Tacrolimus Concentrations Research Articles

The effect of the use of omeprazole versus famotidine on the kidney transplant function: a randomized controlled study

Tacrolimus is metabolized in the liver with the participation of cytochrome P450 isoforms 3A4 and 3A5 (CYP3A4, CYP3A5). Omeprazole, unlike famotidine, is a substrate and inhibitor of CYP2C19, CYP3A4, CYP3A5 enzymes. The aim of the study is to compare the effect of omeprazole and famotidine on the tacrolimus concentration and the kidney transplant function. A randomized study was conducted in 24 adult patients with stable kidney transplant function who received a standard triple immunosuppression regimen. Patients were assigned to the group I (n = 12) additionally receiving omeprazole (20 mg) or the group II (n = 12) receiving famotidine (20 mg). At the time of qualification and during follow-up visits, tacrolimus blood concentration and selected laboratory tests were performed. Statistical analysis was performed using the MedCalc system. The value of tacrolimus concentration in the blood increased after a year in the group I (7.27 ± 2.33 vs 9.20 ± 2.46 ng/mL, p = 0.0478). A reduction in tacrolimus dosage was observed after three years in the group I (3.56 ± 1.75 vs 2.78 ± 1.00 mg, p = 0.0440) and in the group II (2.72 ± 0.84 vs 2.10 ± 0.48 mg, p = 0.0051). There was significant difference in the percentage changes of glomerular filtration rate between the groups after 3 years of the study (− 5.56% vs 9.13%, p = 0.0343). Omeprazole significantly change the concentration of tacrolimus in the blood when administered together with tacrolimus after one year of observation. There was no effect of famotidine or omeprazole on the function of the kidney transplant. ClinicalTrials.gov identifier: NCT05061303.

Bibliometric study and visual analysis of postoperative diabetes mellitus in kidney transplant recipients based on WoSCC database

Background In recent years, the increase of the post-transplantation diabetes mellitus (PTDM) after renal transplantation encourages people to do a lot of research on the disease. This paper conducted a bibliometric study on PTDM related literature to explore the risk factors of diabetes after kidney transplantation, as well as the current status, hotspots and development trends of PTDM research, so as to provide reference for researchers in related fields. Methods We searched the Web of Science Core Collection (WoSCC) database for PTDM literature from January 1, 1990, to August 20, 2023, and used VOSviewer, CiteSpace, and the R package ‘bibliometrix’ to do bibliometric analysis. Results Obesity, 3 months after transplantation tacrolimus concentration >10 ng/mL, temporary hyperglycemia, delayed graft function, acute rejection is specific risk factors related to PTDM in renal transplant recipients. In addition, 74 countries led by China and the United States published 1546 papers, and the number of PTDM-related publications is increasing every year. Primary institutions included the University of California, Los Angeles, Mayo Clinic, University of Oslo, and University of Toronto. The Journal of Transplantation is the most widely read journal in the subject. The authors with the most published literature are Trond Jenssen and Adnan Sharif, and the most cited author is Kasiske BL. Expectations for continued growth in global PTDM research are increasingly high. Future studies will mainly focus on exploring the risk factors of PTDM and identifying new therapeutic approaches and targets.

Innovative Personalized Medicine for Immunosuppressive Drugs Based on Novel Control Theory of Pharmacokinetics

Tacrolimus is widely recognized as an anti-rejection agent due to its immunosuppressive characteristics. It binds to the immunophilin FK506-binding protein (FKBP) and thus to calcineurin, and inhibits its activity. Tacrolimus' therapeutic concentration range in blood is narrow, and its pharmacokinetics are highly variable among individuals. First, because tacrolimus primarily distributes to red blood cells (RBCs), anemia and blood transfusions can cause fluctuations in tacrolimus blood concentrations. Variations in blood tacrolimus concentration significantly correlated with variations in RBC count, hemoglobin level, and hematocrit value, but not with variations in white blood cell or platelet counts. Interestingly, FKBP played an important role in tacrolimus distribution to RBCs. The effects of intracellular and extracellular FKBP levels on RBC distribution of tacrolimus in circulating blood were substantial. Secondly, proteins affecting pharmacokinetics can differ at the genetic level in their expression and functional potency. Genetic polymorphisms that influence tacrolimus pharmacokinetics have been reported. A polymorphism in the gene encoding the metabolic enzyme cytochrome P450 (CYP) 3A5 is a particularly influential factor affecting tacrolimus pharmacokinetics in Japanese patients. CYP3A5 polymorphisms correlated with individual differences in tacrolimus blood concentration changes after starting continuous infusion in allogeneic hematopoietic stem cell transplantation (HSCT) recipients. In addition, CYP3A5*3 polymorphism also correlated with differences in the frequency of acute graft-versus-host disease (GVHD) development in allogeneic HSCT recipients.

