Pharmacokinetics of tacrolimus in liver transplant patients

Getting Tacrolimus Dosing Right

ABSTRACT

Tacrolimus (TAC) dosing is typically guided by the trough concentration (C0). Yet, significant relationships between TAC C0 and clinical outcomes have seldom been reported or only with adverse events. Large retrospective studies found a moderate correlation between TAC C0 and the area under the curve (AUC), where, for any given C0 value, the AUC varied 3- to 4-fold between patients (and vice versa). However, no randomized controlled trial evaluating the dose adjustment based on TAC AUC has been conducted yet. A few observational studies have shown that the AUC is associated with efficacy and, to a lesser extent, adverse effects. Other studies showed the feasibility of reaching predefined target ranges and reducing underexposure and overexposure. TAC AUC0-12 h is now most often assessed using Bayesian estimation, but machine learning is a promising approach. Microsampling devices are well accepted by patients and represent a valuable alternative to venous blood sample collection during hospital visits, especially when a limited sampling strategy is required. As AUC monitoring cannot be proposed very frequently, C0 monitoring has to be used in the interim, which has led to fluctuating doses in patients with an AUC/C0 ratio far from the population mean, because of different dose recommendations between the 2 biomarkers. We proposed estimating the individual AUC/C0 ratio and derived individual C0 targets to be used in between or as a replacement for AUC monitoring. Existing technology and evidence are now sufficient to propose AUC monitoring interspersed with individualized-C0 monitoring for all patients with kidney transplants while collecting real-world data to strengthen the evidence.

Effect of early post-hematopoietic stem cell transplant tacrolimus concentration on transplant outcomes in pediatric recipients: One facility's ten-year experience of immunosuppression with tacrolimus

Acute graft-versus-host disease (GVHD) is a common life-threatening complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT), ranking as the second leading cause of death among recipients, surpassed only by disease relapse. Tacrolimus is commonly used for GVHD prophylaxis, but achieving therapeutic blood levels is challenging, particularly in pediatrics, due to the narrow therapeutic window and the high interindividual variability. The retrospective study conducted at IRCCS "Burlo Garofolo" in Italy aimed to assess the impact of early post-HSCT tacrolimus levels on transplant-related outcomes in pediatric recipients. The population pharmacokinetic model (POP/PK) was set up to describe tacrolimus pharmacokinetics. Elevated tacrolimus (>12-15 ng/ml) levels within the initial weeks post-HSCT are associated with reduced post-transplant infections (p < 0.0001) and decreased incidence of early transplant-related events (p < 0.01), including a lower incidence of acute GVHD (p < 0.05 on day 0). High tacrolimus exposure can lead to an increased risk of chronic GVHD (p < 0.0001) and reduced overall survival (p < 0.01). Personalized dosing and therapeutic monitoring of tacrolimus are crucial to ensure optimal outcomes. POP/PK could help achieve this goal, giving us a model by which we can balance immunosuppression while looking at the patient's general well-being and providing the necessary treatment.

A joint population pharmacokinetic model to assess the high variability of whole-blood and intracellular tacrolimus in early adult renal transplant recipients

Tacrolimus (TAC) has high pharmacokinetic (PK) variability during the early transplantation period. The relationships between whole-blood and intracellular TAC concentrations and clinical outcomes remain controversial. This study identifies the factors affecting the PK variability of TAC and characterizes the relationships between whole-blood and intracellular TAC concentrations. Data regarding whole-blood TAC concentrations of 1,787 samples from 215 renal transplant recipients (<90 days postoperative) across two centers and intracellular TAC concentrations (648 samples) digitized from previous studies were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were screened, and the distribution of whole-blood to intracellular TAC concentration ratios (RWB:IC) was estimated. The final model was evaluated using bootstrap, goodness of fit, and prediction-corrected visual predictive checks. The optimal dosing regimens and target ranges for each type of immune cell subsets were determined using Monte Carlo simulations. A two-compartment model adequately described the data, and the estimated mean TAC CL/F was 23.6 L·h-1 (relative standard error: 11.5 %). The hematocrit level, CYP3A5*3 carrier status, co-administration with Wuzhi capsules, and tapering prednisolone dose may contribute to the high variability of TAC PK variability during the early post-transplant period. The estimated RWB:IC of all TAC concentrations in peripheral blood mononuclear cells (PBMCs) was 4940, and inter-center variability of PBMCs was observed. The simulated TAC target range in PBMCs was 20.2-85.9 pg·million cells-1. Inter-center variability in intracellular concentrations should be taken into account in further analyses. TAC dosage adjustments can be guided based on PK/PD variability and simulated intracellular concentrations.

Tacrolimus-associated neurotoxicity isolated to the brainstem: two illustrative cases and a systematic review of the literature

INTRODUCTION

Tacrolimus-associated neurotoxicity (TAN) manifests with wide clinical spectrum, ranging from mild tremors to severe encephalopathy. The isolated involvement of the brainstem is a rarely documented presentation of TAN, and its clinical and diagnostic characteristics are unclear.

METHODS

We report two cases of brainstem-isolated TAN (bi-TAN). Moreover, we performed a systematic review of the literature on bi-TAN and extracted data concerning demographics, clinical characteristics, radiological features, and management. The systematic literature search followed PRISMA guidelines and a pre-defined protocol.

RESULTS

Eleven patients, including our two, were identified (mean age: 41.3 years, ± 18.8; five males, 45%). Speech disturbance was the most common clinical presentation (45%). The mean latency from Tacrolimus initiation to bi-TAN onset was 26 days (± 30.8). Tacrolimus serum level tested above the reference range in three patients (mean: 26.83 ± 5.48). Brain MRI showed T2-FLAIR hyperintensities; three showed restricted diffusion on ADC maps. Neurological symptoms resolved completely in seven patients (63%) after Tacrolimus withdrawal or dose reduction.

CONCLUSIONS

Our findings suggest that bi-TAN could represent a brainstem variant of posterior reversible encephalopathy syndrome. Recognition of bi-TAN as a potential cause of isolated brainstem lesions is crucial to disentangle the diagnostic work-up and ensure prompt withdrawal or reduction of the offending agent.

Determining Plasma Tacrolimus Concentrations Using High-Performance LC-MS/MS in Renal Transplant Recipients

BACKGROUND

Whole-blood therapeutic drug monitoring of tacrolimus is conducted to maintain tacrolimus concentrations within a safe and effective range. Changes in hematocrit cause variability in blood concentrations of tacrolimus because it is highly bound to erythrocytes. Measuring plasma concentrations may eliminate this variability; however, current methods have limitations owing to the use of cross-reactive immunoassays, plasma separation at nonbiological temperatures, and lack of clinical validation. This study aimed to develop and validate a clinically applicable method to measure plasma tacrolimus concentrations in renal transplant recipients and to examine the concentration differences between genotypic CYP3A5 expressors and nonexpressors.

