GlaxoSmithKline Pharmaceuticals, Collegeville, PA 19426, USA. (6) Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, The University of Manchester, Manchester, UK
Introduction: Following the first theoretical work on optimal design for nonlinear mixed effect models, this research theme has rapidly grown both in methodological and application developments. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PK and PD models and proposed optimization of the experimental designs. In 2006, the Population Optimal Design of Experiments workshop was created with a meeting every year in May (www.maths.qmul.ac.uk/~bb/PODE/PODE2007.html). This year at PODE07 a special session was organized to present different software tools for population PK/PD optimal design and to compare them with respect to their statistical methodology.
Objectives: ) To present the different software tools; 2) To compare the statistical methods implemented in these tools; 3) To report the conclusion of the PODE07 meeting with respect to future software development in population PK/PD design.
Methods: The software tools will be compared with respect to: a) their availability, b) required language, c) library of PK or PD models, d) ability to deal with multiresponse models and/or with models defined by differential equations, e) approximations made to compute the Fisher information matrix, f) optimisation criteria, g)optimisation algorithms, h) ability to optimize design structure, i) ability to deal with constraints in sampling times, j) availability of optimisation trough sampling windows, k) assessment of user specified designs, l) ability to deal with unbalanced multiresponse designs, m) ability to deal with correlations between random effects, o) provided outputs ...
Results: The five software tools discussed at PODE07 are (in alphabetical order): PFIM (S. Retout & F. Mentré), PkStaMP (S. Leonov), PopDes (K. Ogungbenro & I. Gueorguieva) PopED (A. Hooker), and WinPOPT (S. Duffull). Tables comparing the software with respect to the different aspects described in the method section will be reported. The conclusions of the PODE07 meeting regarding future software development for optimal design in population PK/PD will be presented.
