Clinical influencing factors for daily dose, trough level, and relative clearance of tacrolimus in renal transplant recipients

Effects of CYP3A4*22 and POR*28 variations on the pharmacokinetics of tacrolimus in renal transplant recipients: a meta-analysis of 18 observational studies

PURPOSE

This study aimed to investigate the association between cytochrome P450 (CYP) 3A4*22 and cytochrome P450 oxidoreductase (POR)*28 variations and the pharmacokinetics of tacrolimus.

METHODS

Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science (SCI), MEDLINE, and Embase were systematically searched from inception to August 2022. The outcomes were weight-adjusted daily dose and dose-adjusted trough concentration (C0/Dose).

RESULTS

The study included 2931 renal transplant recipients from 18 publications. Weight-adjusted daily dose of CYP3A4*1/*1 carriers was 0.04 (WMD = 0.04, 95% CI: 0.02 to 0.06), 0.03 (WMD = 0.03, 95% CI: 0.02 to 0.05), 0.02 (WMD = 0.02, 95% CI: 0.01 to 0.03), or 0.02 mg/kg/day (WMD = 0.02, 95% CI: 0.00 to 0.04) higher than CYP3A4*22 carriers in Caucasians at 1 month, 3 months, 6 months, or 12 months post-transplantation. Conversely, C0/Dose was lower for CYP3A4*1/*1 carriers at 3 days (SMD = -0.35, 95% CI: -0.65 to -0.06), 1 month (SMD = -0.67, 95% CI: -1.16 to -0.18), 3 months (SMD = -0.60, 95% CI: -0.89 to -0.31), 6 months (SMD = -0.76, 95% CI: -1.49 to -0.04), or 12 months post-transplantation (SMD = -0.69, 95% CI: -1.37 to 0.00). Furthermore, C0/Dose of POR*1/*1 carriers was 22.64 (WMD = 22.64, 95% CI: 2.54 to 42.74) or 19.41 (ng/ml)/(mg/kg/day) (WMD = 19.41, 95% CI: 9.58 to 29.24) higher than POR*28 carriers in CYP3A5 expressers at 3 days or 7 days post-transplantation, and higher in Asians at 6 months post-transplantation (SMD = 0.96, 95% CI: 0.50 to 1.43).

CONCLUSIONS

CYP3A4*22 variant in Caucasians restrains the metabolism of tacrolimus, while POR*28 variant in CYP3A5 expressers enhances the metabolism of tacrolimus for renal transplant recipients. However, further well-designed prospective studies are necessary to substantiate these conclusions given some limitations.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSION

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

Initial Dosage Optimization of Tacrolimus in Pediatric Patients With Thalassemia Major Undergoing Hematopoietic Stem Cell Transplantation Based on Population Pharmacokinetics

BACKGROUND

Hematopoietic stem cell transplantation (HSCT) is an effective treatment for hematological disorders. Tacrolimus is widely used after HSCT, but it has highly interindividual variable pharmacokinetics. Population pharmacokinetics (PPK) researches of tacrolimus in children with β-thalassemia major (β-TM) undergoing HSCT are insufficient.

OBJECTIVE

To establish a PPK model of tacrolimus in children with β-TM and optimize initial dosing regimen for achieving target concentration of 5 to 15 ng/mL.

METHODS

Data on patients aged <18 years were retrospectively collected from January 2017 to December 2018. PPK analysis and Monte Carlo simulations were performed using nonlinear mixed-effects modeling.

RESULTS

A data set of 55 patients with 332 concentrations was included. A 2-compartment model could best describe the pharmacokinetics of tacrolimus. The body surface area and gender were significant covariates in the final model. The typical value of clearance, the distribution volume of the central room, the distribution volume of the peripheral room, and the intercompartmental clearance were 5.05L/h, 4.33L, 155L, and 6.22L/h, respectively. The optimal initial dosing regimen of 0.03, 0.04, 0.05, 0.06, and 0.10 mg/kg were appropriate for female children with a weight (WT) of 50 to 10 kg. The regimen of 0.04, 0.05, 0.06, 0.07, and 0.12 mg/kg is suitable for male children with a WT of 50 to 10 kg. The probability of target attainment (PTA) of each regimen reached 91%.

CONCLUSION AND RELEVANCE

A stable PPK model of tacrolimus was established. The proposed dosage regimen reached a good PTA, which could provide a reference for tacrolimus therapy.

