Search

Aim: Alemtuzumab is a monoclonal antibody used as induction immunosuppressive therapy in kidney transplantation. It targets CD52 on lymphocytes, inducing profound immune cell depletion upon administration. Owing to its off-label status in kidney transplantation, its pharmacokinetic characteristics are largely unknown in this setting, and its current fixed dosing algorithm originates from other populations. We developed a population pharmacokinetic model for alemtuzumab in kidney transplant recipients and investigated the potential of personalized alemtuzumab therapy., Methods: In total, 362 pharmacokinetic observations drawn 0-165 days after transplantation were available from 61 adult kidney transplant recipients who received two consecutive doses of 15 mg alemtuzumab subcutaneously. A population pharmacokinetic model was developed using nonlinear mixed-effects modelling and applied to simulate various dosing regimens., Results: The alemtuzumab concentration-time data were best described by a two-compartmental model with first-order absorption and parallel first-order and time-varying concentration-dependent elimination, with between-subject variability on the first-order elimination (39.6%) and central distribution volume (39.6%). Alemtuzumab pharmacokinetics varied with body size, rendering lighter individuals exposed to lympholytic alemtuzumab concentrations (>0.1 mg/L) for prolonged durations as compared to their heavier peers. This between-subject variability could be reduced through lean bodyweight-adjusted dosing, showing a twofold to threefold reduction in the slope of the median alemtuzumab exposure over the bodyweight range., Conclusion: Alemtuzumab displays substantial pharmacokinetic variability in kidney transplant recipients, which may warrant a personalized treatment strategy. Lean bodyweight-adjusted dosing poses an option for individualized dosing, but further evaluation of its potential clinical benefit is warranted., (© 2022 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Aims: Immunosuppressant and kidney function monitoring are crucial for kidney transplant recipient follow-up. Microsamples enable remote sampling and minimise patient burden as compared to conventional venous sampling at the clinic. We developed a liquid chromatography-tandem mass spectrometry assay to quantify tacrolimus, mycophenolic acid (MPA), creatinine and iohexol in dried blood spot (DBS), and volumetric absorptive microsample (VAMS) samples., Methods: The assay was successfully validated analytically for all analytes. Clinical validation was conducted by direct comparison of paired DBS, VAMS and venous reference samples from 25 kidney transplant recipients. Patients received iohexol 5-15 minutes before immunosuppressant intake and were sampled 0, 1, 2 and 3 hours thereafter, enabling tacrolimus and MPA area under the concentration-time curve (AUC) and creatinine-based and iohexol-based glomerular filtration rate (GFR) estimation. Method agreement was evaluated using Passing-Bablok regression, Bland-Altman analysis and the percentages of values within 15-30% of the reference (P 15 -P 30 ) with a P 20 acceptance threshold of 80%., Results: For DBS samples, method agreement was excellent for tacrolimus trough concentrations (n = 25, P 15  = 92.0%) and AUCs (n = 25; P 20  = 95.8%) and adequate for creatinine-based GFR trend monitoring (n = 25; P 20  = 80%). DBS-based MPA AUC assessment showed suboptimal agreement (n = 16; P 20  = 68.8%), but was considered acceptable given its P 30 of 100%. The assay performed inadequately for DBS-based iohexol GFR determination (n = 24; P 20  = 75%). The VAMS technique generally showed inferior performance, but can be considered for certain situations., Conclusion: The assay was successfully validated for tacrolimus, MPA and creatinine quantification in DBS samples, enabling simultaneous remote kidney function trend monitoring and immunosuppressant therapeutic drug monitoring in kidney transplant recipients., (© 2022 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing., Competing Interests: Declarations of interest The authors declare no conflicts of interests in relation to this work., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Iohexol plasma clearance-based glomerular filtration rate (GFR) determination provides an accurate method for renal function evaluation. This technique is increasingly advocated for clinical situations that dictate highly accurate renal function assessment, as an alternative to conventional serum creatinine-based methods with limited accuracy or poor feasibility. In the renal transplantation setting, this particularly applies to living renal transplant donor eligibility screening, renal transplant function monitoring and research purposes. The dependency of current iohexol GFR estimation techniques on extensive sampling, however, has limited its clinical application. We developed a population pharmacokinetic model and limited sampling schedules, implemented in the online InsightRX precision dosing platform, to facilitate pragmatic iohexol GFR assessment., Methods: Iohexol concentrations (n = 587) drawn 5 min to 4 h after administration were available from 67 renal transplant recipients and 41 living renal transplant donor candidates with measured iohexol GFRs of 27-117 mL/min/1.73 m 2 . These were split into a model development (n = 72) cohort and an internal validation (n = 36) cohort. External validation was performed with 1040 iohexol concentrations from 268 renal transplant recipients drawn between 5 min and 4 h after administration, and extended iohexol curves up to 24 h from 11 random patients with impaired renal function. Limited sampling schedules based on one to four blood draws within 4 h after iohexol administration were evaluated in terms of bias and imprecision, using the mean relative prediction error and mean absolute relative prediction error. The total deviation index and percentage of limited sampling schedule-based GFR predictions within ± 10% of those of the full model (P 10 ) were assessed to aid interpretation., Results: Iohexol pharmacokinetics was best described with a two-compartmental first-order elimination model, allometrically scaled to fat-free mass, with patient type as a covariate on clearance and the central distribution volume. Model validity was confirmed during the internal and external validation. Various limited sampling schedules based on three to four blood draws within 4 h showed excellent predictive performance (mean relative prediction error < ± 0.5%, mean absolute relative prediction error < 3.5%, total deviation index < 5.5%, P 10 > 97%). The best limited sampling schedules based on three to four blood draws within 3 h showed reduced predictive performance (mean relative prediction error < ± 0.75%, mean absolute relative prediction error < 5.5%, total deviation index < 9.5%, P 10 ≥ 85%), but may be considered for their enhanced clinical feasibility when deemed justified., Conclusions: Our online pharmacometric tool provides an accurate, pragmatic, and ready-to-use technique for measured GFR-based renal function evaluation for clinical situations where conventional methods lack accuracy or show limited feasibility. Additional adaptation and validation of our model and limited sampling schedules for renal transplant recipients with GFRs below 30 mL/min is warranted before considering this technique in these patients., (© 2021. The Author(s).)

