Drug interactions with tacrolimus

Providing care for kidney transplant recipients: An overview for generalists

Kidney transplantation is the preferred treatment for patients with advanced chronic kidney disease and end-stage kidney disease, offering superior quality of life and survival compared to dialysis. This manuscript provides an updated overview of post-transplant care, highlighting recent advancements and current practices to assist generalists in managing these patients. It covers key areas such as immunosuppression strategies, drug interactions, and the management of transplant-specific acute kidney injury. The focus includes the use of sodium-glucose cotransporter-2 inhibitors and cell-free DNA monitoring for evaluating allograft health and immune-mediated injury. The manuscript reviews the fundamentals of immunosuppression, including both induction and maintenance therapies, and underscores the importance of monitoring kidney function, as well as addressing hypertension, diabetes, and infections. It also provides recommendations for vaccinations and cancer screening tailored to kidney transplant recipients and emphasizes lifestyle management strategies, such as exercise and sodium intake, to reduce post-transplant complications.

Evaluation of drug-drug interaction between rosuvastatin and tacrolimus and the risk of hepatic injury in rats

Multimorbidity, therapeutic complexity, and polypharmacy, which greatly increases the risk of drug-drug interactions (DDIs) and adverse medical outcomes, have become important and growing challenges in clinical practice. Statins are frequently prescribed to manage post-transplant dyslipidemia and reduce overall cardiovascular risk in solid organ transplant recipients. This study aimed to determine whether rosuvastatin has significant DDIs with tacrolimus (the first-line immunosuppressant) and to evaluate the risk of hepatotoxicity associated with concomitant therapy. We first studied whether a rat model could be established to assess the magnitude of rosuvastatin-tacrolimus DDI. The liver function index and histopathological examination were performed to investigate the characteristics of hepatotoxicity in the presence and absence of DDI. The clinical DDI potential between rosuvastatin and tacrolimus was also explored. Single-dose intravenous administration of tacrolimus did not significantly affect the area under the plasma concentration-time curve (AUC0-∞), clearance (CL), and volume of distribution at steady-state (Vss) of rosuvastatin in rats, despite a 96.7% increase in the rosuvastatin maximum plasma concentration (P = 0.024). Multiple doses of intravenous tacrolimus had no effect on the systemic disposition of rosuvastatin, but significantly increased aspartate transaminase (AST) by 42.6% (P = 0.043). Multiple doses of intravenous tacrolimus and rosuvastatin significantly altered the disposition of rosuvastatin, reducing alanine aminotransferase (ALT) and AST by 38.3% (P = 0.040) and 31.6% (P = 0.019), respectively. Histological evaluation of the liver specimens revealed patterns of drug-induced liver injury in rats. At clinically relevant doses, tacrolimus was predicted to be unable to cause pharmacokinetic interactions with rosuvastatin through basic models. The concomitant administration of tacrolimus and rosuvastatin has a minor impact on rosuvastatin pharmacokinetics; however, mild hepatotoxicity has been observed in rats.

Tacrolimus- and Mycophenolate-Mediated Toxicity: Clinical Considerations and Options in Management of Post-Transplant Patients

Tacrolimus and mycophenolate are important immunosuppressive agents used to prevent organ rejection in post-transplant patients. While highly effective, their use is associated with significant toxicity, requiring careful management. Tacrolimus, a calcineurin inhibitor, is linked to nephrotoxicity, neurotoxicity, metabolic disturbances such as diabetes mellitus and dyslipidemia, and cardiovascular complications such as hypertension and arrhythmias. Mycophenolate, a reversible inhibitor of inosine monophosphate dehydrogenase, frequently causes gastrointestinal disturbances, including diarrhea and colitis, as well as hematologic side effects like anemia and leukopenia, which increase infection risk. Therapeutic drug monitoring (TDM) and pharmacogenomics have emerged as essential strategies for mitigating these toxicities. TDM ensures tacrolimus trough levels are maintained within a therapeutic range, minimizing the risks of nephrotoxicity and rejection. Pharmacogenomic insights, such as CYP3A5 polymorphisms, allow for personalized tacrolimus dosing based on individual metabolic profiles. For mycophenolate, monitoring inosine monophosphate dehydrogenase activity provides a pharmacodynamic approach to dose optimization, reducing gastrointestinal and hematologic toxicities. Emerging tools, including dried blood spot sampling and pharmacokinetic modeling, offer innovative methods to simplify monitoring and enhance precision in outpatient settings. Despite their utility, the toxicity profiles of these drugs, including those of early immunosuppressants such as cyclosporine and azathioprine, necessitate further consideration of alternative immunosuppressants like sirolimus, everolimus, and belatacept. Although promising, these newer agents require careful patient selection and further research. Future directions in immunosuppressive therapy include integrating individual pharmacogenetic data to refine dosing, minimize side effects, and improve long-term graft outcomes. This narrative review underscores the importance of personalized medicine and advanced monitoring in optimizing post-transplant care.

Analytical modelling techniques for enhancing tacrolimus dosing in solid organ transplantation: a systematic review protocol

INTRODUCTION

Tacrolimus is an immunosuppressant commonly administered in transplant recipients. Given its narrow therapeutic range and susceptibility to various influencing variables, determining its optimal dosage is challenging. This systematic review seeks to identify effective analytical modelling techniques and methods for optimal tacrolimus dose prediction in solid transplant recipients.

METHODS AND ANALYSIS

This review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. The study will review the literature published from database inception to 11 March 2024, that assesses predictive models of tacrolimus dosing through analytical modelling techniques. We will include both randomised and non-randomised, as well as cross-sectional, qualitative and before-and-after studies and will perform our searches in four main databases-Ovid/MEDLINE, PubMed/MEDLINE, Scopus, Embase and Web of Science, and search engines including Centers for Disease Control (CDC) and Google Scholar. Papers that are not published in English or French are excluded from this study. A narrative synthesis and meta-analysis will be done if the extracted information permits such analysis. Conference abstracts will be ignored unless they are recent (published within 2 years of the search date).

ETHICS AND DISSEMINATION

Ethics clearance is not required for this study as no primary data will be collected. The completed manuscript will be published, and the results of the study will be presented at conferences.

STUDY REGISTRATION

International Prospective Register of Systematic Reviews (PROSPERO), CRD42024537212.

