Effect of CYP3A5*3 Polymorphism on Pharmacokinetic Drug Interaction between Tacrolimus and Amlodipine

Drug-drug interaction between diltiazem and tacrolimus in relation to CYP3A5 genotype status in Chinese pediatric patients with nephrotic range proteinuria: a retrospective study

Background

Tacrolimus is widely used to treat pediatric nephrotic range proteinuria (NRP). Diltiazem, a CYP3A4/5 inhibitor, is often administered with tacrolimus, affecting its pharmacokinetic profile. The impact of this combination on tacrolimus exposure, particularly in CYP3A5*3 genetic polymorphism, remains unclear in pediatric NRP patients. This study aimed to evaluate the effects of diltiazem on tacrolimus pharmacokinetics, focusing on the CYP3A5*3 polymorphism.

Methods

We conducted a retrospective clinical study involving pediatric NRP patients, divided into two groups: those receiving tacrolimus with diltiazem and those receiving tacrolimus alone. Propensity score matching (PSM) was used to balance the baseline characteristics between the groups. We compared daily dose-adjusted trough concentrations (C0/D) of tacrolimus in both the original and PSM cohorts. The influence of diltiazem on tacrolimus C0/D, stratified by CYP3A5*3 genetic polymorphism, was assessed in a self-controlled case series study.

Results

Before PSM, the tacrolimus C0/D in patients taking diltiazem was significantly higher compared to those with tacrolimus alone (75.84 vs. 56.86 ng/mL per mg/kg, P = 0.034). This finding persisted after PSM (75.84 vs. 46.93 ng/mL per mg/kg, P= 0.028). In the self-controlled case study, tacrolimus C0/D elevated about twofold (75.84 vs. 34.76 ng/mL per mg/kg, P < 0.001) after diltiazem administration. CYP3A5 expressers (CYP3A5*1/*1 and *1/*3) and CYP3A5 non-expressers (CYP3A5*3/*3) experienced a 1.8-fold and 1.3-fold increase in tacrolimus C0/D when combined with diltiazem, respectively.

Conclusion

Diltiazem significantly increased tacrolimus C0/D, with CYP3A5*3 expressers showing higher elevations than non-expressers among pediatric NRP patients. These findings highlight the importance of personalized tacrolimus therapy based on CYP3A5*3 genotypes in pediatric patients taking diltiazem.

Interaction between tacrolimus and calcium channel blockers based on CYP3A5 genotype in Chinese renal transplant recipients

Objective

To investigate the effect of calcium channel blockers (CCBs) on tacrolimus blood concentrations in renal transplant recipients with different CYP3A5 genotypes.

Methods

This retrospective cohort study included renal transplant recipients receiving tacrolimus-based immunosuppressive therapy with or without CCBs in combination. Patients were divided into combination and control groups based on whether or not they were combined with CCBs, and then further analyzed according to the type of CCBs (nifedipine/amlodipine/felodipine). Propensity score matching was conducted for the combination and the control groups using SPSS 22.0 software to reduce the impact of confounding factors. The effect of different CCBs on tacrolimus blood concentrations was evaluated, and subgroup analysis was performed according to the patients' CYP3A5 genotypes to explore the role of CYP3A5 genotypes in drug-drug interactions between tacrolimus and CCBs.

Results

A total of 164 patients combined with CCBs were included in the combination groups. After propensity score matching, 83 patients with nifedipine were matched 1:1 with the control group, 63 patients with felodipine were matched 1:2 with 126 controls, and 18 patients with amlodipine were matched 1:3 with 54 controls. Compared with the controls, the three CCBs increased the dose-adjusted trough concentration (C0/D) levels of tacrolimus by 41.61%-45.57% (P < 0.001). For both CYP3A5 expressers (CYP3A5*1*1 or CYP3A5*1*3) and non-expressers (CYP3A5*3*3), there were significant differences in tacrolimus C0/D between patients using felodipine/nifedipine and those without CCBs (P < 0.001). However, among CYP3A5 non-expressers, C0/D values of tacrolimus were significantly higher in patients combined with amlodipine compared to the controls (P = 0.001), while for CYP3A5 expressers, the difference in tacrolimus C0/D values between patients with amlodipine and without was not statistically significant (P = 0.065).

