AIMS: To study the population pharmacokinetics of thioTEPA and its main metabolite TEPA in patients receiving high-dose chemotherapy consisting of thioTEPA (80-120 mg x m(-2) x day(-1)), cyclophosphamide (1000-1500 mg x m(-2) x day(-1)) and carboplatin (265-400 mg x m(-2) x day(-1)) for 4 days. METHODS: ThioTEPA and TEPA kinetic data were processed with a two-compartment model using the nonlinear mixed effect modelling program NONMEM. Interindividual variability (IIV), interoccasion variability (IOV) and residual variability in the pharmacokinetics were estimated. The influence of patient characteristics on the pharmacokinetics was also determined. RESULTS: A total number of 40 patients receiving 65 courses of chemotherapy was included. Clearance of thioTEPA (CL) was 34 l x h(-1) with an IIV and IOV of 18 and 11%, respectively. The volume of distribution of thioTEPA was 47 l (IIV = 7.5%; IOV = 19%). The fraction of thioTEPA converted to TEPA divided by the volume of distribution of TEPA was 0.030 l-1 (IIV = 39%; IOV = 32%) and the elimination rate constant of TEPA was 0.64 h(-1) (IIV = 27%; IOV = 32%). CL of thioTEPA was correlated with alkaline phosphatase and serum albumin. The volume of distribution of thioTEPA and the elimination rate constant of TEPA were correlated with total protein levels and body weight, respectively. CONCLUSIONS: A model for the description of the pharmacokinetics of thioTEPA and TEPA was developed. Factors involved in the interpatient variability of thioTEPA and TEPA pharmacokinetics were identified. Since, IOV of both thioTEPA and TEPA was equal to or smaller than IIV, therapeutic drug monitoring based on data of previous courses may be meaningful using this population model.
AIMS: To study the population pharmacokinetics of thioTEPA and its main metabolite TEPA in patients receiving high-dose chemotherapy consisting of thioTEPA (80-120 mg x m(-2) x day(-1)), cyclophosphamide (1000-1500 mg x m(-2) x day(-1)) and carboplatin (265-400 mg x m(-2) x day(-1)) for 4 days. METHODS:ThioTEPA and TEPA kinetic data were processed with a two-compartment model using the nonlinear mixed effect modelling program NONMEM. Interindividual variability (IIV), interoccasion variability (IOV) and residual variability in the pharmacokinetics were estimated. The influence of patient characteristics on the pharmacokinetics was also determined. RESULTS: A total number of 40 patients receiving 65 courses of chemotherapy was included. Clearance of thioTEPA (CL) was 34 l x h(-1) with an IIV and IOV of 18 and 11%, respectively. The volume of distribution of thioTEPA was 47 l (IIV = 7.5%; IOV = 19%). The fraction of thioTEPA converted to TEPA divided by the volume of distribution of TEPA was 0.030 l-1 (IIV = 39%; IOV = 32%) and the elimination rate constant of TEPA was 0.64 h(-1) (IIV = 27%; IOV = 32%). CL of thioTEPA was correlated with alkaline phosphatase and serum albumin. The volume of distribution of thioTEPA and the elimination rate constant of TEPA were correlated with total protein levels and body weight, respectively. CONCLUSIONS: A model for the description of the pharmacokinetics of thioTEPA and TEPA was developed. Factors involved in the interpatient variability of thioTEPA and TEPA pharmacokinetics were identified. Since, IOV of both thioTEPA and TEPA was equal to or smaller than IIV, therapeutic drug monitoring based on data of previous courses may be meaningful using this population model.
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