Renal Allograft Function and the Tacrolimus C/D Ratio: Insights from a Prospective Study on MeltDose Tacrolimus

Background: The tacrolimus concentration-to-dose (C/D) ratio is valuable for optimizing nephrotoxicity-related renal outcomes. Prospective data on the C/D ratio in kidney transplant recipients newly treated with MeltDose tacrolimus are limited. We analyzed the C/D ratio pattern of MeltDose tacrolimus and its effect on posttransplant renal function, comparing it with the literature data on immediate-release tacrolimus (IR-Tac). Methods: In total, 101 adult kidney transplant recipients on a standard immunosuppressive regimen including MeltDose tacrolimus were enrolled in this prospective, multicenter cohort study and followed for 12 months. The C/D ratio classified patients as fast, intermediate, or slow metabolizers. Renal function was assessed via the estimated glomerular filtration rate (eGFR). MeltDose tacrolimus data were compared with previous IR-Tac data by bootstrapping. Results: The cohort exhibited a right-skewed C/D ratio distribution with a mean of 2.12 ng/mL × 1/mg, which was significantly greater than the 1.29 mean for IR-Tac (p < 0.001). Compared with fast metabolizers, slow metabolizers of MeltDose tacrolimus experienced greater eGFR gains at 6 months post-transplantation (median +7.9 vs. -3.6 mL/min; p = 0.005). A Bayesian linear mixed-effects model predicting the eGFR at month 12 identified the baseline eGFR, time from transplant, body mass index, and log-transformed C/D ratio as significant variables. A one-unit increase in the log-transformed C/D ratio corresponded to an approximate increase of 4.5 mL/min in the eGFR at month 12. Conclusions: Slow metabolizers of MeltDose tacrolimus had significantly better renal function outcomes than fast metabolizers. MeltDose tacrolimus is associated with slower metabolism than is IR-Tac, as evidenced by its higher C/D ratios.

Tacrolimus Dose Requirement in De Novo Adult Kidney Transplant Patients Treated With Adoport® Can Be Anticipated

All the factors potentially influencing tacrolimus dose requirement and combinations thereof have never been thoroughly investigated, precluding accurate prediction of tacrolimus starting dose. This prospective, non-interventional, multicenter study in de novo adult kidney transplant recipients over the first year after transplantation aimed to investigate the factors influencing tacrolimus dose-standardized trough blood concentration (C0/D) over the first week post-transplant (D4-D7, primary objective), D8-M3 and M3-M12 (secondary objectives). Statistical analysis employed mixed linear models with repeated measures. Eighteen sites enrolled 440 patients and followed them up for 9.5 ± 4.1 months. Age at baseline (p = 0.0144), end-stage renal disease (p = 0.0092), CYP3A phenotype (p < 0.0001), dyslipidemia at baseline (p = 0.0031), hematocrit (p = 0.0026), total bilirubin (p = 0.0261) and plasma creatinine (p = 0.0484) independently increased with log(C0/D) over D4-D7, explaining together 72.3% of the interindividual variability, and representing a robust model to estimate tacrolimus initial dose. Donor age and CYP3A phenotype were also influential over D8-M3 and M3-12, in addition to recipient age. Corticosteroids, diabetes at baseline, and ASAT yielded inconstant results between D8-M3 and M3-M12. We found no ethnicity effect when CYP3A phenotype was accounted for, and no food effect. Intra-individual variability over M3-M12 was moderate, and significantly lower in patients with chronic hepatic disorder (p = 0.0196) or cancer (p = 0.0132).

Early CYP3A5 Genotype-Based Adjustment of Tacrolimus Dosage Reduces Risk of De Novo Donor-Specific HLA Antibodies and Rejection among CYP3A5-Expressing Renal Transplant Patients

BACKGROUND/OBJECTIVES

Our previous retrospective single-center cohort study found, at 3-year follow-up, a trend toward low tacrolimus trough levels and an increased risk of de novo donor-specific anti-HLA antibodies (DSAs) and of antibody-mediated rejection (ABMR) in CYP3A5-expressing patients. Determining CYP3A5-expression status immediately after renal transplant would allow early genotype-based dosage adjustment of tacrolimus and might prevent the occurrence of de novo DSAs and ABMR, improving transplant outcome.

METHODS

160 renal allograft recipients who underwent renal transplant at the University Hospital Essen between May 2019 and May 2022 were genotyped for the CYP3A5 rs776746 polymorphism within the first two weeks after transplant, and genotype-based dose adjustment of tacrolimus was performed for the follow-up of 2 years.

RESULTS

CYP3A5 expression was detected in 33 (21%) of the 160 patients. Tacrolimus trough levels were similar in CYP3A5 expressers and nonexpressers over the entire 2-year follow-up period. However, we observed a trend toward slightly higher tacrolimus trough levels in CYP3A5 expressers, who, as expected, required tacrolimus dosages twice as high as did nonexpressers during follow-up. Calcineurin inhibitor (CNI) nephrotoxicity-free survival rates were comparable between CYP3A5 expressers and nonexpressers (p = 0.49). Rejection-free survival rates (p = 0.89), de novo anti-HLA antibody-free survival rates (p = 0.57) and de novo DSA-free survival rates (p = 0.61) did not differ between the two groups.

CONCLUSIONS

Early detection of CYP3A5-expression status and resultant genotype-based adjustment of tacrolimus dosage after renal transplant protected patients from transplant rejection and de novo DSA formation and was not associated with increased incidence of CNI toxicity among CYP3A5 expressers.

Tacrolimus intra-patient variability measures and its associations with allograft clinical outcomes in kidney transplantation

AIMS

Tacrolimus (Tac) is commonly prescribed in solid organ transplantation to prevent immune-mediated damage to the graft. However, its pharmacokinetics show substantial variability between and within patients. Intra-patient variability of tacrolimus (Tac-IPV) has emerged as a novel marker to predict transplant outcomes. Numerous studies report varying associations between Tac-IPV and clinical outcomes, with Tac-IPV measures showing wide discrepancies among these studies. This inconsistency could be a significant factor that influences the various outcomes reported in different studies. Our review comprehensively assesses the relationship between various Tac-IPV measures and their associations with clinical outcomes in transplant patients.

METHODS

A comprehensive literature search was conducted using the PubMed and Embase databases, covering the period from 2004 to March 31, 2023. The search focused on studies that examined the relationship between Tac-IPV and clinical outcomes in kidney transplantation (KT). The inclusion criteria were specific to studies addressing Tac-IPV, including measures such as standard deviation (SD), coefficient of variation (CV), time-weighted coefficient of variability (CV), mean absolute deviation (MAD), and Tac variability score (TVS). Clinical outcomes included the development of de novo donor-specific antibodies (dnDSA), rejection episodes, graft loss, and graft failure.

RESULTS

Among the 33 studies that met the inclusion criteria, a notable proportion presented conflicting findings in their assessment of various Tac-IPV measures regarding dnDSA, rejection episodes, graft loss, and graft failure.