Conclusion

CCBs (felodipine/nifedipine/amlodipine) can affect tacrolimus blood concentration levels by inhibiting its metabolism. The CYP3A5 genotype may play a role in the drug interaction between tacrolimus and amlodipine. Therefore, genetic testing for tacrolimus and therapeutic drug monitoring are needed when renal transplant recipients are concurrently using CCBs.

Improving prediction of tacrolimus concentration using a combination of population pharmacokinetic modeling and machine learning in chinese renal transplant recipients

Aims

The population pharmacokinetic (PPK) model-based machine learning (ML) approach offers a novel perspective on individual concentration prediction. This study aimed to establish a PPK-based ML model for predicting tacrolimus (TAC) concentrations in Chinese renal transplant recipients.

Methods

Conventional TAC monitoring data from 127 Chinese renal transplant patients were divided into training (80%) and testing (20%) datasets. A PPK model was developed using the training group data. ML models were then established based on individual pharmacokinetic data derived from the PPK basic model. The prediction performances of the PPK-based ML model and Bayesian forecasting approach were compared using data from the test group.

Results

The final PPK model, incorporating hematocrit and CYP3A5 genotypes as covariates, was successfully established. Individual predictions of TAC using the PPK basic model, postoperative date, CYP3A5 genotype, and hematocrit showed improved rankings in ML model construction. XGBoost, based on the TAC PPK, exhibited the best prediction performance.

Conclusion

The PPK-based machine learning approach emerges as a superior option for predicting TAC concentrations in Chinese renal transplant recipients.

Drug Interactions and Safe Prescription Writing for Liver Transplant Recipients

Immunosuppression optimization is central to graft function in liver transplant recipients. Post-transplantation patients develop new onset or worsening metabolic syndrome, are prone to atypical infections, and are at higher risk of developing cardiac and brain-related clinical events. In this context, liver transplant recipients are at risk of using multiple comedications alongside immunosuppressants. It is imperative for the transplant physician to understand the various drug-drug interactions that potentially reduce or promote toxicity of immunosuppression, as well as associated synergistic or antagonistic effects on extrahepatic organ systems. This comprehensive review discusses drug-drug interactions in liver transplant recipients and the impact and role of complementary and alternative medicines among individuals on immunosuppression.

Wuzhi Capsule Dosage Affects Tacrolimus Elimination in Adult Kidney Transplant Recipients, as Determined by a Population Pharmacokinetics Analysis

Purpose

In this study, we aimed to establish a tacrolimus population pharmacokinetic model and better understand the drug-drug interaction between Wuzhi capsule and tacrolimus in Chinese renal transplant recipients.

Patients and Methods

We performed a population pharmacokinetic analysis using a non-linear mixed-effects model to determine the suitable Wuzhi capsule dose in combination with tacrolimus. Data on 1378 tacrolimus steady-state concentrations were obtained from 142 patients who received kidney transplant in Changhai Hospital and Huashan Hospital. Demographic characteristics, laboratory tests, genetic polymorphisms, and co-medications were evaluated.

Results

The one-compartment model best described data. Our final model identified creatinine clearance rate, hematocrit, Wuzhi capsule dose, CYP3A5*3 genetic polymorphisms, and tacrolimus daily dose as significant covariates for tacrolimus clearance, with the value of 14.4 L h^-1, and the between-subject variability (BSV) was 25.4%. The Wuzhi capsule showed a dose-dependent effect on tacrolimus pharmacokinetics, demonstrating a stronger inhibitory effect than inductive effect.

Conclusion

Our model can accurately describe population pharmacokinetics of tacrolimus when combined with different doses of Wuzhi capsule. Additionally, this model can be used for individualizing tacrolimus dose following kidney transplantation.

CYP3A5 Genotype-Dependent Drug-Drug Interaction Between Tacrolimus and Nifedipine in Chinese Renal Transplant Patients

Purpose: The drug-drug interactions (DDIs) of tacrolimus greatly contributed to pharmacokinetic variability. Nifedipine, frequently prescribed for hypertension, is a competitive CYP3A5 inhibitor which can inhibit tacrolimus metabolism. The objective of this study was to investigate whether CYP3A5 genotype could influence tacrolimus-nifedipine DDI in Chinese renal transplant patients.