METHODS

Plasma tacrolimus concentrations were measured in 9 stable renal transplant recipients who were genotypic CYP3A5 expressors or nonexpressors. Tacrolimus was extracted from plasma using solid-phase extraction, and liquid chromatography-tandem mass spectrometry was used for detection and quantitation.

RESULTS

This assay was sensitive, selective, and linear between 100 and 5000 ng/L, with intraassay and interassay imprecision and inaccuracy <10% and <5% respectively. The extraction recovery of tacrolimus and ascomycin was 74%. Matrix ion suppression effects were 31.5% and 35% with overall recovery of 50.6% and 48.3% for tacrolimus and ascomycin, respectively. Whole-blood concentrations accounted for approximately 46% of the variation in plasma concentrations in CYP3A5 expressors and nonexpressors. No difference in dose-adjusted whole-blood and plasma concentrations was observed between CYP3A5 expressors and nonexpressors.

CONCLUSIONS

This assay is clinically applicable with excellent performance and demonstrated that tacrolimus plasma concentrations highly correlated with whole-blood concentrations.

Nirmatrelvir/ritonavir-induced elevation of blood tacrolimus levels in a patient in the maintenance phase post liver transplantation

Nirmatrelvir is an orally administered anti-SARS-CoV-2 drug used in combination with ritonavir, the drug-metabolizing cytochrome P450 (CYP) 3A inhibitor, to evade metabolism and extend bioavailability. Meanwhile, the immunosuppressant tacrolimus is a CYP3A4/5 substrate, and CYP3A inhibition results in drug-drug interactions. Herein, we report the case of a coronavirus disease 19 (COVID-19) patient in the maintenance phase post liver transplantation, receiving tacrolimus treatment, with a marked increase of blood tacrolimus levels after the initiation of concomitant nirmatrelvir/ritonavir treatment. A 61-year-old Japanese woman underwent a living donor liver transplant for Caroli disease 25 years ago and received tacrolimus 2 mg/day for immunosuppressive treatment. Three days before the observed high tacrolimus blood concentration, she presented to our emergency department with a fever and was diagnosed with COVID-19. She was prescribed an adjusted dose of nirmatrelvir/ritonavir (150 mg/100 mg, twice daily) for 5 days as a high-risk case with immunosuppressive treatment and reduced renal function (estimated glomerular filtration rate, eGFR: 46.6 mL/min/1.73 m2). At the return visit on day 1, blood tacrolimus level was >60 ng/mL on trough sampling, above the upper limit of measurement, with nausea and vomiting as side effects. Tacrolimus treatment was discontinued on the same day. Drug-drug interactions resulting from CYP3A inhibition by nirmatrelvir/ritonavir were deemed responsible for elevated blood tacrolimus levels. Therefore, in liver transplant recipients, tacrolimus dose reduction or discontinuation is required during COVID-19 treatment with nirmatrelvir/ritonavir.

Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease

BACKGROUND

Routine therapeutic drug monitoring (TDM) relies heavily on measuring trough drug concentrations. Trough concentrations are affected not only by drug bioavailability and clearance, but also by various patient and disease factors and the volume of distribution. This often makes interpreting differences in drug exposure from trough data challenging. This study aimed to combine the advantages of top-down analysis of therapeutic drug monitoring data with bottom-up physiologically-based pharmacokinetic (PBPK) modeling to investigate the effect of declining renal function in chronic kidney disease (CKD) on the nonrenal intrinsic metabolic clearance ( CLint ) of tacrolimus as a case example.

METHODS

Data on biochemistry, demographics, and kidney function, along with 1167 tacrolimus trough concentrations for 40 renal transplant patients, were collected from the Salford Royal Hospital's database. A reduced PBPK model was developed to estimate CLint for each patient. Personalized unbound fractions, blood-to-plasma ratios, and drug affinities for various tissues were used as priors to estimate the apparent volume of distribution. Kidney function based on the estimated glomerular filtration rate ( eGFR ) was assessed as a covariate for CLint using the stochastic approximation of expectation and maximization method.

RESULTS

At baseline, the median (interquartile range) eGFR was 45 (34.5-55.5) mL/min/1.73 m 2 . A significant but weak correlation was observed between tacrolimus CLint and eGFR (r = 0.2, P < 0.001). The CLint declined gradually (up to 36%) with CKD progression. Tacrolimus CLint did not differ significantly between stable and failing transplant patients.

CONCLUSIONS

Kidney function deterioration in CKD can affect nonrenal CLint for drugs that undergo extensive hepatic metabolism, such as tacrolimus, with critical implications in clinical practice. This study demonstrates the advantages of combining prior system information (via PBPK) to investigate covariate effects in sparse real-world datasets.

A Physiologically Based Pharmacokinetic Approach to Recommend an Individual Dose of Tacrolimus in Adult Heart Transplant Recipients

Tacrolimus is the principal immunosuppressive drug which is administered after heart transplantation. Managing tacrolimus therapy is challenging due to a narrow therapeutic index and wide pharmacokinetic (PK) variability. We aimed to establish a physiologically based pharmacokinetic (PBPK) model of tacrolimus in adult heart transplant recipients to optimize dose regimens in clinical practice. A 15-compartment full-PBPK model (Simbiology® Simulator, version 5.8.2) was developed using clinical observations from 115 heart transplant recipients. This study detected 20 genotypes associated with tacrolimus metabolism. CYP3A5*3 (rs776746), CYP3A4*18B (rs2242480), and IL-10 G-1082A (rs1800896) were identified as significant genetic covariates in tacrolimus pharmacokinetics. The PBPK model was evaluated using goodness-of-fit (GOF) and external evaluation. The predicted peak blood concentration (Cmax) and area under the drug concentration-time curve (AUC) were all within a two-fold value of the observations (fold error of 0.68-1.22 for Cmax and 0.72-1.16 for AUC). The patients with the CYP3A5*3/*3 genotype had a 1.60-fold increase in predicted AUC compared to the patients with the CYP3A5*1 allele, and the ratio of the AUC with voriconazole to alone was 5.80 when using the PBPK model. Based on the simulation results, the tacrolimus dosing regimen after heart transplantation was optimized. This is the first PBPK model used to predict the PK of tacrolimus in adult heart transplant recipients, and it can serve as a starting point for research on immunosuppressive drug therapy in heart transplant patients.

A Reversibly Thermoresponsive, Theranostic Nanoemulgel for Tacrolimus Delivery to Activated Macrophages: Formulation and In Vitro Validation

Despite long-term immunosuppression, organ transplant recipients face the risk of immune rejection and graft loss. Tacrolimus (TAC, FK506, Prograf®) is an FDA-approved keystone immunosuppressant for preventing transplant rejection. However, it undergoes extensive first-pass metabolism and has a narrow therapeutic window, which leads to erratic bioavailability and toxicity. Local delivery of TAC directly into the graft, instead of systemic delivery, can improve safety, efficacy, and tolerability. Macrophages have emerged as promising therapeutic targets as their increased levels correlate with an increased risk of organ rejection and a poor prognosis post-transplantation. Here, we present a locally injectable drug delivery platform for macrophages, where TAC is incorporated into a colloidally stable nanoemulsion and then formulated as a reversibly thermoresponsive, pluronic-based nanoemulgel (NEG). This novel formulation is designed to undergo a sol-to-gel transition at physiological temperature to sustain TAC release in situ at the site of local application. We also show that TAC-NEG mitigates the release of proinflammatory cytokines and nitric oxide from lipopolysaccharide (LPS)-activated macrophages. To the best of our knowledge, this is the first TAC-loaded nanoemulgel with demonstrated anti-inflammatory effects on macrophages in vitro.