Impact of POR and CYP3A5 Polymorphisms on Trough Concentration to Dose Ratio of Tacrolimus in the Early Post-operative Period Following Kidney Transplantation

BACKGROUND

Tacrolimus, a critical dose drug, is widely used in transplantation. Knowing the contribution of genetic factors, which significantly influence tacrolimus variability, is beneficial in the personalization of its starting dose. The significant impact of CYP3A5*3 polymorphisms on tacrolimus exposure has been reported. Conflicting results of the additional influence of POR*28 polymorphisms on tacrolimus pharmacokinetic interindividual variability have been observed among different populations. The objective of this study was to explore the interaction between POR*28 and CYP3A5*3 polymorphisms and their main effects on tacrolimus trough concentration to dose ratios on day 7 after kidney transplantation.

METHODS

Two hundred sixteen adult kidney transplant recipients participated in this retrospective study. All participants received a twice daily tacrolimus regimen. Blood samples and data were collected on day 7 after transplantation. A 2-way analysis of covariance was performed. Tested covariates were age, hemoglobin, serum albumin, and prednisolone dose.

RESULTS

A 2 × 2 analysis of covariance revealed that the interaction between CYP3A5 polymorphisms (CYP3A5 expresser and CYP3A5 nonexpresser) and POR polymorphisms (POR*28 carrier and POR*28 noncarrier) was not significant (F(1, 209) = 2.473, P = 0.117, (Equation is included in full-text article.)= 0.012). The predicted main effect of CYP3A5 and POR polymorphisms was significant (F(1, 209) = 105.565, P < 0.001, (Equation is included in full-text article.)= 0.336 and F(1, 209) = 4.007, P = 0.047, (Equation is included in full-text article.)= 0.019, respectively). Hemoglobin, age, and steroid dose influenced log C0/dose of tacrolimus (F(1, 209) = 20.612, P < 0.001, (Equation is included in full-text article.)= 0.090; F(1, 209) = 14.360, P < 0.001, (Equation is included in full-text article.)= 0.064; and F(1, 209) = 5.512, P = 0.020, (Equation is included in full-text article.)= 0.026, respectively).

CONCLUSIONS

After adjusting for the influences of hemoglobin, age, and prednisolone dose, significant impacts of the CYP3A5 and POR polymorphisms on tacrolimus exposure were found. The effect of POR*28 and CYP3A5*3 polymorphisms during the very early period after kidney transplantation is independent of each other.

Lack of a significant pharmacokinetic interaction between maraviroc and tacrolimus in allogeneic HSCT recipients

OBJECTIVES

Emerging data suggest that the combination of tacrolimus and the CCR5 antagonist maraviroc, both cytochrome P450-3A4 substrates, may be effective in preventing graft-versus-host disease in patients undergoing allogeneic HSCT. This study evaluated whether a pharmacokinetic interaction exists between these agents.

METHODS

The study included 36 allogeneic HSCT recipients who received maraviroc + tacrolimus and 43 recipients of tacrolimus alone. We used a difference-in-differences analysis to examine the change in the concentration/dose ratios of tacrolimus after the discontinuation of maraviroc. In addition, we analysed the concentrations and dose requirements of tacrolimus in the two groups.

RESULTS

There was no significant difference in tacrolimus concentration/dose ratios in patients receiving maraviroc + tacrolimus compared with tacrolimus alone. Upon discontinuation of maraviroc, the change in concentration/dose ratio was small and not significant relative to the control group, and the effect estimate was further attenuated after adjustment for confounders [-0.35 (ng/mL)/(mg/day); P = 0.46]. In addition, the change in mean tacrolimus dose after discontinuation of maraviroc was similar between the groups (0.12 mg/day; P = 0.56), as was the change in mean tacrolimus concentration (0.02 ng/mL; P = 0.97).

CONCLUSIONS

Our findings do not support a significant inhibitory effect of maraviroc on the metabolism of tacrolimus. These data demonstrate that this drug combination is safe and imply that the protective effect of maraviroc against graft-versus-host disease was not mediated through an increase in tacrolimus concentrations. These findings are important for the design of clinical trials that evaluate maraviroc in combination with cytochrome P450-3A4 substrates.