Method: All renal transplant patients were divided into CYP3A5*3/*3 homozygotes (group I) and CYP3A5*1 allele carriers (CYP3A5*1/*1 + CYP3A5*1/*3) (group II). Each group was subdivided into patients taking tacrolimus co-administered with nifedipine (CONF) and that administrated with tacrolimus alone (Controls). Tacrolimus trough concentrations (C₀) were measured using high performance liquid chromatography. A retrospective analysis compared tacrolimus dose (D)-corrected trough concentrations (C₀) (C₀/D) between CONF and Controls in group I and II, respectively. At the same time, a multivariate line regression analysis was made to evaluate the effect of variates on C₀/D.

Results: In this study, a significant DDI between tacrolimus and nifedipine with respect to the CYP3A5*3 polymorphism was confirmed. In group I (n = 43), the C₀/D of CONF was significantly higher than in Controls [225.2 ± 66.3 vs. 155.1 ± 34.6 ng/ml/(mg/kg); p = 0.002]. However, this difference was not detected in group II (n = 27) (p = 0.216). The co-administrated nifedipine and CYP3A5*3/*3 homozygotes significantly increased tacrolimus concentrations in multivariate line regression analysis.

Discussion: A CYP3A5 genotype-dependent DDI was found between tacrolimus and nifedipine. Therefore, personalized therapy accounting for CYP3A5 genotype detection as well as therapeutic drug monitoring are necessary for renal transplant patients when treating with tacrolimus and nifedipine.

Investigation of the Impact of CYP3A5 Polymorphism on Drug-Drug Interaction between Tacrolimus and Schisantherin A/Schisandrin A Based on Physiologically-Based Pharmacokinetic Modeling

Wuzhi capsule (WZC) is commonly prescribed with tacrolimus in China to ease drug-induced hepatotoxicity. Two abundant active ingredients, schisantherin A (STA) and schisandrin A (SIA) are known to inhibit CYP3A enzymes and increase tacrolimus’s exposure. Our previous study has quantitatively demonstrated the contribution of STA and SIA to tacrolimus pharmacokinetics based on physiologically-based pharmacokinetic (PBPK) modeling. In the current work, we performed reversible inhibition (RI) and time-dependent inhibition (TDI) assays with CYP3A5 genotyped human liver microsomes (HLMs), and further integrated the acquired parameters into the PBPK model to predict the drug–drug interaction (DDI) in patients with different CYP3A5 alleles. The results indicated STA was a time-dependent and reversible inhibitor of CYP3A4 while only a reversible inhibitor of CYP3A5; SIA inhibited CYP3A4 and 3A5 in a time-dependent manner but also reversibly inhibited CYP3A5. The predicted fold-increases of tacrolimus exposure were 2.70 and 2.41, respectively, after the multidose simulations of STA. SIA also increased tacrolimus’s exposure but to a smaller extent compared to STA. An optimized physiologically-based pharmacokinetic (PBPK) model integrated with CYP3A5 polymorphism was successfully established, providing more insights regarding the long-term DDI between tacrolimus and Wuzhi capsules in patients with different CYP3A5 genotypes.

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.

Clinical observation on the effect of Wuzhi soft capsule on FK506 concentration in membranous nephropathy patients

The current research aimed to investigate the correlation between the effect of Wuzhi soft capsule (WZC) on FK506 concentration and CYP3A5 gene polymorphism in patients with membranous nephropathy (MN).Seventy-five patients with idiopathic MN were enrolled and divided according to the expression of CYP3A5 gene metabolic enzyme into group A (CP3A5 metabolic enzyme function expression types CYP3A5*1/*1 type and CYP3A5*1/*3 type), and group B (non-expression type CYP3A5*3/*3 type). All patients were given oral administration of tacrolimus capsule at the initial dose of 1 mg for twice a day 1 hour before breakfast and dinner. Afterwards, the oral administration of WZC was added at the dose of 0.5 g for 3 times a day within half an hour after 3 meals.The blood concentrations of FK506 in groups A and B were significantly higher than those before administration. Compared with that before administration, the FK506 blood concentration was increased by 3.051 ± 0.774 ng/ml after adding the WZC. Besides, the blood concentrations of FK506 in group A were lower than those in group B before and after administration; meanwhile, the 24 hours total urine protein and the biochemical indexes in both groups displayed no statistically significant difference. Only 1 case of diarrhea was observed, which was relieved after the reduction of tacrolimus.Wuzhi soft capsule can significantly increase the blood concentration of FK506 in MN patients. Moreover, the CYP3A5 genotyping should be considered when WZC is used to increase the blood concentration of FK506.