Investigating Tacrolimus Disposition in Paediatric Patients with a Physiologically Based Pharmacokinetic Model Incorporating CYP3A4 Ontogeny, Mechanistic Absorption and Red Blood Cell Binding

Tacrolimus is a crucial immunosuppressant for organ transplant patients, requiring therapeutic drug monitoring due to its variable exposure after oral intake. Physiologically based pharmacokinetic (PBPK) modelling has provided insights into tacrolimus disposition in adults but has limited application in paediatrics. This study investigated age dependency in tacrolimus exposure at the levels of absorption, metabolism, and distribution. Based on the literature data, a PBPK model was developed to predict tacrolimus exposure in adults after intravenous and oral administration. This model was then extrapolated to the paediatric population, using a unique reference dataset of kidney transplant patients. Selecting adequate ontogeny profiles for hepatic and intestinal CYP3A4 appeared critical to using the model in children. The best model performance was achieved by using the Upreti ontogeny in both the liver and intestines. To mechanistically evaluate the impact of absorption on tacrolimus exposure, biorelevant in vitro solubility and dissolution data were obtained. A relatively fast and complete release of tacrolimus from its amorphous formulation was observed when mimicking adult or paediatric dissolution conditions (dose, fluid volume). In both the adult and paediatric PBPK models, the in vitro dissolution profiles could be adequately substituted by diffusion-layer-based dissolution modelling. At the level of distribution, sensitivity analysis suggested that differences in blood plasma partitioning of tacrolimus may contribute to the variability in exposure in paediatric patients.

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.

Tacrolimus 4-hour monitoring in liver transplant patients is non-inferior to trough monitoring: The randomized controlled FK04 trial

BACKGROUND

After liver transplantation (LT), tacrolimus and ciclosporin treatment can lead to, partially concentration-dependent, chronic kidney disease. Monitoring ciclosporin with two-hour levels reduced overexposure and led to better renal function than trough-monitoring (C0). For tacrolimus, a 4-hour level (C4) can give a reasonable approximation of total drug exposure. We evaluated whether monitoring tacrolimus in stable patients after LT by C4 was superior to C0 regarding renal function, rejection and metabolic parameters.

METHODS

This open label randomized controlled trial compared C4 monitoring of tacrolimus BID (Prograft) to trough (C0) monitoring in stable LT recipients. The target range for C4 of 7.8-16 ng/ml was calculated to be comparable with target C0 of 4-8 ng/ml. Primary endpoint was the effect on renal function and secondary endpoints were the occurrence of treated biopsy-proven acute rejection, blood pressure and metabolic parameters, during 3 months of follow-up.

RESULTS

Fifty patients were randomized to C0 (n = 25) or C4 (n = 25) monitoring. There was no difference in renal function between the C0 and the C4 group (p = .98 and p = .13 for CG and MDRD at 3 months). Also, the amount of proteinuria was similar (p = .59). None of the patients suffered from graft loss or was treated for rejection. Metabolic parameters did not differ between the two groups.

CONCLUSION

Tacrolimus 4-hour monitoring in stable LT patients is not superior to trough monitoring, regarding the effect on renal function, but is safe for use to facilitate tacrolimus monitoring in an afternoon outpatient clinic.

Prospective population pharmacokinetic study of tacrolimus in adult recipients early after liver transplantation: A comparison of Michaelis-Menten and theory-based pharmacokinetic models

Background and Objective: Tacrolimus, a calcineurin inhibitor widely used as a potent immunosuppressant to prevent graft rejection, exhibits nonlinear kinetics in patients with kidney transplantation and nephrotic syndrome. However, whether nonlinear drug metabolism occurs in adult patients undergoing liver transplantation remains unclear, as do the main underlying mechanisms. Therefore, here we aimed to further confirm the characteristics of nonlinearity through a large sample size, and determine the potential influence of nonlinearity and its possible mechanisms.

Methods: In total, 906 trough concentrations from 176 adult patients (150 men/26 women; average age: 50.68 ± 9.71 years, average weight: 64.54 ± 11.85 kg after first liver transplantation) were included in this study. Population pharmacokinetic analysis was performed using NONMEM®. Two modeling strategies, theory-based linear compartmental and nonlinear Michaelis–Menten (MM) models, were evaluated and compared. Potential covariates were screened using a stepwise approach. Bootstrap, prediction-, and simulation-based diagnostics (prediction-corrected visual predictive checks) were performed to determine model stability and predictive performance. Finally, Monte Carlo simulations based on the superior model were conducted to design dosing regimens.

Results: Postoperative days (POD), Aspartate aminotransferase (AST), daily tacrolimus dose, triazole antifungal agent (TAF) co-therapy, and recipient CYP3A5*3 genotype constituted the main factors in the theory-based compartmental final model, whereas POD, Total serum bilirubin (TBIL), Haematocrit (HCT), TAF co-therapy, and recipient CYP3A5*3 genotype were important in the nonlinear MM model. The theory-based final model exhibited 234 L h−1 apparent plasma clearance and 11,000 L plasma distribution volume. The maximum dose rate (Vmax) of the nonlinear MM model was 6.62 mg day−1; the average concentration at steady state at half-Vmax (Km) was 6.46 ng ml−1. The nonlinear MM final model was superior to the theory-based final model and used to propose dosing regimens based on simulations.

Conclusion: Our findings demonstrate that saturated tacrolimus concentration-dependent binding to erythrocytes and the influence of daily tacrolimus dose on metabolism may partly contribute to nonlinearity. Further investigation is needed is need to explore the causes of nonlinear pharmacokinetic of tacrolimus. The nonlinear MM model can provide reliable support for tacrolimus dosing optimization and adjustment in adult patients undergoing liver transplantation.

Use of Pharmacogenetics to Optimize Immunosuppressant Therapy in Kidney-Transplanted Patients

Immunosuppressant drugs (ISDs) are routinely used in clinical practice to maintain organ transplant survival. However, these drugs are characterized by a restricted therapeutic index, a high inter- and intra-individual pharmacokinetic variability, and a series of severe adverse effects. In particular, genetic factors have been estimated to play a role in this variability because of polymorphisms regarding genes encoding for enzymes and transporters involved in the ISDs pharmacokinetic. Several studies showed important correlations between genetic polymorphisms and ISDs blood levels in transplanted patients; therefore, this review aims to summarize the pharmacogenetics of approved ISDs. We used PubMed database to search papers on pharmacogenetics of ISDs in adults or pediatric patients of any gender and ethnicity receiving immunosuppressive therapy after kidney transplantation. We utilized as search term: “cyclosporine or tacrolimus or mycophenolic acid or sirolimus or everolimus and polymorphism and transplant”. Our data showed that polymorphisms in CYP3A5, CYP3A4, ABCB1, and UGT1A9 genes could modify the pharmacokinetics of immunosuppressants, suggesting that patient genotyping could be a helpful strategy to select the ideal ISDs dose for each patient.