Effect of CYP3A5, CYP3A4, and ABCB1 genotypes as determinants of tacrolimus dose and clinical outcomes after heart transplantation

BACKGROUND

Tacrolimus (Tac) is mainly metabolized by cytochrome P450 3A isoenzymes. In a cohort of heart transplant recipients, we investigated the effect of CYP3A5, CYP3A4, and ABCB1/MDR1 polymorphisms on Tac dose requirements and the risk of developing new-onset diabetes after transplantation (NODAT).

METHODS

A total of 65 heart transplant recipients were genotyped for 3 single nucleotide polymorphisms (SNPs) in the CYP3A5 (SNP rs776746), CYP3A4 (SNP rs2740574), and ABCB1 (SNP rs104564). The mean Tac dose values were compared between the genotypes.

RESULTS

CYP3A5 3 homozygotes (nonexpressers; n = 55, 85%) received significantly higher Tac dose compared with CYP3A5 1 carriers (expressers). No different NODAT frequencies were found between the genotypes.

CONCLUSIONS

The CYP3A5 polymorphism was the main determinant of Tac dose requirements among heart transplant recipients. This common functional polymorphism had no influence on the risk of developing NODAT.

Association of CYP3A polymorphisms with the pharmacokinetics of cyclosporine A in early post-renal transplant recipients in China

AIM

To evaluate retrospectively the association of cytochrome P450 3A (CYP3A) and ATP-binding cassette sub-family B member 1 (ABCB1) gene polymorphisms with the pharmacokinetics of cyclosporine A (CsA) in Chinese renal transplant patients.

METHODS

One hundred and twenty-six renal transplant patients were recruited. Blood samples were collected, and corresponding clinical indices were recorded on the seventh day after the procedure. The patients were genotyped for CYP3A4*1G, CYP3A5*3C, ABCB1 1236 C>T, ABCB1 2677 G>T/A, and ABCB1 3435 C>T polymorphisms. Whole blood trough concentrations of CsA at time zero (C(0)) were measured before the drug administration. A multiple regression model was developed to analyze the effects of genetic factors on the CsA dose-adjusted C(0) (C(0)/dose) based on several clinical indices.

RESULTS

The CYP3A5*3C polymorphism influenced the C(0) and C(0)/dose of CsA, which were significantly higher in patients with the GG genotype than in patients with the AA or GA genotypes. No significant differences were detected for other SNPs (CYP3A4*1G, ABCB1 1236 C>T, ABCB1 2677 G>T/A, and ABCB1 3435 C>T). In a univariate analysis using Pearson's correlation test, age, hemoglobin, blood urea nitrogen and blood creatinine levels were significantly correlated with the log-transformed CsA C(0)/dose. In the multiple regression model, CYP3A5*3C, age, hemoglobin and blood creatinine level were associated with the log-transformed CsA C(0)/dose.

CONCLUSION

CYP3A5*3C correlates with the C(0)/dose of CsA on the seventh day after renal transplantation. The allele is a putative indicator for the optimal CsA dosage in the early phase of renal transplantation in the Chinese population.

Erythroid recovery affects tacrolimus levels after engraftment during stem cell transplantation

Tacrolimus is commonly used in stem-cell transplants (SCT) for prophylaxis of graft-versus-host disease and is continuously administered throughout transplantation. The dose of tacrolimus is frequently decreased to maintain a desired concentration during the recovery of hemocytes after engraftment. If parameters which affect tacrolimus clearance are identified, it is of clinical use to estimate concentrations and aid dosing. The objective of this study was to identify which hematologic parameters affect tacrolimus clearance. Seventeen consecutive Japanese patients with hematological malignancies who received allogeneic SCT between March 2004 and January 2007 were enrolled in this study. Their steady-state concentrations were routinely measured and standardized as the concentration/dose (C/D) ratio ((ng/mL)/(mg/kg/d)). Multivariate analysis was performed to identify which hemocyte parameters affected the C/D ratio. Of the 13 patients, gradual dose reduction was required to combat elevated tacrolimus concentrations. The mean post-engraftment C/D ratio was higher than the pre-engraftment C/D ratio in each patient. The mean C/D ratio for all patients after engraftment was 1.56-fold higher (p=0.00004, range: 1.04-3.03) than that before engraftment. The variation ratio was calculated by dividing the C/D ratio by that on the engraftment day. Multivariate analysis revealed that the reticulocyte (RET) level (×10(3) count/µL) was the sole parameter influencing this ratio, and both parameters were expressed as: Variation ratio=0.004×RET+1.0. RET recovery of patients could influence the C/D ratio and tacrolimus clearance was affected by recipient original red blood cells, but not that of transfused red blood cells.