A Phase I Trial of the Pharmacokinetic Interaction Between Cannabidiol and Tacrolimus.

One in six Americans uses cannabidiol-based or cannabis-derived products. Cannabidiol is a substrate of CYP3A, but its role as a potential CYP3A inhibitor remains unclear. We hypothesized that cannabidiol would inhibit CYP3A-mediated metabolism of tacrolimus. This report is an interim analysis of an open-label, three-period, fixed-sequence, crossover study in healthy participants. Participants first received a single dose of tacrolimus 5 mg orally. After washout, participants later received cannabidiol titrated to 5 mg/kg twice daily for 14 days to reach a steady state, followed by a second single dose of tacrolimus 5 mg orally. Tacrolimus concentrations in whole blood were measured by UHPLC-MS/MS method. Pharmacokinetic parameters were calculated by noncompartmental analysis. Twelve participants completed all periods of the study. The maximum concentration (Cmax) of tacrolimus increased 4.2-fold (P < 0.0001) with cannabidiol (40.2 ± 13.5 ng/mL) compared with without cannabidiol (9.85 ± 4.63 ng/mL). The area under the concentration-vs.-time curve (AUC0-∞) increased 3.1-fold (P < 0.0001). No change in half-life (t1/2) was observed. This study demonstrates that cannabidiol increases tacrolimus exposure. Our data suggest the need for dose reduction in tacrolimus and frequent therapeutic dose monitoring in transplant patients taking cannabidiol concomitantly. Whether this observed interaction occurred due to the inhibition of CYP3A4 and/or CYP3A5 in the liver, intestine, or both, or intestinal drug transporters (e.g., p-glycoprotein) during the first-pass elimination remains to be elucidated.

Chlorogenic acid improves urogenital dysfunction induced by exposure to ambient particulate matter.

Oxidative stress is a well-known underlying mechanism for several diseases in response to environmental pollution. Although there is a lack of evidence on the relationship between air pollution and an established risk factor for urogenital dysfunction. The aim of this study was to investigate the mechanism of particulate matter (PM) on urogenital function and evaluate the potential efficacy of chlorogenic acid (CGA) in preventing urogenital damage in rats. Forty Wistar rats were divided into five groups (n = 8): control, particulate matter exposure (animals were exposed to fine dust in an inhalation chamber for 4 weeks, 3 days a week, for 3 h, PM10 concentration adjusted to 500-2000 µg/m3), and particulate matter plus 3 concentrations of chlorogenic acid (100, 200, and 400 mg/kg, gavage, 4 weeks, 3 days a week). At the end of the study, kidney biomarkers, oxidative stress markers, antioxidant enzymes, the oxidation resistance 1 (OXR1) and its downstream gene expression, sperm count, gonadotropin hormones, and the structure of the kidney, epididymis, and seminal vesicle were evaluated in response to PM exposure and CGA treatment in all groups. The data obtained from the current study showed that PM exposure led to kidney dysfunction and inhibition of oligospermia through oxidative stress, as evidenced by an increase in MDA and a decrease in TAC, SOD, CAT, and GSH concentration levels in blood samples. These results were consistent with the down-regulation of OXR1, Nrf2, and P21 gene expression. In contrast, CGA improved urogenital biomarkers and histopathology structures of the kidney, epididymis, and seminal vesicle by enhancing antioxidant defense system enzymes and modulating the OXR1 signaling pathway. Our findings suggest that environmental air pollution contributes to kidney dysfunction and urogenital damage. Modulation of oxidative stress through the OXR1, P21, and Nrf2 signaling pathways may be the underlying mechanism. Furthermore, chlorogenic acid supplementation could be recommended as a new protective or treatment strategy to safeguard urogenital function against exposure to particulate matter.

