Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation

Individualized dosing parameters for tacrolimus in the presence of voriconazole: a real-world PopPK study

Objectives

Significant increase in tacrolimus exposure was observed during co-administration with voriconazole, and no population pharmacokinetic model exists for tacrolimus in renal transplant recipients receiving voriconazole. To achieve target tacrolimus concentrations, an optimal dosage regimen is required. This study aims to develop individualized dosing parameters through population pharmacokinetic analysis and simulate tacrolimus concentrations under different dosage regimens.

Methods

We conducted a retrospective study of renal transplant recipients who were hospitalized at the Second Xiangya Hospital of Central South University between January 2016 and March 2021. Subsequently, pharmacokinetic analysis and Monte Carlo simulation were employed for further analysis.

Results

Nineteen eligible patients receiving tacrolimus and voriconazole co-therapy were included in the study. We collected 167 blood samples and developed a one-compartment model with first-order absorption and elimination to describe the pharmacokinetic properties of tacrolimus. The final typical values for tacrolimus elimination rate constant (Ka), apparent volume of distribution (V/F), and apparent oral clearance (CL/F) were 8.39 h-1, 2690 L, and 42.87 L/h, respectively. Key covariates in the final model included voriconazole concentration and serum creatinine. Patients with higher voriconazole concentration had lower tacrolimus CL/F and V/F. In addition, higher serum creatinine levels were associated with lower tacrolimus CL/F.

Conclusion

Our findings suggest that clinicians can predict tacrolimus concentration and estimate optimal tacrolimus dosage based on voriconazole concentration and serum creatinine. The effect of voriconazole concentration on tacrolimus concentration was more significant than serum creatinine. These findings may inform clinical decision-making in the management of tacrolimus and voriconazole therapy in solid organ transplant recipients.

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review

AIMS

This study aimed to provide up-to-date information on paediatric population pharmacokinetic models of tacrolimus and to identify factors influencing tacrolimus pharmacokinetic variability.

METHODS

Systematic searches in the Web of Science, PubMed, Scopus, Science Direct, Cochrane, EMBASE databases and reference lists of articles were conducted from inception to March 2023. All population pharmacokinetic studies of tacrolimus using nonlinear mixed-effect modelling in paediatric solid organ transplant patients were included.

RESULTS

Of the 21 studies reviewed, 62% developed from liver transplant recipients and 33% from kidney transplant recipients. Most studies used a 1-compartment model to describe tacrolimus pharmacokinetics. Body weight was a significant predictor for tacrolimus volume of distribution (Vd/F). The estimated Vd/F for 1-compartment models ranged from 20 to 1890 L, whereas the peripheral volume of distribution (Vp/F) for 2-compartment models was between 290 and 1520 L. Body weight, days post-transplant, CYP3A5 genotype or haematocrit were frequently reported as significant predictors of tacrolimus clearance. The estimated apparent clearance values range between 0.12 and 2.18 L/h/kg, with inter-individual variability from 13.5 to 110.0%. Only 29% of the studies assessed the generalizability of the models with external validation.

CONCLUSION

This review highlights the potential factors, modelling approaches and validation methods that impact tacrolimus pharmacokinetics in a paediatric population. The clinician could predict tacrolimus clearance based on body weight, CYP3A5 genotype, days post-transplant or haematocrit. Further research is required to determine the relationship between pharmacogenetics and tacrolimus pharmacodynamics in paediatric patients and confirm the applicability of nonlinear kinetics in this population.

Tacrolimus population pharmacokinetics in adult heart transplant patients

INTRODUCTION

Tacrolimus is an immunosuppressant largely used in heart transplantation. However, the calculation of its exposure based on the area under the curve (AUC) requires the use of a population pharmacokinetic (PK) model. The aims of this work were (i) to develop a population PK model for tacrolimus in heart transplant patients, (ii) to derive a maximum a posteriori Bayesian estimator (MAP-BE) based on a limited sampling strategy (LSS) and (iii) to estimate probabilities of target attainment (PTAs) for AUC and trough concentration (C0).

MATERIAL AND METHODS

Forty-seven PK profiles (546 concentrations) of 18 heart transplant patients of the Pharmacocinétique des Immunosuppresseurs chez les patients GREffés Cardiaques study receiving tacrolimus (Prograf®) were included. The database was split into a development (80%) and a validation (20%) set. PK parameters were estimated in MONOLIX® and based on this model a Bayesian estimator using an LSS was built. Simulations were performed to calculate the PTA for AUC and C0.