CONCLUSIONS

Most studies have identified a correlation between high Tac-IPV and poor clinical outcomes; however, this relationship is multifactorial. Influencing factors include the metabolic status of KT patients, the timing of Tac-IPV calculations, and the criteria for defining high and low Tac-IPV thresholds, including the size and selection method. CV, MAD, and TWCV are the metrics that are most frequently used to determine Tac-IPV. Additionally, most of the methods for establishing Tac-IPV thresholds typically employ receiver operating characteristic (ROC) curves and median values. It is also notable that studies examining the clinical significance of Tac-IPV often include tacrolimus levels measured six months after kidney transplantation.

Composite CYP3A (CYP3A4 and CYP3A5) phenotypes and influence on tacrolimus dose adjusted concentrations in adult heart transplant recipients

CYP3A5 genetic variants are associated with tacrolimus metabolism. Controversy remains on whether CYP3A4 increased [*1B (rs2740574), *1 G (rs2242480)] and decreased function [*22 (rs35599367)] genetic variants provide additional information. This retrospective cohort study aims to address whether tacrolimus dose-adjusted trough concentrations differ between combined CYP3A (CYP3A5 and CYP3A4) phenotype groups. Heart transplanted patients (n = 177, between 2008 and 2020) were included and median age was 54 years old. Significant differences between CYP3A phenotype groups in tacrolimus dose-adjusted trough concentrations were found in the early postoperative period and continued to 6 months post-transplant. In CYP3A5 nonexpressers, carriers of CYP3A4*1B or *1 G variants (Group 3) compared to CYP3A4*1/*1 (Group 2) patients were found to have lower tacrolimus dose-adjusted trough concentrations at 2 months. In addition, significant differences were found among CYP3A phenotype groups in the dose at discharge and time to therapeutic range while time in therapeutic range was not significantly different. A combined CYP3A phenotype interpretation may provide more nuanced genotype-guided TAC dosing in heart transplant recipients.

A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus for Tunisian Adults after Renal Transplantation

BACKGROUND

Tacrolimus is the most frequently used immunosuppressive drug for preventing renal rejection. However, its use is hampered by its narrow therapeutic index and large intra and interpatient variability in pharmacokinetics. The objective of this study was to externally validate a tacrolimus population pharmacokinetic model developed for the Dutch population and adjust the model for the Tunisian population for use in predicting the starting dose requirement after kidney transplantation.

METHODS

Data on tacrolimus exposure were obtained from kidney transplant recipients (KTRs) during the first 3 months post-transplantation. External validation of the Dutch model and its adjustment for the Tunisian population was performed using nonlinear mixed-effects modeling.

RESULTS

In total, 1901 whole-blood predose tacrolimus concentrations from 196 adult KTRs were analyzed. According to a visual predictive check, the Dutch model underestimated the starting dose for the Tunisian adult population. The effects of age, together with the CYP3A5*3 and CYP3A4*22 genotypes on tacrolimus clearance were significantly different in the Tunisian population than in the Dutch population. Based on a bodyweight-based dosing, only 21.9% of tacrolimus concentrations were within the target range, whereas this was estimated to be 54.0% with the newly developed model-based dosing. After adjustment, the model was successfully validated internally in a Tunisian population.

CONCLUSIONS

A starting-dose population pharmacokinetic model of tacrolimus for Tunisian KTRs was developed based on a previously published Dutch model. Using this starting dose could potentially increase the percentage of patients achieving target tacrolimus concentrations after the initial starting dose.

Dynamics of torque teno virus load in kidney transplant recipients with indication biopsy and therapeutic modifications of immunosuppression

Following kidney transplantation, lifelong immunosuppressive therapy is essential to prevent graft rejection. On the downside, immunosuppression increases the risk of severe infections, a major cause of death among kidney transplant recipients (KTRs). To improve post-transplant outcomes, adequate immunosuppressive therapy is therefore a challenging but vital aspect of clinical practice. Torque teno virus load (TTVL) was shown to reflect immune competence in KTRs, with low TTVL linked to an elevated risk for rejections and high TTVL associated with infections in the first year post-transplantation. Yet, little is known about the dynamics of TTVL after the first year following transplantation and how TTVL changes with respect to short-term modifications in immunosuppressive therapy. Therefore, we quantified TTVL in 106 KTRs with 108 clinically indicated biopsies, including 65 biopsies performed >12 months post-transplantation, and correlated TTVL to histopathology. In addition, TTVL was quantified at 7, 30, and 90 days post-biopsy to evaluate how TTVL was affected by changes in immunosuppression resulting from interventions based on histopathological reporting. TTVL was highest in patients biopsied between 1 and 12 months post-transplantation (N = 23, median 2.98 × 107 c/mL) compared with those biopsied within 30 days (N = 20, median 7.35 × 103 c/mL) and > 1 year post-transplantation (N = 65, median 1.41 × 104 c/mL; p < 0.001 for both). Patients with BK virus-associated nephropathy (BKVAN) had significantly higher TTVL than patients with rejection (p < 0.01) or other pathologies (p < 0.001). When converted from mycophenolic acid to a mTOR inhibitor following the diagnosis of BKVAN, TTVL decreased significantly between biopsy and 30 and 90 days post-biopsy (p < 0.01 for both). In KTR with high-dose corticosteroid pulse therapy for rejection, TTVL increased significantly between biopsy and 30 and 90 days post-biopsy (p < 0.05 and p < 0.01, respectively). Of note, no significant changes were seen in TTVL within 7 days of changes in immunosuppressive therapy. Additionally, TTVL varied considerably with time since transplantation and among individuals, with a significant influence of age and BMI on TTVL (p < 0.05 for all). In conclusion, our findings indicate that TTVL reflects changes in immunosuppressive therapy, even in the later stages of post-transplantation. To guide immunosuppressive therapy based on TTVL, one should consider inter- and intraindividual variations, as well as potential confounding factors.

Weight, CYP3A5 Genotype, and Voriconazole Co-administration Influence Tacrolimus Initial Dosage in Pediatric Lung Transplantation Recipients with Low Hematocrit based on a Simulation Model

OBJECTIVE

The method of administering the initial doses of tacrolimus in recipients of pediatric lung transplantation, especially in patients with low hematocrit, is not clear. The present study aims to explore whether weight, CYP3A5 genotype, and voriconazole co-administration influence tacrolimus initial dosage in recipients of pediatric lung transplantation with low hematocrit based on safety and efficacy using a simulation model.

METHODS

The present study utilized the tacrolimus population pharmacokinetic model, which was employed in lung transplantation recipients with low hematocrit.