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

A pharmacokinetic model has been developed to quantify the drug-drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes. This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [Emax], Emax, log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment. The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0-9.9) ng/mL (n = 3). The final model comprised the Sigmoid Emax model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin. These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant.

Suspicious of Acute Kidney Graft Rejection: Tacrolimus Pharmacokinetics Under Methylprednisolone Therapy.

Acute rejection remains one of the main complications in the first months after transplantation and may influence long-term outcomes. Tacrolimus has proven its usefulness in solid organ transplants and its monitoring through the application of pharmacokinetic concepts to optimize individual drug therapy. This research proposes to evaluate the tacrolimus pharmacokinetic parameters in patients suspected of acute kidney graft rejection under methylprednisolone pulse therapy. Eleven adult tacrolimus-treated renal recipients were selected from a prospective, single-arm, single-center cohort study, with suspicion of acute rejection although in use of methylprednisolone pulses therapy. They were followed up for three months posttransplantation, being tacrolimus trough serum concentrations determined using a chemiluminescent magnetic immunoassay, and pharmacokinetic parameters were estimated by using a nonlinear mixed-effects model implemented by Monolix 2020R1. A tacrolimus trough serum concentration range of 8 to 12 ng.mL-1 was considered therapeutic. Six patients showed acute cellular rejection, and two of them in addition had an antibody- mediated rejection. Tacrolimus trough serum concentration was below the reference range in eight patients. Most patients showed a high tacrolimus concentration intrapatient and pharmacokinetic parameters variability. The obtained pharmacokinetics parameters helped in understanding the kidney recipient patients' tacrolimus behavior, assisting in the improvement of individual drug therapy and reducing the risk of acute rejection episodes.

Association between salivary microbiota and tacrolimus pharmacokinetic variability in kidney transplant

Kidney transplantation (KT) serves as a highly effective treatment for end-stage renal disease (ESRD). Nonetheless, the administration of tacrolimus, a commonly used immunosuppressant in KT, faces challenges due to the lack of dependable biomarkers for its efficacy and the considerable variability in tacrolimus pharmacokinetics (TacIPV). In this study, 183 saliva samples from 48 KT recipients under tacrolimus therapy, alongside 9 healthy control samples, were subjected to 16S rRNA sequencing. The analysis revealed significant differences in the composition of salivary microbiota among KT recipients, patients with ESRD, and healthy controls. Moreover, trough blood concentrations (C0) of tacrolimus were associated with alterations in microbiota composition. Notably, Capnocytophage consistently exhibited a negative correlation in both group-level and individual trends. Furthermore, distinct taxa were identified that effectively distinguished recipients with varying TacIPV, as demonstrated by a cross-validation random forest model (mean AUC = 0.7560), with Anaerolinea emerging as a prominent contributor to the classifier. These findings suggest that salivary microbiota is closely linked to tacrolimus C0 levels and could aid clinicians in differentiating KT recipients based on TacIPV.

Population pharmacokinetics of tacrolimus whole blood and peripheral blood mononuclear cell concentrations in stable kidney-transplanted patients.

