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

Pharmacokinetic Model of Drug Interaction of Tacrolimus with Combined Administration of CYP3A4 Inhibitors Voriconazole and Clarithromycin After Bone Marrow Transplantation

BACKGROUND AND OBJECTIVES

A pharmacokinetic model has been developed to quantify the drug-drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes.

METHODS

This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [Emax], Emax, log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment.

RESULTS

The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0-9.9) ng/mL (n = 3). The final model comprised the Sigmoid Emax model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin.

CONCLUSIONS

These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant.

Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools

BACKGROUND AND OBJECTIVE

Tacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment.

METHODS

We performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration.

RESULTS

We identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey.

CONCLUSIONS

Our work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

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.

Ultra-Long-Term Delivery of Hydrophilic Drugs Using Injectable In Situ Cross-Linked Depots

Achieving ultra-long-term release of hydrophilic drugs over several months remains a significant challenge for existing long-acting injectables (LAIs). Existing platforms, such as in situ forming implants (ISFI), exhibit high burst release due to solvent efflux and microsphere-based approaches lead to rapid drug diffusion due to significant water exchange and large pores. Addressing these challenges, we have developed an injectable platform that, for the first time, achieves ultra-long-term release of hydrophilic drugs for over six months. This system employs a methacrylated ultra-low molecular weight pre-polymer (polycaprolactone) to create in situ cross-linked depots (ISCD). The ISCD's solvent-free design and dense mesh network, both attributed to the ultra-low molecular weight of the pre-polymer, effectively minimizes burst release and water influx/efflux. In vivo studies in rats demonstrate that ISCD outperforms ISFI by achieving lower burst release and prolonged drug release. We demonstrated the versatility of ISCD by showcasing ultra-long-term delivery of several hydrophilic drugs, including antiretrovirals (tenofovir alafenamide, emtricitabine, abacavir, and lamivudine), antibiotics (vancomycin and amoxicillin) and an opioid antagonist naltrexone. Additionally, ISCD achieved ultra-long-term release of the hydrophobic drug tacrolimus and enabled co-delivery of hydrophilic drug combinations encapsulated in a single depot. We also identified design parameters to tailor the polymer network, tuning drug release kinetics and ISCD degradation. Pharmacokinetic modeling predicted over six months of drug release in humans, significantly surpassing the one-month standard achievable for hydrophilic drugs with existing LAIs. The platform's biodegradability, retrievability, and biocompatibility further underscore its potential for improving treatment adherence in chronic conditions.

Assessing the Utility of a Genotype-Guided Tacrolimus Equation in African American Kidney Transplant Recipients: A Single Institution Retrospective Study

Tacrolimus metabolism is heavily influenced by the CYP3A5 genotype, which varies widely among African Americans (AA). We aimed to assess the performance of a published genotype-informed tacrolimus dosing model in an independent set of adult AA kidney transplant (KTx) recipients. CYP3A5 genotypes were obtained for all AA KTx recipients (n = 232) from 2010 to 2019 who met inclusion criteria at a single transplant center in Philadelphia, Pennsylvania, USA. Medical record data were used to calculate predicted tacrolimus clearance using the published AA KTx dosing equation and two modified iterations. Observed and model-predicted trough levels were compared at 3 days, 3 months, and 6 months post-transplant. The mean prediction error at day 3 post-transplant was 3.05 ng/mL, indicating that the model tended to overpredict the tacrolimus trough. This bias improved over time to 1.36 and 0.78 ng/mL at 3 and 6 months post-transplant, respectively. Mean absolute prediction error-a marker of model precision-improved with time to 2.33 ng/mL at 6 months. Limiting genotype data in the model decreased bias and improved precision. The bias and precision of the published model improved over time and were comparable to studies in previous cohorts. The overprediction observed by the published model may represent overfitting to the initial cohort, possibly limiting generalizability.

Effect of isotretinoin on CYP2D6 and CYP3A activity in patients with severe acne

AIMS

Previously, retinoids have decreased CYP2D6 mRNA expression in vitro and induced CYP3A4 in vitro and in vivo. This study aimed to determine whether isotretinoin administration changes CYP2D6 and CYP3A activities in patients with severe acne.

METHODS

Thirty-three patients (22 females and 11 males, 23.5 ± 6.0 years old) expected to receive isotretinoin treatment completed the study. All participants were genotyped for CYP2D6 and CYP3A5. Participants received dextromethorphan (DM) 30 mg orally as a dual-probe substrate of CYP2D6 and CYP3A activity at two study timepoints: pre-isotretinoin treatment and with isotretinoin for at least 1 week. The concentrations of isotretinoin, DM and their metabolites were measured in 2-h postdose plasma samples and in cumulative 0-4-h urine collections using liquid chromatography-mass spectrometry.

RESULTS

In CYP2D6 extensive metabolizers, the urinary dextrorphan (DX)/DM metabolic ratio (MR) (CYP2D6 activity marker) was numerically, but not significantly, lower with isotretinoin administration compared to pre-isotretinoin (geometric mean ratio [GMR] [90% confidence interval (CI)] 0.78 [0.55, 1.11]). The urinary 3-hydroxymorphinan (3HM)/DX MR (CYP3A activity marker) was increased (GMR 1.18 [1.03, 1.35]) and the urinary DX-O-glucuronide/DX MR (proposed UGT2B marker) was increased (GMR 1.22 [1.06, 1.39]) with isotretinoin administration compared to pre-isotretinoin.

CONCLUSIONS

Administration of isotretinoin did not significantly reduce CYP2D6 activity in extensive metabolizers, suggesting that the predicted downregulation of CYP2D6 based on in vitro data does not translate into humans. We observed a modest increase in CYP3A activity (predominantly CYP3A4) with isotretinoin treatment. The data also suggest that DX glucuronidation is increased following isotretinoin administration.