Background and Objective: The immunosuppressant everolimus is increasingly applied in renal transplantation. Its extensive pharmacokinetic variability necessitates therapeutic drug monitoring, typically based on whole-blood trough concentrations (C 0 ). Unfortunately, therapeutic drug monitoring target attainment rates are often unsatisfactory and patients with on-target exposure may still develop organ rejection. As everolimus displays erythrocyte partitioning, haematocrit-normalised whole-blood exposure has been suggested as a more informative therapeutic drug monitoring marker. Furthermore, model-informed precision dosing has introduced options for more sophisticated dose adaptation. We have previously developed a mechanistic population pharmacokinetic model, which described everolimus plasma pharmacokinetics and enabled estimation of haematocrit-normalised whole-blood exposure. Here, we externally evaluated this model for its utility for model-informed precision dosing., Methods: The retrospective dataset included 4123 pharmacokinetic observations from routine clinical therapeutic drug monitoring in 173 renal transplant recipients. Model appropriateness was confirmed with a visual predictive check. A fit-for-purpose analysis was conducted to evaluate whether the model accurately and precisely predicted a future C 0 or area under the concentration-time curve (AUC) from prior pharmacokinetic observations. Bias and imprecision were expressed as the mean percentage prediction error (MPPE) and mean absolute percentage prediction error (MAPE), stratified on 6 months post-transplant. Additionally, we compared dose adaptation recommendations of conventional C 0 -based therapeutic drug monitoring and C 0 - or AUC-based model-informed precision dosing, and assessed the percentage of differences between observed and haematocrit-normalised C 0 (∆C 0 ) and AUC (∆AUC) exceeding ± 20%., Results: The model showed adequate accuracy and precision for C 0 and AUC prediction at ≤ 6 months (MPPE C0 : 8.1 ± 2.5%, MAPE C0 : 26.8 ± 2.1%; MPPE AUC : - 9.7 ± 5.1%, MAPE AUC : 13.3 ± 3.9%) and > 6 months post-transplant (MPPE C0 : 4.7 ± 2.0%, MAPE C0 : 25.4 ± 1.4%; MPPE AUC : - 0.13 ± 4.8%, MAPE AUC : 13.3 ± 2.8%). On average, dose adaptation recommendations derived from C 0 -based and AUC-based model-informed precision dosing were 2.91 ± 0.01% and 13.7 ± 0.18% lower than for conventional C 0 -based therapeutic drug monitoring at ≤ 6 months, and 0.93 ± 0.01% and 3.14 ± 0.04% lower at > 6 months post-transplant. The ∆C 0 and ∆AUC exceeded ± 20% on 13.6% and 14.3% of occasions, respectively., Conclusions: We demonstrated that our population pharmacokinetic model was able to accurately and precisely predict future everolimus exposure from prior pharmacokinetic measurements. In addition, we illustrated the potential added value of performing everolimus therapeutic drug monitoring with haematocrit-normalised whole-blood concentrations. Our results provide reassurance to implement this methodology in clinical practice for further evaluation.