Therapeutic drug monitoring of tacrolimus based on whole blood drug concentrations is routinely performed. The concentration of tacrolimus in peripheral blood mononuclear cells (PMBCs) is likely to better reflect drug exposure at the treatment target site. We aimed to describe the relationship between tacrolimus whole blood and PBMC concentrations, and the influence of patient characteristics on this relationship by developing a population pharmacokinetic model. We prospectively enrolled 63 stable adult kidney-transplanted patients and collected dense (12-h, n = 18) or sparse (4-h, n = 45) pharmacokinetic profiles of tacrolimus. PBMCs were isolated from whole blood (Ficoll density gradient centrifugation), and drug concentrations in whole blood and PBMCs were analysed using liquid chromatography-mass spectrometry. Patient genotype (CYP3A4/5, ABCB1, NR1I2) was assessed with PCR. Population pharmacokinetic modelling and statistical evaluation was performed using NONMEM. Tacrolimus whole blood concentrations were well described using a two-compartment pharmacokinetic model with a lag-time and first-order absorption and elimination. Tacrolimus PBMC concentrations were best estimated from whole blood concentrations with the use of a scaling factor, the ratio of whole blood to PBMC concentrations (RC:PBMC), which was the extent of tacrolimus distribution into PBMC. CYP3A5*1 non-expressors and NR1I2-25 385T allele expressors demonstrated higher RC:PBMC ratios of 42.4% and 60.7%, respectively. Tacrolimus PBMC concentration could not be accurately predicted from whole blood concentrations and covariates because of significant residual unexplained variability in the distribution of tacrolimus into PBMCs and may need to be measured directly if required for future studies.

B-297 Tacrolimus Concentrations in Envarsus vs Prograf Patients: An Evaluation of the Clinical Impact of LC-MS/MS and Immunoassay Methods on Tacrolimus measurement

Abstract Background Tacrolimus is a calcineurin inhibitor used as part of an immunosuppressive regimen in kidney and liver transplant patients to prevent graft-versus-host disease (GvHD) and requires therapeutic drug monitoring due to its narrow therapeutic index. Tacrolimus levels are commonly measured using two different methodologies - immunoassay and liquid chromatography tandem mass spectrometry (LC-MS/MS). A global proficiency study to assess and compare the measurement of trough levels by these two methodologies noted a positive bias with the ARCHITECT immunoassay which is likely due to the presence of tacrolimus metabolites. The aim of our study is to assess the impact of two different formulations of tacrolimus on the accuracy of its analytical measurement. While differences between immunoassay and LC-MS/MS results have been evaluated for immediate-release tacrolimus (Prograf), it has yet to be characterized for extended-release formulations such as Envarsus. The discrepancy between immunoassay and LC-MS/MS has clinical implications, as dosage modifications are based on measured concentrations, analytical variation may cause intervals of subtherapeutic or supratherapeutic exposure, increasing the risk of graft rejection or toxicity. Methods Development of an LC-MS/MS method for the simultaneous quantification of tacrolimus and its major metabolite, desmethyl tacrolimus, was performed in whole blood. Traceable calibrators and quality control material for tacrolimus and specimens supplemented with desmethyl tacrolimus were used to determine accuracy and precision. Tacrolimus concentrations were measured by LC-MS/MS and ARCHITECT immunoassay methods in excess whole blood specimens from patients treated with either Prograf or Envarsus. Measurement biases between LC-MS/MS and immunoassay methodologies were determined for both formulations of tacrolimus. Results External calibration curves for both tacrolimus and desmethyl tacrolimus were linear (R2&amp;gt;0.995), and the analytical measurement range (AMR) for tacrolimus spanned from 1.1 - 31.6 ng/ml. Calibrator and Quality control (QC) biases were within 15% of their target values throughout the AMR and within-run imprecision was less than 10% (n=25) for all calibrators and QCs. Between-run imprecision for Low, Mid, and High QC levels over a period of 2 weeks (n=5 days) was less than 10%. Comparative bias of tacrolimus concentrations between immunoassay and LC-MS/MS was significantly lower (P value=0.0074) for Envarsus (n=20 specimens) relative to Prograf (n=32 specimens). Conclusions The differential bias between immunoassay and LC-MS/MS in the measurement of tacrolimus in patients dosed with immediate-release versus extended-release formulations suggests that their distinct pharmacokinetic profile may impact the accuracy of the measurement. Therefore, applying observed measurement biases from different assays derived from Prograf patients to Envarsus patients and vice versa may result in erroneous estimation of tacrolimus concentrations.