Population Pharmacokinetics and Initial Dosage Optimization of Tacrolimus in Pediatric Hematopoietic Stem Cell Transplant Patients

Background: There is a substantial lack of tacrolimus pharmacokinetic information in pediatric hematopoietic stem cell transplant (HSCT) patients. This study aimed to develop population pharmacokinetics (PopPK) of tacrolimus in pediatric HSCT patients and to devise model-guided dosage regimens. Methods: A retrospective analysis was performed on 86 pediatric HSCT patients who received tacrolimus intravenously or orally. A total of 578 tacrolimus trough concentrations (C₀) were available for pharmacokinetic analysis using a non-linear mixed-effects modeling method. Demographic and clinical data were included and assessed as covariates via the stepwise method. Bayesian estimators were used to devise pediatric dosage regimens that targeted C₀ of 5-15 ng mL^-1. Results: A one-compartment model with first-order absorption adequately described the tacrolimus pharmacokinetics. Clearance (CL), volume of distribution (V), and typical bioavailability (F) in this study were estimated to be 2.42 L h^-1 (10.84%), 79.6 L (16.51%), and 19% (13.01%), respectively. Body weight, hematocrit, post-transplantation days, and caspofungin and azoles concomitant therapy were considered significant covariates for tacrolimus CL. Hematocrit had a significant impact on the V of tacrolimus. In the subgroup cohort of children (n = 24) with CYP3A5 genotype, the clearance was 1.38-fold higher in CYP3A5 expressers than in non-expressers. Simulation indicated that the initial dosage optimation of tacrolimus for intravenous and oral administration was recommended as 0.025 and 0.1 mg kg^-1 d^-1 (q12h), respectively. Conclusion: A PopPK model for tacrolimus in pediatric HSCT patients was developed, showing good predictive performance. Model-devised dosage regimens with trough tacrolimus concentrations provide a practical strategy for achieving the therapeutic range.

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.

Predicting model‐informed precision dosing: A test‐case in tacrolimus dose adaptation for kidney transplant recipients

Before investing resources into the development of a precision dosing (model‐informed precision dosing [MIPD]) tool for tacrolimus, the performance of the tool was evaluated in silico. A retrospective dataset of 315 de novo kidney transplant recipients was first used to identify a one‐compartment pharmacokinetic (PK) model with time‐dependent clearance. MIPD performance was subsequently evaluated by calculating errors to predict future concentrations, which is directly related to dosing precision and probability of target attainment (PTA). Based on the identified model residual error, the theoretical upper limit was 45% PTA for a target of 13.5 ng/ml and an acceptable range of 12–15 ng/ml. Using empirical Bayesian estimation, this limit was reached on day 5 post‐transplant and beyond. By incorporating correlated within‐patient variability when predicting future individual concentrations, PTA improved beyond the theoretical upper limit. This yielded a Bayesian feedback dosing algorithm accurately predicting future trough concentrations and adapting each dose to reach a target concentration. Simulated concentration‐time profiles were then used to quantify MIPD‐based improvement on three end points: average PTA increased from 28% to 39%, median time to three concentrations in target decreased from 10 to 7 days, and mean log‐squared distance to target decreased from 0.080 to 0.055. A study of 200 patients was predicted to have sufficient power to demonstrate these nuanced PK end points reliably. These simulations supported our decision to develop a precision dosing tool for tacrolimus and test it in a prospective trial.

Case Report: Low Hematocrit Leading to Tacrolimus Toxicity

Tacrolimus is a calcineurin inhibitor characterized by a narrow therapeutic index and high intra- and inter-individual pharmacokinetic variability. Therapeutic drug monitoring in whole-blood is the standard monitoring procedure. However, tacrolimus extensively binds to erythrocytes, and tacrolimus whole-blood distribution and whole-blood trough concentrations are strongly affected by hematocrit. High whole-blood tacrolimus concentrations at low hematocrit may result in high unbound plasma concentrations and increased toxicity. We present the case of a 16-year-old girl with kidney and liver transplant in whom low concentrations of tacrolimus in the context of low hematocrit led to significant increase in the dosage of tacrolimus and participate, along with a genetic polymorphism of ABCB1, in nephrotoxicity.

Treatment optimization of maintenance immunosuppressive agents in pediatric renal transplant recipients

Introduction: Graft survival in pediatric kidney transplant patients has increased significantly within the last three decades, correlating with the discovery and utilization of new immunosuppressants as well as improvements in patient care. Despite these developments in graft survival for patients, there is still improvement needed, particularly in long-term care in pediatric patients receiving grafts from deceased donor patients. Maintenance immunosuppressive therapies have narrow therapeutic indices and are associated with high inter-individual and intra-individual variability.Areas covered: In this review, we examine the impact of pharmacokinetic variability on renal transplantation and its association with age, genetic polymorphisms, drug-drug interactions, drug-disease interactions, renal insufficiency, route of administration, and branded versus generic drug formulation. Pharmacodynamics are outlined in terms of the mechanism of action for each immunosuppressant, potential adverse effects, and the utility of pharmacodynamic biomarkers.Expert opinion: Acquiring abetter quantitative understanding of immunosuppressant pharmacokinetics and pharmacodynamic components should help clinicians implement treatment regimens to maintain the balance between therapeutic efficacy and drug-related toxicity.

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation

Systems-level insights into inflammatory events after vascularized composite allotransplantation (VCA) are critical to the success of immunomodulatory strategies of these complex procedures. To date, the effects of tacrolimus (TAC) immunosuppression on inflammatory networks in VCA, such as in acute rejection (AR), have not been investigated. We used a systems biology approach to elucidate the effects of tacrolimus on dynamic networks and principal drivers of systemic inflammation in the context of dynamic tissue-specific immune responses following VCA. Lewis (LEW) rat recipients received orthotopic hind limb VCA from fully major histocompatibility complex-mismatched Brown Norway (BN) donors or matched LEW donors. Group 1 (syngeneic controls) received LEW limbs without TAC, and Group 2 (treatment group) received BN limbs with TAC. Time-dependent changes in 27 inflammatory mediators were analyzed in skin, muscle, and peripheral blood using Principal Component Analysis (PCA), Dynamic Bayesian Network (DyBN) inference, and Dynamic Network Analysis (DyNA) to define principal characteristics, central nodes, and putative feedback structures of systemic inflammation. Analyses were repeated on skin + muscle data to construct a "Virtual VCA", and in skin + muscle + peripheral blood data to construct a "Virtual Animal." PCA, DyBN, and DyNA results from individual tissues suggested important roles for leptin, VEGF, various chemokines, the NLRP3 inflammasome (IL-1β, IL-18), and IL-6 after TAC treatment. The chemokines MCP-1, MIP-1α; and IP-10 were associated with AR in controls. Statistical analysis suggested that 24/27 inflammatory mediators were altered significantly between control and TAC-treated rats in peripheral blood, skin, and/or muscle over time. "Virtual VCA" and "Virtual Animal" analyses implicated the skin as a key control point of dynamic inflammatory networks, whose connectivity/complexity over time exhibited a U-shaped trajectory and was mirrored in the systemic circulation. Our study defines the effects of TAC on complex spatiotemporal evolution of dynamic inflammation networks in VCA. We also demonstrate the potential utility of computational analyses to elucidate nonlinear, cross-tissue interactions. These approaches may help define precision medicine approaches to better personalize TAC immunosuppression in VCA recipients.