Prediction of tacrolimus dosage in the early period after heart transplantation: a population pharmacokinetic approach

Aim: The aim of this study was to evaluate tacrolimus population pharmacokinetics and investigate factors that explain tacrolimus variability in adult heart transplant patients. Methods: A total of 707 tacrolimus concentrations from 107 adult heart transplant patients were included in model development. The effects of demographic, clinical factors and CYP3A5 genotype on tacrolimus clearance were evaluated using a nonlinear mixed-effects modeling. 24 patients with 106 tacrolimus concentrations were used for external validation. Results: The pharmacokinetic data were adequately described by a one-compartment model with first-order absorption and elimination. The estimated apparent clearance and volume of distribution of tacrolimus were 13.7 l/h and 791 l, respectively. Tacrolimus apparent clearance was significantly reduced in CYP3A5 nonexpressers (CYP3A5*3/*3), concomitant with azole antifungal drugs and Wuzhi capsule (WZ). A predictive performance was further confirmed in an external validation by Bayesian estimation. Recommended dose regimens were obtained by simulations based on the established model. Conclusion: This is the first population pharmacokinetic study conducted in Chinese heart transplant recipients. These findings are of great importance with regards to tacrolimus dose optimization in heart transplantation patients.

Effects of triptolide on pharmacokinetics of amlodipine in rats by using LC-MS/MS

CONTEXT

Triptolide and amlodipine are often simultaneously used for reducing urine protein excretion after renal transplantation in China clinics.

OBJECTIVE

This study investigated the effects of triptolide on the pharmacokinetics of amlodipine in male Sprague-Dawley rats.

MATERIALS AND METHODS

The pharmacokinetics of amlodipine (1 mg/kg) with or without triptolide pre-treatment (2 mg/kg/day for seven days) were investigated using a sensitive and reliable LC-MS/MS method. Additionally, the inhibitory effects of triptolide on the metabolic stability of amlodipine were investigated using rat liver microsome incubation systems.

RESULTS

The results indicated that when the rats were pre-treated with triptolide, the Cmax of amlodipine increased from 13.78 ± 3.57 to 19.96 ± 4.56 ng/mL (p < 0.05), the Tmax increased from 4.04 ± 1.15 to 5.89 ± 1.64 h (p < 0.05), and the AUC0-t increased by approximately 104% (p < 0.05), which suggested that the pharmacokinetic behaviour of amlodipine was affected after oral co-administration of triptolide. Additionally, the metabolic half-life was prolonged from 22.5 ± 4.26 to 36.8 ± 6.37 min (p < 0.05) with the pre-treatment of triptolide.

CONCLUSIONS

In conclusion, these results indicated that triptolide could affect the pharmacokinetics of amlodipine, possibly by inhibiting the metabolism of amlodipine in rat liver when they are co-administered.

Effect Of epigallocatechin-3-gallate on the pharmacokinetics of amlodipine in rats

This study investigates the effect of epigallocatechin-3-gallate (EGCG), a major ingredient of green tea, on the pharmacokinetics of amlodipine in rats. The pharmacokinetics of orally administered amlodipine (1 mg/kg) with or without EGCG pretreatment (30 mg/kg/day for 10 days) were investigated. Plasma concentrations of amlodipine were determined by using a sensitive and reliable liquid chromatography with tandem mass spectroscopy (LC-MS/MS) method. The effects of EGCG on the metabolic stability of amlodipine were investigated by using rat liver microsome incubation systems. The results indicated that when the rats were pretreated with EGCG, the C_max of amlodipine increased from 16.32 ± 2.57 to 21.44 ± 3.56 ng/mL (p < 0.05), the T_max decreased from 5.98 ± 1.25 to 4.01 ± 1.02 h (p < 0.05), and the AUC_0-t increased from 258.12 ± 76.25 to 383.34 ± 86.95 μg h L^-1 (p < 0.05), which suggested that the pharmacokinetic behavior of amlodipine was affected after oral co-administration of EGCG. Additionally, the metabolic half-life was prolonged from 31.3 ± 5.6 to 52.6 ± 7.9 min (p < 0.05) with the pretreatment of EGCG. It can be speculated that the drug-drug interaction between EGCG and amlodipine might occur, which might have resulted from the metabolism inhibition of amlodipine by EGCG when they were co-administered.