B-222 Receptor-donor CYP3A5 and CYP3A4 genotype testing in liver transplant patients and its influence in tacrolimus blood levels: a retrospective study

Abstract Background Optimal immunosupression is crucial for transplant success. In orthohepatic transplants, blood target levels of tacrolimus, when coadministred with corticoids and mycophenolic acid, are between 6 and 10 ng/mL during the first three months post-transplant. Notwithstanding, achieving tacrolimus concentrations into this range may be tough because of factors such as liver function status, age, sex, drug-drug interactions, etc. In this way, pharmacogenetic testing of CYP3A5 and CYP3A4 genes have demonstrated to be useful in tacrolimus dosing optimization. Nonetheless, there is no evidence enough for pharmacogenetic based adjusting in liver transplant, specially if receptor and graft’s genotypes differ in these loci. The aim of the present study is to find out how the receptor and donor genotypes in CYP3A5 and CYP3A4 genes affect tacrolimus pharmacokinetics. Methods Genotypic profiling of 108 receptor-donor's pairs biopsies gathered from patients who were underwent hepatic transplant from 2012 to 2019 were carried out using Taqman® OpenArray™ PGx Express 120 panel (ThermoFisher™). We focused on CYP3A5*3, *6 and *7; and CYP3A4*1B, *3 and *22 alleles. Next to pharmacogenetic testing, each patient was classified as very poor, poor, intermediate, rapid or ultrarapid metabolizer according to their own genotype, graft’s genotype or both of them. Patient’s initial dose, at seven days after treatment start and after discharge of tacrolimus and their trough concentrations (C0) were collected from their electronic health records. Tacrolimus levels were measured by affinity chrome-mediated immunoassay. C0 was normalized by weight-adjusted dosage (C/D ratio); then, median C/D ratios between different metabolic profiles were compared through Kruskal-Wallis test. Results When patients were classified based on donor’s genotype isolated or combined with receptor’s genotype, lower C/D ratios were found as metabolizer ability increases (p=0.045 for donors and p=0.027 for combined genotypes, respectively). No statistically differences were found for C/D ratios at seven days and discharge, though that differences were almost significant for donor’s genotypes (p=0.06 in both cases). Conclusions These results show that previous information about both patient’s and specially donor’s CYP genes genotype may improve initial immunosupression and avoid tacrolimus induced toxicity. Pharmacogenetics has been currently proposed as a guide for tacrolimus treatment of some solid organ transplants as kidney transplanted patients. Better understanding of how receptor and donor’s CYP genotype affects its pharmacokinetics, along with liver’s damage markers and other genetic polymorphisms will allow clinicians, in the era of personalized medicine, to improve immunosupressive management.

Effect of TaC content on microstructure and wear behavior of PRMMC Fe-TaC coating manufactured by electrospark deposition on AISI304 stainless steel

The Fe-TaC coatings on stainless steel by electrospark granule deposition in an anode mixture of iron granules and tantalum carbide powder were first obtained. The material deposition rate on the substrate increased with the TaC powder concentration growth in the anode mixture, facilitating the initiation of electrical discharges. X-ray analysis of deposited coatings shows the presence of the TaC, γFe, and αFe phases. The tantalum carbide concentration grows with an increase in the content of TaC powder in the anode mixture, from 2.4 to 14.8 vol%. The dependence of the wear rate of coatings on the concentration of tantalum carbide in the anode mixture had a parabola form, with a minimum of 5 vol%. However, with a further increase in the TaC concentration in the anode mixture, the wear rate of the coatings monotonically increased due to spalling of TaC grains due to a deficiency of the metal binder.

Optimal Trough Concentration of Tacrolimus in Pediatric Patients With Primary Nephrotic Syndrome.

The trough concentration (C0) of tacrolimus in children with nephrotic syndrome (NS) has rarely been explored, so its target level was based on transplant research. This study aimed to determine the optimal tacrolimus C0 in NS children. Data from primary NS children treated with tacrolimus at Wuhan Children's Hospital in the last 10 years were retrospectively collected. According to the cutoff C0 analyzed by receiver-operator characteristics (ROC) analysis, patients were divided into very low- (< 4 ng/mL), low- (4-5 ng/mL), medium- (5-7 ng/mL), and high-concentration (7-10 ng/mL) groups. A total of 196 patients were enrolled for primary outcome analysis. Compared to medium-concentration group, only the very low-concentration group obtained significant inferior primary outcomes, including overall remission rate, relapse-free survival rate, and relapse rate at 6 months. For secondary outcomes, the very low-concentration group experienced more frequent treatment failure in 12 months, whereas the high-concentration group suffered a higher risk of adverse events than the medium-concentration group. For steroid-resistant NS, very low- and low-concentration groups required longer time to achieve remission compared to medium-concentration group. For steroid-sensitive NS, the very low-concentration group suffered a higher relapse frequency than medium-concentration group. Lastly, the dose of tacrolimus required for children with different CYP3A5 genotypes with or without Wuzhi capsules was analyzed. In conclusion, tacrolimus may be targeted to C0 of 4-7 ng/mL during the first 6 months in children with NS. For steroid-resistant NS, C0 of 5-7 ng/mL can achieve a rapid remission.