Effect of Tacrolimus Formulation (Prolonged-Release vs Immediate-Release) on Its Susceptibility to Drug-Drug Interactions with St. John's Wort

Tacrolimus is metabolized by cytochrome P450 3A (CYP3A) and is susceptible to interactions with the CYP3A and P-glycoprotein inducer St. John's Wort (SJW). CYP3A isozymes are predominantly expressed in the small intestine and liver. Prolonged-release tacrolimus (PR-Tac) is largely absorbed in distal intestinal segments and is less susceptible to CYP3A inhibition. The effect of induction by SJW is unknown. In this randomized, crossover trial, 18 healthy volunteers received single oral tacrolimus doses (immediate-release [IR]-Tac or PR-Tac, 5 mg each) alone and during induction by SJW. Concentrations were quantified using ultra-high performance liquid chromatography coupled with tandem mass spectrometry and non-compartmental pharmacokinetics were evaluated. SJW decreased IR-Tac exposure (area under the concentration-time curve) to 73% (95% confidence interval 60%-88%) and maximum concentration (Cmax ) to 61% (52%-73%), and PR-Tac exposure to 67% (55%-81%) and Cmax to 69% (58%-82%), with no statistical difference between the 2 formulations. The extent of interaction appeared to be less pronounced in volunteers with higher baseline CYP3A4 activity and in CYP3A5 expressors. In contrast to CYP3A inhibition, CYP3A induction by SJW showed a similar extent of interaction with both tacrolimus formulations. A higher metabolic baseline capacity appeared to attenuate the extent of induction by SJW.

Dosage optimization of tacrolimus based on the glucocorticoid dose and pharmacogenetics in adult patients with systemic lupus erythematosus

BACKGROUND

The purpose of the study was to develop a genotype-incorporated population pharmacokinetic (PPK) model of tacrolimus (TAC) in adults with systemic lupus erythematosus (SLE) to investigate the factors influencing TAC pharmacokinetics and to develop an individualized dosing regimen based on the model. In addition, a non-genotype-incorporated model was also established to assess its predictive performance compared to the genotype-incorporated model.

METHODS

A total of 365 trough concentrations from 133 adult SLE patients treated with TAC were collected to develop a genotype-incorporated PPK model and a non-genotype-incorporated PPK model of TAC using a nonlinear mixed-effects model (NONMEM). External validation of the two models was performed using data from an additional 29 patients. Goodness-of-fit diagnostic plots, bootstrap method, and normalized predictive distribution error test were used to validate the predictive performance and stability of the final models. The goodness-of-fit of the two final models was compared using the Akaike information criterion (AIC). The dosing regimen was optimized using Monte Carlo simulations based on the developed optimal model.

RESULTS

The typical value of the apparent clearance (CL/F) of TAC estimated in the final genotype-incorporated model was 14.3 L h-1 with inter-individual variability of 27.6%. CYP3A5 polymorphism and coadministered medication were significant factors affecting TAC-CL/F. CYP3A5 rs776746 GG genotype carriers had only 77.3% of the TAC-CL/F of AA or AG genotype carriers. Omeprazole reduced TAC-CL/F by 3.7 L h-1 when combined with TAC, while TAC-CL/F increased nonlinearly as glucocorticoid dose increased. Similar findings were demonstrated in the non-genotype-incorporated PPK model. Comparing these two models, the genotype-incorporated PPK model was superior to the non-genotype-incorporated PPK model (AIC = 643.19 vs. 657.425). Monte Carlo simulation based on the genotype-incorporated PPK model indicated that CYP3A5 rs776746 AA or AG genotype carriers required a 1/2-1 fold higher dose of TAC than GG genotype carriers to achieve the target concentration. And as the daily dose of prednisone increases, the dose of TAC required to reach the target concentration increases appropriately.

CONCLUSIONS

We developed the first pharmacogenetic-based PPK model of TAC in adult patients with SLE and proposed a dosing regimen based on glucocorticoid dose and CYP3A5 genotype according to the model, which could facilitate individualized dosing for TAC.

Bayesian optimization of tacrolimus exposure in stable kidney transplant patients

STUDY OBJECTIVE

The objective was to compare tacrolimus AUC0-12 determined by Non-Compartmental Analysis (NCA) using intensive sampling to Maximum a Posteriori-Bayesian (MAP-Bayesian) estimates from robust (n = 9 samples/subject) and sparse (n = 2 samples/subject) sampling in 67 stable KTRs and a validation group of similar patients.

DESIGN

This open-label, prospective, single center 12-h PK study included nine serial samples collected in KTRs to determine steady-state NCA tacrolimus AUC0-12 .

SETTING

This study was conducted at a single site within a large, urban hospital in the western New York area.

PATIENTS

This study described tacrolimus pharmacokinetics in stable kidney transplant recipients on maintenance tacrolimus therapy.

INTERVENTION

Robust and sparse AUC0-12 estimates by a MAP-Bayesian approach were obtained using the Advanced Dosing Solutions (AdDS) and ADAPT5 freeware. Limited sampling strategies were evaluated using the original population PK model (n = 67), which was also assessed using a validation group (n = 15). AUC0-12 agreement was tested by paired t-tests with intraclass correlation coefficient (ICC) and Bland Altman analysis.

MEASUREMENTS AND MAIN RESULTS

A total of 35 Black and 32 White stable KTRs (estimated glomerular filtration rate [eGFR] = 55.2 ± 15.7 mL/min/1.73m2 ) received the tacrolimus dose of 3.4 ± 1.7 mg/study with troughs of 6.8 ± 1.8 ng/mL. The NCA-AUC0-12 was 123.8 ± 33.6 μg·h/L compared to MAP-Bayesian estimates for Robust-AUC0-12 of 124.7 ± 33.3 μg·h/L and optimal 2-specimen Sparse-AUC0-12 of 119.7 ± 32.7 μg·h/L for the training group. Comparison of Robust-AUC0-12 to NCA-AUC0-12 had an ICC of 0.96 (p = 0.99) while comparison of Robust-AUC0-12 to Sparse-AUC0-12 using Pre-dose trough [C(t0h )] and 1 h [C(t1h )] resulted in an ICC of 0.93 (p = 0.014). In the validation group, 5 Black and 10 White KTRs (eGFR = 56.4 ± 16.8 mL/min/1.73m2 ) received a mean tacrolimus dose of 1.9 ± 1.2 mg/study with a trough of 6.0 ± 1.7 ng/mL. The validation group's NCA-AUC0-12 (88.4 ± 33.1 μg·h/L) was comparable to Robust-AUC0-12 (85.1 ± 33.8 μg·h/L, ICC = 0.93; p = 0.12) and Sparse-AUC0-12 determined from C(t0h ) and C(t4h ) (86.7 ± 33.9 μg·h/L, ICC = 0.91; p = 0.61).