RESULTS

For pediatric lung transplantation recipients not carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-13, 13-19, 19-22, 22-35, 35-38, and 38-40 kg are 0.03, 0.04, 0.05, 0.06, 0.07, and 0.08 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-18, 18-30, and 30-40 kg are 0.06, 0.08, 0.11 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients not carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20 and 20-40 kg are 0.02 and 0.03 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20, 20-33, and 33-40 kg are 0.03, 0.04, and 0.05 mg/kg/day, which are split into two doses, respectively.

CONCLUSION

The present study is the first to recommend the initial dosages of tacrolimus in recipients of pediatric lung transplantation with low hematocrit using a simulation model.

Voclosporin: Unique Chemistry, Pharmacology and Toxicity Profile, and Possible Options for Implementation into the Management of Lupus Nephritis

Calcineurin inhibitors (CNI) can suppress allo- and autoimmunity by suppressing T cell function but also have anti-proteinuric effects by stabilizing the cellular components of the kidney's filtration barrier. Therefore, CNI are used in autoimmune kidney diseases with proteinuria. However, the traditional CNI, cyclosporine A and tacrolimus, have a narrow therapeutic range, need monitoring of drug levels, and their use is associated with nephrotoxicity and metabolic alterations. Voclosporin (VOC), a novel CNI, no longer requires drug level monitoring and seems to lack these adverse effects, although hypertension and drug-drug interactions still occur. VOC demonstrated efficacy superior to standard-of-care in controlling active lupus nephritis in the phase 2 AURA-LV and the phase 3 AURORA-1 trials and was approved for the treatment of active lupus nephritis. However, how to implement VOC into the current and changing treatment landscape of lupus nephritis is still debated. Here, we review the unique chemistry, pharmacology, and toxicity profile of VOC, summarize the efficacy and safety data from the AURA-LV and AURORA-1 trials, and discuss the following four possible options to implement VOC into the management of lupus nephritis, namely regarding B cell-targeting therapy with belimumab (BEL). These include: 1. patient stratification to either VOC or BEL, 2. VOC/BEL combination therapy, 3. VOC-BEL sequential therapy, or 4. alternative options for the rapid antiproteinuric effect of VOC.

Importance of Pharmacogenetics and Drug-Drug Interactions in a Kidney Transplanted Patient

Tacrolimus (TAC) is a narrow-therapeutic-range immunosuppressant drug used after organ transplantation. A therapeutic failure is possible if drug levels are not within the therapeutic range after the first year of treatment. Pharmacogenetic variants and drug-drug interactions (DDIs) are involved. We describe a patient case of a young man (16 years old) with a renal transplant receiving therapy including TAC, mycophenolic acid (MFA), prednisone and omeprazole for prophylaxis of gastric and duodenal ulceration. The patient showed great fluctuation in TAC blood concentration/oral dose ratio, as well as pharmacotherapy adverse effects (AEs) and frequent diarrhea episodes. Additionally, decreased kidney function was found. A pharmacotherapeutic follow-up, including pharmacogenetic analysis, was carried out. The selection of the genes studied was based on the previous literature (CYP3A5, CYP3A4, POR, ABCB1, PXR and CYP2C19). A drug interaction with omeprazole was reported and the nephrologist switched to rabeprazole. A lower TAC concentration/dose ratio was achieved, and the patient's condition improved. In addition, the TTT haplotype of ATP Binding Cassette Subfamily B member 1 (ABCB1) and Pregnane X Receptor (PXR) gene variants seemed to affect TAC pharmacotherapy in the studied patient and could explain the occurrence of long-term adverse effects post-transplantation. These findings suggest that polymorphic variants and co-treatments must be considered in order to achieve the effectiveness of the immunosuppressive therapy with TAC, especially when polymedicated patients are involved. Moreover, pharmacogenetics could influence the drug concentration at the cellular level, both in lymphocyte and in renal tissue, and should be explored in future studies.

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.

Composite CYP3A (CYP3A4 and CYP3A5) phenotypes and influences on tacrolimus dose adjusted concentration in adult heart transplant recipients

CYP3A5 genetic variants are associated with tacrolimus metabolism. Controversy remains on whether CYP3A4 increased [* 1B (rs2740574), *1G (rs2242480)] and decreased function [*22 (rs35599367)] genetic variants provide additional information. This study aims to address whether tacrolimus dose-adjusted trough concentrations differ between combined CYP3A (CYP3A5 and CYP3A4) phenotype groups. Significant differences between CYP3A phenotype groups in tacrolimus dose-adjusted trough concentrations were found in the early postoperative period and continued to 6 months post-transplant. In CYP3A5 nonexpressers, carriers of CYP3A4*7Bor *7G variants (Group 3) compared to CYP3A4*1/*1 (Group 2) patients were found to have lower tacrolimus dose-adjusted trough concentrations at 2 months. In addition, significant differences were found among CYP3A phenotype groups in the dose at discharge and time to therapeutic range while time in therapeutic range was not significantly different. A combined CYP3A phenotype interpretation may provide more nuanced genotype-guided TAC dosing in heart transplant recipients.

Factors Affecting Day-to-Day Variations in Tacrolimus Concentration among Children and Young Adults Undergoing Allogeneic Hematopoietic Stem Cell Transplantation

Tacrolimus is widely used as prophylaxis for graft-versus-host disease (GVHD) in allogeneic stem cell transplantation (allo-HSCT). It has a narrow therapeutic index range; high tacrolimus concentrations are associated with toxicity, whereas low concentrations are associated with an increased risk of GVHD. Although dose adjustments based on therapeutic drug monitoring are performed, unexpected large variations in tacrolimus concentration are sometimes encountered. The available evidence suggests that the factors affecting tacrolimus concentration are not fully understood. This study was aimed primarily at investigating the factors affecting day-to-day variations in tacrolimus concentration in children and young adults who received continuous tacrolimus infusion after allo-HSCT. The secondary objective was to identify the factors causing large variations (>20%) in tacrolimus concentrations. This retrospective cohort study comprised 123 consecutive pediatric and young adult patients (age <25 years) who received continuous i.v. tacrolimus infusion after allo-HSCT at Shinshu University Hospital, Matsumoto, Japan, between January 2009 and December 2021. To compare day-to-day variations in tacrolimus concentration without consideration of the tacrolimus dose, 2 consecutive days when the tacrolimus dose was not changed were selected from between the first post-allo-HSCT day of a tacrolimus concentration >7 ng/mL and day 28 post-allo-HSCT. Subsequently, information for the subsequent 24 hours was collected along with the tacrolimus concentrations and hematocrit values. Tacrolimus concentration was determined using whole blood samples. Tacrolimus concentrations were significantly higher in patients who received red blood cell concentrate (RCC) transfusions (P < .0001) and methotrexate (P = .0162), patients with persistent fever (P = .0056), and patients with a decline in fever (P = .0003). In contrast, tacrolimus concentrations were significantly lower in patients who received platelet concentrate (PC) transfusions (P < .0001), who redeveloped fever (P = .0261), and who had a replaced tacrolimus administration route set (P = .0008). Variations in tacrolimus concentration were significantly correlated with variations in hematocrit (r = .556; P < .0001). Body weight (P < .0001), RCC transfusion (P < .0001), methotrexate use (P = .0333), persistent fever (P = .0150), and decline in fever (P = .0073) were associated with a sharp increase in tacrolimus concentration. In contrast, body weight (P < .0001), PC transfusion (P = .0025), and replacement of the tacrolimus administration route set (P = .0025) were associated with a sharp decrease in tacrolimus concentration. RCC and PC transfusions, fever, methotrexate administration, and replacement of the tacrolimus administration route set were independent factors affecting day-to-day variations in tacrolimus concentration. In addition to these factors, low body weight was a risk factor for both sharp increases and decreases in tacrolimus concentration. These findings suggest the need for better control of tacrolimus concentration using whole blood samples.

