A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus Following Pediatric Renal Transplantation

A descriptive study of the single-nucleotide polymorphisms known to affect the Tacrolimus trough concentration per dose, among a population of kidney failure patients in a tertiary hospital in Ghana

BACKGROUND

The burden of chronic kidney disease (CKD) and kidney failure in Ghana is on the ascendency, with the prevalence of CKD estimated at 13.3%. Patients with CKD who progress to kidney failure require life sustaining kidney replacement therapy (KRT) which is almost exclusively available in Ghana as haemodialysis. Kidney transplantation is considered the best KRT option for patients with irreversible kidney failure due to its relative cost efficiency as well as its superiority in terms of survival and quality of life. However, because transplants may trigger an immune response with potential organ rejection, immunosuppressants such as tacrolimus dosing are required.

OBJECTIVE

This study sought to determine single nucleotide polymorphisms in CYP3A5, CYP3A4 and MDR1 genes that affect the pharmacokinetics of Tacrolimus in a population of Ghanaian patients with kidney failure.

METHOD

This cross-sectional study comprised of 82 kidney failure patients undergoing maintenance haemodialysis at the Renal and Dialysis unit of Korle-Bu Teaching Hospital (KBTH). Clinical and demographic data were collected and genomic DNA isolated. Samples were genotyped for specific SNPs using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP).

RESULTS

Participants, 58/82 (70.73%) harbored the wildtype CYP3A5*1/*1 AA genotype, 20/82 (24.39%) carried the heterozygous CYP3A5*1/*3 AG genotype, and 4/82 (4.88%) had the homozygous mutant CYP3A5*3/*3 GG genotype. Also, 6/82 (7.32%) carried the wildtype AA genotype, 11/82 (13.41%) had the heterozygous AG genotype, and 65/82 (79.27%) harbored the homozygous mutant GG genotype of CYP3A4*1B (-290 A>G). For MDR1_Ex21 (2677 G>T), 81/82 (98.78%) carried the wildtype GG genotype, while 1/82 (1.22%) had the heterozygous GT genotype. For MDR1_Ex26 (3435 C>T), 63/82 (76.83%) had the wildtype CC genotype, while 18/82 (21.95%) carried the heterozygous CT genotype, and 1/82 (1.22%) harbored the mutant TT genotype.

CONCLUSION

SNPs in CYP3A4, CYP3A5, and MDR1 genes in a population of Ghanaian kidney failure patients were described. The varying SNPs of the featured genes suggest the need to consider the genetic status of Ghanaians kidney failure patients prior to transplantation and tacrolimus therapy.

A prospective controlled, randomized clinical trial of kidney transplant recipients developed personalized tacrolimus dosing using model-based Bayesian Prediction

For three decades, tacrolimus (Tac) dose adjustment in clinical practice has been calculated empirically according to the manufacturer's labeling based on a patient's body weight. Here, we developed and validated a Population pharmacokinetic (PPK) model including pharmacogenetics (cluster CYP3A4/CYP3A5), age, and hematocrit. Our study aimed to assess the clinical applicability of this PPK model in the achievement of Tac Co (therapeutic trough Tac concentration) compared to the manufacturer's labelling dosage. A prospective two-arm, randomized, clinical trial was conducted to determine Tac starting and subsequent dose adjustments in 90 kidney transplant recipients. Patients were randomized to a control group with Tac adjustment according to the manufacturer's labeling or the PPK group adjusted to reach target Co (6-10 ng/ml) after the first steady state (primary endpoint) using a Bayesian prediction model (NONMEM). A significantly higher percentage of patients from the PPK group (54.8%) compared with the control group (20.8%) achieved the therapeutic target fulfilling 30% of the established superiority margin defined. Patients receiving PPK showed significantly less intra-patient variability compared to the control group, reached the Tac Co target sooner (5 days vs 10 days), and required significantly fewer Tac dose modifications compared to the control group within 90 days following kidney transplant. No statistically significant differences occurred in clinical outcomes. Thus, PPK-based Tac dosing offers significant superiority for starting Tac prescription over classical labeling-based dosing according to the body weight, which may optimize Tac-based therapy in the first days following transplantation.

Individualized dosing algorithms for tacrolimus in kidney transplant recipients: current status and unmet needs

INTRODUCTION

Tacrolimus is a potent immunosuppressive drug with many side effects including nephrotoxicity and post-transplant diabetes mellitus. To limit its toxicity, therapeutic drug monitoring (TDM) is performed. However, tacrolimus' pharmacokinetics are highly variable within and between individuals, which complicates their clinical management. Despite TDM, many kidney transplant recipients will experience under- or overexposure to tacrolimus. Therefore, dosing algorithms have been developed to limit the time a patient is exposed to off-target concentrations.

AREAS COVERED

Tacrolimus starting dose algorithms and models for follow-up doses developed and/or tested since 2015, encompassing both adult and pediatric populations. Literature was searched in different databases, i.e. Embase, PubMed, Web of Science, Cochrane Register, and Google Scholar, from inception to February 2023.

EXPERT OPINION

Many algorithms have been developed, but few have been prospectively evaluated. These performed better than bodyweight-based starting doses, regarding the time a patient is exposed to off-target tacrolimus concentrations. No benefit in reduced tacrolimus toxicity has yet been observed. Most algorithms were developed from small datasets, contained only a few tacrolimus concentrations per person, and were not externally validated. Moreover, other matrices should be considered which might better correlate with tacrolimus toxicity than the whole-blood concentration, e.g. unbound plasma or intra-lymphocytic tacrolimus concentrations.

Predictive Capacity of Population Pharmacokinetic Models for the Tacrolimus Dose Requirements of Pediatric Solid Organ Transplant Recipients

BACKGROUND

Transplant recipients require individualized tacrolimus doses to maximize graft survival. Multiple pediatric tacrolimus population pharmacokinetic (PopPK) models incorporating CYP3A5 genotype and other covariates have been developed. Identifying the optimal popPK model is necessary for clinical implementation in pediatric solid organ transplant. The primary objective was to compare the dose prediction capabilities of the developed models in pediatric kidney and heart transplant recipients.

METHODS

Pediatric kidney or heart transplant recipients treated with tacrolimus and available CYP3A5 genotype data were identified. The initial weight-based tacrolimus dose and first therapeutic tacrolimus dose were collected retrospectively. Three published popPK models were used to predict the tacrolimus dose required to achieve a tacrolimus trough concentration of 10 ng/mL. Model dose predictions were compared with the initial and first therapeutic doses using Friedman test. The first therapeutic dose was plotted against the model-predicted dose.

RESULTS

The median initial dose approximately 2-fold lower than the first therapeutic dose for CYP3A5 expressers. The Chen et al model provided the closest estimates to the first therapeutic dose for kidney transplant recipients; however, all 3 models tended to underpredict the observed therapeutic dose. For heart transplant recipients, Andrews et al model predicted doses that were higher than the initial dose but similar to the actual therapeutic dose.