CONCLUSION

MAP-Bayesian estimation for patient-specific AUC0-12 using sparse, two-specimen sampling is comparable to NCA and may enhance tacrolimus TDM in stable KTRs.

The Value of Pharmacogenomics for White and Indigenous Americans after Kidney Transplantation

BACKGROUND

There is a paucity of evidence to inform the value of pharmacogenomic (PGx) results in patients after kidney transplant and how these results differ between Indigenous Americans and Whites. This study aims to identify the frequency of recommended medication changes based on PGx results and compare the pharmacogenomic (PGx) results and patients' perceptions of the findings between a cohort of Indigenous American and White kidney transplant recipients.

METHODS

Thirty-one Indigenous Americans and fifty White kidney transplant recipients were studied prospectively. Genetic variants were identified using the OneOme RightMed PGx test of 27 genes. PGx pharmacist generated a report of the genetic variation and recommended changes. Pre- and post-qualitative patient surveys were obtained.

RESULTS

White and Indigenous American subjects had a similar mean number of medications at the time of PGx testing (mean 13 (SD 4.5)). In the entire cohort, 53% received beta blockers, 30% received antidepressants, 16% anticoagulation, 47% pain medication, and 25% statin therapy. Drug-gene interactions that warranted a clinical action were present in 21.5% of patients. In 12.7%, monitoring was recommended. Compared to the Whites, the Indigenous American patients had more normal CYP2C19 (p = 0.012) and CYP2D6 (p = 0.012) activities. The Indigenous American patients had more normal CYP4F2 (p = 0.004) and lower VKORC (p = 0.041) activities, phenotypes for warfarin drug dosing, and efficacy compared to the Whites. SLC6A4, which affects antidepressant metabolism, showed statistical differences between the two cohorts (p = 0.017); specifically, SLC6A4 had reduced expression in 45% of the Indigenous American patients compared to 20% of the White patients. There was no significant difference in patient perception before and after PGx.

CONCLUSIONS

Kidney transplant recipients had several drug-gene interactions that were clinically actionable; over one-third of patients were likely to benefit from changes in medications or drug doses based on the PGx results. The Indigenous American patients differed in the expression of drug-metabolizing enzymes and drug transporters from the White patients.

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.

Adaptation of a population pharmacokinetic model to inform tacrolimus therapy in heart transplant recipients

AIM

Existing tacrolimus population pharmacokinetic models are unsuitable for guiding tacrolimus dosing in heart transplant recipients. This study aimed to develop and evaluate a population pharmacokinetic model for tacrolimus in heart transplant recipients that considers the tacrolimus-azole antifungal interaction.

METHODS

Data from heart transplant recipients (n = 87) administered the oral immediate-release formulation of tacrolimus (Prograf®) were collected. Routine drug monitoring data, principally trough concentrations, were used for model building (n = 1099). A published tacrolimus model was used to inform the estimation of Ka , V2 /F, Q/F and V3 /F. The effect of concomitant azole antifungal use on tacrolimus CL/F was quantified. Fat-free mass was implemented as a covariate on CL/F, V2 /F, V3 /F and Q/F on an allometry scale. Subsequently, stepwise covariate modelling was performed. Significant covariates influencing tacrolimus CL/F were included in the final model. Robustness of the final model was confirmed using prediction-corrected visual predictive check (pcVPC). The final model was externally evaluated for prediction of tacrolimus concentrations of the fourth dosing occasion (n = 87) from one to three prior dosing occasions.

RESULTS

Concomitant azole antifungal therapy reduced tacrolimus CL/F by 80%. Haematocrit (∆OFV = -44, P < .001) was included in the final model. The pcVPC of the final model displayed good model adequacy. One recent drug concentration is sufficient for the model to guide tacrolimus dosing.

CONCLUSION

A population pharmacokinetic model that adequately describes tacrolimus pharmacokinetics in heart transplant recipients, considering the tacrolimus-azole antifungal interaction was developed. Prospective evaluation is required to assess its clinical utility to improve patient outcomes.

Influence of CYP3A5, IL-10 polymorphisms and metabolism rate on tacrolimus exposure in renal post-transplant recipients

Aim: To investigate the influence of CYP3A5 and IL-10 polymorphisms on tarcolimus metabolism and renal function for renal transplantation recipients at a stable period. Methods: CYP3A5 and IL-10 polymorphisms, together with other clinical factors, were collected for 149 renal transplantation patients at postoperative stable period. Statistics analysis was performed to explore key factors affecting tarcolimus metabolism. Results: CYP3A5 6986A >G and IL-10 -819C >T significantly impacted tacrolimus metabolism (p < 0.001). CYP3A5 6986A >G G allele and IL-10 -819C >T T allele were associated with poorer tacrolimus metabolic capability. Patients with various tacrolimus metabolism rates presented little difference in renal functions at stable period. Conclusion: Genotyping of CYP3A5 and IL-10 might benefit the precision dosage of tacrolimus for renal transplantation recipients.

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.

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

Population Pharmacokinetic Evaluation with External Validation of Tacrolimus in Chinese Primary Nephrotic Syndrome Patients

PURPOSE

The generalizability of numerous tacrolimus population pharmacokinetic (popPK) models constructed to promote optimal tacrolimus dosing in patients with primary nephrotic syndrome (PNS) is unclear. This study aimed to evaluate the predictive performance of published tacrolimus popPK models for PNS patients with an external data set.