Pharmacogenetics of tacrolimus after renal transplantation: analysis of polymorphisms in genes encoding 16 drug metabolizing enzymes

BACKGROUND

Tacrolimus (Tac) is an immunosuppressive drug used to prevent post-transplant (PT) organ rejection. Continuous Tac monitoring is necessary to adjust the dose and prevent toxicity or rejection. Tac is metabolized by cytochrome-P450 (CYP) enzymes, and variation at the CYP and other drug metabolizing enzymes could influence Tac bio-availability and dose requirements. Our aim was to define the effect of DNA variants at 16 drug metabolising enzymes on Tac dose in patients with kidney transplants.

METHODS

The REDINREN Pharmacogenetics Project was a multicenter study designed to evaluate the effect of DNA polymorphisms on Tac dose requirements. A total of 200 patients who received a first cadaveric kidney and Tac as primary immunosuppressive drug were genotyped for 96 DNA polymorphisms on 16 genes. Significant associations were further replicated in a second group of 200 patients. The Tac daily dose was adjusted to achieve a blood concentration of 10-15 ng/mL in the period 0-3 months PT, and 5-10 ng/mL thereafter. The dose of tacrolimus dose and blood concentrations were compared between genotypes at 1 week, 6 months, and 1 year PT.

RESULTS

The CYP3A5 genotype (SNP rs776746) was the strongest predictor of Tac dose requirements. Patients who were CYP3A5*3*3 (CYP3A5 non-expressors) received significantly higher Tac dose at 1 week, 6 months, and 1 year PT (p<0.0001). At 1 week, 41% of the CYP3A5 non-expressors achieved target blood concentrations compared to 26% of the CYP3A5 expressors (p=0.007). We also found a significant effect of CYP3A4 genotype (SNP rs2740574) on Tac dose requirements in patients who were CYP3A5 non-expressors. None of the other polymorphisms were related to Tac dose requirements or modified the effect of the CYP3A5 genotype.

CONCLUSIONS

rs776746 (CYP3A5) and rs2740574 (CYP3A4) were the only SNPs associated with Tac dosage. The genotyping of these polymorphisms could be a useful pharmacogenetic tool to determine the Tac dose immediately after transplantation.

Pharmacogenetics of psoriasis

Psoriasis is an inflammatory hyperproliferative skin disorder with a strong genetic predisposition. While many effective modalities are currently available for treating psoriasis, response to therapy is quite variable among patients. The genetic component underlying the response to pharmacotherapy in psoriasis is slowly beginning to emerge and represents a specialized field of genetics referred to as pharmacogenetics. The identification of genetic variants has the potential to improve the management of patient care by identifying which patients should avoid a specific drug and which patients should be administered a modified dose. A suitable approach in implementing such a strategy could potentially reduce medical costs and improve success of drug therapy. This article summarizes the clinical aspects of psoriasis, its genetic susceptibility and highlights the current landscape of genetic targets for psoriasis pharmacotherapy.

Role of tacrolimus combination therapy with mycophenolate mofetil in the prevention of organ rejection in kidney transplant patients

Introduction:

Several new medications are now available for immunosuppression in the kidney transplant field. Tacrolimus and mycophenolate mofetil were first introduced for immunosuppression in renal transplantation in the mid 1990s. Since then, the combination of tacrolimus and mycophenolate mofetil has been evaluated in numerous clinical trials. The outcomes of these trials have varied due to differences in induction and/or maintenance therapy, drug dosing and monitoring protocols, and study design. The aim of this review is to analyze the literature critically and to provide an overview of tacrolimus and mycophenolate mofetil combination therapy in renal transplantation.

