Introduction: Intra-lymphocyte exposure of everolimus may be a better marker of therapeutic effect compared to trough whole blood concentrations. We aimed to develop pharmacokinetic population models and Bayesian estimators based on a limited sampling strategy for estimation of whole blood and intra-lymphocyte dose interval exposures of everolimus in renal transplants.
Methods: Full whole-blood and intra-lymphocyte concentration-time profiles of everolimus were obtained from 12 stable renal transplants on two different occasions, 4 weeks apart. The dataset was treated as 24 individual profiles and split into a development dataset (n=20) and a validation dataset (n=4). The pharmacokinetic model was developed using non-parametric modeling (Pmetrics) and its performances and those of the derived Bayesian estimator were evaluated in the validation set.
Results: A structural two compartment model with first-order elimination and two absorption phases described by a sum of two gamma distributions were developed. None of the tested covariates (age, gender, CYP3A5-genotype, hematocrit, fat-free mass) were retained in the final model. A limited sampling schedule of two whole blood samples at 0 and 1.5 hours and one intra-lymphocyte sample at 1.5 hours post dose provided accurate estimates of the area under the curve (AUC) in comparison with the trapezoidal reference AUC (relative bias ± SD = -3.9 ±10.6% and 4.1 ±12.3% for whole blood and intra-lymphocyte concentrations, respectively).
Conclusion: The developed model allows a simultaneous and accurate prediction of whole blood and intra-lymphocyte everolimus exposure based on two sample times and one intracellular concentrations determination. The model supplies a base for a feasible exploration of the relationships between intra-lymphocyte exposure and therapeutic effects in prospective trials.