METHODS

We prospectively collected 223 concentrations from 50 Chinese adult patients with PNS who were undergoing tacrolimus treatment. Data on published tacrolimus popPK models for adults and children with PNS were extracted from the literature. Model predictability was evaluated with prediction-based and simulation-based diagnostics and Bayesian forecasting.

RESULTS

In prediction-based evaluation, none of the 11 identified published popPK models of tacrolimus had met a predefined criteria of a mean prediction error ≤  ± 20%, and the prediction error within ± 30% of the identified models didn't exceed 50%. Simulation-based diagnostics also indicated unsatisfactory predictability. Bayesian forecasting demonstrated amelioration in the model predictability with the inclusion of 2-3 prior observations. Moreover, the predictive performance of nonlinear models was not better than that of one-compartment models.

CONCLUSIONS

The prediction of tacrolimus concentrations for patients with PNS remains challenging; published models are not applicable for extrapolation to other hospitals. Bayesian forecasting significantly improved model predictability and thereby helped to individualize tacrolimus dosing.

Race and sex associations with tacrolimus pharmacokinetics in stable kidney transplant recipients

Study Objective

This study investigated race and sex differences in tacrolimus pharmacokinetics and pharmacodynamics in stable kidney transplant recipients.

Design and Setting

A cross‐sectional, open‐label, single center, 12‐h pharmacokinetic‐pharmacodynamic study was conducted. Tacrolimus pharmacokinetic parameters included area under the concentration‐time curve (AUC_0–12), AUC_0–4, 12‐h troughs (C_12 h), maximum concentrations (C_max), oral clearance (Cl), with dose‐normalized AUC_0–12, troughs, and C_max with standardized adverse effect scores. Statistical models were used to analyze end points with individual covariate‐adjustment including clinical factors, genotypic variants CYP3A5*3, CYP3A5*6, CYP3A5*7(CYP3A5*3*6*7) metabolic composite, and ATP binding cassette gene subfamily B member 1 (ABCB1) polymorphisms.

Patients

65 stable, female and male, Black and White kidney transplant recipients receiving tacrolimus and mycophenolic acid ≥6 months post‐transplant were evaluated.

Measurements and Main Results

Black recipients exhibited higher tacrolimus AUC_0–12 (Race: p = 0.005), lower AUC* (Race: p < 0.001; Race × Sex: p = 0.068), and higher Cl (Race: p < 0.001; Sex: p = 0.066). Greater cumulative (Sex: p < 0.001; Race × Sex: p = 0.014), neurologic (Sex: p = 0.021; Race × Sex: p = 0.005), and aesthetic (Sex: p = 0.002) adverse effects were found in females, with highest scores in Black women. In 84.8% of Black and 68.8% of White patients, the target AUC_0–12 was achieved (p = 0.027). In 31.3% of White and 9.1% of Black recipients, AUC_0–12 was <100 ng‧h/ml despite tacrolimus troughs in the target range (p = 0.027). The novel CYP3A5*3*6*7 metabolic composite was the significant covariate accounting for 15%–19% of tacrolimus variability in dose (p = 0.002); AUC_0–12 h* (p < 0.001), and Cl (p < 0.001).

Conclusions

Tacrolimus pharmacokinetics and adverse effects were different among stable kidney transplant recipient groups based upon race and sex with interpatient variability associated with the CYP3A5*3*6*7 metabolic composite. More cumulative, neurologic, and aesthetic adverse effects were noted among females. Tacrolimus regimens that consider race and sex may reduce adverse effects and enhance allograft outcomes by facilitating more patients to achieve the targeted AUC_0–12 h.

Tacrolimus Therapy in Adult Heart Transplant Recipients: Evaluation of a Bayesian Forecasting Software

BACKGROUND

Therapeutic drug monitoring is recommended to guide tacrolimus dosing because of its narrow therapeutic window and considerable pharmacokinetic variability. This study assessed tacrolimus dosing and monitoring practices in heart transplant recipients and evaluated the predictive performance of a Bayesian forecasting software using a renal transplant-derived tacrolimus model to predict tacrolimus concentrations.

METHODS

A retrospective audit of heart transplant recipients (n = 87) treated with tacrolimus was performed. Relevant data were collected from the time of transplant to discharge. The concordance of tacrolimus dosing and monitoring according to hospital guidelines was assessed. The observed and software-predicted tacrolimus concentrations (n = 931) were compared for the first 3 weeks of oral immediate-release tacrolimus (Prograf) therapy, and the predictive performance (bias and imprecision) of the software was evaluated.

RESULTS

The majority (96%) of initial oral tacrolimus doses were guideline concordant. Most initial intravenous doses (93%) were lower than the guideline recommendations. Overall, 36% of initial tacrolimus doses were administered to transplant recipients with an estimated glomerular filtration rate of <60 mL/min/1.73 m despite recommendations to delay the commencement of therapy. Of the tacrolimus concentrations collected during oral therapy (n = 1498), 25% were trough concentrations obtained at steady-state. The software displayed acceptable predictions of tacrolimus concentration from day 12 (bias: -6%; 95%confidence interval, -11.8 to 2.5; imprecision: 16%; 95% confidence interval, 8.7-24.3) of therapy.

CONCLUSIONS

Tacrolimus dosing and monitoring were discordant with the guidelines. The Bayesian forecasting software was suitable for guiding tacrolimus dosing after 11 days of therapy in heart transplant recipients. Understanding the factors contributing to the variability in tacrolimus pharmacokinetics immediately after transplant may help improve software predictions.

Evaluation of published population pharmacokinetic models to inform tacrolimus dosing in adult heart transplant recipients

BACKGROUND AND AIM

Identification of the most appropriate population pharmacokinetic model-based Bayesian estimation is required prior to its implementation in routine clinical practice to inform tacrolimus dosing decisions. This study aimed to determine the predictive performances of relevant population pharmacokinetic models of tacrolimus developed from various solid organ transplant recipient populations in adult heart transplant recipients, stratified based on concomitant azole antifungal use. Concomitant azole antifungal therapy alters tacrolimus pharmacokinetics substantially, necessitating dose adjustments.