Aims: Tacrolimus and mycophenolic acid dosing after renal transplantation is individualized through therapeutic drug monitoring (TDM). Home-based dried blood spot (DBS) sampling has the potential to replace conventional TDM sampling at the clinic. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed to quantify tacrolimus and mycophenolic acid in DBS and clinically validated for abbreviated area under the concentration-time curve (AUC) monitoring using an innovative volumetric DBS sampling device., Methods: Clinical validation was performed by direct comparison of paired DBS and whole blood (WB) (tacrolimus) and plasma (mycophenolic acid) concentrations and AUCs. Agreement was evaluated using Passing-Bablok regression, Bland-Altman analysis and DBS-to-WB predictive performance. TDM dosing recommendations based on both methods were compared to assess clinical impact., Results: Paired tacrolimus (n = 200) and mycophenolic acid (n = 192) DBS and WB samples were collected from 65 kidney(-pancreas) transplant recipients. Differences for tacrolimus and mycophenolic acid were within ±20% for 84.5% and 76.6% of concentrations and 90.5% and 90.7% of AUCs, respectively. Tacrolimus and mycophenolic acid dosing recommendation differences occurred on 44.4% and 4.7% of occasions. Tacrolimus DBS dosing recommendations were 0.35 ± 0.14 mg higher than for WB and 8 ± 3% of the initial dose. Mycophenolic acid DBS dosing recommendations were 23.3 ± 31.9 mg lower than for plasma and 2 ± 3.5% of the initial dose., Conclusions: Tacrolimus and mycophenolic acid TDM for outpatient renal transplant recipients, based on abbreviated AUC collected with a DBS sampling device, is comparable to conventional TDM based on WB sampling. Patient training and guidance on good blood-spotting practices is essential to ensure method feasibility., (© 2018 The British Pharmacological Society.)