Guiding the starting dose of the once-daily formulation of tacrolimus in "de novo" adult renal transplant patients: a population approach.

The once-daily extended-release tacrolimus formulation (ER-Tac) has demonstrated similar efficacy and safety to the twice-daily immediate-release formulation (IR-Tac), but few population-based pharmacokinetic models have been developed in de novo kidney transplant patients to optimize doses. Therefore, this study aimed i) at developing a population pharmacokinetic model for ER-Tac in de novo adult kidney transplant patients ii) and identifying genetic factors and time-varying covariates predictive of pharmacokinetic variability to guide tacrolimus dosage during the early post-transplant period. A total of 1,067 blood tacrolimus concentrations from 138 kidney transplant patients were analyzed. A total of 29 out of 138 patients were intensively sampled for 24h on the day 5 post-transplantation; meanwhile, for the remaining patients, concentrations were collected on days 5, 10, and 15 after transplantation. Tacrolimus daily doses and genetic and demographic characteristics were retrieved from the medical files. Biochemistry time-varying covariates were obtained on different days over the pharmacokinetic (PK) study. A simultaneous PK analysis of all concentrations was carried out using the non-linear mixed-effects approach with NONMEM 7.5. A two-compartment model with linear elimination and delayed absorption best described the tacrolimus pharmacokinetics. Between-patient variability was associated with oral blood clearance (CL/F) and the central compartment distribution volume (Vc/F). Tacrolimus concentrations standardized to a hematocrit value of 45% significantly improved the model (p < 0.001). This method outperformed the standard covariate modeling of the hematocrit-blood clearance relationship. The effect of the CYP3A5 genotype was statistically (p < 0.001) and clinically significant on CL/F. The CL/F of patients who were CYP3A5*1 carriers was 51% higher than that of CYP3A5*1 non-carriers. Age also influenced CL/F variability (p < 0.001). Specifically, CL/F declined by 0.0562 units per each increased year from the value estimated in patients who were 60years and younger. The 36% between-patient variability in CL/F was explained by CYP3A5 genotype, age, and hematocrit. Hematocrit standardization to 45% explained the variability of tacrolimus whole-blood concentrations, and this was of utmost importance in order to better interpret whole-blood tacrolimus concentrations during therapeutic drug monitoring. The dose requirements of CYP3A5*/1 carriers in patients aged 60years or younger would be highest, while CYP3A5*/1 non-carriers older than 60years would require the lowest doses.

Optimizing tacrolimus dosing in Hispanic renal transplant patients: insights from real-world data.