Increased Exposure of Tacrolimus by Co-administered Mycophenolate Mofetil: Population Pharmacokinetic Analysis in Healthy Volunteers

The objective of the study was to investigate the pharmacokinetic drug-drug interactions between tacrolimus (TAC) and mycophenolate mofetil (MMF) in healthy Korean male volunteers. Seventeen volunteers participated in a three-period, single-dose, and fixed sequence study. They sequentially received MMF, TAC, and the combination. Concentrations of TAC, mycophenolic acid (MPA), and its metabolites MPA 7-O-glucuronide and MPA acyl glucuronide were measured. The variants of CYP3A4, CYP3A5, SLCO1B1, SLCO1B3, ABCC2, UGT1A9, and UGT2B7 were genotyped. Drug interaction was evaluated with a non-compartmental analysis and population pharmacokinetic modelling to quantify the interaction effect. A total of 1,082 concentrations of those analytes were analysed. AUC_0-inf of TAC increased by 22.1% (322.4 ± 174.1 to 393.6 ± 121.7 ng·h/mL; P < 0.05) when co-administered with MMF, whereas the pharmacokinetic parameters of MPA and its metabolites were not changed by TAC. Apparent clearance (CL/F) of TAC was 17.8 L/h [relative standard error (RSE) 11%] or 13.8 L/h (RSE 11%) without or with MMF, respectively. Interaction was explained by the exponential model. The CYP3A5 genotype was the only significant covariate. The population estimate of CL/F of TAC was 1.48-fold (RSE 16%) in CYP3A5 expressers when compared to nonexpressers. CL/F of TAC was decreased when co-administered with MMF in these subjects.

Effect of Ginkgo Leaf Tablets on the Pharmacokinetics of Amlodipine in Rats

BACKGROUND AND OBJECTIVE

Ginkgo leaf tablet (GLT) is an effective traditional Chinese multi-herbal formula, which is often combined with amlodipine for treating senile hypertension in clinic. The aim of this study was to study the pharmacokinetics of amlodipine after oral administration of amlodipine and GLT and to investigate the potential for pharmacokinetic herb-drug interactions between GLT and amlodipine in rats.

METHODS

A liquid chromatography-tandem mass spectrometry (LC-MS/MS) analytical method was developed for quantification of amlodipine in rat plasma. The accuracy, precision, linearity, selectivity and recovery were all within an acceptable range. Male Sprague-Dawley rats were randomly assigned to two groups: amlodipine group and amlodipine + GLT group. Plasma concentrations of amlodipine were determined at the designated time points after oral administration by using the developed LC-MS/MS method, and the main pharmacokinetic parameters were calculated and compared. As ginkgolides A, ginkgolides B, bilobalide, quercetin and kaempferol were the main components of GLT, the effects of these ingredients in GLT on metabolism of amlodipine were further investigated in rat liver microsomes.

RESULTS

The pharmacokinetic parameters, maximum plasma concentration (C _max), time to reach C _max (T _max), area under the concentration-time curve (AUC), area under the first moment plasma concentration-time curve (AUMC) and elimination half-life (t _1/2), of amlodipine were significantly increased in amlodipine + GLT group, which suggested that GLT may influence the pharmacokinetic behavior after oral co-administration with amlodipine. Amlodipine is metabolized by cytochrome P450 (CYP) 3A4, so it was speculated that GLT may change the pharmacokinetic parameters of amlodipine through modulating the metabolism of CYP3A4 enzymes. When ginkgolides B, bilobalide, or quercetin and amlodipine were co-incubated in the rat liver microsomes, the metabolic rate of amlodipine was prolonged to 533.1, 216.1 and 407.6 min, respectively, from 73.7 min.

CONCLUSIONS

These results suggested that these components in GLT inhibit the metabolism of amlodipine. So it can be speculated that the herb-drug interactions between GLT and amlodipine resulted from inhibiting the metabolism of amlodipine by GLT when they were co-administered.

A pharmacogenomic study on the pharmacokinetics of tacrolimus in healthy subjects using the DMETTM Plus platform

Genetic association studies on the pharmacokinetics of tacrolimus have reported conflicting results, except for the role of the CYP3A5*3 polymorphism. The objective of this study was to identify genetic variants affecting the pharmacokinetics of tacrolimus using the DMETTM Plus microarray in 42 healthy males. Aside from CYP3A5*3, the rs3814055 polymorphism in the NR1I2 gene was associated with the tacrolimus pharmacokinetics based on false discovery rate-corrected multiple tests and the least absolute shrinkage and selection operator analysis. The area under the concentration-time curve to the last quantifiable time point (AUClast) was 3.42 times greater in subjects with homozygous mutations in both genes (CYP3A5*3/*3 and NR1I2 T/T) than in wild-type subjects. The two variants explained the 54% variability in the tacrolimus AUClast. An in vitro luciferase reporter assay indicated that downregulation of PXR expression is the likely molecular mechanism responsible for the increased exposure to tacrolimus in subjects carrying the rs3814055 C>T variant.