Pharmacogenetics of calcineurin inhibitors in renal transplantation

Cyclosporine A and tacrolimus (Tac) are inmunosuppresive drugs with a narrow therapeutic range. Underdosing is associated with organ rejection, whereas overdosing could result in toxicity. Therapeutic drug monitoring at different postdose times is necessary to maintain the blood concentrations within a target window. These calcineurin inhibitors are characterized by a broad interindividual pharmacokinetics variability, which makes the determination of the initial dose difficult. In a patient receiving a dose, the amount of the drug that is measured in the blood determines its bioavailability, which depends on the absorption, biotransformation, and elimination of the drug. These processes are primarily controlled by efflux pumps and enzymes of the cytochrome P (CYP) 450 family. DNA variants at the genes encoding these proteins contribute to the interindividual heterogeneity for calcineurin inhibitors metabolism. Cyclosporine A and Tac are metabolized by CYP3A4 and CYP3A5, and several single nucleotide polymorphisms in the two genes have been associated with differences in drug clearance. Carriers of the CYP3A5 wild-type allele have a higher CYP3A5 expression compared with individuals who are homozygous for a common DNA variant that affects gene splicing (CYP3A5*3). For renal transplant recipients receiving Tac, homozygotes for this nonexpression allele would exhibit significantly lower Tac clearance and may require a lower dose to remain within the blood target concentration compared with CYP3A5 expressors. To date, this CYP3A5 variant is the only reported genetic factor to predict the appropiate starting dosage of Tac, avoiding overdosing and improving the outcome of renal transplantation.

Population pharmacokinetics of tacrolimus and CYP3A5, MDR1 and IL-10 polymorphisms in adult liver transplant patients

BACKGROUND AND OBJECTIVE

Tacrolimus, an immunosuppressant widely used after liver transplantation, is characterized by a large inter-individual variability in its pharmacokinetics. The aim of this study was to perform population pharmacokinetic analysis of oral tacrolimus in liver transplant recipients and clarify the potential role of CYP3A5, MDR1 and IL-10 genetic polymorphisms in the variability of population pharmacokinetic parameters.

METHODS

Tacrolimus blood concentration data (n = 1106) were collected from 104 full liver transplant patients and were analysed using a non-linear mixed-effects modelling program (nonmem). The CYP3A5*3, MDR1 G2677T/A and C3435T genetic polymorphisms were determined using polymerase chain reaction (PCR)-restriction fragment length polymorphism analysis. The IL-10 G-1082A variant was studied by allele-specific PCR method.

RESULTS AND DISCUSSION

The liver function in patients as indicated by the total bilirubin level (TBIL) and different CYP3A5*3 genotypes in donors (CYPD) and recipients (CYPR) were observed to influence tacrolimus pharmacokinetic parameter of apparent clearance (Cl/F). The final regression model can be expressed as Cl/F = 15.9 - 1.88 TBIL + 7.65 CYPD + 7.00 CYPR. The relative standard errors (%RSE) of the parameter estimation were lower than 30% and the residual variability of tacrolimus trough blood concentration was 2.81 ng/mL. No significant effect of MDR1 and IL-10 polymorphisms was observed on population pharmacokinetic parameter of tacrolimus within 175 days after liver transplantation.

CONCLUSION

The TBIL in patients and CYP3A5*3 genetic polymorphism in both donors and recipients contribute to the inter-individual variability of oral tacrolimus apparent clearance in Chinese adult liver transplant patients.

Therapeutic monitoring of calcineurin inhibitors for the nephrologist

The calcineurin inhibitors (CNI) cyclosporine and tacrolimus remain the backbone of immunosuppression for most kidney transplant recipients. Despite many years of experience, protocols that optimize efficacy with minimal toxicity remain a subject of debate. Nevertheless, studies of the pharmacokinetic properties of the CNI, particularly cyclosporine, have led to improved dosing strategies. The purpose of this article is to review the current understanding of CNI pharmacokinetics and its relevance to proper dosing and monitoring of these medications. This article also reviews the trials that have helped to define the optimal dosages and discusses the effect of adjunctive immunosuppressive agents on CNI pharmacokinetics and dosing.

Population pharmacokinetics of tacrolimus in full liver transplant patients: modelling of the post-operative clearance

OBJECTIVE

To investigate the population pharmacokinetics of tacrolimus in an adult liver transplant cohort using routine drug monitoring data and to identify patient characteristics that influence pharmacokinetic parameters.

METHODS

Tacrolimus pharmacokinetics was studied in 37 adult patients using a population approach performed with NONMEM.

RESULTS

A one-compartment open model with linear absorption and elimination adequately described the data. The apparent clearance (CL) was approximately zero in the immediate post-operative days (PODs) and then rapidly increased as a function of POD to reach a plateau. This was modelled as a sigmoid relationship with the characteristic parameters CL(max) (plateau), TCL(50) (time to obtain 50% of the plateau) and gamma (coefficient of sigmoidicity). This clearance model was thought to describe the hepatic function regeneration after transplantation. Typical population estimates (percentage inter-individual variability) of CL(max), TCL50, and gamma and apparent distribution volumes (V) were 36 l/h (43%), 6.3 days (33%), and 4.9 l and 1870 l (49%), respectively. The CL(max) was negatively related to plasma albumin, and TCL50 was positively related to aspartate amino transferase (ASAT). Bayesian estimations performed at different POD times indicated that acceptable precisions in individual pharmacokinetic predictions could be obtained after the 15th POD.

