Paclitaxel (Taxol®) is now widely used against breast, ovarian and non-small-cell lung cancer. Anticancer agents generally have narrow therapeutic indices, often with myelosuppression (mainly neutropenia) as dose-limiting side effect. A further complicating factor is that paclitaxel when given as Taxol® has a nonlinear pharmacokinetic (PK) behaviour in plasma. Identifying risk groups more sensitive to chemotherapy due to either a PK or pharmacodynamic (PD) interindividual variability is of importance. The aim of the thesis was to develop predictive mechanism-based PK and PD models applicable for paclitaxel.
PK and PK/PD models were developed for patient data from studies with relatively frequent sampling or sparse sampling schedules. Population analyses were performed using the software NONMEM.
A pharmacokinetic model describing unbound, total plasma and blood concentrations of paclitaxel from known binding mechanisms was developed and validated. The nonlinear PK in plasma could to a large extent be explained by the micelle forming vehicle Cremophor EL (CrEL) and the unbound drug showed linear PK. Besides a binding component directly proportional to concentrations of CrEL, the model included both linear and nonlinear binding components in plasma and blood. Further, relations between the PK parameters and different demographic factors, including polymorphisms in the cytochrome P450s involved in paclitaxel metabolism, were investigated.
A semi-physiological PD model for chemotherapy-induced myelosuppression was developed and applied to different anticancer drugs. The model included a self-renewal for proliferating cells, transit compartments describing the delay in observed myelosuppression and a feedback parameter reflecting the effect on the bone marrow from growth factors that can result in an overshoot in white blood cells. The system-related parameters estimated showed consistency across drugs and the difference in the drug-related parameter reflected the relative bone marrow toxicity of the drugs. Relations between demographic factors and the PD parameters were identified.
The developed mechanism-based models promote a better understanding of paclitaxel PK and PD and may be used as tools in dosing individualisation and in development of dosing strategies for new administration forms and new drugs in the same area.