Tacrolimus Predose Concentration Is Associated With Hypertension in Pediatric Liver Transplant Recipients

BACKGROUND

The aim of the study was to analyze the incidence of hypertension in pediatric liver transplantation (LT) recipients using ambulatory blood pressure measurements (ABPM) and to identify factors associated with hypertension. We also investigated whether hypertension or tacrolimus predose concentration (TAC C0) was associated with increased left ventricular (LV) wall thickness.

PATIENTS AND METHODS

On a retrospective longitudinal base, we included 39 pediatric LT recipients. Median time since transplantation was 65 months (range: 11-183). Two consecutive ABPM were analyzed with a median time interval of 13 months. Data from echocardiographic evaluation parallel to the baseline ABPM were analyzed. All patients except 1 were prescribed tacrolimus. The median TAC C0 was 4 ng/mL (range 0.9-11.2). Univariate and multivariate logistic regression models were fitted to identify factors associated with systolic and diastolic hypertension and LV wall thickness.

RESULTS

Twenty-two of 39 children were hypertensive at baseline and 19 of 32 were hypertensive at follow-up. At baseline 10 (26%) children had masked systolic hypertension. TAC C0 was associated with systolic (P = 0.007, Exp(B) 2.02, 95% CI 1.2-3.3) and diastolic (P = 0.044, Exp(B) 1.48, 95% CI 1.0-2.2) hypertension. LV wall thickness was increased in children after LT compared with healthy population, but it was not associated with hypertension or TAC C0.

CONCLUSIONS

Given the high prevalence of masked hypertension, ABPM should be performed in all pediatric LT recipients. Systolic and diastolic hypertension is associated with TAC C0; therefore, children with a higher target TAC C0 require a more intensive blood pressure surveillance.

Tacrolimus in preventing transplant rejection in Chinese patients--optimizing use

Tacrolimus is a product of fermentation of Streptomyces, and belongs to the family of calcineurin inhibitors. It is a widely used immunosuppressive drug for preventing solid-organ transplant rejection. Compared to cyclosporine, tacrolimus has greater immunosuppressive potency and a lower incidence of side effects. It has been accepted as first-line treatment after liver and kidney transplantation. Tacrolimus has specific features in Chinese transplant patients; its in vivo pharmacokinetics, treatment regimen, dose and administration, and adverse-effect profile are influenced by multiple factors, such as genetics and the spectrum of primary diseases in the Chinese population. We reviewed the clinical experience of tacrolimus use in Chinese liver- and kidney-transplant patients, including the pharmacology of tacrolimus, the immunosuppressive effects of tacrolimus versus cyclosporine, effects of different factors on tacrolimus metabolism on Chinese patients, personalized medicine, clinical safety profile, and patient satisfaction and adherence. This article provides guidance for the rational and efficient use of tacrolimus in Chinese organ-transplant patients.

Amlodipine metabolism in human liver microsomes and roles of CYP3A4/5 in the dihydropyridine dehydrogenation

Amlodipine is a commonly prescribed calcium channel blocker for the treatment of hypertension and ischemic heart disease. The drug is slowly cleared in humans primarily via dehydrogenation of its dihydropyridine moiety to a pyridine derivative (M9). Results from clinical drug-drug interaction studies suggest that CYP3A4/5 mediate metabolism of amlodipine. However, attempts to identify a role of CYP3A5 in amlodipine metabolism in humans based on its pharmacokinetic differences between CYP3A5 expressers and nonexpressers failed. Objectives of this study were to determine the metabolite profile of amlodipine (a racemic mixture and S-isomer) in human liver microsomes (HLM), and to identify the cytochrome P450 (P450) enzyme(s) involved in the M9 formation. Liquid chromatography/mass spectrometry analysis showed that amlodipine was mainly converted to M9 in HLM incubation. M9 underwent further O-demethylation, O-dealkylation, and oxidative deamination to various pyridine derivatives. This observation is consistent with amlodipine metabolism in humans. Incubations of amlodipine with HLM in the presence of selective P450 inhibitors showed that both ketoconazole (an inhibitor of CYP3A4/5) and CYP3cide (an inhibitor of CYP3A4) completely blocked the M9 formation, whereas chemical inhibitors of other P450 enzymes had little effect. Furthermore, metabolism of amlodipine in expressed human P450 enzymes showed that only CYP3A4 had significant activity in amlodipine dehydrogenation. Metabolite profiles and P450 reaction phenotyping data of a racemic mixture and S-isomer of amlodipine were very similar. The results from this study suggest that CYP3A4, rather than CYP3A5, plays a key role in metabolic clearance of amlodipine in humans.