Early impact of donor CYP3A5 genotype and Graft-to-Recipient Weight Ratio on tacrolimus pharmacokinetics in pediatric liver transplant patients

Tacrolimus (TAC) pharmacokinetics is influenced by the donor CYP3A5 genotype and the age of pediatric liver recipients. However, an optimization of a genotype-based algorithm for determining TAC starting is needed to earlier achieve stable target levels. As the graft itself is responsible for its metabolism, the Graft-to-Recipient Weight Ratio (GRWR) might play a role in TAC dose requirements. A single-center study was carried out in a cohort of 49 pediatric recipients to analyse the impact of patient and graft characteristics on TAC pharmacokinetics during the first 15 post-transplant days. Children < 2 years received grafts with a significantly higher GRWR (4.2%) than children between 2–8 (2.6%) and over 8 (2.7%). TAC concentration/weight-adjusted dose ratio was significantly lower in recipients from CYP3A5*1/*3 donors or with extra-large (GRWR > 5%) or large (GRWR 3–5%) grafts. The donor CYP3A5 genotype and GRWR were the only significant predictors of the TAC weight adjusted doses. Patients with a GRWR > 4% had a higher risk of acute rejection, observed in 20/49 (41%) patients. In conclusion, TAC starting dose could be guided according to the donor CYP3A5 genotype and GRWR, allowing for a quicker achievement of target concentrations and eventually reducing the risk of rejection.

Whole blood or plasma: what is the ideal matrix for pharmacokinetic-driven drug candidate selection?

In the present era of drug development, quantification of drug concentrations following pharmacokinetic studies has preferentially been performed using plasma as a matrix rather than whole blood. However, it is critical to realize the difference between measuring drug concentrations in blood versus plasma and the consequences thereof. Pharmacokinetics using plasma data may be misleading if concentrations differ between plasma and red blood cells (RBCs) because of differential binding in blood. In this review, factors modulating the partitioning of drugs into RBCs are discussed and the importance of determining RBC uptake of drugs for drug candidate selection is explored. In summary, the choice of matrix (plasma vs whole blood) is an important consideration to be factored in during drug discovery.

Population pharmacokinetics of tacrolimus in umbilical cord blood transplant patients focusing on the variation in red blood cell counts

WHAT IS KNOWN AND OBJECTIVE

The distribution of tacrolimus (TAC), an immunosuppressant used during cord blood transplantation (CBT)-one of the haematopoietic stem cell transplantations, to red blood cell (RBC) is approximately 90% in whole blood. In CBT patients, the total RBC count shows dramatic fluctuation due to conditioning before transplantation, including anticancer agents and total body irradiation, as well as RBC transfusions during the treatment period. Therefore, the amount of TAC in whole blood may show wide variation. However, therapeutic drug monitoring (TDM) of TAC has been performed based on the whole blood concentration. In this study, to contribute to TDM of TAC in CBT, we performed the population pharmacokinetic (PPK) analysis of TAC in 56 CBT patients and investigated the factors that affected the concentration of TAC, focusing the variation of RBC count.

METHOD

A one-compartment model was applied to the observed whole blood TAC concentrations, and a PPK analysis was conducted with a non-linear mixed effect model.

RESULTS AND DISCUSSION

Our final PPK model indicated good robustness and accuracy. In addition, haemoglobin (Hb) level was an influential covariate on Vd, which was expressed as Vd(L) = 91.4 × (Hb/8.2)^(-1.07) .

WHAT IS NEW AND CONCLUSION

In this study, our results showed the necessity for the Hb level monitoring during TDM of TAC in CBT patients and provided useful information for improving TDM strategy of TAC.

Population pharmacokinetics and dosing regimen optimization of tacrolimus in Chinese lung transplant recipients

We aimed to (i) develop a population pharmacokinetic model of tacrolimus in Chinese lung transplant recipients and (ii) propose model-based dosing regimens for individualized treatment. We obtained 807 tacrolimus steady-state whole blood concentrations from 52 lung transplant patients and genotyped CYP3A5*3. Population pharmacokinetic analysis was performed using nonlinear mixed-effects modeling. Monte Carlo simulations were employed to determine the initial dosing regimens. Tacrolimus pharmacokinetics was described by a one-compartment model with first-order absorption and elimination processes. In CYP3A5*3/*3 70-kg patients with 30% hematocrit and voriconazole-free therapy, the mean estimated apparent clearance was 13.1 l h^-1 with 20.1% between-subject variability, which was lower than that in Caucasian lung transplant patients (17.5-36.5 l h^-1). Hematocrit, postoperative days, tacrolimus daily dose, voriconazole concomitant therapy, and CYP3A5*3 genotype were identified as significant covariates for tacrolimus clearance. To achieve target trough concentration (10-15 ng ml^-1) on the 8th day post-transplant, a higher initial dosage than the current regimen of 0.04 mg kg^-1 every 12 h is recommended for CYP3A5*1/*3 patients without voriconazole concomitant therapy. Given the nonlinear kinetics of tacrolimus and large variability, population pharmacokinetic model should be combined with therapeutic drug monitoring to optimize individualized therapy.

Population pharmacokinetics model and initial dose optimization of tacrolimus in children and adolescents with lupus nephritis based on real-world data

The present study aimed to establish a population pharmacokinetics model of tacrolimus and further optimize the initial dosing regimen of tacrolimus in pediatric and adolescent patients with lupus nephritis (LN). Pediatric and adolescent patients with LN were recruited between August 2014 and September 2019 at the Children's Hospital of Fudan University (Shanghai, China). Relevant information was used to set up a population pharmacokinetics model with a Nonlinear Mixed Effect Model and the initial dosage regimen was simulated with the Monte Carlo method. Body weight and co-administration of wuzhi capsule were indicated to influence tacrolimus clearance in pediatric and adolescent patients with LN, and at the same body weight, the rate of tacrolimus clearance in patients without vs. with co-administration of wuzhi capsule was 1:0.71. In addition, in patients who were not administered wuzhi capsule, an initial dosage regimen of 0.15 mg/kg/day was recommended for a body weight of 10-23 kg and 0.10 mg/kg/day for 23-60 kg; in patients who were administered wuzhi capsule, an initial dosage regimen of 0.10 mg/kg/day was recommended for a body weight of 10-23 kg and 0.05 mg/kg/day for 23-60 kg. To the best of our knowledge, the present study was the first to establish a population pharmacokinetics model of tacrolimus in order to determine the optimal initial dosage regimen of tacrolimus in pediatric and adolescent patients with LN.