METHODS

Population pharmacokinetic models of tacrolimus were selected (n = 17) for evaluation from a recent systematic review. The models were transcribed and implemented in NONMEM version 7.4.3. Data from 85 heart transplant recipients (2387 tacrolimus concentrations) administered the oral immediate-release formulation of tacrolimus (Prograf) were obtained up to 391 days post-transplant. The performance of each model was evaluated using: (i) prediction-based assessment (bias and imprecision) of the individual predicted tacrolimus concentration of the fourth dosing occasion (MAXEVAL = 0, FOCE-I) from 1-3 prior dosing occasions; and (ii) simulation-based assessment (prediction-corrected visual predictive check). Both assessments were stratified based on concomitant azole antifungal use.

RESULTS

Regardless of the number of prior dosing occasions (1-3) and concomitant azole antifungal use, all models demonstrated unacceptable individual predicted tacrolimus concentration of the fourth dosing occasion (n = 152). The prediction-corrected visual predictive check graphics indicated that these models inadequately predicted observed tacrolimus concentrations.

CONCLUSION

All models evaluated were unable to adequately describe tacrolimus pharmacokinetics in adult heart transplant recipients included in this study. Further work is required to describe tacrolimus pharmacokinetics for our heart transplant recipient cohort.

Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review

BACKGROUND AND OBJECTIVES

Numerous population pharmacokinetic (PK) models of tacrolimus in adult transplant recipients have been published to characterize tacrolimus PK and facilitate dose individualization. This study aimed to (1) investigate clinical determinants influencing tacrolimus PK, and (2) identify areas requiring additional research to facilitate the use of population PK models to guide tacrolimus dosing decisions.

METHODS

The MEDLINE and EMBASE databases, as well as the reference lists of all articles, were searched to identify population PK models of tacrolimus developed from adult transplant recipients published from the inception of the databases to 29 February 2020.

RESULTS

Of the 69 studies identified, 55% were developed from kidney transplant recipients and 30% from liver transplant recipients. Most studies (91%) investigated the oral immediate-release formulation of tacrolimus. Few studies (17%) explained the effect of drug-drug interactions on tacrolimus PK. Only 35% of the studies performed an external evaluation to assess the generalizability of the models. Studies related variability in tacrolimus whole blood clearance among transplant recipients to either cytochrome P450 (CYP) 3A5 genotype (41%), days post-transplant (30%), or hematocrit (29%). Variability in the central volume of distribution was mainly explained by body weight (20% of studies).

CONCLUSION

The effect of clinically significant drug-drug interactions and different formulations and brands of tacrolimus should be considered for any future tacrolimus population PK model development. Further work is required to assess the generalizability of existing models and identify key factors that influence both initial and maintenance doses of tacrolimus, particularly in heart and lung transplant recipients.

The CYP3A5 and ABCB1 Gene Polymorphisms in Kidney Transplant Patients and Establishment of Initial Daily Tacrolimus Dosing Formula

BACKGROUND

Tacrolimus is an immunosuppressive drug used to prevent organ rejections. Many factors could influence blood concentration of tacrolimus.

OBJECTIVE

To detect genotypes of cytochrome P450 3A5 (CYP3A5) and ABCB1 in kidney transplant patients and establish initial daily tacrolimus dosing formula based on genotypes of CYP3A5 and ABCB1 and patients' clinical parameters.

METHODS

Sequence specific primer polymerase chain reaction (PCR) and PCR restriction fragment length polymorphism were used to detect genotypes of CYP3A5 and ABCB1. The blood cell, procalcitonin, C-reactive protein, height, weight, age, gender and other clinical parameters were recorded. Multiple linear regression analysis and Pearson correlation analysis were used to conduct date analysis.

RESULTS

102 cases were enrolled in cohort 1, and there were 10 cases of CYP3A5 *1/*1 (9.8%), 28 cases of CYP3A5 *1/*3 (27.5%), and 64 cases of CYP3A5 *3/*3 (62.7%). The distributions of ABCB1 C3435T genotype were CC 36 (35.3%), CT 52 (51.0%), and TT 14 (13.7%). The distributions of ABCB1 G2677T/A genotype were GG 39 (38.2%), GT 40 (39.2%), and TT 23 (22.5%). The formula was 7.499 + (0.053 × Weight) - (0.029 × Hemoglobin concentration) - (1.045 × CYP3A5 genotype) (CYP3A5 genotype: *1/*1 type inputs 0, *1/*3 type inputs 1, *3/*3 type inputs 2). The predicted doses from the established formula had a significant correlation (r = 0.605) with actual clinical doses (P < 0.05).

CONCLUSION AND RELEVANCE

Hemoglobin concentration, weight, and CYP3A5 genotype should be considered using tacrolimus. The initial daily tacrolimus dosing formula established can make a good prediction.

Model-informed precision dosing to optimise immunosuppressive therapy in renal transplantation

Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.

The impact of IL-10 and CYP3A5 gene polymorphisms on dose-adjusted trough blood tacrolimus concentrations in early post-renal transplant recipients

BACKGROUND

The strong inter-individual pharmacokinetic variability and the narrow therapeutic window of tacrolimus (TAC) have hampered the clinical application. Gene polymorphisms play an important role in TAC pharmacokinetics. Here, we investigate the influence of genotypes of IL-10, CYP3A5, CYP2C8, and ABCB1 on dose-adjusted trough blood concentrations (the C₀/D ratio) of TAC to reveal unclear genetic factors that may affect TAC dose requirements for renal transplant recipients.

METHODS

Genetic polymorphisms of IL-10, CYP3A5, CYP2C8, and ABCB1 in 188 renal transplant recipients were determined using Kompetitive Allele Specific PCR (KASP). Statistical analysis was applied to examine the effect of genetic variation on the TAC C₀/D at 5, 10, 15, and 30 days after transplantation.

