Population pharmacokinetics of ciclosporin in haematopoietic allogeneic stem cell transplantation with emphasis on limited sampling strategy

AIM

To develop a population pharmacokinetic model of ciclosporin (CsA) in haematopoietic allogeneic stem cell transplantation to facilitate a limited sampling strategy to determine systemic exposure (area under the curve [AUC]), in order to optimize CsA therapy in this patient population.

METHODS

The pharmacokinetics of CsA were investigated prospectively in 20 patients following allogeneic haematopoietic stem cell transplantation (HSCT). CsA was given twice daily, as a 3 h i.v. infusion starting at day 1 of the conditioning scheme, and orally later on, when oral intake was well tolerated. Fluconazole was given as antimycotic prophylaxis. Pharmacokinetic parameter estimation was performed using nonlinear mixed effect modelling as implemented in the NONMEM program. A first order absorption model with lag time was compared with Erlang frequency distribution and Weibull distribution models. The influence of demographic variables on the individual empirical Bayesian estimates of clearance and distribution volume was tested. Subsequently two limited sampling strategies (LSS) were evaluated: posterior Bayesian fitting and limited sampling equations.

RESULTS

Twenty patients were included and 435 samples were collected after i.v. and oral administration of CsA. A two compartment model with first order absorption best described the data. Clearance (CL) was 21.9 l h⁻¹ (relative standard deviation [RSD]± 5.2%) with an inter-individual variability of 21%. The central volume of distribution (V_c) was 18.3 l (RSD ± 8.7%) with an inter-individual variability of 29%. Bioavailability (F) was 0.71 (RSD ± 9.9%) with and inter-individual variability of 25% and lag time (t_lag) was 0.44 h (RSD 5.5%). Weight, body surface area, haematocrit, albumin, ALAT and ASAT had no significant influence on pharmacokinetic parameters. The best multiple point combination for posterior Bayesian fitting, in terms of estimating systemic CsA exposure, appeared to be C0 + C2 + C3.Two selected LSS two time point equations and all selected three and four time point equations predicted de all AUC(0,12 h) within 15% bias and prediction.

CONCLUSIONS

The i.v. and oralcurves were best described with a two compartment model with first-order absorption with lag time. With the Bayesian estimators from this model, the area under the concentration−time curve in HSCT patients taking fluconazole can be estimated with only three blood samples (0, 2, 3 h) with a bias of 1% and precision of 4%.