EVALUATION OF BAYESIAN-ESTIMATION IN COMPARISON TO NONMEM FOR POPULATION PHARMACOKINETIC DATA-ANALYSIS - APPLICATION TO PEFLOXACIN IN INTENSIVE-CARE UNIT PATIENTS

The pharmacokinetics of pefloxacin (PF) were investigated in a populat ion of 74 intensive care unit patients receiving 400 mg bid as 1-hr in fusion using (i) Bayesian estimation (BE) of individual patient parame ters followed by multiple linear regression (MLR) analysis and (ii) NO NMEM analysis. The data consisted of 3 to 9 PF plasma levels per patie nt measured over 1 to 3 dosage intervals (total 113) according to four different limited (suboptimal) sampling 3-point protocols. Twenty-nin e covariates (including 15 comedications) were considered to explain t he interpatient variability. Predicted PF CL for a patient with median covariates values was similar in both BE/MLR and NONMEM analysis (4.0 2 and 3.92 L/hr, respectively). Bilirubin level and age were identifie d as the major determinants of PF CL by both approaches with similar p redicted magnitude of effects (about 40 and 30% decrease of median CL, respectively). Confounding effects were observed between creatinine c learance (26% decrease of PF CL in the BE/MLR model), simplified acute physiology score (a global score based on 14 biological and clinical variables) (18% decrease of median CL in the NONMEM model) and age (en tered in both models) which were highly correlated in our data base. H owever, both models predicted similar PF CL for actual subpopulations by using actual covariate values. Finally, the NONMEM analysis allowed identification of an effect of weight on CL (decrease of CL for weigh t < 65 kg) whereas the BE/MLR analysis predicted an increase of CL in patients treated with phenobarbital. In conclusion, both approaches al lowed identification of the major risk factors of PF pharmacokinetics in ICU patients. Their potential use at different stages of drug devel opment is discussed.