Aims: This study aimed at identifying pharmacological factors such as pharmacogenetics and drug exposure as new predictive biomarkers for delayed graft function (DGF), acute rejection (AR) and/or subclinical rejection (SCR)., Methods: Adult renal transplant recipients (n = 361) on cyclosporine-based immunosuppression were followed for the first 6 months after transplantation. The incidence of DGF and AR were documented as well as the prevalence of SCR at 6 months in surveillance biopsies. Demographic, transplant-related factors, pharmacological and pharmacogenetic factors (ABCB1, CYP3A5, CYP3A4, CYP2C8, NR1I2, PPP3CA and PPP3CB) were analysed in a combined approach in relation to the occurrence of DGF, AR and prevalence of SCR at month 6 using a proportional odds model and time to event model., Results: Fourteen per cent of the patients experienced at least one clinical rejection episode and only DGF showed a significant effect on the time to AR. The incidence of DGF correlated with a deceased donor kidney transplant (27% vs. 0.6% of living donors). Pharmacogenetic factors were not associated with risk for DGF, AR or SCR. A deceased donor kidney and acute rejection history were the most important determinants for SCR, resulting in a 52% risk of SCR at 6 months (vs. 11% average). In a sub-analysis of the patients with AR, those treated with rejection treatment including ATG, significantly less frequent SCR was found in the 6-month biopsy (13% vs. 50%)., Conclusions: Transplant-related factors remain the most important determinants of DGF, AR and SCR. Furthermore, rejection treatment with depleting antibodies effectively prevented SCR in 6-month surveillance biopsies., (© 2016 The British Pharmacological Society.)

The mammalian target of rapamycin (mTOR) inhibitors sirolimus and everolimus have shown their efficacy in kidney transplantation, but their wider introduction has been limited by relative high discontinuation rates. Their main advantage compared with calcineurin inhibitors (CNIs) is their relative lack of nephrotoxicity. They differ mainly in pharmacokinetic characteristics and have variable inter- and intra-individual pharmacokinetics. They are metabolized by cytochrome (CYP)-3A4/5 and CYP2C8 enzymes and are substrates for P-glycoprotein (P-gp). Their most important adverse effects are thrombocytopenia, leukopenia, hypercholesterolemia, stomatitis, diarrhea, and, although rare, interstitial pneumonitis. The narrow therapeutic window makes therapeutic drug monitoring (TDM) essential to prevent toxicity or rejection. As we discuss here, the main future challenge is to further optimize mTOR inhibitor (mTORi)-based immunosuppressive therapy., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background and Objective: Everolimus is a novel macrolide immunosuppressant used in the prevention of acute and chronic rejection of solid organ transplants. Everolimus is being actively investigated worldwide as a non-nephrotoxic alternative for calcineurin inhibitors. Its highly variable pharmacokinetics and narrow therapeutic window make it difficult to maintain an adequate exposure to prevent serious adverse effects. The primary objective of this study was to improve prediction of everolimus systemic exposure in renal transplant patients by describing the pharmacokinetics of everolimus and identifying the influence of demographic factors and a selection of polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR. The secondary objective of this study was to develop a limited sampling strategy to enable prediction of everolimus exposure in an efficient way and to compare it with the widely used trough blood concentration (C(trough)) monitoring., Methods: A total of 783 blood samples were obtained from 53 renal transplant patients who had been switched from a triple therapy of ciclosporin, mycophenolate mofetil and prednisolone to a calcineurin inhibitor-free dual therapy of everolimus (twice daily) and prednisolone. Everolimus blood concentrations were analysed in whole blood using liquid chromatography-tandem mass spectrometry during routine therapeutic drug monitoring targeting an area under the blood concentration-time curve from time zero to 12 hours (AUC(12)) of 120 μg · h/L. A population pharmacokinetic model was developed and demographic factors and genetic polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR were included as covariates. In addition, a limited sampling strategy was developed., Results: Maintaining everolimus systemic exposure at an AUC(12) of 120 μg · h/L resulted in low rejection rates but considerable numbers of adverse events and toxicity. Everolimus pharmacokinetics were best described by a two-compartment model with lag-time (oral clearance = 17.9 L/h; volume of distribution of the central compartment after oral administration [V(1)/F] = 148 L and first-order absorption rate constant [k(a)] = 7.36 h-1). Ideal body weight was significantly related to V(1)/F. None of the selected polymorphisms in genes coding for enzymes involved in distribution and metabolism of everolimus had a significant influence on everolimus pharmacokinetics. The pharmacokinetic limited sampling model (C(trough) and whole blood drug concentration at 2 hours postdose [C(2)]) resulted in a significantly improved prediction of everolimus exposure compared with the widely used C(trough) monitoring., Conclusion: 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.