CONCLUSIONS

Weight-based tacrolimus dosing appears to underestimate the tacrolimus dose requirements. The development of a separate popPK model is necessary for heart transplant recipients. A genotype-guided strategy based on the Chen et al model provided the best estimates for doses in kidney transplant recipients and should be prospectively evaluated.

Pharmacogenetic Aspects of Drug Metabolizing Enzymes and Transporters in Pediatric Medicine: Study Progress, Clinical Practice and Future Perspectives

As the activity of certain drug metabolizing enzymes or transporter proteins can vary with age, the effect of ontogenetic and genetic variation on the activity of these enzymes is critical for the accurate prediction of treatment outcomes and toxicity in children. This makes pharmacogenetic research in pediatrics particularly important and urgently needed, but also challenging. This review summarizes pharmacogenetic studies on the effects of genetic polymorphisms on pharmacokinetic parameters and clinical outcomes in pediatric populations for certain drugs, which are commonly prescribed by clinicians across multiple therapeutic areas in a general hospital, organized from those with the most to the least pediatric evidence among each drug category. We also further discuss the research status of the gene-guided dosing regimens and clinical implementation of pediatric pharmacogenetics. More and more drug-gene interactions are demonstrated to have clinical validity for children, and pharmacogenomics in pediatrics have shown evidence-based benefits to enhance the efficacy and precision of existing drug dosing regimens in several therapeutic areas. However, the most important limitation to the implementation is the lack of high-quality, rigorous pediatric prospective clinical studies, so adequately powered interventional clinical trials that support incorporation of pharmacogenetics into the care of children are still needed.

Model-Based Tacrolimus Follow-up Dosing in Adult Renal Transplant Recipients: A Simulation Trial

BACKGROUND

Initial algorithm-based dosing appears to be effective in predicting tacrolimus dose requirement. However, achieving and maintaining the target concentrations is challenging. Model-based follow-up dosing, which considers patient characteristics and pharmacological data, may further personalize treatment. This study investigated whether model-based follow-up dosing could lead to more accurate tacrolimus exposure than standard therapeutic drug monitoring (TDM) in kidney transplant recipients after an initial algorithm-based dose.

METHODS

This simulation trial included patients from a prospective trial that received an algorithm-based tacrolimus starting dose followed by TDM. For every measured tacrolimus predose concentration (C 0,obs ), model-based dosing advice was simulated using the InsightRX software. Based on previous tacrolimus doses and C 0 , age, body surface area, CYP3A4 and CYP3A5 genotypes, hematocrit, albumin, and creatinine, the optimal next dose, and corresponding tacrolimus concentration (C 0,pred ) were predicted.

RESULTS

Of 190 tacrolimus C 0 values measured in 59 patients, 121 (63.7%; 95% CI 56.8-70.5) C 0,obs were within the therapeutic range (7.5-12.5 ng/mL) versus 126 (66.3%, 95% CI 59.6-73.0) for C 0,pred ( P = 0.89). The median absolute difference between the tacrolimus C 0 and the target tacrolimus concentration (10.0 ng/mL) was 1.9 ng/mL for C 0,obs versus 1.6 ng/mL for C 0,pred . In a historical cohort of 114 kidney transplant recipients who received a body weight-based starting dose followed by TDM, 172 of 335 tacrolimus C 0 (51.3%) were within the therapeutic range (10.0-15.0 ng/mL).

CONCLUSIONS

The combination of an algorithm-based tacrolimus starting dose with model-based follow-up dosing has the potential to minimize under- and overexposure to tacrolimus in the early posttransplant phase, although the additional effect of model-based follow-up dosing on initial algorithm-based dosing seems small.

Model-informed Estimation of Acutely Decreased Tacrolimus Clearance and Subsequent Dose Individualization in a Pediatric Renal Transplant Patient with Posterior Reversible Encephalopathy Syndrome

BACKGROUND

Considerable inter-patient and inter-occasion variability has been reported in tacrolimus pharmacokinetics (PK) in the pediatric renal transplant population. The present study investigated tacrolimus PK in a 2-year-old post-renal transplant patient and a known CYP3A5 expresser who developed posterior reversible encephalopathy syndrome (PRES) and had significantly elevated tacrolimus blood concentrations during tacrolimus treatment. A model-informed PK assessment was performed to assist with precision dosing. Tacrolimus clearance was evaluated both before and after the development of PRES on post-transplant day (PTD) 26.

METHODS

A retrospective chart review was conducted to gather dosing data and tacrolimus concentrations, as part of a clinical pharmacology consultation service. Individual PK parameters were estimated by Bayesian estimation using a published pediatric PK model. Oral clearance (CL/F) was estimated for three distinct time periods-before CNS symptoms (PTD 25), during the PRES event (PTD 27-30), and after oral tacrolimus was re-started (PTD 93).

RESULTS

Bayesian estimation showed an estimated CL/F of 15.0 L/h in the days preceding the PRES event, compared to a population mean of 16.3 L/h (95% confidence interval 14.9-17.7 L/h) for CYP3A5 expressers of the same age and weight. Samples collected on PTD 27-30 yielded an estimated CL/F of 3.6 L/h, a reduction of 76%, coinciding with clinical confirmation of PRES and therapy discontinuation. On PTD 93, an additional assessment showed a stable CL/F value of 14.5 L/h one month after re-initiating tacrolimus and was used to recommend a continued maintenance dose.

CONCLUSION

This is the first report to demonstrate acutely decreased tacrolimus clearance in PRES, likely caused by the downregulation of metabolizing enzymes in response to inflammatory cytokines. The results suggest the ability of model-informed Bayesian estimation to characterize an acute decline in oral tacrolimus clearance after the development of PRES, and the role that PK estimation may play in supporting dose selection and individualization.

CYP3A4/5 genotypes and age codetermine tacrolimus concentration and dosage in pediatric heart transplant recipients

Tacrolimus (TAC) is the cornerstone of immunosuppressive therapy for pediatric heart transplantation (HTx) recipients. However, little information is known on the interaction of developmental and genetic variants on TAC disposition in this population, which makes TAC dose optimization more difficult. The aim of study was to investigate the relationship between genotypes and age on TAC concentrations and dosage during the early post-operation period in pediatric HTx recipients. Sixty-six pediatric HTx recipients were enrolled and divided into three groups according to the age (<6, ≥6-≤12, 12-18 years old). CYP3A4/5, POR and ABCB1 polymorphisms were genotyped. The associations between genotypes and age on TAC dose-adjusted trough concentrations (C₀/D), dose requirement as well as acute kidney injury (AKI) were evaluated. CYP3A5*3 and CYP3A4*1G were significantly correlated with TAC C₀/D and dose requirement in the pediatric recipients ≥ 6 years. The C₀/D in children aged ≥ 6-≤12 years and 12-18 years is 2.8 and 4.2 fold of these < 6 years old, respectively. TAC dose requirements in children aged < 6 years were 2.4 times and 3.5 times of these aged ≥ 6-≤12 years and 12-18 years, respectively. Among the same CYP3A5*3 or CYP3A4*1G genotypes, age was positively increased with TAC C₀/D and negatively correlated with targeted dose. No genetic variants were found to be associated with AKI during the early post-operation period. CYP3A4/5 genotypes and age should be taken into consideration to TAC dosage in pediatric HTx recipients.