CONCLUSION

Tacrolimus clearance modelling showed that there was a large variation in individual CL estimates up to the 15th day post-surgery. After this period, the mean error resulting from the Bayesian estimation was strongly decreased and this estimation method could be applicable and should limit tacrolimus monitoring.

Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation

The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immunosuppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.

Time-related clinical determinants of long-term tacrolimus pharmacokinetics in combination therapy with mycophenolic acid and corticosteroids: a prospective study in one hundred de novo renal transplant recipients

BACKGROUND

Tacrolimus is an efficient primary immunosuppressive drug in renal transplantation but its long-term use is associated with calcineurin-inhibitor-related toxicity. The specific characteristics of the inter-relationship between dose, concentration and clinical (side-)effects for tacrolimus have not yet been identified and extensive long-term pharmacokinetic studies are presently lacking.

OBJECTIVE

To establish the characteristics of the long-term pharmacokinetics of tacrolimus, to determine the time-dependent factors that influence the pharmacokinetics within the first critical post-transplant year and to identify a more appropriate way of monitoring drug exposure in clinical practice.

STUDY DESIGN

A prospective pharmacokinetic study of tacrolimus was conducted in 100 de novo renal allograft recipients during the first year post-transplantation.

METHODS

Area under the concentration-time curve (AUC) blood samplings for tacrolimus were performed on days 7, 42, 90, 180 and 360 for all patients. Model-independent pharmacokinetic parameters for tacrolimus were calculated and dose-corrected when appropriate: AUC12, peak plasma concentration (Cmax), pre-dose trough concentration (C0), time to Cmax, average steady-state blood concentration, steady-state total body clearance, terminal half-life, volume of distribution and an estimate for tacrolimus bioavailability was derived from additional steady-state intravenous clearance data. The association between tacrolimus pharmacokinetic parameters and different clinical variables was evaluated on days 7, 42, 90, 180 and 360. The clinical variables were either donor-related (e.g. donor age), transplantation-related (e.g. delayed graft function), recipient-related (e.g. bodyweight), biochemical (e.g. serum albumin), therapeutic variables (e.g. corticosteroid dose) or disease variables (e.g. liver dysfunction).

RESULTS

Long-term tacrolimus dose-corrected exposure (AUC12, C0) is characterised by a late significant increase towards the end of the first year post-transplantation as the result of a significant increase in tacrolimus bioavailability (p < 0.05) and a slow decrease in tacrolimus steady-state clearance. Consequently, tacrolimus dose-requirements corrected for bodyweight decrease significantly in the first postoperative year (p < 0.05), in part because of the simultaneous tapering of the corticosteroid dose which significantly affects tacrolimus bioavailability (p < 0.05). Other clinical variables that significantly influenced tacrolimus administration, exposure and bioavailability in a time-related fashion were identified in this study (renal allograft function [p < 0.05], liver dysfunction [p < 0.05], diarrhoea [p < 0.05]), while the clinical relevance of other variables was considerably moderated by our findings (serum albumin, haematocrit). Time-unrelated variables proved to be of significant continuing clinical importance for tacrolimus dose-exposure pharmacokinetics throughout the first post-transplant year (recipient age [p < 0.05], gender [p < 0.01] and donor-receptor gender mismatch [p < 0.05]), while donor hypotension (p < 0.05) and cold ischaemia time (p < 0.05) also proved significant although at present the reasons for this are unknown. Finally, using multiple stepwise regression analysis we demonstrated that classical assessment of tacrolimus exposure by monitoring pre-dose trough blood concentration (or any other single concentration sampling timepoint) is not the most reliable method and that abbreviated AUC measurements may constitute a more accurate clinical tool for (therapeutic) monitoring of drug exposure.

CONCLUSION

Tacrolimus pharmacokinetics in the first year after renal transplantation are characterised by a specific time-dependent evolution. The identification of clinical variables that determine tacrolimus pharmacokinetics is an important aid in the development of reliable drug monitoring strategies using abbreviated AUC measurements.