Background: There is a need to monitor everolimus blood concentrations in renal transplant recipients as a result of its high pharmacokinetic variability and narrow therapeutic window. However, analytical methods to determine blood concentrations often differ in performance. Therefore, we investigated whether two commonly used therapeutic drug monitoring methods for everolimus were in agreement and to what extent their differences could lead to differences in dosage advice., Design and Methods: Six hundred twelve whole blood samples were obtained from 28 adult renal transplant recipients receiving everolimus and prednisolone therapy. These samples included 286 everolimus trough concentrations. The remaining samples were obtained up to 6 hours post everolimus intake and allowed calculation of 84 AUCs0-12h. All samples were analyzed with fluorescence polarization immunoassay (FPIA) on an Abbott TDxFLx analyzer and liquid chromatography-tandem mass spectrometry (LC-MS/MS)., Results: Everolimus blood concentrations measured with FPIA and LC-MS/MS were not in agreement. Concentrations determined by FPIA were, on average, 23% higher than concentrations quantified by LC-MS/MS. Moreover, concentrations lower than 15 mug/L or AUC0-12h determined with FPIA could be twofold higher than with LC-MS/MS. This variability can lead to clinically relevant differences in dose adjustment of up to 1.25 mg everolimus despite using a correction factor of 23%. Finally, when trough concentrations were measured with FPIA, higher intrapatient variability was observed compared with the use of LC-MS/MS., Conclusion: LC-MS/MS outperforms FPIA for clinical drug monitoring and intervention of everolimus therapy in adult renal transplant recipients on dual therapy with prednisolone. Specifically, the use of FPIA can lead to clinically relevant differences in everolimus dosage advice and higher intrapatient variability.

Purpose: Optimal 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., Methods: De 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., Results: The 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., Conclusions: It 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.

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.

Introduction: Specific alleles in human leukocyte antigens (HLAs) are associated with an increased risk of developing drug hypersensitivity reactions induced by abacavir, allopurinol, carbamazepine, oxcarbazepine, phenytoin, lamotrigine, or flucloxacillin. Transplant patients are genotyped for HLA as a routine practice to match a potential donor to a recipient. This study aims to investigate the feasibility and potential impact of repurposing these HLA genotype data from kidney transplant patients to prevent drug hypersensitivity reactions. Methods: A cohort of 1347 kidney transplant recipients has been genotyped in the Leiden University Medical Center (LUMC) using next-generation sequencing (NGS). The risk alleles HLA-A*31:01, HLA-B*15:02, HLA-B*15:11, HLA-B*57:01, and HLA-B*58:01 were retrieved from the NGS data. Medical history, medication use, and allergic reactions were obtained from the patient's medical records. Carrier frequencies found were compared to a LUMC blood donor population. Results: A total of 13.1% of transplant cohort patients carried at least one of the five HLA risk alleles and therefore had an increased risk of drug-induced hypersensitivity for specific drugs. HLA-A*31:01, HLA-B*15:02, HLA-B*57:01, and HLA-B*58:01 were found in carrier frequencies of 4.61%, 1.19%, 4.46%, and 3.35% respectively. No HLA-B*15:11 carrier was found. In total nine HLA-B*57:01 carriers received flucloxacillin and seven HLA-B*58:01 carriers within our cohort received allopurinol. Discussion: Our study shows that repurposing HLA genotype data from transplantation patients for the assignment of HLA risk alleles associated with drug hypersensitivity is feasible. The use of these data by physicians while prescribing drugs or by the pharmacist when dispensing drugs holds the potential to prevent drug hypersensitivity reactions. The utility of this method was highlighted by 13.1% of the transplant cohort patients carrying an actionable HLA allele. [ABSTRACT FROM AUTHOR]