To prevent acute rejection episodes, it is important to reach adequate tacrolimus (TRL) exposure early after kidney transplantation. With a better understanding of the high variability in the pharmacokinetics of TRL, the starting dose can be individualized, resulting in a reduction in dose adjustments to obtain the target exposure. A population pharmacokinetic analysis was performed to estimate the effects of demographic factors, hematocrit, serum albumin concentration, prednisolone dose, TRL dose interval, polymorphisms in genes coding for ABCB1, CYP3A5, CYP3A4, and the pregnane X receptor on TRL pharmacokinetics. Pharmacokinetic data were prospectively obtained in 31 de novo kidney transplant patients randomized to receive TRL once or twice daily, and subsequently, the data were analyzed by means of nonlinear mixed-effects modeling. TRL clearance was 1.5-fold higher for patients with the CYP3A5*1/*3 genotype compared with the CYP3A5*3/*3 genotype (5.5 +/- 0.5 L/h versus 3.7 +/- 0.3 L/h, respectively). This factor explained 30% of the interindividual variability in apparent clearance (exposure). Also, a relationship between the pregnane X receptor A+7635G genotype and TRL clearance was identified with a clearance of 3.9 +/- 0.3 L/h in the A allele carriers versus 5.4 +/- 0.6 L/h in the GG genotype. Finally, a concomitant prednisolone dose of more than 10 mg/d increased the TRL apparent clearance by 15%. In contrast, body weight was not related to TRL clearance in this population. Because patients are typically dosed per kilogram body weight, this might result in underexposure and overexposure in patients, with a low and high body weight, respectively. This integrated analysis shows that adult renal transplant recipients with the CYP3A5*1/*3 genotype require a 1.5 times higher, fixed, starting dose compared with CYP3A5*3/*3 to reach the predefined target exposure early after transplantation.

High busulfan exposure is associated with increased toxicity, for example veno-occlusive disease, whereas low exposure results in less efficacy such as lower engraftment rates. Despite adjusting dose to body weight, interindividual variability in pharmacokinetics and thus drug exposure remained rather large. In this report, the contribution of genetic polymorphisms in the glutathione-S-transferases (GST) isozymes GSTA1, GSTM1, GSTP1, and GSTT1 to the pharmacokinetics of busulfan is studied retrospectively. Seventy-seven children, undergoing myeloablative conditioning for allogeneic hematopoietic stem cell transplantation, were treated with busulfan (Busulvex) during 4 days, receiving busulfan either in one single dose or dived in four doses every 6 hours. Genetic variants of GSTA1, GSTM1, GSTP1, and GSTT1 were determined by pyrosequencing. Pharmacokinetic parameters were estimated by using nonlinear mixed-effect modeling (NONMEM). Subsequently, a combined population pharmacokinetic-pharmacogenetic model was developed describing the pharmacokinetics of busulfan taking into account the GST polymorphisms. In the presented pediatric population, body weight appeared to be the most important covariate and explained a major part of the observed variability in the pharmacokinetics of busulfan. None of the studied polymorphisms in the genes encoding GSTA1 GSTM1, GSTP1, and GSTT1 nor combinations of genotypes were significant covariates. It was concluded that in children, variability in pharmacokinetics of busulfan could not be related to polymorphisms in GST.

A two-compartment pharmacokinetic model with lag-time describing the concentration-time profile of oral everolimus in renal transplant patients has been developed using pharmacokinetic modelling. Ideal body weight significantly influenced V(1)/F of everolimus; however, the selected polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR had no clinically relevant effect on everolimus pharmacokinetics. Everolimus C(trough) and C(2) as a limited sampling model can be used to accurately estimate everolimus systemic exposure, an improvement over the widely used C(trough) monitoring.

We conclude that switching immunosuppressive therapy from P/CsA/MPS to therapy with P/CsA or P/EVL at 6 months after renal transplantation is effective in preventing rejection. Double therapy with P/MPS after withdrawal of P/CsA resulted in an increase in severe acute rejection episodes. These results were the immediate reason to halt the P/MPS arm. Serum creatinine values at the latest follow-up (8+/-5 months after conversion and 14+/-5 months after transplantation) in the P/EVL group were lower than in the P/CsA group.

Treatment failure of CMV infections occurred less frequently in D+R- renal transplant patients on a sequential prophylaxis-preemptive regimen than in patients on a purely preemptive regimen. Antiviral resistance was observed infrequently and apparently played a minor role in treatment failure.

