A POPULATION PHARMACOKINETIC MODEL FOR DOCETAXEL (TAXOTERE(R)) - MODEL-BUILDING AND VALIDATION

A sparse sampling strategy (3 samples per patient, 521 patients) was i mplemented in 22 Phase 2 studies of docetaxel (TaxotereR) at the first treatment cycle for a prospective population pharmacokinetic evaluati on. In addition to the 521 Phase 2 patients, 26 (data rich) patients f rom Phase I studies were included in the analysis. NONMEM analysis of an inner set of 280 patients demonstrated that docetaxel clearance (CL ) is related to al-acid glycoprotein (AAG) level, hepatic function (HE P), age (AGE), and body surface area (BSA). The index set population m odel prediction of CL was compared to that of a naive predictor (NP) u sing a validation set of 267 patients. Qualitatively, the dependence o f CL on AAG, AGE, BSA, and HEP seen in the index set population model was supported in the validation set. Quantitatively, for the validatio n set patients overall, the performance (bias, precision) of the model was good (7 and 21%, respectively), although not better than that of the NP. However, in all the subpopulations with decreased CL, the mode l performed better than the NP; the more the CL differed from the popu lation average, the better the performance. For example, in the subpop ulation of patients with AAG levels >2.27 g/L (n = 26), bias and preci sion of model predictions were 24 and 32% vs. 53 and 53%, respectively , for the NP. The prediction of CL using the model was better (than th at of the NP) in 73% of the patients. The population model was redeter mined using the whole population of 547 patients and a new covariate, albumin plasma level was found to be a significant predictor in additi on to those Sound previously. In the final model, HEP, AAG, and BSA ar e the main predictors of docetaxel CL.