Fasting Status and Circadian Variation Must be Considered When Performing AUC-based Therapeutic Drug Monitoring of Tacrolimus in Renal Transplant Recipients

Therapeutic drug monitoring (TDM) is mandatory for the immunosuppressive drug tacrolimus (Tac). For clinical applicability, TDM is performed using morning trough concentrations. With recent developments making tacrolimus concentration determination possible in capillary microsamples and Bayesian estimator predicted area under the concentration curve (AUC), AUC‐guided TDM may now be clinically applicable. Tac circadian variation has, however, been reported, with lower systemic exposure following the evening dose. The aim of the present study was to investigate tacrolimus pharmacokinetic (PK) after morning and evening administrations of twice‐daily tacrolimus in a real‐life setting without restrictions regarding food and concomitant drug timing. Two 12 hour tacrolimus investigations were performed; after the morning dose and the following evening dose, respectively, in 31 renal transplant recipients early after transplantation both in a fasting‐state and under real‐life nonfasting conditions (14 patients repeated the investigation). We observed circadian variation under fasting‐conditions: 45% higher peak‐concentration and 20% higher AUC following the morning dose. In the real‐life nonfasting setting, the PK‐profiles were flat but comparable after the morning and evening doses, showing slower absorption rate and lower AUC compared with the fasting‐state. Limited sampling strategies using concentrations at 0, 1, and 3 hours predicted AUC after fasting morning administration, and samples obtained at 1, 3, and 6 hours predicted AUC for the other conditions (evening and real‐life nonfasting). In conclusion, circadian variation of tacrolimus is present when performed in patients who are in the fasting‐state, whereas flatter PK‐profiles and no circadian variation was present in a real‐life, nonfasting setting.

Relationship Between Change Rate of Tacrolimus Clearance During Continuous Intravenous Infusion and Recipient Recovery at an Early Stage After Living Donor Liver Transplantation

BACKGROUND AND OBJECTIVE

Tacrolimus clearance (CL) is significantly altered according to recovery of liver function at an early stage after living donor liver transplantation (LDLT). In this study, we aimed to examine the impact of the change rate from postoperative day (POD) 1 in CL (ΔCL) of tacrolimus during continuous intravenous infusion (CIVI) on recipient recovery.

METHODS

A tacrolimus population pharmacokinetic model on POD1 after LDLT was developed using Phoenix NLME 1.3. The CL_POD1 was calculated using the final model. The CL_POD4-7 was calculated by dividing total daily tacrolimus dose by the area under the concentration-time curve from 0 to 24 h.

RESULTS

Data were obtained from 57 LDLT recipients, along with 540 points (177 points on POD1, 363 points on POD4-7) of tacrolimus whole blood concentrations at CIVI. The median tacrolimus CL decreased from POD1 to POD4 (from 2.73 to 1.40 L/h) and was then stable until POD7. Stepwise Cox proportional hazards regression analyses showed that the graft volume (GV)/standard liver volume (SLV) ratio (GV/SLV) and the tacrolimus ΔCL_POD6 were independent factors predicting early discharge (within 64 days median value) of recipients after LDLT [hazard ratio (HR) = 1.041, P = 0.001 and HR = 1.023, P = 0.004].

CONCLUSIONS

The tacrolimus ΔCL during CIVI immediately after LDLT in each recipient was a useful indicator for evaluation of recovery at an early stage after LDLT.

Predictive engines based on pharmacokinetics modelling for tacrolimus personalized dosage in paediatric renal transplant patients

The development of predictive engines based on pharmacokinetic-physiological mathematical models for personalised dosage recommendations is an immature field. Nevertheless, these models are extensively applied during the design of new drugs. This study presents new advances in this subject, through a stable population of patients who underwent kidney transplantation and were prescribed tacrolimus. We developed 2 new population pharmacokinetic models based on a compartmental approach, with one following the physiologically based pharmacokinetic approach and both including circadian modulation of absorption and clearance variables. One of the major findings was an improved predictive capability for both models thanks to the consideration of circadian rhythms, both in estimating the population and in Bayesian individual customisation. This outcome confirms a plausible mechanism suggested by other authors to explain circadian patterns of tacrolimus concentrations. We also discovered significant intrapatient variability in tacrolimus levels a week after the conversion from a fast-release (Prograf) to a sustained-release formulation (Advagraf) using adaptive optimisation techniques, despite high adherence and controlled conditions. We calculated the intrapatient variability through parametric intrapatient variations, which provides a method for quantifying the mechanisms involved. We present a first application for the analysis of bioavailability changes in formulation conversion. The 2 pharmacokinetic models have demonstrated their capability as predictive engines for personalised dosage recommendations, although the physiologically based pharmacokinetic model showed better predictive behaviour.

Is There a Temporal Relationship Between Trough Whole Blood Tacrolimus Concentration and Acute Rejection in the First 14 Days After Kidney Transplantation?

BACKGROUND

There are inconsistent findings regarding the relationship between trough whole blood tacrolimus concentration (TAC C0) and acute kidney rejection in recipients undergoing TAC therapeutic drug monitoring (TDM). However, studies have not always assessed TAC C0 at the time of rejection or accounted for variability in hematocrit. Therefore, this study aimed to investigate the temporal relationship between TAC C0 and acute rejection, including when accounting for variation in hematocrit.

METHODS

For 38 recipients who developed biopsy-proven acute rejection (BPAR) in the first 14 days after kidney transplantation, daily TAC C0 from TDM and hematocrit was collected from case notes. Differences in log10-transformed TAC C0 between the day of BPAR (log Cr), 1 day before BPAR (log Cr-1), and 2 days before BPAR (log Cr-2) and the combined median concentrations for the days preceding these (log Cprior) were examined by repeated-measures analysis of variance with Dunnett post hoc testing. Generalized linear mixed-effects regression (glmer) examined the ability of TAC C0 to predict acute rejection episodes with and without controlling for hematocrit.

RESULTS

Log Cr-1 [mean difference (95% confidence interval) = -0.13 (-0.21 to -0.048), post hoc P = 0.002] and log Cr [-0.13 (-0.24 to -0.025), post hoc P = 0.013] were significantly lower than log Cprior. TAC C0 was a significant (P = 0.0078) predictor of rejection episodes (area under the receiver operating characteristic curve = 0.79) only in glmer models accounting for variability in hematocrit.

CONCLUSIONS

In recipients who developed BPAR, there was a significant temporal relationship between TAC C0 and BPAR incidence under TAC TDM that may not be detected in cross-sectional studies, especially if variability in hematocrit is not addressed. This supports a TAC C0-rejection relationship, which differs between recipients, and may explain why some recipients do or do not experience rejection within or below the TDM range, respectively. However, studies with larger sample sizes are needed to confirm this finding.