RESULTS

The best model to describe the tacrolimus PK was a two-compartment model with a transit absorption and a linear elimination. Only the CYP3A5 covariate was kept in the final model. The derived MAP-BE based on the LSS (0-1-2 h postdose) yielded an AUC bias ± SD = 2.7 ± 10.2% and an imprecision of 9.9% in comparison to the reference AUC calculated using the trapezoidal rule. PTAs based on AUC or C0 allowed new recommendations to be proposed for starting doses (0.11 mg·kg-1 ·12 h-1 for the CYP3A5 nonexpressor and 0.22 mg·kg1 ·12 h-1 for the CYP3A5 expressor).

CONCLUSION

The MAP-BE developed should facilitate estimation of tacrolimus AUC in heart transplant patients.

Impact of tacrolimus intra-patient variability in adverse outcomes after organ transplantation

Tacrolimus (Tac) is currently the most common calcineurin-inhibitor employed in solid organ transplantation. High intra-patient variability (IPV) of Tac (Tac IPV) has been associated with an increased risk of immune-mediated rejection and poor outcomes after kidney transplantation. Few data are available concerning the impact of high Tac IPV in non-kidney transplants. However, even in kidney transplantation, there is still a controversy whether high Tac IPV is indeed detrimental in respect to graft and/or patient survival. This may be due to different methods employed to evaluate IPV and distinct time frames adopted to assess graft and patient survival in those reports published up to now in the literature. Little is also known about the influence of high Tac IPV in the development of other untoward adverse events, update of the current knowledge regarding the impact of Tac IPV in different outcomes following kidney, liver, heart, lung, and pancreas tran splantation to better evaluate its use in clinical practice.

A systematic review and meta-analysis recite the efficacy of Tacrolimus treatment in renal transplant patients in association with genetic variants of CYP3A5 gene

Tacrolimus is an immunosuppressant with a narrow therapeutic index and pharmacokinetic variability. This variability may be attributed to genetic variants in gene CYP3A5 associated with Tacrolimus metabolism. Studies focusing on genetic variants in the CYP3A5 gene associated with Tacrolimus metabolism have been published, a meta-analysis of these published articles may provide a direction that can change the future research and clinical management of renal transplant patients. In this systematic review and meta-analysis, we have reviewed and analyzed the studies and clinical trials conducted to determine the association between genetic variants of CYP3A5 and Tacrolimus metabolism from the PubMed database and clinical trials (www.clinicaltrials.gov). This meta-analysis also assessed the correlation of CYP3A5 genotype (rs776746) with concentration/dose (Co/D) of Tacrolimus in renal transplant patients. The 59 published articles on genetic association of the CYP3A5 on Tacrolimus doses were reviewed for this systematic review. Meta-analysis showed that the Tacrolimus Co/D ratio is significantly lower in the CYP3A5 expressor group as compared with non-expressor in Asian, European as well as in mixed populations at any post-transplant period (P<0.0001). Our study further confirmed that the CYP3A5 variant (rs776746) is clinically relevant for the dose determination of Tacrolimus. Variations in Tacrolimus Co/D have been found to be significantly linked to the patient's CYP3A5 genetic variant (rs776746). The addition of other genetic variants involved in the pharmacokinetic of Tacrolimus may determine efficient regimen for drug dose. Our meta-analysis confirmed that the CYP3A5 genetic variant (rs776746) analysis is relevant in personalizing the Tacrolimus dose determination in renal transplant patients.

External assessment and refinement of a population pharmacokinetic model to guide tacrolimus dosing in pediatric heart transplant

STUDY OBJECTIVE

The immunosuppressant tacrolimus is a first-line agent to prevent graft rejection following pediatric heart transplant; however, it suffers from extensive inter-patient variability and a narrow therapeutic window. Personalized tacrolimus dosing may improve transplant outcomes by more efficiently achieving and maintaining therapeutic tacrolimus concentrations. We sought to externally validate a previously published population pharmacokinetic (PK) model that was constructed with data from a single site.

DATA SOURCE

Data were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2.

MAIN RESULTS

While the model was not successfully validated for use with external data, further covariate searching identified weight (p < 0.0001 on both volume and elimination rate) as a model-significant covariate. This refined model acceptably predicted future tacrolimus concentrations when guided by as few as three concentrations (median prediction error = 7%; median absolute prediction error = 27%).