Population Pharmacokinetics and Initial Dosage Optimization of Tacrolimus in Pediatric Hematopoietic Stem Cell Transplant Patients

Background: There is a substantial lack of tacrolimus pharmacokinetic information in pediatric hematopoietic stem cell transplant (HSCT) patients. This study aimed to develop population pharmacokinetics (PopPK) of tacrolimus in pediatric HSCT patients and to devise model-guided dosage regimens. Methods: A retrospective analysis was performed on 86 pediatric HSCT patients who received tacrolimus intravenously or orally. A total of 578 tacrolimus trough concentrations (C₀) were available for pharmacokinetic analysis using a non-linear mixed-effects modeling method. Demographic and clinical data were included and assessed as covariates via the stepwise method. Bayesian estimators were used to devise pediatric dosage regimens that targeted C₀ of 5-15 ng mL^-1. Results: A one-compartment model with first-order absorption adequately described the tacrolimus pharmacokinetics. Clearance (CL), volume of distribution (V), and typical bioavailability (F) in this study were estimated to be 2.42 L h^-1 (10.84%), 79.6 L (16.51%), and 19% (13.01%), respectively. Body weight, hematocrit, post-transplantation days, and caspofungin and azoles concomitant therapy were considered significant covariates for tacrolimus CL. Hematocrit had a significant impact on the V of tacrolimus. In the subgroup cohort of children (n = 24) with CYP3A5 genotype, the clearance was 1.38-fold higher in CYP3A5 expressers than in non-expressers. Simulation indicated that the initial dosage optimation of tacrolimus for intravenous and oral administration was recommended as 0.025 and 0.1 mg kg^-1 d^-1 (q12h), respectively. Conclusion: A PopPK model for tacrolimus in pediatric HSCT patients was developed, showing good predictive performance. Model-devised dosage regimens with trough tacrolimus concentrations provide a practical strategy for achieving the therapeutic range.

Population Pharmacokinetic Model Development of Tacrolimus in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplantation

Background: With a notably narrow therapeutic window and wide intra- and interindividual pharmacokinetic (PK) variability, initial weight-based dosing along with routine therapeutic drug monitoring of tacrolimus are employed to optimize its clinical utilization. Both supratherapeutic and subtherapeutic tacrolimus concentrations can result in poor outcomes, thus tacrolimus PK variability is particularly important to consider in the pediatric population given the differences in absorption, distribution, metabolism, and excretion among children of various sizes and at different stages of development. The primary goals of the current study were to develop a population PK (PopPK) model for tacrolimus IV continuous infusion in the pediatric and young adult hematopoietic cell transplant (HCT) population and implement the PopPK model in a clinically available Bayesian forecasting tool.

Methods: A retrospective chart review was conducted of 111 pediatric and young adult patients who received IV tacrolimus by continuous infusion early in the post-transplant period during HCT from February 2016 to July 2020 at our institution. PopPK model building was performed in NONMEM. The PopPK model building process included identifying structural and random effects models that best fit the data and then identifying which patient-specific covariates (if any) further improved model fit.

Results: A total of 1,648 tacrolimus plasma steady-state trough concentrations were included in the PopPK modeling process. A 2-compartment structural model best fit the data. Allometrically-scaled weight was a covariate that improved estimation of both clearance and volume of distribution. Overall, model predictions only showed moderate bias, with minor under-prediction at lower concentrations and minor over-prediction at higher predicted concentrations. The model was implemented in a Bayesian dosing tool and made available at the point-of-care.

Discussion: Novel therapeutic drug monitoring strategies for tacrolimus within the pediatric and young adult HCT population are necessary to reduce toxicity and improve efficacy in clinical practice. The model developed presents clinical utility in optimizing the use of tacrolimus by enabling model-guided, individualized dosing of IV, continuous tacrolimus via a Bayesian forecasting platform.

Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients

BACKGROUND AND OBJECTIVE

Tacrolimus is a narrow therapeutic index drug with high pharmacokinetic variability, and several tacrolimus population pharmacokinetic (PopPK) models were developed to guide individualized drug dosing. These models, however, may not perform well in other clinical settings. Therefore, we aimed to assess the predictive ability of published tacrolimus PopPK models using a dataset of Thai kidney transplant patients.

METHODS

The external dataset was retrospectively collected from medical records of Bhumibol Adulyadej Hospital, Thailand. Published tacrolimus PopPK models were systematically searched from PubMed, Science Direct, CINAHL Complete, and Scopus databases. Models conducted using a nonlinear mixed-effects approach with covariate resemblance to our external dataset were selected. The external dataset consisted of Thai kidney transplant patients receiving oral immediate- or extended-release tacrolimus formulations twice or once daily, respectively. Accuracy and precision of predicted concentrations were evaluated using mean absolute prediction error (MAPE), root mean square error (RMSE), and goodness of fit plots.

RESULTS

Only three models produced acceptable population predictions with the MAPE of < 50%. By using the Bayesian posthoc estimate of individual pharmacokinetic parameters, all models well performed with the MAPE and RMSE of < 30% and 40%, respectively, except two models; one could not successfully converge and the other substantially underpredicted tacrolimus concentrations.

CONCLUSION

We evaluated ten tacrolimus PopPK models, and eight models resulted in satisfactorily individual predicted tacrolimus concentrations in Thai kidney transplant patients and may be used to aid tacrolimus dose adjustment along with a clinical judgment.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Unbound Plasma, Total Plasma, and Whole-Blood Tacrolimus Pharmacokinetics Early After Thoracic Organ Transplantation

BACKGROUND AND OBJECTIVE

Therapeutic drug monitoring of tacrolimus whole-blood concentrations is standard care in thoracic organ transplantation. Nevertheless, toxicity may appear with alleged therapeutic concentrations possibly related to variability in unbound concentrations. However, pharmacokinetic data on unbound concentrations are not available. The objective of this study was to quantify the pharmacokinetics of whole-blood, total, and unbound plasma tacrolimus in patients early after heart and lung transplantation.

METHODS

Twelve-hour tacrolimus whole-blood, total, and unbound plasma concentrations of 30 thoracic organ recipients were analyzed with high-performance liquid chromatography-tandem mass spectrometry directly after transplantation. Pharmacokinetic modeling was performed using non-linear mixed-effects modeling.