Mass-producible microporous silicon membranes for specific leukocyte subset isolation, immunophenotyping, and personalized immunomodulatory drug screening in vitro

Widespread commercial and clinical adaptation of biomedical microfluidic technology has been limited in large part due to the lack of mass producibility of polydimethylsiloxane (PDMS) and glass-based devices commonly as reported in the literature. Here, we present a batch-fabricated, robust, and mass-producible immunophenotyping microfluidic device using silicon micromachining processes. Our Si and glass-based microfluidic device, named the silicon microfluidic immunophenotyping assay (SiMIPA), consists of a highly porous (∼40%) silicon membrane that can selectively separate microparticles below a certain size threshold. The device is capable of isolating and stimulating specific leukocyte populations, and allows for measuring their secretion of cell signaling proteins by means of a no-wash homogeneous chemiluminescence-based immunoassay. The high manufacturing throughput (∼170 devices per wafer) makes a large quantity of SiMIPA chips readily available for clinically relevant applications, which normally require large dataset acquisitions for statistical accuracy. With 30 SiMIPA chips, we performed in vitro immunomodulatory drug screening on isolated leukocyte subsets, yielding 5 data points at 6 drug concentrations. Furthermore, the excellent structural integrity of the device allowed for samples and reagents to be loaded using a micropipette, greatly simplifying the experimental protocol.

Population pharmacokinetics and dosing regimen optimization of tacrolimus in Chinese pediatric hematopoietic stem cell transplantation patients

1. Several tacrolimus population pharmacokinetic (PPK) models in hematopoietic stem cell transplantation (HSCT) patients have been set up to recommend an optimal dosage schedule. However, the PPK model of Chinese pediatric HSCT patients has not been reported. The study is to investigate whether published PPK models of HSCT patients can be used to simulate Chinese pediatric HSCT patients and establish the tacrolimus PPK model of Chinese pediatric HSCT patients.2. Published PPK models were collected from the literature and assessed using Chinese pediatric HSCT patients via the individual prediction error method. The establishment of tacrolimus PPK model in Chinese pediatric HSCT patients was characterized with nonlinear mixed-effects modeling (NONMEM).3. Three published HSCT PPK models were identified, two of which could be applied to our external dataset. However, these models were dissatisfactory in terms of individual prediction error and, hence, inadequate for extrapolation. Finally, a new tacrolimus PPK model in Chinese pediatric HSCT patients was established. Based on the simulation results of our model, new initial dosage suggestions were recommended. In conclusion, the tacrolimus PPK model in Chinese pediatric HSCT patients was presented and the model could be used to predict individualized dosing regimens in children with HSCT.

Population pharmacokinetics of tacrolimus in pediatric refractory nephrotic syndrome and a summary of other pediatric disease models

Different tacrolimus (TAC) population pharmacokinetic (PPK) models have been established in various pediatric disease populations. However, a TAC PPK model for pediatric refractory nephrotic syndrome (PRNS) has not been well characterized. The current study aimed to establish a TAC PPK model in Chinese PRNS and provide a summary of previous literature concerning TAC PPK models in different pediatric diseases. A total of 147 TAC conventional therapeutic drug monitoring (TDM) data from multiple blood samples obtained from 65 Chinese patients with PRNS were characterized using nonlinear mixed-effects modeling. The impacts of demographic features, biological characteristics and drug combination were evaluated. Model validation was assessed using the bootstrap method. A one-compartment model with first-order absorption and elimination was determined to be the most suitable model for TDM data in PRNS. The absorption rate constant (Ka) was set at 4.48 h⁻¹. The typical values of apparent oral clearance (CL/F) and apparent volume of distribution (V/F) in the final model were 5.46 l/h and 57.1 l, respectively. The inter-individual variability of CL/F and V/F were 22.2 and 0.2%, respectively. The PPK equation for TAC was: CL/F = 5.46 × exponential function (EXP)(0.0323 × age) × EXP(−0.359 × cystatin-C) × EXP(0.148 × daily dose of TAC). No significant effects of covariates on V/F were observed. In conclusion, the current study developed and validated the first TAC PPK model for patients with PRNS. The study also provided a summary of previous literature concerning other TAC PPK models in different pediatric diseases.

Pharmacokinetics of tacrolimus granules in pediatric de novo liver, kidney, and heart transplantation: The OPTION study

Tacrolimus granules were developed for patients who are unable to swallow capsules. Therapeutic drug monitoring (TDM) is required to optimize efficacy and safety, which is based on C_trough for tacrolimus capsules. Pharmacokinetic (PK) data for tacrolimus granules are required to establish the basis for TDM in those who are unable to swallow capsules. In this phase IV study (NCT01371331) of children undergoing liver, kidney, or heart transplantation, patients received tacrolimus granules 0.15 mg/kg twice daily; first dose was administered within 24 hours of reperfusion. PK analysis samples were collected after reperfusion, after first dose of tacrolimus (Day 1), and at steady state (Day 7; >4 days stable dose). Of the 52 transplant recipients enrolled, 38 had two evaluable PK profiles. Mean AUC_tau after first dose of tacrolimus was 211, 97, and 224 hour*ng/mL in liver, kidney, and heart transplant recipients, respectively; corresponding mean AUC_tau at steady state was 195, 208, and 165 hour*ng/mL. C_trough and AUC_tau were positively correlated after first dose of tacrolimus and at steady state (Pearson's coefficients: r = 0.81 and r = 0.87, respectively). This study demonstrated that C_trough is a reliable marker for TDM in pediatric transplant recipients treated with tacrolimus granules, consistent with TDM for other tacrolimus formulations.

Biomarkers for individualized dosage adjustments in immunosuppressive therapy using calcineurin inhibitors after organ transplantation

Calcineurin inhibitors (CNIs), such as cyclosporine A and tacrolimus, are widely used immunosuppressive agents for the prevention of post-transplantation rejection and have improved 1-year graft survival rates by up to 90%. However, CNIs can induce severe reactions, such as acute or chronic allograft nephropathy, hypertension, and neurotoxicity. Because CNIs have varied bioavailabilities, narrow therapeutic ranges, and individual propensities for toxic effects, therapeutic drug monitoring is necessary for all CNIs. Identifying the genetic polymorphisms in drug-metabolizing enzymes will help to determine personalized dosage regimens for CNIs, as CNIs are substrates for CYP3A5 and P-glycoprotein (P-gp, MDR1). CNIs are often concomitantly administered with voriconazole or proton pump inhibitors (PPIs), giving rise to drug interaction problems. Voriconazole and PPIs can increase the blood concentrations of CNIs, and both are primarily metabolized by CYP2C19. Thus, it is expected that interactions between CNIs and voriconazole or PPI would be affected by CYP2C19 and CYP3A5 polymorphisms. CNI-induced acute kidney injury (AKI) is a serious complication of transplantations. Neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule 1 (KIM-1) are noninvasive urinary biomarkers that are believed to be highly sensitive to CNI-induced AKI. In this article, we review the adverse events and pharmacokinetics of CNIs and the biomarkers related to CNIs, including CYP3A5, CYP2C19, MDR1, NGAL, and KIM-1. We hope that these data will help to identify the optimal biomarkers for monitoring CNI-based immunosuppressive therapy after organ transplantation.