Therapeutic Drug Monitoring and Dosage Adjustments of Immunosuppressive Drugs When Combined With Nirmatrelvir/Ritonavir in Patients With COVID-19

ABSTRACT

Nirmatrelvir/ritonavir (Paxlovid) consists of a peptidomimetic inhibitor (nirmatrelvir) of the SARS-CoV-2 main protease and a pharmacokinetic enhancer (ritonavir). It is approved for the treatment of mild-to-moderate COVID-19. This combination of nirmatrelvir and ritonavir can mediate significant and complex drug-drug interactions (DDIs), primarily due to the ritonavir component. Indeed, ritonavir inhibits the metabolism of nirmatrelvir through cytochrome P450 3A (CYP3A) leading to higher plasma concentrations and a longer half-life of nirmatrelvir. Coadministration of nirmatrelvir/ritonavir with immunosuppressive drugs (ISDs) is particularly challenging given the major involvement of CYP3A in the metabolism of most of these drugs and their narrow therapeutic ranges. Exposure of ISDs will be drastically increased through the potent ritonavir-mediated inhibition of CYP3A, resulting in an increased risk of adverse drug reactions. Although a decrease in the dosage of ISDs can prevent toxicity, an inappropriate dosage regimen may also result in insufficient exposure and a risk of rejection. Here, we provide some general recommendations for therapeutic drug monitoring of ISDs and dosing recommendations when coadministered with nirmatrelvir/ritonavir. Particularly, tacrolimus should be discontinued, or patients should be given a microdose on day 1, whereas cyclosporine dosage should be reduced to 20% of the initial dosage during the antiviral treatment. Dosages of mammalian target of rapamycin inhibitors (m-TORis) should also be adjusted while dosages of mycophenolic acid and corticosteroids are expected to be less impacted.

Does the Tacrolimus Trough Level Adequately Predict Drug Exposure in Patients Requiring a High Tacrolimus Dose?

Tacrolimus (Tac) has a narrow therapeutic range. Dosing is generally targeted at Tac trough levels (C ₀), notwithstanding conflicting reports on the correlation between Tac C ₀ and systemic exposure measured by the area-under-the-concentration-over-time curve (AUC). The Tac dose required to meet the target C ₀ varies highly among patients. We hypothesized that patients requiring a relatively high Tac dose for a certain C ₀ may show a higher AUC.

Methods

We retrospectively analyzed data from 53 patients in which a 24-h Tac AUC₂₄ estimation was performed at our center. Patients were divided into those taking a low (≤0.15 mg/kg) or high (>0.15 mg/kg) once-daily Tac dose. Multiple linear regression models were used to investigate if the association between C ₀ and AUC₂₄ changes according to dose level.

Results

Despite the large difference in mean Tac dose between the low- and high-dose group (7 versus 17 mg/d), C ₀ levels were similar. However, the mean AUC₂₄ was substantially higher in the high-dose group (320 ± 96 h·μg/L versus 255 ± 81 h·μg/L, P < 0.001). This difference remained significant after adjusting for age and race. For a same C ₀, every 0.01 mg/kg increase in Tac dose resulted in an AUC₂₄ increase of 3.59 h·μg/L.

Conclusions

This study challenges the general belief that C ₀ levels are sufficiently reliable to estimate systemic drug exposure. We demonstrated that patients requiring a relatively high Tac dose to attain therapeutic C ₀ levels have higher drug exposure and could therefore potentially be overdosed.

Compare the performance of multiple machine learning models in predicting tacrolimus concentration for infant patients with living donor liver transplantation

BACKGROUND

This study aims to establish multiple ML models and compare their performance in predicting tacrolimus concentration for infant patients who received LDLT within 3 months after transplantation.

METHODS

Retrospectively collected basic information and relevant biochemical indicators of included infant patients. CMIA was used to determine tacrolimus C₀ . PCR was used to determine the donors' and recipients' CYP3A5 genotypes. Multivariate stepwise regression analysis and stepwise elimination covariates were used for covariates selection. Thirteen machine learning algorithms were applied for the development of prediction models. APE, the ratio of the APE ≤3 ng ml^-1 and ideal rate (the proportion of the predicted value with a relative error of 30% or less) were used to evaluate the predictive performance of the model.

RESULTS

A total of 163 infant patients were included in this study. In the case of the optimal combination of covariates, the Ridge model had the lowest APE, 2.01 (0.85, 3.35 ng ml^-1 ). The highest ratio of the APE ≤3 ng ml^-1 was the LAR model (71.77%). And the Ridge model showed the highest ideal rate (55.05%). For the Ridge model, GRWR was the most important predictor.

CONCLUSIONS

Compared with other ML models, the Ridge model had good predictive performance and potential clinical application.

Ruxolitinib as Adjunctive Therapy for Hemophagocytic LymPhohistiocytosis after Liver Transplantation: A Case Report and Literature Review

Hemophagocytic lymphohistiocytosis (HLH) is a rare but potentially fatal hyperinflammatory disorder characterized by dysfunctional cytotoxic T and natural killer cells. Liver transplantation is a predisposing factor for HLH. High mortality rates were reported in 40 cases of HLH following liver transplantation in adults and children. Herein, we describe a case of adult HLH triggered by cytomegalovirus (CMV) infection shortly after liver transplantation. The patient was successfully treated with ruxolitinib combined with a modified HLH-2004 treatment strategy. Our case is the first to report the successful use of ruxolitinib with a modified HLH-2004 strategy to treat HLH in a solid organ transplantation recipient.