RESULTS

Recipients carrying the IL-10 -819C > T TT genotype showed a significantly higher TAC C₀/D than those with the TC/CC genotype (p < 0.05). Additionally, the TAC C₀/D values of recipients with the capacity for low IL-10 activity (-819 TT) engrafted with CYP3A5 non-expressers were higher compared to the intermediate/high activity of IL-10 -819C > T TC or CC carrying CYP3A5 expressers, and the difference was statistically significant at different time points (p < 0.05).

CONCLUSIONS

Genetic polymorphisms of IL-10 -819C > T and CYP3A5 6986A > G influence the TAC C₀/D, which may contribute to variation in TAC dose requirements during the early post-transplantation period. Detecting IL-10 -819C > T and CYP3A5 6986A > G polymorphisms may allow determination of individualized tacrolimus dosage regimens for renal transplant recipients during the early post-transplantation period.

Significance of Ethnic Factors in Immunosuppressive Therapy Management After Organ Transplantation

Clinical outcomes after organ transplantation have greatly improved in the past 2 decades with the discovery and development of immunosuppressive drugs such as calcineurin inhibitors, antiproliferative agents, and mammalian target of rapamycin inhibitors. However, individualized dosage regimens have not yet been fully established for these drugs except for therapeutic drug monitoring-based dosage modification because of extensive interindividual variations in immunosuppressive drug pharmacokinetics. The variations in immunosuppressive drug pharmacokinetics are attributed to interindividual variations in the functional activity of cytochrome P450 enzymes, UDP-glucuronosyltransferases, and ATP-binding cassette subfamily B member 1 (known as P-glycoprotein or multidrug resistance 1) in the liver and small intestine. Some genetic variations have been found to be involved to at least some degree in pharmacokinetic variations in post-transplant immunosuppressive therapy. It is well known that the frequencies and effect size of minor alleles vary greatly between different races. Thus, ethnic considerations might provide useful information for optimizing individualized immunosuppressive therapy after organ transplantation. Here, we review ethnic factors affecting the pharmacokinetics of immunosuppressive drugs requiring therapeutic drug monitoring, including tacrolimus, cyclosporine, mycophenolate mofetil, sirolimus, and everolimus.

Population pharmacokinetics and genetics of oral meltdose tacrolimus (Envarsus) in stable adult liver transplant recipients

AIMS

Meltdose tacrolimus (Envarsus) is marketed as a formulation with a more consistent exposure. Due to the narrow therapeutic window, therapeutic drug monitoring is essential to maintain adequate exposure. The primary objective of this study was to develop a population pharmacokinetic (PK) model of Envarsus among liver transplant patients and select a limited sampling strategy (LSS) for AUC estimation. The secondary objective was to investigate potential covariates including CYP3A/IL genotype suitable for initial dose optimization when converting to Envarsus.

METHODS

Adult liver transplant patients were converted from prolonged release tacrolimus (Advagraf) to Envarsus and blood samples were obtained using whole blood and dried blood spot sampling. Subsequently the population PK parameters were estimated using nonlinear-mixed effect modelling. Demographic factors, and recipient and donor CYP3A4, CYP3A5, IL-6, -10 and -18 genotype were tested as potential covariates to explain interindividual variability.

RESULTS

Fifty-five patients were included. A 2-compartment model with delayed absorption was the most suitable to describe population PK parameters. The population PK parameters were as follows: clearance, 3.27 L/h; intercompartmental clearance, 9.6 L/h; volume of distribution of compartments 1 and 2, 95 and 500 L, respectively. No covariates were found to significantly decrease interindividual variability. The best 3-point LSS was t = 0,4,8 with a median bias of 1.8% (-12.5-12.5).

CONCLUSIONS

The LSS can be used to adequately predict the AUC. No clinically relevant covariates known to influence the PK of Envarsus, including CYP3A status, were identified and therefore do not seem useful for initial dose optimization.

Evaluation of the performance of a prior tacrolimus population pharmacokinetic kidney transplant model among adult allogeneic hematopoietic stem cell transplant patients

Abstract

Tacrolimus is a calcineurin inhibitor used to prevent acute graft versus host disease in adult patients receiving allogeneic hematopoietic stem cell transplantation (HCT). Previous population pharmacokinetic (PK) models have been developed in solid organ transplant, yet none exists for patients receiving HCT. The primary objectives of this study were to (1) use a previously published population PK model in adult patients who underwent kidney transplant and apply it to allogeneic HCT; (2) evaluate model‐predicted tacrolimus steady‐state trough concentrations and simulations in patients receiving HCT; and (3) evaluate covariates that affect tacrolimus PK in allogeneic HCT. A total of 252 adult patients receiving allogeneic HCT were included in the study. They received oral tacrolimus twice daily (0.03 mg/kg) starting 3 days prior to transplant. Data for these analyses included baseline clinical and demographic data, genotype data for single nucleotide polymorphisms in CYP3A4/5 and ABCB1, and the first tacrolimus steady‐state trough concentration. A dosing simulation strategy based on observed trough concentrations (rather than model‐based predictions) resulted in 12% more patients successfully achieving tacrolimus trough concentrations within the institutional target range (5–10 ng/ml). Stepwise covariate analyses identified HLA match and conditioning regimen (myeloablative vs. reduced intensity) as significant covariates. Ultimately, a previously published tacrolimus population PK model in kidney transplant provided a platform to help establish a model‐based dose adjustment strategy in patients receiving allogenic HCT, and identified HCT‐specific covariates to be considered for future prospective studies.