RESULTS

Plasma concentration was < 1% of the whole-blood concentration. Maximum binding capacity of erythrocytes was directly proportional to hematocrit and estimated at 2700 pg/mL (95% confidence interval 1750-3835) with a dissociation constant of 0.142 pg/mL (95% confidence interval 0.087-0.195). The inter-individual variability in the binding constants was considerable (27% maximum binding capacity, and 29% for the linear binding constant of plasma).

CONCLUSIONS

Tacrolimus association with erythrocytes was high and suggested a non-linear distribution at high concentrations. Monitoring hematocrit-corrected whole-blood tacrolimus concentrations might improve clinical outcomes in clinically unstable thoracic organ transplants.

CLINICAL TRIAL REGISTRATION

NTR 3912/EudraCT 2012-001909-24.

A Population Pharmacokinetic Model Does Not Predict the Optimal Starting Dose of Tacrolimus in Pediatric Renal Transplant Recipients in a Prospective Study: Lessons Learned and Model Improvement

Background and Objective

Bodyweight-based dosing of tacrolimus is considered standard care. Currently, at first steady state, a third of pediatric kidney transplant recipients has a tacrolimus pre-dose concentration within the target range. We investigated whether adaptation of the starting dose according to a validated dosing algorithm could increase this proportion.

Methods

This was a multi-center, single-arm, prospective trial with a planned interim analysis after 16 patients, in which the tacrolimus starting dose was based on bodyweight, cytochrome P450 3A5 genotype, and donor status (living vs. deceased donor).

Results

At the interim analysis, 31% of children had a tacrolimus pre-dose concentration within the target range. As the original dosing algorithm was poorly predictive of tacrolimus exposure, the clinical trial was terminated prematurely. Next, the original model was improved by including the data of the children included in this trial, thereby doubling the number of children in the model building cohort. Data were best described with a two-compartment model with inter-individual variability, allometric scaling, and inter-occasion variability on clearance. Cytochrome P450 3A5 genotype, hematocrit, and creatinine influenced the tacrolimus clearance. A new starting dose model was developed in which the cytochrome P450 3A5 genotype was incorporated. Both models were successfully internally and externally validated.

Conclusions

The weight-normalized starting dose of tacrolimus should be higher in patients with a lower bodyweight and in those who are cytochrome P450 3A5 expressers.

Electronic supplementary material

The online version of this article (10.1007/s40262-019-00831-8) contains supplementary material, which is available to authorized users.

Treatment optimization of maintenance immunosuppressive agents in pediatric renal transplant recipients

Introduction: Graft survival in pediatric kidney transplant patients has increased significantly within the last three decades, correlating with the discovery and utilization of new immunosuppressants as well as improvements in patient care. Despite these developments in graft survival for patients, there is still improvement needed, particularly in long-term care in pediatric patients receiving grafts from deceased donor patients. Maintenance immunosuppressive therapies have narrow therapeutic indices and are associated with high inter-individual and intra-individual variability.Areas covered: In this review, we examine the impact of pharmacokinetic variability on renal transplantation and its association with age, genetic polymorphisms, drug-drug interactions, drug-disease interactions, renal insufficiency, route of administration, and branded versus generic drug formulation. Pharmacodynamics are outlined in terms of the mechanism of action for each immunosuppressant, potential adverse effects, and the utility of pharmacodynamic biomarkers.Expert opinion: Acquiring abetter quantitative understanding of immunosuppressant pharmacokinetics and pharmacodynamic components should help clinicians implement treatment regimens to maintain the balance between therapeutic efficacy and drug-related toxicity.

Therapeutic drug monitoring of immunosuppressive drugs in hepatology and gastroenterology

Immunosuppressive drugs have been key to the success of liver transplantation and are essential components of the treatment of inflammatory bowel disease (IBD) and autoimmune hepatitis (AIH). For many but not all immunosuppressants, therapeutic drug monitoring (TDM) is recommended to guide therapy. In this article, the rationale and evidence for TDM of tacrolimus, mycophenolic acid, the mammalian target of rapamycin inhibitors, and azathioprine in liver transplantation, IBD, and AIH is reviewed. New developments, including algorithm-based/computer-assisted immunosuppressant dosing, measurement of immunosuppressants in alternative matrices for whole blood, and pharmacodynamic monitoring of these agents is discussed. It is expected that these novel techniques will be incorporate into the standard TDM in the next few years.

External Evaluation of Vancomycin Population Pharmacokinetic Models at Two Clinical Centers

Background: Numerous vancomycin population pharmacokinetic models in neonates have been published; however, their predictive performances remain unknown. This study aims to evaluate their external predictability and explore the factors that might affect model performance. Methods: Published population pharmacokinetic models in neonates were identified from the literature and evaluated using datasets from two clinical centers, including 171 neonates with a total of 319 measurements of vancomycin levels. Predictive performance was assessed by prediction- and simulation-based diagnostics and Bayesian forecasting. Furthermore, the effect of model structure and a number of identified covariates was also investigated. Results: Eighteen published pharmacokinetic models of vancomycin were identified after a systematic literature search. Using prediction-based diagnostics, no model had a median prediction error of ≤ ± 15%, a median absolute prediction error of ≤30%, and a percentage of prediction error that fell within ±30% of >50%. A simulation-based visual predictive check of most models showed there were large deviations between observations and simulations. After Bayesian forecasting with one or two prior observations, the predicted performance improved significantly. Weight, age, and serum creatinine were identified as the most important covariates. Moreover, employing a maturation model based on weight and age as well as nonlinear model to incorporate serum creatinine level significantly improved predictive performance. Conclusion: The predictability of the pharmacokinetic models for vancomycin is closely related to the approach used for modeling covariates. Bayesian forecasting can significantly improve the predictive performance of models.

Evaluating the Impact of CYP3A5 Genotype on Post-Transplant Healthcare Resource Utilization in Pediatric Renal and Heart Transplant Recipients Receiving Tacrolimus

Purpose

CYP3A5 genotype is a significant contributor to inter-individual tacrolimus exposure and may impact the time required to achieve therapeutic concentrations and number of tacrolimus dose adjustments in transplant patients. Increased modifications to tacrolimus therapy may indicate a higher burden on healthcare resources. The purpose of this study was to evaluate whether CYP3A5 genotype was predictive of healthcare resource utilization in pediatric renal and heart transplant recipients.

Patients and Methods

Patients <18 years of age with a renal or heart transplant between 6/1/2014–12/31/2018 and tacrolimus-based immunosuppression were included. Secondary use samples were obtained for CYP3A5 genotyping. Clinical data was retrospectively collected from the electronic medical record. Healthcare resource utilization measures included the number of dose changes, number of tacrolimus concentrations, length of stay, number of clinical encounters, and total charges within the first year post-transplant. Rejection and donor-specific antibody (DSA) formation within the first year were also collected. The impact of CYP3A5 genotype was evaluated via univariate analysis for the first year and multivariable analysis at 30, 90, 180, 270, and 365 days post-transplant.