CONCLUSION

These findings support the potential clinical utility of a population PK model to provide personalized tacrolimus dosing guidance.

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.

A pharmacometrics approach to assess the feasibility of capillary microsampling to replace venous sampling in clinical studies: Tafenoquine case study

AIM

Microsampling has the advantage of smaller blood sampling volume and suitability in vulnerable populations compared to venous sampling in clinical pharmacokinetics studies. Current regulatory guidance requires correlative studies to enable microsampling as a technique. A post hoc population pharmacokinetic (POPPK) approach was utilized to investigate blood capillary microsampling as an alternative to venous sampling.

METHODS

Pharmacokinetic data from microsampling and venous sampling techniques during a paediatric study evaluating tafenoquine, a single-dose antimalarial for P. vivax, were used. Separate POPPK models were developed and validated based on goodness of fit and visual predictive checks, with pharmacokinetic data obtained via each sampling technique.

RESULTS

Each POPPK model adequately described tafenoquine pharmacokinetics using a two-compartment model with body weight based on allometric scaling of clearance and volume of distribution. Tafenoquine pharmacokinetic parameter estimates including clearance (3.4 vs 3.7 L/h) were comparable across models with slightly higher interindividual variability (38.3% vs 27%) in capillary microsampling-based data. A bioavailability/bioequivalence comparison demonstrated that the point estimate (90% CI) of capillary microsample versus venous sample model-based individual post hoc estimates for area under the concentration-time curve from time zero to infinity (AUC_0-inf ) (100.7%, 98.0-103.5%) and C_max (79.7%, 76.9-82.5%) met the 80-125% and 70-143% criteria, respectively. Overall, both POPPK models led to the same dose regimen recommendations across weight bins based on achieving target AUC.

CONCLUSIONS

This analysis demonstrated that a POPPK approach can be employed to assess the performance of alternative pharmacokinetic sampling techniques. This approach provides a robust solution in scenarios where variability in pharmacokinetic data collected via venous sampling and microsampling may not result in a strong linear relationship. The findings also established that microsampling techniques may replace conventional venous sampling methods.

Current Status of Pharmacokinetic Research in Children: A Systematic Review of Clinical Trial Records

BACKGROUND

Many medications have different pharmacokinetics in children than in adults. Knowledge about the safety and efficacy of medications in children requires research into the pharmacokinetic profiles of children's medicines. By analysing registered clinical trial records, this study determined how frequently pharmacokinetic data is gathered in paediatric drug trials.

METHODS

We searched for the pharmacokinetic data from clinical trial records for preterm infants and children up to the age of 16 from January 2011 to April 2022. The records of trials involving one or more drugs in preterm infants and children up to the age of 16 were examined for evidence that pharmacokinetic data would be collected.

RESULTS

In a total of 1483 records of interventional clinical trials, 136 (9.17%) pharmacokinetic data involved adults. Of those 136 records, 60 (44.1%) records were pharmacokinetics trials involving one or more medicines in children up to the age of 16.20 (33.3%) in America, followed by 19 (31.6%) in Europe. Most trials researched medicines in the field of infection or parasitic diseases 20 (33.3%). 27 (48.2%) and 26 (46.4%) trials investigated medicines that were indicated as essential medicine.

CONCLUSION

The pharmacokinetic characteristics of children's drugs need to be better understood. The current state of pharmacokinetic research appears to address the knowledge gap in this area adequately. Despite slow progress, paediatric clinical trials have experienced a renaissance as the significance of paediatric trials has gained international attention. The outcome of paediatric trials will have an impact on children's health in the future. In recent years, the need for greater availability and access to safe child-size pharmaceuticals has received a lot of attention.

Sensitivity of estimated tacrolimus population pharmacokinetic profile to assumed dose timing and absorption in real-world data and simulated data

AIMS

Use of electronic health record (EHR) data to estimate population pharmacokinetic (PK) profiles necessitates several assumptions. We sought to investigate sensitivity to some of these assumptions about dose timing and absorption rates.

METHODS

A population PK study with 363 subjects was performed using real-world data extracted from EHRs to estimate the tacrolimus population PK profile. Data were extracted and built using our automated system, EHR2PKPD, suitable for quickly constructing large PK datasets from the EHR. Population PK studies for oral medications performed using EHR data often assume a regular dosing schedule as prescribed without incorporating exact dosing time. We assessed the sensitivity of the PK parameter estimates to assumptions about dose timing using last-dose times extracted by our own natural language processing system, medExtractR. We also investigated the sensitivity of estimates to absorption rate constants that are often fixed at a published value in tacrolimus population PK analyses. We conducted simulation studies to investigate how drug PK profiles and experimental designs such as concentration measurements design affect sensitivity to incorrect assumptions about dose timing and absorption rates.

