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A semi‐parametric approach to fitting a nonlinear mixed PK/PD model with an effect compartment using SAS
Author(s) -
Wang Jixian
Publication year - 2005
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.154
Subject(s) - extrapolation , nonlinear system , interpolation (computer graphics) , compartment (ship) , parametric statistics , biological system , mathematics , pharmacokinetics , parametric model , nonmem , computer science , chemistry , algorithm , mathematical optimization , statistics , pharmacology , physics , artificial intelligence , motion (physics) , medicine , oceanography , quantum mechanics , biology , geology
Abstract Modelling of the relationship between concentration (PK) and response (PD) plays an important role in drug development. The modelling becomes complicated when the drug concentration and response measurements are not taken simultaneously and/or hysteresis occurs between the response and the concentration. A model‐based approach fits a joint pharmacokinetic (PK) and concentration–response (PK/PD) model, including an effect compartment if necessary, to concentration and response data. However, this approach relies on the PK data being well described by a common PK model. We propose an algorithm for a semi‐parametric approach to fitting nonlinear mixed PK/PD models including an effect compartment using linear interpolation and extrapolation for concentration data. This approach is independent of the PK model, and the algorithm can easily be implemented using SAS PROC NLMIXED. Practical issues in programming and computing are also discussed. The properties of this approach are examined using simulations. This approach is used to analyse data from a study of the PK/PD relationship between insulin and glucose levels. Copyright © 2005 John Wiley & Sons, Ltd.