Results

Eighty-five subjects were included, 48 renal transplant recipients and 37 heart transplant recipients. CYP3A5 genotype was not associated with any outcomes in renal transplant, however, a CYP3A5 expresser phenotype was a predictor of more dose changes, more tacrolimus concentrations, longer length of stay, and higher total charges in heart transplant recipients. CYP3A5 genotype was not associated with rejection or DSA formation. Age and induction therapy were associated with higher total charges.

Conclusion

CYP3A5 genotype may predict healthcare resource utilization in the first year post-transplant, although this may be mitigated by differences in tacrolimus management. Future studies should evaluate the impact of genotype-guided dosing strategies for tacrolimus on healthcare utilization resources.

Avoiding Tacrolimus Underexposure and Overexposure with a Dosing Algorithm for Renal Transplant Recipients: A Single Arm Prospective Intervention Trial

Bodyweight‐based tacrolimus dosing followed by therapeutic drug monitoring is standard clinical care after renal transplantation. However, after transplantation, a meager 38% of patients are on target at first steady‐state and it can take up to 3 weeks to reach the target tacrolimus predose concentration (C₀). Tacrolimus underexposure and overexposure is associated with an increased risk of rejection and drug‐related toxicity, respectively. To minimize subtherapeutic and supratherapeutic tacrolimus exposure in the immediate post‐transplant phase, a previously developed dosing algorithm to predict an individual’s tacrolimus starting dose was tested prospectively. In this single‐arm, prospective, therapeutic intervention trial, 60 de novo kidney transplant recipients received a tacrolimus starting dose based on a dosing algorithm instead of a standard, bodyweight‐based dose. The algorithm included cytochrome P450 (CYP)3A4 and CYP3A5 genotype, body surface area, and age as covariates. The target tacrolimus C₀, measured for the first time at day 3, was 7.5–12.5 ng/mL. Between February 23, 2019, and July 7, 2020, 60 patients were included. One patient was excluded because of a protocol violation. On day 3 post‐transplantation, 34 of 59 patients (58%, 90% CI 47–68%) had a tacrolimus C₀ within the therapeutic range. Markedly subtherapeutic (< 5.0 ng/mL) and supratherapeutic (> 20 ng/mL) tacrolimus concentrations were observed in 7% and 3% of the patients, respectively. Biopsy‐proven acute rejection occurred in three patients (5%). In conclusion, algorithm‐based tacrolimus dosing leads to the achievement of the tacrolimus target C₀ in as many as 58% of the patients on day 3 after kidney transplantation.

Evaluating risk factors for acute graft versus host disease in pediatric hematopoietic stem cell transplant patients receiving tacrolimus

To identify the clinical and pharmacological risk factors associated with tacrolimus pharmacodynamics for acute graft‐versus‐host disease (aGVHD) in pediatric patients receiving allogeneic hematopoietic stem cell transplantation (HSCT) from a matched related donor. A retrospective cohort single center chart review study was conducted with pediatric patients who received tacrolimus prophylaxis after allogeneic HSCT between January 1, 2017, and December 31, 2019. Potential risk factors were tested separately between aGVHD and non‐aGVHD cohorts and were further analyzed in a logistic regression model with backward elimination and a partial least squares discriminant analysis. Thirty‐three patient cases were included in our study and 52% (17/33) developed aGVHD while on tacrolimus prophylaxis. When tested independently, donor age and sibling versus parent donor/recipient relation were shown to be statistically significant between aGVHD and non‐aGVHD patients (p < 0.005). Pharmacological factors associated with tacrolimus treatment failed to demonstrate a significant impact on patient’s risk of aGVHD. Using a best fit logistic regression model that tested all the variables together, donor age was the only significant variable predicting patient’s risk of aGVHD (p < 0.01). Donor relationship and donor age were unable to be evaluated separately and are therefore confounding variables. Among pediatric patients receiving allogeneic HSCT, aGVHD risk is significantly decreased by either sibling donor and/or younger donors. Although no conclusions were drawn on the effect of tacrolimus therapy (p = 0.08), results warrant additional research with a larger sample size to evaluate the accuracy of monitoring tacrolimus serum trough levels.

Predictors of tacrolimus pharmacokinetic variability: current evidences and future perspectives

INTRODUCTION

In kidney transplantation, tacrolimus (TAC) is at the cornerstone of current immunosuppressive strategies. Though because of its narrow therapeutic index, it is critical to ensure that TAC levels are maintained within this sharp window through reactive adjustments. This would allow maximizing efficiency while limiting drug-associated toxicity. However, TAC high intra- and inter-patient pharmacokinetic (PK) variability makes it more laborious to accurately predict the appropriate dosage required for a given patient.

AREAS COVERED

This review summarizes the state-of-the-art knowledge regarding drug interactions, demographic and pharmacogenetics factors as predictors of TAC PK. We provide a scoring index for each association to grade its relevance and we present practical recommendations, when possible for clinical practice.

EXPERT OPINION

The management of TAC concentration in transplanted kidney patients is as critical as it is challenging. Recommendations based on rigorous scientific evidences are lacking as knowledge of potential predictors remains limited outside of DDIs. Awareness of these limitations should pave the way for studies looking at demographic and pharmacogenetic factors as well as gut microbiota composition in order to promote tailored treatment plans. Therapeutic approaches considering patients' clinical singularities may help allowing to maintain appropriate concentration of TAC.

Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients

Tacrolimus is a first-line calcineurin inhibitor (CNI) and an integral part of the immunosuppressive strategy in solid organ transplantation. Being a dose-critical drug, tacrolimus has a narrow therapeutic index that necessitates periodic monitoring to maintain the drug’s efficacy and reduce the consequences of overexposure. Tacrolimus is characterized by substantial intra- and inter-individual pharmacokinetic variability. At steady state, the tacrolimus blood concentration to daily dose ratio (C/D ratio) has been described as a surrogate for the estimation of the individual metabolism rate, where a low C/D ratio reflects a higher rate of metabolism. Fast tacrolimus metabolism (low C/D ratio) is associated with the risk of poor outcomes after transplantation, including reduced allograft function and survival, higher allograft rejection, CNI nephrotoxicity, a faster decline in kidney function, reduced death-censored graft survival (DCGS), post-transplant lymphoproliferative disorders, dyslipidemia, hypertension, and cardiovascular events. In this article, we discuss the potential role of the C/D ratio in a noninvasive monitoring strategy for identifying patients at risk for potential adverse events post-transplant.