Tacrolimus, an immunosuppressant used to prevent organ rejection in renal transplant patients, exhibits high inter-patient variability, necessitating therapeutic drug monitoring. Early post-transplant tacrolimus exposure in Hispanics is understudied. Although genotypic information is linked to pharmacokinetic differences, its clinical application remains limited. This study aimed to use a real-world data-driven, pharmacokinetic model-based approach for tacrolimus in Hispanics to determine a suitable initial dose and design an optimal dose titration strategy by simulations to achieve plasma trough concentration target levels of 10-12ng/mL at the earliest. Sparse concentration-time data of tacrolimus were obtained from electronic medical records for self-identified Hispanic subjects following renal transplant. Rich pharmacokinetic literature data was leveraged to estimate structural pharmacokinetic model parameters, which were then fixed in the current analysis. Only apparent clearance was estimated with the sparse tacrolimus data and potential covariates were identified. Simulations of various starting doses and different dose titration strategies were then evaluated. The analysis included 121 renal transplant patients with 2,215 trough tacrolimus concentrations. A two-compartment transit absorption model with allometrically scaled body weight and time-varying hematocrit on apparent clearance adequately described the data. The estimated apparent clearance was 13.7L/h for a typical patient weighing 70kg and at 30% hematocrit, demonstrating a 40% decrease in clearance compared to other patient populations. Model based simulations indicated the best initial dose for the Hispanic population is 0.1mg/kg/day. The proposed titration strategy, with three dose adjustments based on trough levels of tacrolimus, increased the proportion of patients within the target range (10-12ng/mL) more than 2.5-fold and decreased the proportion of patients outside the therapeutic window by 50% after the first week of treatment. Hispanic renal transplant population showed an estimated 40% decrease of apparent clearance in the typical patient compared to other populations with similar characteristics. The proposed dose adjustment attained the target range rapidly and safely. This study advocates for tailored tacrolimus dosing regimens based on population pharmacokinetics to optimize therapy in Hispanic renal transplant recipients.

Individualized dosing parameters for tacrolimus in the presence of voriconazole: a real-world PopPK study.

Significant increase in tacrolimus exposure was observed during co-administration with voriconazole, and no population pharmacokinetic model exists for tacrolimus in renal transplant recipients receiving voriconazole. To achieve target tacrolimus concentrations, an optimal dosage regimen is required. This study aims to develop individualized dosing parameters through population pharmacokinetic analysis and simulate tacrolimus concentrations under different dosage regimens. We conducted a retrospective study of renal transplant recipients who were hospitalized at the Second Xiangya Hospital of Central South University between January 2016 and March 2021. Subsequently, pharmacokinetic analysis and Monte Carlo simulation were employed for further analysis. Nineteen eligible patients receiving tacrolimus and voriconazole co-therapy were included in the study. We collected 167 blood samples and developed a one-compartment model with first-order absorption and elimination to describe the pharmacokinetic properties of tacrolimus. The final typical values for tacrolimus elimination rate constant (Ka), apparent volume of distribution (V/F), and apparent oral clearance (CL/F) were 8.39h-1, 2690L, and 42.87L/h, respectively. Key covariates in the final model included voriconazole concentration and serum creatinine. Patients with higher voriconazole concentration had lower tacrolimus CL/F and V/F. In addition, higher serum creatinine levels were associated with lower tacrolimus CL/F. Our findings suggest that clinicians can predict tacrolimus concentration and estimate optimal tacrolimus dosage based on voriconazole concentration and serum creatinine. The effect of voriconazole concentration on tacrolimus concentration was more significant than serum creatinine. These findings may inform clinical decision-making in the management of tacrolimus and voriconazole therapy in solid organ transplant recipients.

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

Tacrolimus is widely used to treat pediatric nephrotic range proteinuria (NRP). Diltiazem, a CYP3A4/5 inhibitor, is often administered with tacrolimus, affecting its pharmacokinetic profile. The impact of this combination on tacrolimus exposure, particularly in CYP3A5*3 genetic polymorphism, remains unclear in pediatric NRP patients. This study aimed to evaluate the effects of diltiazem on tacrolimus pharmacokinetics, focusing on the CYP3A5*3 polymorphism. We conducted a retrospective clinical study involving pediatric NRP patients, divided into two groups: those receiving tacrolimus with diltiazem and those receiving tacrolimus alone. Propensity score matching (PSM) was used to balance the baseline characteristics between the groups. We compared daily dose-adjusted trough concentrations (C0/D) of tacrolimus in both the original and PSM cohorts. The influence of diltiazem on tacrolimus C0/D, stratified by CYP3A5*3 genetic polymorphism, was assessed in a self-controlled case series study. Before PSM, the tacrolimus C0/D in patients taking diltiazem was significantly higher compared to those with tacrolimus alone (75.84 vs. 56.86ng/mL per mg/kg, P = 0.034). This finding persisted after PSM (75.84 vs. 46.93ng/mL per mg/kg, P= 0.028). In the self-controlled case study, tacrolimus C0/D elevated about twofold (75.84 vs. 34.76ng/mL per mg/kg, P < 0.001) after diltiazem administration. CYP3A5 expressers (CYP3A5*1/*1 and *1/*3) and CYP3A5 non-expressers (CYP3A5*3/*3) experienced a 1.8-fold and 1.3-fold increase in tacrolimus C0/D when combined with diltiazem, respectively. Diltiazem significantly increased tacrolimus C0/D, with CYP3A5*3 expressers showing higher elevations than non-expressers among pediatric NRP patients. These findings highlight the importance of personalized tacrolimus therapy based on CYP3A5*3 genotypes in pediatric patients taking diltiazem.