RESULTS

There was no appreciable difference in parameter estimates with assumed versus extracted last-dose time, and our sensitivity analysis revealed little difference between parameters estimated across a range of assumed absorption rate constants.

CONCLUSION

Our findings suggest that drugs with a slower elimination rate (or a longer half-life) are less sensitive to dose timing errors and that experimental designs which only allow for trough blood concentrations are usually insensitive to deviation in absorption rate.

Dose tailoring of tacrolimus based on a non-linear pharmacokinetic model in children with refractory nephrotic syndrome

The population pharmacokinetics (PPK) of tacrolimus (TAC) in children with refractory nephrotic syndrome (RNS) have not been well-characterized. This study aimed to investigate the significant factors affecting the TAC PPK characteristics of children with RNS and to optimize the dosing regimen. A total of 494 concentrations from 108 children were obtained from routine therapeutic drug monitoring between 2016 and 2018. Information regarding the demographic features, laboratory test results, genetic polymorphisms of CYP3A5 (rs776746) and co-therapy medications were collected. PPK analysis was performed using the nonlinear mixed-effects modelling (NONMEM) software and two modelling strategies (the linear one-compartment model and nonlinear Michaelis-Menten model) were evaluated and compared. CYP3A5 genotype, weight, daily dose of TAC and daily dose of diltiazem were retained in the final linear model. The absorption rate constant (Ka) was set at 4.48 h^-1 in the linear model, and the apparent clearance (CL/F) and volume of distribution (V/F) in the final linear model were 14.2 L/h and 172 L, respectively. CYP3A5 genotype, weight and daily dose of diltiazem were the significant factors retained in the final nonlinear model. The maximal dose rate (V_max) and the average steady-state concentration at half-Vmax (K_m) in the final nonlinear model were 2.15 mg/day and 0.845 ng/ml, respectively. The nonlinear model described the pharmacokinetic data of TAC better than the linear model in children with RNS. A dosing regimen was proposed based on weight, CYP3A5 genotype and daily dose of diltiazem according to the final nonlinear PK model, which may facilitate individualized drug therapy with TAC.

Important considerations for drugs, nutritional, and herbal supplements in pediatric solid organ transplant recipients

Pediatric transplant recipients are on multiple prescription and non-prescription drugs. Many patients also use dietary, nutritional, and herbal supplements. This manuscript researched formulations of immunosuppressive drugs currently available and presents information on generic immunosuppressive drugs, commonly used non-prescription medications, dietary supplements, and herbal supplements. Immunosuppressive drugs are available in various formulations. Not all formulations are interchangeable. A number of FDA-approved generic formulations are available commercially in the United States. Generally generic formulations produce similar blood concentration vs time profiles compared to brand name products in adults and are considered to be bioequivalent. NSAID should be avoided in transplant patients due to potential drug interactions and increased risk associated with NSAID use; and appropriate doses of acetaminophen should be used for treatment of pain. Over-the-counter medications, such as guaifenesin and dextromethorphan, antihistamine medications, including diphenhydramine, loratadine, cetirizine, and fexofenadine, can be safely used in pediatric solid organ transplant population. Many safe and effective over-the-counter options exist for stool softening and as laxative. Diarrhea can lead to an increase in calcineurin inhibitor levels. Food can alter the absorption of immunosuppressive drugs. Several herbal products can alter immune status of the patients or alter the blood concentration of immunosuppressive drugs or may produce renal or hepatic toxicities and should be avoided in pediatric transplant recipients. It is important to educate pediatric transplant recipients and their families about not only immunosuppressive drug therapy but also about non-prescription drugs, dietary, and herbal supplement use.

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.

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.

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.