Impact of CYP3A4/5 and ABCB1 polymorphisms on tacrolimus exposure and response in pediatric primary nephrotic syndrome

Aim: To evaluate the impact of CYP3A4*1G, CYP3A5*3 and ABCB1-C3435T polymorphisms on tacrolimus concentrations, efficacy and tolerance in pediatric primary nephrotic syndrome. Methods: Dose-adjusted concentrations (C₀/D), daily dose, frequency and time to relapse, cumulative remission days, and adverse reactions in 65 Chinese patients with various genotypes were retrospectively collected and compared. Results: C₀/D increased in CYP3A4*1/*1, CYP3A5*3/*3 and CYP3A4*1/*1-3A5*3/*3 diplotype carriers by 38.4, 69.7 and 40.9% compared with CYP3A4*1/*1G, CYP3A5*1/*3 and noncarriers, respectively. Recurrence risks were decreased in CYP3A4*1/*1 (0.43 of hazard ratio to *1/*1G) and CYP3A5*3/*3 carriers (0.43 of hazard ratio to *1/*3). None of polymorphisms was linked to adverse reactions. Conclusion: The genotypes of CYP3A4*1G and CYP3A5*3 rather than ABCB1-C3435T potentially predicted tacrolimus exposure and clinical response in pediatric primary nephrotic syndrome.

Predictive engines based on pharmacokinetics modelling for tacrolimus personalized dosage in paediatric renal transplant patients

The development of predictive engines based on pharmacokinetic-physiological mathematical models for personalised dosage recommendations is an immature field. Nevertheless, these models are extensively applied during the design of new drugs. This study presents new advances in this subject, through a stable population of patients who underwent kidney transplantation and were prescribed tacrolimus. We developed 2 new population pharmacokinetic models based on a compartmental approach, with one following the physiologically based pharmacokinetic approach and both including circadian modulation of absorption and clearance variables. One of the major findings was an improved predictive capability for both models thanks to the consideration of circadian rhythms, both in estimating the population and in Bayesian individual customisation. This outcome confirms a plausible mechanism suggested by other authors to explain circadian patterns of tacrolimus concentrations. We also discovered significant intrapatient variability in tacrolimus levels a week after the conversion from a fast-release (Prograf) to a sustained-release formulation (Advagraf) using adaptive optimisation techniques, despite high adherence and controlled conditions. We calculated the intrapatient variability through parametric intrapatient variations, which provides a method for quantifying the mechanisms involved. We present a first application for the analysis of bioavailability changes in formulation conversion. The 2 pharmacokinetic models have demonstrated their capability as predictive engines for personalised dosage recommendations, although the physiologically based pharmacokinetic model showed better predictive behaviour.

Toward precision medicine in pediatric population using cytochrome P450 phenotyping approaches and physiologically based pharmacokinetic modeling

The activity of drug-metabolizing enzymes (DME) shows high inter- and intra-individual variability. Genetic polymorphisms, exposure to drugs, and environmental toxins are known to significantly alter DME expression. In addition, the activity of these enzymes is highly age-dependent due to maturation processes that occur during development. Currently, there is a vast choice of phenotyping methods in adults using exogenous probes to characterize the activity of these enzymes. However, this can hardly be applied to children since it requires the intake of non-therapeutic xenobiotics. In addition, sampling may be challenging in the pediatric population for a variety of reasons: limited volume (e.g., blood), inappropriate sampling methods for age (e.g., urine), and metric requiring invasive or multiple blood samples. This review covers the main existing methods that can be used in the pediatric population to determine DME activity, with a particular focus on cytochrome P450 enzymes. Less invasive tools are described, including phenotyping using endogenous probes. Finally, the potential of pediatric model-informed precision dosing using physiologically based pharmacokinetic modeling is discussed.

Off-label use of tacrolimus in children with glomerular disease: Effectiveness, safety and pharmacokinetics

Glomerular diseases are leading causes of end-stage renal disease in children. Tacrolimus is frequently used off-label in the treatment of glomerular diseases. The effectiveness, safety and pharmacokinetic data of tacrolimus in the treatment of glomerular diseases in children are reviewed in this paper to provide evidence to support its rational use in clinical practice. The remission rates in previously published studies were different. In 19 clinical trials on children with nephrotic syndrome, the overall remission rate was 52.6-97.6%. In four clinical trials on children with lupus nephritis, the overall remission rate was 81.8-89.5%. In a pilot study with paediatric Henoch-Schönlein purpura nephritis patients, the overall remission rate was 100.0%. Infection, nephrotoxicity, gastrointestinal symptoms and hypertension are the most common adverse events. Body weight, age, CYP3A5 genotype, cystatin-C and daily dose of tacrolimus may have significant effects on the pharmacokinetics of tacrolimus in children with glomerular disease. More prospective controlled trials with long follow-up are needed to demonstrate definitely the effectiveness, safety and pharmacokinetics of tacrolimus in children with glomerular diseases.

Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach

AIMS

The objective of this study is to develop a generic model for tacrolimus pharmacokinetics modelling using a meta-analysis approach, that could serve as a first step towards a prediction tool to inform pharmacokinetics-based optimal dosing of tacrolimus in different populations and indications.

METHODS

A systematic literature review was performed and a meta-model developed with NONMEM software using a top-down approach. Historical (previously published) data were used for model development and qualification. In-house individual rich and sparse tacrolimus blood concentration profiles from adult and paediatric kidney, liver, lung and heart transplant patients were used for model validation. Model validation was based on successful numerical convergence, adequate precision in parameter estimation, acceptable goodness of fit with respect to measured blood concentrations with no indication of bias, and acceptable performance of visual predictive checks. External validation was performed by fitting the model to independent data from 3 external cohorts and remaining previously published studies.

RESULTS

A total of 76 models were found relevant for meta-model building from the literature and the related parameters recorded. The meta-model developed using patient level data was structurally a 2-compartment model with first-order absorption, absorption lag time and first-time varying elimination. Population values for clearance, intercompartmental clearance, central and peripheral volume were 22.5 L/h, 24.2 L/h, 246.2 L and 109.9 L, respectively. The absorption first-order rate and the lag time were fixed to 3.37/h and 0.33 hours, respectively. Transplanted organ and time after transplantation were found to influence drug apparent clearance whereas body weight influenced both the apparent volume of distribution and the apparent clearance. The model displayed good results as regards the internal and external validation.

CONCLUSION

A meta-model was successfully developed for tacrolimus in solid organ transplantation that can be used as a basis for the prediction of concentrations in different groups of patients, and eventually for effective dose individualization in different subgroups of the population.