Pharmacokinetic drug-drug interactions between 1,4-dihydropyridine calcium channel blockers and statins: factors determining interaction strength and relevant clinical risk management

Background

Coadministration of 1,4-dihydropyridine calcium channel blockers (DHP-CCBs) with statins (or 3-hydroxy-3-methylglutaryl-coenzyme A [HMG-CoA] reductase inhibitors) is common for patients with hypercholesterolemia and hypertension. To reduce the risk of myopathy, in 2011, the US Food and Drug Administration (FDA) Drug Safety Communication set a new dose limitation for simvastatin, for patients taking simvastatin concomitantly with amlodipine. However, there is no such dose limitation for atorvastatin for patients receiving amlodipine. The combination pill formulation of amlodipine/atorvastatin is available on the market. There been no systematic review of the pharmacokinetic drug–drug interaction (DDI) profile of DHP-CCBs with statins, the underlying mechanisms for DDIs of different degree, or the corresponding management of clinical risk.

Methods

The relevant literature was identified by performing a PubMed search, covering the period from January 1987 to September 2013. Studies in the field of drug metabolism and pharmacokinetics that described DDIs between DHP-CCB and statin or that directly compared the degree of DDIs associated with cytochrome P450 (CYP)3A4-metabolized statins or DHP-CCBs were included. The full text of each article was critically reviewed, and data interpretation was performed.

Results

There were three circumstances related to pharmacokinetic DDIs in the combined use of DHP-CCB and statin: 1) statin is comedicated as the precipitant drug (pravastatin–nimodipine and lovastatin–nicardipine); 2) statin is comedicated as the object drug (isradipine–lovastatin, lacidipine–simvastatin, amlodipine–simvastatin, benidipine-simvastatin, azelnidipine– simvastatin, lercanidipine–simvastatin, and amlodipine–atorvastatin); and 3) mutual interactions (lercanidipine–fluvastatin). Simvastatin has an extensive first-pass effect in the intestinal wall, whereas atorvastatin has a smaller intestinal first-pass effect. The interaction with simvastatin seems mainly driven by CYP3A4 inhibition at the intestinal level, whereas the interaction with atorvastatin is more due to hepatic CYP3A4 inhibition. The interaction of CYP3A4 inhibitor with simvastatin has been more pronounced compared with atorvastatin. From the current data, atorvastatin seems to be a safer CYP3A4-statin for comedication with DHP-CCB. There is no convincing evidence that amlodipine is an unusual DHP-CCB, either as a precipitant drug or as an object drug, from the perspective of CYP3A4-mediated drug metabolism. Amlodipine may have interactions with CYP3A5 in addition to CYP3A4, which may explain its particular characteristics in comparison with other DHP-CCBs. The degree of DDIs between the DHP-CCB and statin and the clinical outcome depends on many factors, such as the kind of statin, physicochemical proprieties of the DHP-CCB, the dose of either the precipitant drug or the object drug, the sex of the patient (eg, isradipine–lovastatin), route of drug administration (eg, oral versus intravenous nicardipine–lovastatin), the administration schedule (eg, nonconcurrent dosing method versus concurrent dosing method), and the pharmacogenetic status (eg, CYP3A5-nonexpressers versus CYP3A5-expressers).

Conclusion

Clinical professionals should enhance risk management regarding the combination use of two classes of drugs by increasing their awareness of the potential changes in therapeutic efficacy and adverse drug reactions, by rationally prescribing alternatives, by paying attention to dose adjustment and the administration schedule, and by review of the appropriateness of physician orders. Further study is needed – the DDIs between DHP-CCBs and statins have not all been studied in humans, from either a pharmacokinetic or a clinical perspective; also, the strength of the different pharmacokinetic interactions of DHP-CCBs with statins should be addressed by systematic investigations.