Limited sampling strategy to predict the area under the curve of tacrolimus in Mexican renal transplant pediatric patients receiving Prograf® or non-innovator formulations

TDM of tacrolimus is usually performed with trough levels (C_0h ). However, in pediatric patients, C_0h may not be an adequate marker. The AUC is considered a more suitable indicator of drug exposure. As several blood samples are needed for the estimation of AUC, and LSS for predicting tacrolimus AUC and optimizing the dose adjustment have been proposed. Moreover, in emerging countries such as Mexico, non-innovator formulations, which bioequivalence has not been demonstrated, are frequently used. Hence, the aim of this study was to develop and validate a LSS to predict the tacrolimus AUC_0-12h in Mexican pediatric kidney transplant recipients who received either Prograf^® or non-innovator tacrolimus formulations. A total of 56 pharmacokinetic profiles were randomized into two groups: model development (n = 28) and model validation (n = 28). The limited sampling equations were obtained after a stepwise multiple regression using AUC as the dependent variable and tacrolimus blood concentrations, quantified by CMIA, at different time points as the independent variables. The final equation included observed concentrations at 1 hour (C_1h ) and 4 hours (C_4h ) after dose administration. The predictive performance of the model was adequate in terms of both, bias and precision. Results strongly suggest that the clinical use of this LSS could provide an ethical, cost-, and time-effective method in the TDM of tacrolimus in pediatric patients with kidney transplant. The model proved to be adequate with either Prograf^® or non-innovator tacrolimus formulations of dubious bioequivalence.

Population pharmacokinetics of tacrolimus in pediatric patients with systemic-onset juvenile idiopathic arthritis: Initial dosage recommendations

Pediatric patients with systemic-onset juvenile idiopathic arthritis (SOJIA) may be treated with tacrolimus. However, the therapeutic range for tacrolimus is narrow with considerable inter- and intra-individual variability, making it difficult to formulate an ideal dosage regimen for personalized treatment. The purpose of the present study was to set up a population pharmacokinetics (PPK) model of tacrolimus treatment for SOJIA to determine the optimal initial dosage. Patients with SOJIA were analyzed using non-linear mixed-effects modeling. Different regimens were analyzed using Monte Carlo simulation with concentration profiles. A first-order absorption and elimination one-compartment model was selected as the most appropriate model for SOJIA. Based on initial dosage recommendations, the regimen of 0.5 mg every 24 h (q24h) appeared to be most suitable for subjects with a body weight of 5 kg, while the 0.5 mg q12h regimen was most suitable for subjects with a body weight of 15–25 kg, the 1/0.5 mg q24h regimen was appropriate for the 26–35 kg group and the 1 mg q12h regimen was suitable for the subjects with a body weight of 36–50 kg. To the best of our knowledge, the present study established the first PPK model of tacrolimus treatment that may be used for the selection of the initial dose based on body weight of pediatric patients with SOJIA.

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

Background

Multiple clinical, demographic, and genetic factors affect the pharmacokinetics of tacrolimus in children, yet in daily practice, a uniform body-weight based starting dose is used. It can take weeks to reach the target tacrolimus pre-dose concentration.

Objectives

The objectives of this study were to determine the pharmacokinetics of tacrolimus immediately after kidney transplantation and to find relevant parameters for dose individualization using a population pharmacokinetic analysis.

Methods

A total of 722 blood samples were collected from 46 children treated with tacrolimus over the first 6 weeks after renal transplantation. Non-linear mixed-effects modeling (NONMEM^®) was used to develop a population pharmacokinetic model and perform a covariate analysis. Simulations were performed to determine the optimal starting dose and to develop dosing guidelines.

Results

The data were accurately described by a two-compartment model with allometric scaling for bodyweight. Mean tacrolimus apparent clearance was 50.5 L/h, with an inter-patient variability of 25%. Higher bodyweight, lower estimated glomerular filtration rate, and higher hematocrit levels resulted in lower total tacrolimus clearance. Cytochrome P450 3A5 expressers and recipients who received a kidney from a deceased donor had a significantly higher tacrolimus clearance. The model was successfully externally validated. In total, these covariates explained 41% of the variability in clearance. From the significant covariates, the cytochrome P450 3A5 genotype, bodyweight, and donor type were useful to adjust the starting dose to reach the target pre-dose concentration. Dosing guidelines range from 0.27 to 1.33 mg/kg/day.

Conclusion

During the first 6 weeks after transplantation, the tacrolimus weight-normalized starting dose should be higher in pediatric kidney transplant recipients with a lower bodyweight, those who express the cytochrome P450 3A5 genotype, and those who receive a kidney from a deceased donor.

