PURPOSE: Our aim was to develop an optimal sampling strategy for the description of the pharmacokinetics of rubitecan and its active metabolite 9-aminocamptothecin (9-AC) for use in phase II/III studies with oral rubitecan administered in a daily times five schedule. METHODS:Concentration-time data of rubitecan and 9-AC were obtained from 14 patients who had received 1.5 mg/m(2) per day rubitecan orally. Population pharmacokinetic analysis of both the parent and the metabolite was performed using the nonlinear mixed effect modelling program (NONMEM). Optimal sampling points were selected on the basis of the assessed population pharmacokinetic parameters using a D-optimality algorithm. RESULTS: The pharmacokinetics of both rubitecan and 9-AC were adequately described with a one-compartment model. The absorption rate constant, apparent volume of distribution and apparent clearance of rubitecan were 0.81 h(-1), 50 l and 1.7 l/h, respectively. For 9-AC the corresponding values of the apparent volume of distribution and the elimination rate constant were 51 l and 0.102 h(-1). Interindividual variability of the pharmacokinetic parameters ranged from 38% to 49%. For the first dose, optimal sampling points were 1, 3, 5, 8 and 24 h after dosing. Monte Carlo simulations indicated that the sampling schedule produced parameter estimates which were unbiased and precise. CONCLUSIONS: An optimal sampling schedule was derived which allowed assessment of the pharmacokinetic parameters of both the parent compound and its metabolite 9-AC after oral administration of rubitecan.
RCT Entities:
PURPOSE: Our aim was to develop an optimal sampling strategy for the description of the pharmacokinetics of rubitecan and its active metabolite 9-aminocamptothecin (9-AC) for use in phase II/III studies with oral rubitecan administered in a daily times five schedule. METHODS: Concentration-time data of rubitecan and 9-AC were obtained from 14 patients who had received 1.5 mg/m(2) per day rubitecan orally. Population pharmacokinetic analysis of both the parent and the metabolite was performed using the nonlinear mixed effect modelling program (NONMEM). Optimal sampling points were selected on the basis of the assessed population pharmacokinetic parameters using a D-optimality algorithm. RESULTS: The pharmacokinetics of both rubitecan and 9-AC were adequately described with a one-compartment model. The absorption rate constant, apparent volume of distribution and apparent clearance of rubitecan were 0.81 h(-1), 50 l and 1.7 l/h, respectively. For 9-AC the corresponding values of the apparent volume of distribution and the elimination rate constant were 51 l and 0.102 h(-1). Interindividual variability of the pharmacokinetic parameters ranged from 38% to 49%. For the first dose, optimal sampling points were 1, 3, 5, 8 and 24 h after dosing. Monte Carlo simulations indicated that the sampling schedule produced parameter estimates which were unbiased and precise. CONCLUSIONS: An optimal sampling schedule was derived which allowed assessment of the pharmacokinetic parameters of both the parent compound and its metabolite 9-AC after oral administration of rubitecan.
Authors: S-J Lee; M Gounder; E H Rubin; Jong Ming Li; Zheming Gu; A Thalasila; E Loyer; A P Kudelka; C F Verschraegen Journal: Invest New Drugs Date: 2008-07-04 Impact factor: 3.850
Authors: William C Zamboni; Ramesh K Ramanathan; Howard L McLeod; Sridhar Mani; Douglas M Potter; Sandra Strychor; Lauren J Maruca; Cristi R King; Laura L Jung; Robert A Parise; Merrill J Egorin; Todd A Davis; Sharon Marsh Journal: Invest New Drugs Date: 2006-09 Impact factor: 3.651