Racial Disparity in Drug Disposition in the Digestive Tract

The major determinants of drug or, al bioavailability are absorption and metabolism in the digestive tract. Genetic variations can cause significant differences in transporter and enzyme protein expression and function. The racial distribution of selected efflux transporter (i.e., Pgp, BCRP, MRP2) and metabolism enzyme (i.e., UGT1A1, UGT1A8) single nucleotide polymorphisms (SNPs) that are highly expressed in the digestive tract are reviewed in this paper with emphasis on the allele frequency and the impact on drug absorption, metabolism, and in vivo drug exposure. Additionally, preclinical and clinical models used to study the impact of transporter/enzyme SNPs on protein expression and function are also reviewed. The results showed that allele frequency of the major drug efflux transporters and the major intestinal metabolic enzymes are highly different in different races, leading to different drug disposition and exposure. The conclusion is that genetic polymorphism is frequently observed in different races and the related protein expression and drug absorption/metabolism function and drug in vivo exposure can be significantly affected, resulting in variations in drug response. Basic research on race-dependent drug absorption/metabolism is expected, and FDA regulations of drug dosing adjustment based on racial disparity are suggested.

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.

Beyond Single Nucleotide Polymorphisms: CYP3A5∗3∗6∗7 Composite and ABCB1 Haplotype Associations to Tacrolimus Pharmacokinetics in Black and White Renal Transplant Recipients

Interpatient variability in tacrolimus pharmacokinetics is attributed to metabolism by cytochrome P-450 3A5 (CYP3A5) isoenzymes and membrane transport by P-glycoprotein. Interpatient pharmacokinetic variability has been associated with genotypic variants for both CYP3A5 or ABCB1. Tacrolimus pharmacokinetics was investigated in 65 stable Black and Caucasian post-renal transplant patients by assessing the effects of multiple alleles in both CYP3A5 and ABCB1. A metabolic composite based upon the CYP3A5 polymorphisms: ∗3(rs776746), ∗6(10264272), and ∗7(41303343), each independently responsible for loss of protein expression was used to classify patients as extensive, intermediate and poor metabolizers. In addition, the role of ABCB1 on tacrolimus pharmacokinetics was assessed using haplotype analysis encompassing the single nucleotide polymorphisms: 1236C > T (rs1128503), 2677G > T/A(rs2032582), and 3435C > T(rs1045642). Finally, a combined analysis using both CYP3A5 and ABCB1 polymorphisms was developed to assess their inter-related influence on tacrolimus pharmacokinetics. Extensive metabolizers identified as homozygous wild type at all three CYP3A5 loci were found in 7 Blacks and required twice the tacrolimus dose (5.6 ± 1.6 mg) compared to Poor metabolizers [2.5 ± 1.1 mg (P < 0.001)]; who were primarily Whites. These extensive metabolizers had 2-fold faster clearance (P < 0.001) with 50% lower AUC∗ (P < 0.001) than Poor metabolizers. No differences in C12 h were found due to therapeutic drug monitoring. The majority of blacks (81%) were classified as either Extensive or Intermediate Metabolizers requiring higher tacrolimus doses to accommodate the more rapid clearance. Blacks who were homozygous for one or more loss of function SNPS were associated with lower tacrolimus doses and slower clearance. These values are comparable to Whites, 82% of who were in the Poor metabolic composite group. The ABCB1 haplotype analysis detected significant associations of the wildtype 1236T-2677T-3435T haplotype to tacrolimus dose (P = 0.03), CL (P = 0.023), CL/LBW (P = 0.022), and AUC∗ (P = 0.078). Finally, analysis combining CYP3A5 and ABCB1 genotypes indicated that the presence of the ABCB1 3435 T allele significantly reduced tacrolimus clearance for all three CPY3A5 metabolic composite groups. Genotypic associations of tacrolimus pharmacokinetics can be improved by using the novel composite CYP3A5∗3∗4∗5 and ABCB1 haplotypes. Consideration of multiple alleles using CYP3A5 metabolic composites and drug transporter ABCB1 haplotypes provides a more comprehensive appraisal of genetic factors contributing to interpatient variability in tacrolimus pharmacokinetics among Whites and Blacks.

Association of Genetic Variants in CYP3A4, CYP3A5, CYP2C8, and CYP2C19 with Tacrolimus Pharmacokinetics in Renal Transplant Recipients

BACKGROUND

Our study aimed to investigate the pharmacogenetics of cytochrome P3A4 (CYP3A4), CYP3A5, CYP2C8, and CYP2C19 and their influence on TAC Pharmacokinetics (PKs) in short-term renal transplant recipients.

METHODS

A total of 105 renal transplant recipients were enrolled. Target Sequencing (TS) based on next-generation sequencing technology was used to detect all exons, exon/intron boundaries, and flanking regions of CYP3A4, CYP3A5, CYP2C8, and CYP2C19. After adjustment of Minor Allele Frequencies (MAF) and Hardy-Weinberg Equilibrium (HWE) analysis, tagger Single-nucleotide Polymorphisms (SNPs) and haplotypes were identified. Influence of tagger SNPs on TAC concentrations was analyzed.

RESULTS

A total of 94 SNPs were identified in TS analysis. Nine tagger SNPs were selected, and two SNPs (rs15524 and rs4646453) were noted to be significantly associated with TAC PKs in short-term post-transplant follow-up. Measurement time points of TAC, body mass index (BMI), usage of sirolimus, and incidence of Delayed Graft Function (DGF) were observed to be significantly associated with TAC PKs. Three haplotypes were identified, and rs15524-rs4646453 was found to remarkably contribute to TAC PKs. Recipients carrying H2/H2 (GG-AA) haplotype also showed significantly high weight- and dose-adjusted TAC concentrations in posttransplant periods of 7, 14, and 30 days and 3 and 6 months.

CONCLUSIONS

Two tagger SNPs, namely, rs15524 and rs4646453, are significantly related to the variability of TAC disposition, and TAC measurement time points, BMI, usage of sirolimus, and incidence of DGF contribute to this influence. Recipients carrying H2/H2 (GG-AA) haplotype in rs15524-rs4646453 may require a low dosage of TAC during 1-year follow-up posttransplant.

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.