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 Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Tacrolimus, a calcineurin inhibitor, is a common immunosuppressant prescribed after organ transplantation and has notable inter- and intrapatient pharmacokinetic variability. The sources of variability have been investigated using population pharmacokinetic modeling over the last 2 decades. This article provides an updated synopsis on published nonlinear mixed-effects analyses developed for tacrolimus in transplant recipients. The objectives were to establish a detailed overview of the current data and to investigate covariate relationships determined by the models. Sixty-three published analyses were reviewed, and data regarding the study design, modeling approach, and resulting findings were extracted and summarized. Most of the studies investigated tacrolimus pharmacokinetics in adult and pediatric renal and liver transplants after administration of the immediate-release formulation. Model structures largely depended on the study sampling strategy, with ∼50% of studies developing a 1-compartment model using trough concentrations and a 2-compartment model with delayed absorption from intensive sampling. The CYP3A5 genotype, as a covariate, consistently impacted tacrolimus clearance, and dosing adjustments were required to achieve similar drug exposure among patients. Numerous covariates were identified as sources of interindividual variability on tacrolimus pharmacokinetics with limited consistency across these studies, which may be the result of the study designs. Additional analyses are required to further evaluate the potential impact of these covariates and the clinical implementation of these models to guide tacrolimus dosing recommendations. This article may be useful for guiding the design of future population pharmacokinetic studies and provides recommendations for the selection of an existing optimal model to individualize tacrolimus therapy.

Tacrolimus Population Pharmacokinetics and Multiple CYP3A5 Genotypes in Black and White Renal Transplant Recipients

Tacrolimus exhibits inter-patient pharmacokinetic variability attributed to CYP3A5 isoenzymes and the efflux transporter, P-glycoprotein. Most black renal transplant recipients require higher tacrolimus doses compared to whites to achieve similar troughs when race-adjusted recommendations are used. An established guideline provides tacrolimus genotype dosing recommendations based on CYP3A5*1(W/T) and loss of protein function variants: CYP3A5*3 (rs776746), CYP3A5*6 (rs10264272), CYP3A5*7 (rs41303343) and may provide more comprehensive race-adjusted dosing recommendations. Our objective was to develop a tacrolimus population pharmacokinetic model evaluating demographic, clinical, and genomic factors in stable black and white renal transplant recipients. A secondary objective investigated race-based tacrolimus regimens and genotype-specific dosing. Sixty-seven recipients receiving oral tacrolimus and mycophenolic acid ≥6 months completed a 12-hour pharmacokinetic study. CYP3A5*3,*6,*7 and ABCB1 1236C>T, 2677G>T/A, 3435C>T polymorphisms were characterized. Patients were classified as extensive, intermediate, and poor metabolizers using a novel CYP3A5*3*6*7 metabolic composite. Modeling and simulation was performed with computer software (NONMEM 7.3, ICON Development Solutions; Ellicott City, Maryland). A 2-compartment model with first-order elimination and absorption with lag time best described the data. The CYP3A5*3*6*7 metabolic composite was significantly associated with tacrolimus clearance (P value < .05), which was faster in extensive (mean: 45.0 L/hr) and intermediate (29.5 L/hr) metabolizers than poor metabolizers (19.8 L/hr). Simulations support CYP3A5*3*6*7 genotype-based tacrolimus dosing to enhance general race-adjusted regimens, with dose increases of 1.5-fold and 2-fold, respectively, in intermediate and extensive metabolizers for comparable exposures to poor metabolizers. This model offers a novel approach to determine tacrolimus dosing adjustments that maintain comparable therapeutic exposure between black and white recipients with different CYP3A5 genotypes.

A New CYP3A5*3 and CYP3A4*22 Cluster Influencing Tacrolimus Target Concentrations: A Population Approach

BACKGROUND

Single nucleotide polymorphisms (SNPs) in the CYP3A5 and CYP3A4 genes have been reported to be an important cause of variability in the pharmacokinetics of tacrolimus in renal transplant patients. The aim of this study was to merge all of the new genetic information available with tacrolimus pharmacokinetics to generate a more robust population model with data from renal transplant recipients.

METHODS

Tacrolimus exposure data from 304 renal transplant recipients were collected throughout the first year after transplantation and were simultaneously analyzed with a population pharmacokinetic approach using NONMEM^® version 7.2.