Retrospective Review of ART Regimens in HIV-Positive to HIV-Positive Kidney Transplant Recipients

Introduction

The management of complex interactions between antiretroviral therapy (ART) and calcineurin inhibitor (CNI) immunosuppression regimens in HIV-positive to HIV-positive renal transplant recipients can be challenging. Literature describing ART regimens and indications for regimen switching in these patients is limited.

Methods

This retrospective review included 53 HIV-positive to HIV-positive renal transplant recipients. Data on ART regimens, reasons for ART switching, and timing of switches were described from day of transplant to study endpoint (end of study date, death, or graft failure). The association between rejection and ART regimen (protease inhibitor [PI] -based vs. non-PI-based regimen) was analyzed using negative binomial regression.

Results

There were a total of 46 switches in 31 of 53 patients (58%). Protocol switches (n = 17 of 46, 37%) accounted for most switches, of which the majority were from non-nucleoside reverse transcriptase inhibitors (NNRTIs) to PIs. Other common reasons for switching include cytochrome P450 enzyme induction from efavirenz (EFV) (9 of 46, 20%), tenofovir disoproxil fumarate (TDF) nephrotoxicity (8 of 46, 17%) or side effects (6 of 46, 13%). Of the 46 switches, nearly half (n = 21, 46%) occurred during the transplant admission period, and approximately two-thirds (n = 28, 62%) were during the first year post-transplantation. There was an association between rejection and being maintained on a PI-based regimen (incidence rate ratio 2.77 (95% confidence interval 1.03-7.48), P = 0.044).

Conclusion

Despite frequent switching of ART regimens, HIV viral loads remained supressed and graft function remained stable in most HIV-positive kidney transplant recipients in our cohort. There was however a concerning signal for increased rejection rates in those on a PI-based regimen.

Signal of safety due to adverse drug reactions induced by tacrolimus with or without azithromycin

INTRODUCTION

We identified two reports of drug levels increased and acute kidney injury caused by the drug-drug interaction between azithromycin (AZM) and tacrolimus (TAC). However, it is unclear whether the combined of these two drugs causes additive or synergistic adverse drug reactions. Therefore, we evaluated the disproportionality in reporting drug level increased and acute kidney injury for these two drugs are used alone and in combination with each other.

METHOD

Data from the U.S. Food and Drug Administration's Adverse Event Reporting System from 1974 to Q3/2021 were used. Reports based on exposure to macrolide antibiotic alone, TAC alone, and each macrolide antibiotic + TAC were extracted. Proportional Reporting Ratios (PRR) and 95% confidence intervals (CI) were calculated, and a lower limit of the 95% CI (Lower95CI) value of 2.0 or higher was interpreted as a signal of safety.

RESULTS

Lower95CIs for macrolide antibiotic alone and TAC showed no potential signals of safety, including drug level increased, acute kidney injury, and control event. The PRRs and 95% CI for drug level increased was 3.27 (2.69-3.97) with AZM + TAC, and 10.81 (9.59-12.17) for clarithromycin (CAM) + TAC. For CAM + TAC, the PRR and 95% CI was 8.42 (7.51-9.44) in acute kidney injury. However, AZM + TAC was not associated with a signal of safety in acute kidney injury.

CONCLUSIONS

This suggests that AZM + TAC has a low risk of causing acute kidney injury but may cause drug level increased. This article is protected by copyright. All rights reserved.

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

Background and Objective

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

Methods

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

Results

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

Conclusions

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

Electronic supplementary material

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

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.

Therapeutic drug monitoring of immunosuppressive drugs in hepatology and gastroenterology

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

CYP3A5*3 polymorphism and age affect tacrolimus blood trough concentration in myasthenia gravis patients

The study aims to identify clinical factors affecting tacrolimus blood trough concentration (C0) in myasthenia gravis (MG) patients and to optimize the initial dose of tacrolimus in MG treatment. A total of 103 MG patients participated in this study, and their clinical factors, medication regimens, C0 values and CYP3A5*3 polymorphisms were collected in detail. We used a linear mixed model to analyze the effect of multiple factors on the dosage-weighted C0 (C0:D) and performed subgroup analyses to investigate the consistency of correlations between influencing factors and the C0:D ratios. Among all factors, CYP3A5*3 polymorphism and age showed a strong positive correlation with C0:D ratios. The C0:D ratios (ng/ml·mg^-1) were higher for CYP3A5*3/*3 than for CYP3A5*1 (mean difference: 1.038, 95% confidence interval [CI]: 0.820-1.256, P-value <0.001), and for age in the range of 45-64 and ≥ 65 years than for age < 45 years (mean difference [95% CI] and P-value: 0.531[0.257-0.805] and P-value <0.001, 0.703 [0.377-1.029] and P-value <0.001, respectively). The C0:D ratios were not related to corticosteroid dosage, body weight, sex, hematocrit or the concomitant use of calcium channel blockers. The consistencies of the correlations between C0:D ratios and CYP3A5*3 polymorphism or age were confirmed by subgroup analyses. Thus, CYP3A5*3 polymorphism and age should be considered in optimizing the initial dose of tacrolimus for MG treatment.

Effects of antifungal drugs on the plasma concentrations and dosage of tacrolimus in kidney transplant patients

OBJECTIVES

Tacrolimus is one of the three basic immunosuppressants used following kidney transplantation, and its plasma concentration is susceptible to antifungal drugs. Abnormal tacrolimus concentrations may lead to adverse outcomes for patients. Adjustment of the tacrolimus dose after administering antifungal drugs to patients with fungal infection after transplantations therefore has important clinical significance. Our objective is to measure the impact of antifungal drugs on the plasma concentration of tacrolimus in kidney transplant patients.

METHODS

A retrospective study was carried out in 109 kidney transplant recipients treated with a tacrolimus-based regimen and antifungal drugs simultaneously. Tacrolimus levels and dosage requirements were compared before and during antifungal therapy.

RESULTS

The plasma levels of tacrolimus were significantly increased after the combination with voriconazole and fluconazole (p<0.05). Consequently, the daily dose of tacrolimus was significantly reduced after the combination (p<0.05). However, although the tacrolimus concentration was significantly decreased after the administration of caspofungin (p<0.05), no apparent change in the daily dose of tacrolimus was found. Moreover, there were no significant changes in the tacrolimus levels and the daily dose after the combination with micafungin (p>0.05).

CONCLUSIONS

Our results suggest that there is considerable variability in the interaction between tacrolimus and different antifungal drugs. The dose of tacrolimus should be reduced by two-thirds and one-third before the combination with voriconazole and fluconazole, respectively. It is not recommended that the dose should be adjusted before combination with other antifungal drugs, and the dose should be adjusted under the guidance of therapeutic drug monitoring.

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.