Tacrolimus troughs and genetic determinants of metabolism in kidney transplant recipients: A comparison of four ancestry groups

Tacrolimus trough and dose requirements vary dramatically between individuals of European and African American ancestry. These differences are less well described in other populations. We conducted an observational, prospective, multicenter study from which 2595 kidney transplant recipients of European, African, Native American, and Asian ancestry were studied for tacrolimus trough, doses, and genetic determinants of metabolism. We studied the well-known variants and conducted a CYP3A4/5 gene-wide analysis to identify new variants. Daily doses, and dose-normalized troughs were significantly different between the four groups (P < .001). CYP3A5*3 (rs776746) was associated with higher dose-normalized tacrolimus troughs in all groups but occurred at different allele frequencies and had differing effect sizes. The CYP3A5*6 (rs10264272) and *7 (rs413003343) variants were only present in African Americans. CYP3A4*22 (rs35599367) was not found in any of the Asian ancestry samples. We identified seven suggestive variants in the CYP3A4/5 genes associated with dose-normalized troughs in Native Americans (P = 1.1 × 10^-5 -8.8 × 10^-6 ) and one suggestive variant in Asian Americans (P = 5.6 × 10^-6 ). Tacrolimus daily doses and dose-normalized troughs vary significantly among different ancestry groups. We identified potential new variants important in Asians and Native Americans. Studies with larger populations should be conducted to assess the importance of the identified suggestive variants.

Identification of Factors Affecting Tacrolimus Trough Levels in Latin American Pediatric Liver Transplant Patients

Tacrolimus is the cornerstone in pediatric liver transplant immunosuppression. Despite close monitoring, fluctuations in tacrolimus blood levels affect safety and efficacy of immunosuppressive treatments. Identifying the factors related to the variability in tacrolimus exposure may be helpful in tailoring the dose. The aim of the present study was to characterize the clinical, pharmacological, and genetic variables associated with systemic tacrolimus exposure in pediatric liver transplant patients. De novo transplant patients with a survival of more than 1 month were considered for inclusion and were genotyped for cytochrome P450 3A5 (CYP3A5). Peritransplant clinical factors and laboratory covariates were recorded retrospectively between 1 month and 2 years after transplant, including alanine aminotransferase (ALT), aspartate aminotransferase, hematocrit, and tacrolimus predose steady-state blood concentrations collected 12 hours after tacrolimus dosing. A linear mixed effect (LME) model was used to assess the association of these factors and the log-transformed tacrolimus dose-normalized trough concentration (logC0/D) levels. Bootstrapping was used to internally validate the final model. External validation was performed in an independent group of patients who matched the original population. The developed LME model described that logC0/D increases with increases in time after transplant (β = 0.019, 95% confidence interval [CI], 0.010-0.028) and ALT values (β = 0.00030, 95% CI, 0.00002-0.00056), whereas logC0/D is significantly lower in graft CYP3A5 expressers compared with nonexpressers (β = -0.349, 95% CI, -0.631 to -0.062). In conclusion, donor CYP3A5 genotype, time after transplant, and ALT values are associated with tacrolimus disposition between 1 month and 2 years after transplant. A better understanding of tacrolimus exposure is essential to minimize the occurrence of an out-of-range therapeutic window that may lead to adverse drug reactions or acute rejection.

Population pharmacokinetic analysis of linezolid in patients with different types of shock: Effect of platelet count

Linezolid was approved by the Food and Drug Administration for the treatment of serious infections. However, patients with serious frequently develop shock, and it is currently elusive whether shock affects the pharmacokinetics of linezolid. The aim of the present study was to explore whether the pharmacokinetics of linezolid are different among patients with various types of shock or patients without shock and whether potential confounders are involved in their outcomes. A population pharmacokinetic analysis using a non-linear mixed-effects model was performed to examine the pharmacokinetics of patients with different types of shock or patients without shock. The pharmacokinetics of linezolid in patients with different types of shock or patients without shock was described by a one-compartment model. In our results, the patients with different types of shock or patients without shock demonstrated no differences in pharmacokinetics, whereas the platelet count was identified as a significant influencing factor. The results demonstrated that the pharmacokinetics of linezolid exhibited no significant differences among patients with different types of shock or patients without shock, whereas the platelet count significantly affected the clearance rate of linezolid.

Drug-metabolizing enzymes CYP3A as a link between tacrolimus and vitamin D in renal transplant recipients: is it relevant in clinical practice?

CYP3A enzymes are involved in the metabolism of calcineurin inhibitor tacrolimus as well as vitamin D. In this review, we summarize the clinical aspects of CYP3A-mediated metabolism of tacrolimus and vitamin D with emphasis on the influence of single-nucleotide polymorphisms on tacrolimus disposition. We describe the utility of 4β hydroxycholesterol as a marker of CYP3A activity. Then, we discuss the possible interaction between calcineurin inhibitors and vitamin D in solid organ transplant recipients. Also, we review other mechanisms which may contribute to side effects of calcineurin inhibitors on bone. Lastly, suggestions for future research and clinical perspectives are discussed.

Population pharmacokinetics of immediate- and prolonged-release tacrolimus formulations in liver, kidney and heart transplant recipients

Aims

Develop a population pharmacokinetics model of tacrolimus in organ transplant recipients receiving twice‐daily, immediate‐release (IR‐T; Prograf) and/or once‐daily, prolonged‐release (PR‐T; Advagraf or Astagraf XL) tacrolimus.

Methods

Tacrolimus concentration–time profiles were analysed from 8 Phase II studies in adult and paediatric liver, kidney and heart transplant patients receiving IR‐T and/or PR‐T. A tacrolimus population pharmacokinetic model, including identification of significant covariates, was developed using NONMEM.

Results

Overall, 23,176 tacrolimus concentration records were obtained from 408 patients. A 2‐compartment model with first‐order absorption and elimination described the concentration–time profiles. Tacrolimus absorption rate was 50% slower with PR‐T vs IR‐T. Tacrolimus apparent oral clearance was 44.3 L/h in Whites and 59% higher in Asians. Tacrolimus central volume of distribution was 108 L in males and 55% lower in females; trough concentrations were similar between formulations. Tacrolimus relative bioavailability was similar between formulations (geometric mean ratio PR‐T:IR‐T 95%, 90% confidence intervals: 89%, 101%). Asians had 83% and 51% higher relative bioavailability than Whites and Blacks, respectively, for IR‐T and PR‐T. Whites had 49% and 77% higher relative bioavailability than Blacks for PR‐T and IR‐T, respectively. Blacks had 52% lower relative bioavailability than Whites and Asians for IR‐T and PR‐T. Type of organ transplanted and patient population (adult/paediatric) did not have a significant effect on tacrolimus pharmacokinetics.

Conclusions

This population pharmacokinetic model described data from transplant recipients who received IR‐T and/or PR‐T. Tacrolimus trough concentrations and relative bioavailability were similar between formulations, supporting 1 mg:1 mg conversion from Prograf to Advagraf/Astagraf XL in clinical practice.