PurposeOptimal ciclosporin A (CsA) exposure in kidney transplant recipients is difficult to attain because of variability in CsA pharmacokinetics. A better understanding of the variability in CsA exposure could be a good means of individualizing therapy. Specifically, genetic variability in genes involved in CsA metabolism could explain exposure differences. Therefore, this study is aimed at identifying a relationship between genetic polymorphisms and the variability in CsA exposure, while accounting for non-genetic sources of variability.MethodsDe novo kidney transplant patients (n = 33) were treated with CsA for 1 year and extensive blood sampling was performed on multiple occasions throughout the year. The effects of the non-genetic covariates hematocrit, serum albumin concentration, cholesterol, demographics (i.e., body weight), CsA dose interval, prednisolone dose and genetic polymorphisms in genes encoding ABCB1, CYP3A4, CYP3A5, and PXR on CsA pharmacokinetics were studied using non-linear mixed effect modeling.ResultsThe pharmacokinetics of CsA were described by a two-compartment disposition model with delayed absorption. Body weight was identified as the most important covariate and explained 35% of the random inter-individual variability in CsA clearance. Moreover, concurrent prednisolone use at a dosage of 20 mg/day or higher was associated with a 22% higher clearance of CsA, hence lower CsA exposure. In contrast, no considerable genotype effects (i.e., greater than 30–50%) on CsA clearance were found for the selected genes.ConclusionsIt appears that the selected genetic markers explain variability in CsA exposure insufficiently to be of clinical relevance. Therefore, therapeutic drug monitoring is still required to optimize CsA exposure after administration of individualized doses based on body weight and, as this study suggests, co-administration of prednisolone.

CsA is commonly used after haematological SCT (HSCT) as GVHD prophylaxis. In solid organ transplantation, area under the blood concentration vs time curve (AUC) correlates with clinical outcome. However, in HSCT, it has not been determined whether the AUC is superior to trough level monitoring to optimize clinical efficacy of CsA therapy. Therefore, the aim of this study was to investigate the relationships between CsA trough levels and/or AUC early after HSCT with clinical outcome. A total of 91 children (1.1-17.3 years) were treated consecutively with HSCT for a haematological malignancy. CsA trough levels were obtained and were used to estimate the AUC, retrospectively, with a NONMEM (Non-Linear Mixed Effects Modelling) method. Subsequently, these exposure parameters were correlated to the occurrence of acute GVHD, relapse risk (RR) and OS. Low CsA trough levels were found to correlate with the occurrence of acute GVHD. In addition, a CsA AUC over 3000 mcg h/l in AML patients was associated with a higher RR and a reduced OS. This was not the case for ALL patients. Thus, monitoring CsA exposure early after HSCT and adjusting the CsA dose to a predefined target trough level and AUC may provide a tool to influence GVHD/GVL balance.

Patient variability in clinical response to the calcineurin inhibitors (CNIs) cyclosporine A and tacrolimus partly results from differences in CNI exposure. For tacrolimus drug interactions and genetic variability relate to tacrolimus exposure. Patients carrying the CYP3A5*1 allele have an increased tacrolimus metabolism, hence lower drug exposure. Adjusting the tacrolimus dose to this genotype is a tool to optimize therapy from a pharmacokinetic perspective. In contrast, no genetic variants have been found to clearly relate to cyclosporine A exposure. Despite therapeutic drug monitoring aimed at individualizing CNI therapy, patients still suffer from acute or chronic rejection and CNI toxicity. To further optimize CNI therapy future research may incorporate genetic polymorphisms in proteins involved in CNI pharmacodynamics (i.e. drug target). Proteins potentially relevant for drug response are calcineurin and the CNI binding proteins immunophilins. Moreover, since the expression of the nuclear factor of activated T-cells (NFAT) is reduced after calcineurin inhibition, genetic polymorphisms in the genes encoding NFAT may also be interesting candidates for studying inter-patient differences in CNI efficacy and toxicity. In addition, the existence of isoforms and differences in tissue distribution of the calcineurin protein could potentially explain variable drug response. At present, the focus has been on the metabolism of CNIs and not on variability in the drug target. Therefore, future improvements in CNI therapy are likely to occur from a systems pharmacology approach taking into account genetic markers for both CNI pharmacokinetics and pharmacodynamics.