Immunologic Risk Assessment and Approach to Immunosuppression Regimen in Kidney Transplantation

The outcomes of kidney transplantation show a steady improvement with an increasing number of transplantations and decreasing incidence of acute rejection episodes. Successful transplantation begins with a comprehensive immunologic risk assessment and judicious choice of therapeutic agents. In this review, we discuss the trends in transplant immunosuppression practices and outcomes in the United States. We discuss practical testing algorithms for clinical decision making in induction therapy and fine-tuning maintenance immunosuppression. We introduce assessment tools for immune monitoring after transplantation and speculate on future directions in management.

Late intra-patient tacrolimus trough level variability as a major problem in kidney transplantation: A Collaborative Transplant Study Report

Intra-patient variability (IPV) of tacrolimus trough level has been associated with poor outcome after kidney transplantation. These findings were derived from single-center analyses and restricted mainly to measurements early after transplantation. We analyzed in a multicenter effort whether high IPV of tacrolimus levels at posttransplant years 1, 2, and 3 was associated with impaired clinical outcome. More than 6600 patients who received a deceased donor kidney transplant during 2000-2014 and had a functioning graft for >3 years were studied. Graft survival was significantly impaired with increasing IPV (P < 0.001). As compared to patients with a low IPV of <30%, the risk of graft loss during years 4-6 increased 32% in patients with an IPV of 30% to 44% and 66% in patients with an IPV of ≥45% (P = 0.002 and P < 0.001). About one-third of patients showed an IPV of ≥30% with substantially impaired outcome. Even in patients with good outcome during the first 3 posttransplant years, a high IPV was associated with inferior graft survival. Our data indicate that a fluctuating tacrolimus trough level at years 1, 2, and 3 posttransplant is a major problem in kidney transplantation.

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

Background

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

Objectives

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

Methods

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

Results

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

Conclusion

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

Assessment of tacrolimus intrapatient variability in stable adherent transplant recipients: Establishing baseline values

The purpose of this study was to determine the intrapatient (within the same patient) variability of tacrolimus in adherent patients. Daily tacrolimus trough levels were obtained at home using dried blood spot technology in kidney and liver transplant recipients. Patients were randomized to receive 3 formulations of tacrolimus, each for two 1-week periods. Adherence was monitored by patient diary, pill counts, and use of the Medication Event Monitoring System (MEMS). Variability was quantified as the coefficient of variation (CV). Comparison of CV between groups was by independent t test or one-way ANOVA as appropriate. The population was found to be adherent with a rate of 99.9% with a mean interval between the evening and morning dose of tacrolimus of 11.86 hours. The median CV for the entire population was 15.2% (range 4.8%-110%). There were no differences in CV by allograft type or tacrolimus formulation. The multivariate analysis did not identify any demographic characteristics associated with a CV > 30%. In a highly adherent population, tacrolimus did not display high intrapatient variability. Given the association between IPV and poor allograft outcomes, future studies are needed to quantitate the influence of adherence and establish target IPV goals.

The Effect of Tanreqing Injection on the Pharmacokinetics of Sirolimus in Rats

To evaluate the effect of Tanreqing injection on the pharmacokinetics of sirolimus in rats, a high performance liquid chromatography tandem mass spectrometry method was developed for sirolimus assay in whole blood. Calibration curve of sirolimus was acquired over a concentration ranging from 2.5 to 100 ng/mL with r²= 0.9955. The matrix effects and extraction recoveries of sirolimus ranged from 144% to 152% and from 80% to 96%, respectively. The inter- and intraday relative standard deviations were both <10%. The stability investigation showed that the blood samples were stable for 30-day-storage at −20°C, for 8 h storage at room temperature, for 24 h storage in the auto-sampler at 4°C, and for three freeze-thaw cycle process. The pharmacokinetic results demonstrated that the C_max, AUC, and AUMC of sirolimus in rats (7.5 mg/kg, i.g.) were increased after beincoadministration with Tanreqing Injection at 2.5, 5.0, and 7.5 mL/kg (i.v.), respectively, or at 5 min, 2 h, and 4 h (5.0 mL/kg, i.v.) after SRL dosing, respectively. For the first time, the results proved the herb-drug interaction between Tanreqing Injection and sirolimus and accordingly suggested avoiding concurrent reception of those two drugs for patients.

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

Aims

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

Methods

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

Results

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

Conclusions

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

The level of intracellular tacrolimus in T cell is affected by CD44+ABCB1+activities triggered by inflammation

Rejection is an important issue in kidney transplant. Although with adequate trough level of tacrolimus, acute rejection occurs, and we are focused on these cases. We hypothesized that the lower concentration of tacrolimus in the peripheral blood mononuclear cell would be a cause of rejection; in this regard, we describe ABCB1, which regulates intracellular concentration of tacrolimus. The effect of inflammation on the intracellular concentration of tacrolimus was evaluated, as was the association between that concentration and ABCB1 and CD44 activities. Seven kidney recipients experiencing acute rejection were prospectively enrolled. Both the whole blood concentration of tacrolimus and intracellular concentration of tacrolimus were measured at the time of enrollment and after stabilization. A human T lymphoblastoid cell line (Jurkat T cell) was treated with various concentrations of tacrolimus for 21 h and then stimulated for 3 h. The levels of mRNA interleukin-2, interleukin-8, and interferon-γ decreased dose dependently by tacrolimus. Furthermore, a fluorescence-activated cell sorter was used to count cells expressing CD44 and ABCB1; changes in intracellular concentration of tacrolimus were explored after tacrolimus treatment and stimulation. Also, B6 splenocytes were tested in the same manner as previous Jurkat T cell experiments. The tacrolimus ratio of three patients was lower at the time of acute rejection than when patients were stabilized. In vitro, the intracellular concentration of tacrolimus decreased after stimulation. Under the same conditions, CD44+ABCB1+cells increased in proportion on tacrolimus treatment and stimulation. This work supports the hypothesis that inflammation reduces the intracellular tacrolimus level, possibly via drug efflux mediated by CD44+ABCB1+and inflammation could lead to acute rejection.

Immunosuppressants in Organ Transplantation

The goal of immunosuppressive therapy post-transplantation in pediatric renal transplant recipients is to prevent acute and chronic rejection while minimizing drug side effects. Most therapies alter immune response mechanisms but are not immunologically specific, and a careful balance is required to find the dose that prevents rejection of the graft while minimizing the risks of overimmunosuppression leading to infection and cancer. While this chapter because of space constraints focuses on immunosuppressive therapy in pediatric renal transplant recipients, many aspects can be applied on pediatric recipients of other solid organ transplants such as the liver and heart. The major maintenance immunosuppressive agents currently used in various combination regimens are tacrolimus, cyclosporine, mycophenolate mofetil, azathioprine, everolimus, sirolimus, and glucocorticoids (steroids). Although data from adult renal transplantation trials are used to help guide management decisions in pediatric patients, immunosuppressive therapy in pediatric renal transplant recipients often must be modified because of the unique dosage requirements and clinical effects of these agents in children, including their impact on growth and development. The optimal immunosuppressive therapy post-transplant is not established. The goal remains to find the best combination of immunosuppressive agents that optimizes allograft survival by preventing acute rejection while limiting drug toxicities.

