Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662.

摘要: AIMS: Previously published pharmacokinetic (PK) models for sunitinib and its active metabolite SU12662 were based on a limited dataset or lacked important elements such as correlations between metabolite. The current study aimed to develop an improved PK model that circumvented these limitations prove the utility of in treatment optimization clinical practice. METHODS: One thousand two hundred five plasma samples from 70 cancer patients collected three studies with SU12662. A semi-physiological was developed incorporating pre-systemic metabolism using non-linear mixed effects modelling (nonmem). Allometric scaling body weight applied. final used simulation different regimens. RESULTS: Sunitinib best described by one compartment model, respectively. Introduction formation strongly fit, compared solely systemic metabolism. clearance estimated at 35.7 (relative standard error (RSE) 5.7%) l h(-1) 17.1 (RSE 7.4%) h(-1), respectively kg patients. Correlation coefficients inter-individual variability both clearances, volumes distribution volume 0.53, 0.48 0.45, Simulation predicted correctly ratio who did not reach proposed targets efficacy. CONCLUSIONS: presented including superior previous many aspects.