The potential impact of hematocrit correction on evaluation of tacrolimus target exposure in pediatric kidney transplant patients

BACKGROUND

Tacrolimus is an important immunosuppressive agent with high intra- and inter-individual pharmacokinetic variability and a narrow therapeutic index. As tacrolimus extensively accumulates in erythrocytes, hematocrit is a key factor in the interpretation of tacrolimus whole blood concentrations. However, as hematocrit values in pediatric kidney transplant patients are highly variable after kidney transplantation, translating whole blood concentration targets without taking hematocrit into consideration is theoretically incorrect. The aim of this study is to evaluate the potential impact of hematocrit correction on tacrolimus target exposure in pediatric kidney transplant patients.

METHODS

Data were obtained from 36 pediatric kidney transplant patients. Two hundred fifty-five tacrolimus whole blood samples were available, together responsible for 36 area under the concentration-time curves (AUCs) and trough concentrations. First, hematocrit corrected concentrations were derived using a formula describing the relationship between whole blood concentrations, hematocrit, and plasma concentrations. Subsequently, target exposure was evaluated using the converted plasma target concentrations. Ultimately, differences in interpretation of target exposure were identified and evaluated.

RESULTS

In total, 92% of our patients had lower hematocrit (median 0.29) than the reference value of adult kidney transplant patients. A different evaluation of target exposure for either trough level, AUC, or both was defined in 42% of our patients, when applying hematocrit corrected concentrations.

CONCLUSION

A critical role for hematocrit in therapeutic drug monitoring of tacrolimus in pediatric kidney transplant patients is suggested in this study. Therefore, we believe that hematocrit correction could be a step towards improvement of tacrolimus dose individualization.

The computation of biomarkers in pharmacokinetics with the aid of singular perturbation methods

In pharmacokinetics, exact solutions to one-compartment models with nonlinear elimination kinetics cannot be found analytically, if dosages are assumed to be administered repetitively through extravascular routes (Tang and Xiao in J Pharmacokinet Pharmacodyn 34(6):807-827, 2007). Hence, for the corresponding impulsed dynamical system, alternative methods need to be developed to find approximate solutions. The primary purpose of this paper is to use the method of matched asymptotic expansions (Holmes Introduction to Perturbation Methods, vol 20. Springer Science & Business Media, Berlin, 2012), a singular perturbation method (Holmes, Introduction to Perturbation Methods, vol 20. Springer Science & Business Media, Berlin, 2012; Keener Principles of Applied Mathematics, Addison-Wesley, Boston, 1988), to obtain approximate solutions. With this method, we are able to rigorously determine conditions under which there is a stable periodic solution of the model equations. Furthermore, typical important biomarkers that enable the design of practical, efficient and safe drug delivery protocols, such as the time the drug concentration reaches the peak and the peak concentrations, are theoretically estimated by the perturbation method we employ.

18F-FAC PET Selectively Images Liver-Infiltrating CD4 and CD8 T Cells in a Mouse Model of Autoimmune Hepatitis

Immune cell-mediated attack on the liver is a defining feature of autoimmune hepatitis and hepatic allograft rejection. Despite an assortment of diagnostic tools, invasive biopsies remain the only method for identifying immune cells in the liver. We evaluated whether PET imaging with radiotracers that quantify immune activation (¹⁸F-FDG and ¹⁸F-1-(2'-deoxy-2'-fluoro-arabinofuranosyl)cytosine [¹⁸F-FAC]) and hepatocyte biology (¹⁸F-2-deoxy-2-fluoroarabinose [¹⁸F-DFA]) can visualize and quantify liver-infiltrating immune cells and hepatocyte inflammation, respectively, in a preclinical model of autoimmune hepatitis. Methods: Mice treated with concanavalin A (ConA) to induce a model of autoimmune hepatitis or vehicle were imaged with ¹⁸F-FDG, ¹⁸F-FAC, and ¹⁸F-DFA PET. Immunohistochemistry, digital autoradiography, and ex vivo accumulation assays were used to localize areas of altered radiotracer accumulation in the liver. For comparison, mice treated with an adenovirus to induce a viral hepatitis were imaged with ¹⁸F-FDG, ¹⁸F-FAC, and ¹⁸F-DFA PET. ¹⁸F-FAC PET was performed on mice treated with ConA and vehicle or with ConA and dexamethasone. Biopsy samples of patients with autoimmune hepatitis were immunostained for deoxycytidine kinase. Results: Hepatic accumulation of ¹⁸F-FDG and ¹⁸F-FAC was 173% and 61% higher, respectively, and hepatic accumulation of ¹⁸F-DFA was 41% lower, in a mouse model of autoimmune hepatitis than in control mice. Increased hepatic ¹⁸F-FDG accumulation was localized to infiltrating leukocytes and inflamed sinusoidal endothelial cells, increased hepatic ¹⁸F-FAC accumulation was concentrated in infiltrating CD4 and CD8 cells, and decreased hepatic ¹⁸F-DFA accumulation was apparent in hepatocytes throughout the liver. In contrast, viral hepatitis increased hepatic ¹⁸F-FDG accumulation by 109% and decreased hepatic ¹⁸F-DFA accumulation by 20% but had no effect on hepatic ¹⁸F-FAC accumulation (nonsignificant 2% decrease). ¹⁸F-FAC PET provided a noninvasive biomarker of the efficacy of dexamethasone for treating the autoimmune hepatitis model. Infiltrating leukocytes in liver biopsy samples from patients with autoimmune hepatitis express high levels of deoxycytidine kinase, a rate-limiting enzyme in the accumulation of ¹⁸F-FAC. Conclusion: Our data suggest that PET can be used to noninvasively visualize activated leukocytes and inflamed hepatocytes in a mouse model of autoimmune hepatitis.

Ribavirin-induced anaemia reduced tacrolimus level in a hepatitis C patient receiving haemodialysis

A 37-year-old man with hepatitis C virus (HCV) genotype 3A developed renal failure. In 2007, the patient received a renal transplant and started receiving tacrolimus (Tac); the transplant subsequently failed. In April 2015, the patient restarted haemodialysis and in May initiated sofosbuvir 400 mg and ribavirin 400 mg daily. Baseline Tac level was 6.6 ng/mL and haemoglobin (Hb) was 10.3 g/dL. The patient then left the country for vacation and Hb was found to be dramatically low at 3.7 g/dL on return on 5 August. Ribavirin was put on hold, while darbepoetin dose was increased. On 23 August, Tac level was found undetectable; hence, dosage was increased. Hb eventually bounced back to >10 g/dL in October and Tac to 7.2 ng/mL; ribavirin was restarted at 200 mg three times weekly. HCV RNA level was undetectable at 3 months and remained undetectable 12 weeks after therapy finished.