Clinical aspects of tacrolimus use in paediatric renal transplant recipients

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

Immunosuppression following organ transplantation. Part 1: mechanisms and immunosuppressive agents

Solid organ transplantation has revolutionised medical care by providing a definitive cure for a wide spectrum of end-stage medical conditions. This treatment, however, does not come without complications and poses the risks of rejection, life-threatening infection, malignancies and recurrent organ failure, with significant impacts on patient outcomes. One of the major challenges involved in optimising post-transplant outcomes is managing the immune system's response to the transplanted graft and preventing organ rejection. This is mainly accomplished through the use of immunosuppressant agents, which have become a mainstay of treatment for a majority of post-transplant patients. This article, the first of two parts, discusses the concept of immunosuppression and its importance in the care of patients who have received an organ transplant. It focuses on the pathophysiologic mechanisms involved in transplant rejection and discusses the pharmacologic aspects of immunosuppression and its implications for patient care.

High tacrolimus intra-patient variability is associated with graft rejection, and de novo donor-specific antibodies occurrence after liver transplantation

AIM

To investigate the role of tacrolimus intra-patient variability (IPV) in adult liver-transplant recipients.

METHODS

We retrospectively assessed tacrolimus variability in a cohort of liver-transplant recipients and analyzed its effect on the occurrence of graft rejection and de novo donor-specific antibodies (dnDSAs), as well as graft survival during the first 2 years posttransplantation. Between 02/08 and 06/2015, 116 patients that received tacrolimus plus mycophenolate mofetil (with or without steroids) were included.

RESULTS

Twenty-two patients (18.5%) experienced at least one acute-rejection episode (BPAR). Predictive factors for a BPAR were a tacrolimus IPV of > 35% [OR = 3.07 95%CI (1.14-8.24), P = 0.03] or > 40% [OR = 4.16 (1.38-12.50), P = 0.01), and a tacrolimus trough level of < 5 ng/mL [OR=3.68 (1.3-10.4), P =0.014]. Thirteen patients (11.2%) developed at least one dnDSA during the follow-up. Tacrolimus IPV [coded as a continuous variable: OR = 1.1, 95%CI (1.0-1.12), P = 0.006] of > 35% [OR = 4.83, 95%CI (1.39-16.72), P = 0.01] and > 40% [OR = 9.73, 95%CI (2.65-35.76), P = 0.001] were identified as predictors to detect dnDSAs. IPV did not impact on patient- or graft-survival rates during the follow-up.

CONCLUSION

Tacrolimus-IPV could be a useful tool to identify patients with a greater risk of graft rejection and of developing a de novo DSA after liver transplantation

Long-term efficacy and safety of add-on tacrolimus for persistent, active rheumatoid arthritis despite treatment with methotrexate and tumor necrosis factor inhibitors

AIM

To assess the long-term efficacy and safety of adding tacrolimus for patients with active rheumatoid arthritis (RA) despite anti-tumor necrosis factor (TNF) therapy with methotrexate.

METHODS

Consecutive patients who were treated with adding tacrolimus onto anti-TNF therapy with methotrexate for active RA despite anti-TNF therapy with methotrexate, were retrospectively analyzed in terms of treatment response, achieving remission, subsequent treatment tapering and adverse events.

RESULTS

Fifteen patients could be analyzed. Median symptom duration was 2.9 years and prior duration of anti-TNF therapy was 40 weeks. Median value of Disease Activity Score in 28 joints was 4.6. Five, eight and two were on infliximab, etanercept and adalimumab at the onset of tacrolimus, respectively. At 2 years, the proportions of patients achieving responses of American College of Rheumatology 50, 70 and 90, were 80%, 73% and 40%, respectively, and those achieving remission as defined by Simplified Disease Activity Index ≤ 3.3 were 67%. All patients could discontinue oral glucocorticoids and 10 had been successfully withdrawn from anti-TNF therapy for more than 1 year at the final observation.

CONCLUSION

Adding tacrolimus onto anti-TNF therapy is a promising therapeutic option with sustained benefit for refractory RA patients despite treatment with anti-TNF therapy combined with methotrexate.

The Effect of Weight and CYP3A5 Genotype on the Population Pharmacokinetics of Tacrolimus in Stable Paediatric Renal Transplant Recipients

BACKGROUND

The aim of this study was to develop a population pharmacokinetic model of tacrolimus in paediatric patients at least 1 year after renal transplantation and simulate individualised dosage regimens.

PATIENTS AND METHODS

We included 54 children with median age of 11.1 years (range 3.8-18.4 years) with 120 pharmacokinetic profiles performed over 2 to 4 h. The pharmacokinetic analysis was performed using the non-linear mixed-effects modelling software (NONMEM(®)). The impact of covariates including concomitant medications, age, the cytochrome P450 (CYP) CYP3A5*3 gene and the adenosine triphosphate binding cassette protein B1 (ABCB1) 3435 C→T gene polymorphism on tacrolimus pharmacokinetics was analysed. The final model was externally validated on an independent dataset and dosing regimens were simulated.

RESULTS

A two-compartment model adequately described tacrolimus pharmacokinetics. Apparent oral clearance (CL/F) was associated with weight (allometric scaling) but not age. Children with lower weight and CYP3A5 expressers required higher weight-normalised tacrolimus doses. CL/F was inversely associated with haematocrit (P < 0.05) and γ-glutamyl transpeptidase (γGT) (P < 0.001) and was increased by 45 % in carriers of the CYP3A5*1 allele (P < 0.001). CL/F was not associated with concomitant medications. Dose simulations show that a daily tacrolimus dose of 0.2 mg/kg generates a pre-dose concentration (C 0) ranging from 5 to 10 µg/L depending on the weight and CYP3A5 polymorphism. The median area under the plasma concentration-time curve (AUC) corresponding with a tacrolimus C 0 of 4-8 µg/L was 97 h·µg/L (interquartile range 80-120).

CONCLUSIONS

In patients beyond the first year after transplantation, there is a cumulative effect of CYP3A5*1 polymorphism and weight on the tacrolimus C 0. Children with lower weight and carriers of the CYP3A5*1 allele have higher weight-normalised tacrolimus dose requirements.