RESULTS

The tacrolimus whole-blood concentration versus time data were best described by a two-open-compartment model with inter-occasion variability assigned to plasma clearance. The following factors led to the final model, which significantly decreased the minimum objective function value (p < 0.001): a new genotype cluster variable combining the CYP3A5*3 and CYP3A4*22 SNPs defined as extensive, intermediate, and poor metabolizers; the standardization of tacrolimus whole blood concentrations to a hematocrit value of 45%; and age included as patients <63 years versus patients ≥63 years. External validation confirmed the prediction ability of the model with median bias and precision values of 1.17 ng/mL (95% confidence interval [CI] -3.68 to 4.50) and 1.64 ng/mL (95% CI 0.11-5.50), respectively. Simulations showed that, for a given age and hematocrit at the same fixed dose, extensive metabolizers required the highest doses followed by intermediate metabolizers and then poor metabolizers.

CONCLUSIONS

Tacrolimus disposition in renal transplant recipients was described using a new population pharmacokinetic model that included the CYP3A5*3 and CYP3A4*22 genotype, age, and hematocrit.

Predicting tacrolimus concentrations in children receiving a heart transplant using a population pharmacokinetic model

OBJECTIVE

Immunosuppressant therapy plays a pivotal role in transplant success and longevity. Tacrolimus, a primary immunosuppressive agent, is well known to exhibit significant pharmacological interpatient and intrapatient variability. This variability necessitates the collection of serial trough concentrations to ensure that the drug remains within therapeutic range. The objective of this study was to build a population pharmacokinetic (PK) model and use it to determine the minimum number of trough samples needed to guide the prediction of an individual's future concentrations.

DESIGN SETTING AND PATIENTS

Retrospective data from 48 children who received tacrolimus as inpatients at Primary Children's Hospital in Salt Lake City, Utah were included in the study. Data were collected within the first 6 weeks after heart transplant.

OUTCOME MEASURES

Data analysis used population PK modelling techniques in NONMEM. Predictive ability of the model was determined using median prediction error (MPE, a measure of bias) and median absolute prediction error (MAPE, a measure of accuracy). Of the 48 children in the study, 30 were used in the model building dataset, and 18 in the model validation dataset.

RESULTS

Concentrations ranged between 1.5 and 37.7 μg/L across all collected data, with only 40% of those concentrations falling within the targeted concentration range (12 to 16 μg/L). The final population PK model contained the impact of age (on volume), creatinine clearance (on elimination rate) and fluconazole use (on elimination rate) as covariates. Our analysis demonstrated that as few as three concentrations could be used to predict future concentrations, with negligible bias (MPE (95% CI)=0.10% (-2.9% to 3.7%)) and good accuracy (MAPE (95% CI)=24.1% (19.7% to 27.7%)).

CONCLUSIONS

The use of PK in dose guidance has the potential to provide significant benefits to clinical care, including dose optimisation during the early stages of therapy, and the potential to limit the need for frequent drug monitoring.

CYP3A5 Genotype and Time to Reach Tacrolimus Therapeutic Levels in Renal Transplant Children

BACKGROUND

CYP3A5 gene polymorphism rs776746 has been associated with lower tacrolimus dose requirements and bioavailability in both adults and children. This variant causes a loss of CYP3A5 activity owing to a splice site variant leading to a truncated inactive enzyme. The aim of this study was to determine if the rs776746 gene polymorphism is related to the time to reach tacrolimus therapeutic levels in renal transplant children.

METHODS

A prospective study was performed in renal transplant children receiving tacrolimus as part of their immunosuppressive regime. CYP3A5 genotype was determined by direct sequencing. Tacrolimus trough levels and serum creatinine at 1 week and 1 month after renal transplantation was obtained from clinical chart.

RESULTS

A total of 42 patients were included; 19 (45.2%) were female, 23 (54.8%) received living-donor transplants, and 21 patients expressed CYP3A5*1/*1 or CYP3A5*1/*3. Tacrolimus dose was higher in expressers at week 1 (0.13 vs 0.10 mg/kg/d; P = .011), and week 4 after transplantation (0.17 vs 0.09 mg/kg/d; P < .0001). At 4 weeks after renal transplantation, only 9 patients from the expressers group (42.8%) had levels ≥7 ng/mL, in contrast to 18 in the nonexpressers group (85.7%; Fisher exact P = .008).

CONCLUSIONS

Tacrolimus dose was significant higher in functional CYP3A5 expressers. Only 42.8% of such expressers had tacrolimus trough levels ≥7 ng/mL at 1 month after transplantation despite dose adjustments. Long-term follow up is needed to address the consequences of early post-transplantation bioavailability differences due to CYP3A5 genotype.