Application of Size and Maturation Functions to Population Pharmacokinetic Modeling of Pediatric Patients

Traditionally, dosage for pediatric patients has been optimized using simple weight-scaled methods, but these methods do not always meet the requirements of children. To overcome this discrepancy, population pharmacokinetic (PK) modeling of size and maturation functions has been proposed. The main objective of the present study was to evaluate a new modeling method for pediatric patients using clinical data from three different clinical studies. To develop the PK models, a nonlinear mixed effect modeling method was employed, and to explore PK differences in pediatric patients, size with allometric and maturation with Michaelis–Menten type functions were evaluated. Goodness of fit plots, visual predictive check and bootstrap were used for model evaluation. Single application of size scaling to PK parameters was statistically significant for the over one year old group. On the other hand, simultaneous use of size and maturation functions was statistically significant for infants younger than one year old. In conclusion, population PK modeling for pediatric patients was successfully performed using clinical data. Size and maturation functions were applied according to established criteria, and single use of size function was applicable for over one year ages, while size and maturation functions were more effective for PK analysis of neonates and infants.

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Aims

The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient.

Methods

Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates.

Results

A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h⁻¹, clearance was 23.0 l h^–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dosemg=222nghml–1*22.5lh–1*1.0ifCYP3A5*3/*3or1.62ifCYP3A5*1/*3orCYP3A5*1/*1*1.0ifCYP3A4*1or unknownor0.814ifCYP3A4*22*Age56−0.50*BSA1.930.72/1000Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model.

Conclusions

For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

The potential impact of hematocrit correction on evaluation of tacrolimus target exposure in pediatric kidney transplant patients

BACKGROUND

Tacrolimus is an important immunosuppressive agent with high intra- and inter-individual pharmacokinetic variability and a narrow therapeutic index. As tacrolimus extensively accumulates in erythrocytes, hematocrit is a key factor in the interpretation of tacrolimus whole blood concentrations. However, as hematocrit values in pediatric kidney transplant patients are highly variable after kidney transplantation, translating whole blood concentration targets without taking hematocrit into consideration is theoretically incorrect. The aim of this study is to evaluate the potential impact of hematocrit correction on tacrolimus target exposure in pediatric kidney transplant patients.

METHODS

Data were obtained from 36 pediatric kidney transplant patients. Two hundred fifty-five tacrolimus whole blood samples were available, together responsible for 36 area under the concentration-time curves (AUCs) and trough concentrations. First, hematocrit corrected concentrations were derived using a formula describing the relationship between whole blood concentrations, hematocrit, and plasma concentrations. Subsequently, target exposure was evaluated using the converted plasma target concentrations. Ultimately, differences in interpretation of target exposure were identified and evaluated.

RESULTS

In total, 92% of our patients had lower hematocrit (median 0.29) than the reference value of adult kidney transplant patients. A different evaluation of target exposure for either trough level, AUC, or both was defined in 42% of our patients, when applying hematocrit corrected concentrations.

CONCLUSION

A critical role for hematocrit in therapeutic drug monitoring of tacrolimus in pediatric kidney transplant patients is suggested in this study. Therefore, we believe that hematocrit correction could be a step towards improvement of tacrolimus dose individualization.

Clinical aspects of tacrolimus use in paediatric renal transplant recipients

The calcineurin inhibitor tacrolimus, cornerstone of most immunosuppressive regimens, is a drug with a narrow therapeutic window: underexposure can lead to allograft rejection and overexposure can result in an increased incidence of infections, toxicity and malignancies. Tacrolimus is metabolised in the liver and intestine by the cytochrome P450 3A (CYP3A) isoforms CYP3A4 and CYP3A5. This review focusses on the clinical aspects of tacrolimus pharmacodynamics, such as efficacy and toxicity. Factors affecting tacrolimus pharmacokinetics, including pharmacogenetics and the rationale for routine CYP3A5*1/*3 genotyping in prospective paediatric renal transplant recipients, are also reviewed. Therapeutic drug monitoring, including pre-dose concentrations and pharmacokinetic profiles with the available "reference values", are discussed. Factors contributing to high intra-patient variability in tacrolimus exposure and its impact on clinical outcome are also reviewed. Lastly, suggestions for future research and clinical perspectives are discussed.

Population pharmacokinetics of tacrolimus in children with nephrotic syndrome

AIMS

Nephrotic syndrome (NS) is the most common clinical manifestation of glomerular disease in children. Currently, tacrolimus (TAC) is widely used in children with NS. However, pharmacokinetic data in children with nephrotic syndrome is limited. This study was intended to evaluate the population pharmacokinetics (PPK) of TAC in paediatric NS and to optimize dosing regimen.

METHODS

Blood samples from NS children treated with TAC were collected and the blood concentrations of TAC were detected using HPLC-MS/MS. A PPK model was developed using NONMEM software. Pharmacogenetic analysis was carried out in the CYP3A5 gene.

RESULTS

The data from 28 children were used for PPK analysis. A one-compartment model and first-order elimination were accorded with the TAC data in paediatric NS. A covariate analysis showed that body weight and CYP3A5 genotype significantly affected TAC pharmacokinetics. Monte Carlo simulation indicated that NS children with CYP3A5*3/*3 receiving 0.10 mg kg-1  dose-1 twice daily and NS children with CYP3A5*1 receiving 0.25 mg kg-1  dose-1 twice daily TAC could achieve the target concentrations of 5-10 ng ml-1 .

CONCLUSION

The PPK of TAC was estimated in children with NS and a CYP3A5 genotype-based dosing regimen was set up based on simulations.

Pharmacokinetic considerations related to therapeutic drug monitoring of tacrolimus in kidney transplant patients

INTRODUCTION

Tacrolimus (Tac) is the cornerstone of immunosuppressive therapy after solid organ transplantation and will probably remain so. Excluding belatacept, no new immunosuppressive drugs were registered for the prevention of acute rejection during the last decade. For several immunosuppressive drugs, clinical development halted because they weren't sufficiently effective or more toxic. Areas covered: Current methods of monitoring Tac treatment, focusing on traditional therapeutic drug monitoring (TDM), controversies surrounding TDM, novel matrices, pharmacogenetic and pharmacodynamic monitoring are discussed. Expert opinion: Due to a narrow therapeutic index and large interpatient pharmacokinetic variability, TDM has been implemented for individualization of Tac dose to maintain drug efficacy and minimize the consequences of overexposure. The relationship between predose concentrations and the occurrence of rejection or toxicity is controversial. Acute cellular rejection also occurs when the Tac concentration is within the target range, suggesting that Tac whole blood concentrations don't necessarily correlate with pharmacological effect. Intracellular Tac, the unbound fraction of Tac or pharmacodynamic monitoring could be better biomarkers/tools for adequate Tac exposure - research into this has been promising. Traditional TDM, perhaps following pre-emptive genotyping for Tac-metabolizing enzymes, must suffice for a few years before these strategies can be implemented in clinical practice.