Population Pharmacokinetic Analysis of Immediate-Release Oral Tacrolimus Co-administered with Mycophenolate Mofetil in Corticosteroid-Free Adult Kidney Transplant Recipients

BACKGROUND AND OBJECTIVE

Tacrolimus is the mainstay calcineurin inhibitor frequently administered with mycophenolic acid with or without corticosteroids to prevent graft rejection in adult kidney transplant recipients. The primary objective of this study was to develop and evaluate a population pharmacokinetic model characterizing immediate-release oral tacrolimus co-administered with mycophenolate mofetil (a pro-drug of mycophenolic acid) in adult kidney transplant recipients on corticosteroid-free regimens. The secondary objective was to investigate the effects of clinical covariates on the pharmacokinetics of tacrolimus, emphasizing the interacting effects of mycophenolic acid.

METHODS

Population modeling and evaluation were conducted with Monolix (Suite-2018R1) using the stochastic approximation expectation-maximization algorithm in 49 adult subjects (a total of 320 tacrolimus whole-blood concentrations). Effects of clinical variables on tacrolimus pharmacokinetics were determined by population covariate modeling, regression modeling, and categorical analyses.

RESULTS

A two-compartment, first-order absorption with a lag-time, linear elimination, and constant error model best represented the population pharmacokinetics of tacrolimus. The apparent clearance value for tacrolimus was 17.9 l/h (6.95% relative standard error) in our model, which is lower compared with similar subjects on corticosteroid-based therapy. The glomerular filtration rate had significant effects on the apparent clearance and central compartment volume of distribution. Conversely, mycophenolic acid did not affect the apparent clearance of tacrolimus.

CONCLUSION

We have developed and internally evaluated a novel population pharmacokinetic model for tacrolimus co-administered with mycophenolate mofetil in corticosteroid-free adult kidney transplant patients. These findings are clinically important and provide further reasons for conducting therapeutic drug monitoring in this specific 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.

Influence of Calcineurin Inhibitor and Sex on Mycophenolic Acid Pharmacokinetics and Adverse Effects Post-Renal Transplant

Tacrolimus or cyclosporine is prescribed with mycophenolic acid posttransplant and contributes to interpatient variability in mycophenolic acid pharmacokinetics and response. Cyclosporine inhibits enterohepatic circulation of the metabolite mycophenolic acid glucuronide, which is not described with tacrolimus. This study investigated mycophenolic acid pharmacokinetics and adverse effects in stable renal transplant recipients and the association with calcineurin inhibitors, sex, and race. Mycophenolic acid and mycophenolic acid glucuronide area under the concentration-time curve from 0 to 12 hours (AUC0-12h ) and apparent clearance were determined at steady state in 80 patients receiving cyclosporine with mycophenolate mofetil and 67 patients receiving tacrolimus with mycophenolate sodium. Gastrointestinal adverse effects and hematologic parameters were evaluated. Statistical models evaluated mycophenolic acid pharmacokinetics and adverse effects. Mycophenolic acid AUC0-12h was 1.70-fold greater with tacrolimus (68.9 ± 30.9 mg·h/L) relative to cyclosporine (40.8 ± 17.6 mg·h/L); P < .001. Target mycophenolic acid AUC0-12h of 30-60 mg·h/L was achieved in 56.3% on cyclosporine compared with 34.3% receiving tacrolimus (P < .001). Mycophenolic acid clearance was 48% slower with tacrolimus (10.6 ± 4.7 L/h) relative to cyclosporine (20.5 ± 10.0 L/h); P < .001. Enterohepatic circulation occurred less frequently with cyclosporine (45%) compared with tacrolimus (78%); P < 0.001; with a 2.9-fold greater mycophenolic acid glucuronide AUC0-12h to mycophenolic acid AUC0-12h ratio (P < .001). Race did not affect mycophenolic acid pharmacokinetics. Gastrointestinal adverse effect scores were 2.2-fold higher with tacrolimus (P < .001) and more prominent in women (P = .017). Lymphopenia was more prevalent with tacrolimus (52.2%) than cyclosporine (22.5%); P < 0.001. Calcineurin inhibitors and sex contributed to interpatient variability in mycophenolic acid pharmacokinetics and adverse effects post-renal transplant, which could be attributed to differences in enterohepatic circulation.

The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients

AIMS

Tacrolimus has been associated with notable extrarenal adverse effects (AEs), which are unpredictable and impact patient morbidity. The association between model-predicted tacrolimus exposure metrics and standardized extrarenal AEs in stable renal transplant recipients was investigated and a limited sampling strategy (LSS) was developed to predict steady-state tacrolimus area under the curve over a 12-h dosing period (AUC_ss,0-12h ).

METHODS

All recipients receiving tacrolimus and mycophenolic acid ≥6 months completed a 12-h cross-sectional observational pharmacokinetic-pharmacodynamic study. Patients were evaluated for the presence of individual and composite gastrointestinal, neurological, and aesthetic AEs during the study visit. The associations between AEs and tacrolimus exposure metrics generated from a published population pharmacokinetic model were investigated using a logistic regression analysis in NONMEM 7.3. An LSS was determined using a Bayesian estimation method with the same patients.

RESULTS

Dose-normalized tacrolimus AUC_ss,0-12h and apparent clearance were independently associated with diarrhoea, dyspepsia, insomnia and neurological AE ratio. Dose-normalized tacrolimus maximum concentration was significantly correlated with skin changes and acne. No AE associations were found with trough concentrations. Using limited sampling at 0, 2h; 0, 1, 4h; and 0, 1, 2, 4h provided a precise and unbiased prediction of tacrolimus AUC (root mean squared prediction error < 10%), which was not well characterized using trough concentrations only (root mean squared prediction error >15%).

CONCLUSIONS

Several AEs (i.e. diarrhoea, dyspepsia, insomnia and neurological AE ratio) were associated with tacrolimus dose normalized AUC_ss,0-12h and clearance. Skin changes and acne were associated with dose-normalized maximum concentrations. To facilitate clinical implementation, a LSS was developed to predict AUC_ss,0-12h values using sparse patient data to efficiently assess projected immunosuppressive exposure and potentially minimize AE manifestations.