Machine-learning model to predict the tacrolimus concentration and suggest optimal dose in liver transplantation recipients: a multicenter retrospective cohort study

Titrating tacrolimus concentration in liver transplantation recipients remains a challenge in the early post-transplant period. This multicenter retrospective cohort study aimed to develop and validate a machine-learning algorithm to predict tacrolimus concentration. Data from 443 patients undergoing liver transplantation between 2017 and 2020 at an academic hospital in South Korea were collected to train machine-learning models. Long short-term memory (LSTM) and gradient-boosted regression tree (GBRT) models were developed using time-series doses and concentrations of tacrolimus with covariates of age, sex, weight, height, liver enzymes, total bilirubin, international normalized ratio, albumin, serum creatinine, and hematocrit. We conducted performance comparisons with linear regression and populational pharmacokinetic models, followed by external validation using the eICU Collaborative Research Database collected in the United States between 2014 and 2015. In the external validation, the LSTM outperformed the GBRT, linear regression, and populational pharmacokinetic models with median performance error (8.8%, 25.3%, 13.9%, and − 11.4%, respectively; P < 0.001) and median absolute performance error (22.3%, 33.1%, 26.8%, and 23.4%, respectively; P < 0.001). Dosing based on the LSTM model’s suggestions achieved therapeutic concentrations more frequently on the chi-square test (P < 0.001). Patients who received doses outside the suggested range were associated with longer ICU stays by an average of 2.5 days (P = 0.042). In conclusion, machine learning models showed excellent performance in predicting tacrolimus concentration in liver transplantation recipients and can be useful for concentration titration in these patients.

Population pharmacokinetics study of tacrolimus in liver transplant recipients: a comparison between patients with or without liver cancer before surgery.

The main challenge for immunosuppressive therapy using tacrolimus in liver transplantation is the considerable variability in its oral bioavailability and the narrow treatment range. Many population pharmacokinetic (PopPK) models have been established to precisely estimate the PK variability of tacrolimus in liver transplant recipients. However, it remains unclear whether there is a significant difference in the PK behavior of tacrolimus between patients with or without liver cancer before surgery. Therefore, we aimed to compare the differences of PK parameters and simulate exposures of tacrolimus between populations preoperatively diagnosed with liver cancer or not by PopPK modeling. In total, 802 blood concentrations of tacrolimus from 196 patients (118 liver cancer and 78 non-liver-cancer samples) were included in this study. Demographic data and clinical parameters were integrated to perform a PopPK analysis using the nonlinear mixed-effects modeling approach. Potential covariates were evaluated by using a stepwise method. Goodness-of-fit plot and bootstrap were performed to assess the model stability and predictive performance. Simulations were introduced to optimize dosing regimens of both the liver cancer and non-liver-cancer groups according to the guidance. The PK of tacrolimus was best described by a one-compartment model with first-order absorption and linear elimination, with weight and direct bilirubin as the significant covariates. In the process of constructing the basic model, we tried to separately estimate the PK parameters in liver cancer and non-liver-cancer populations. The results showed that the PK parameters in the two populations were similar, and the individual variation in Ka in non-liver-cancer subjects was large. Hence, the final model did not distinguish between the two populations. Moreover, a minor increase of less than 10% was observed in the simulated exposure in the patients preoperatively diagnosed with liver cancer compared with that in non-liver-cancer groups. The established PopPK model was capable of optimizing tacrolimus dosing in whole populations who underwent liver transplantation. Although a minimal difference was found in tacrolimus exposure between the liver cancer and non-liver-cancer groups, more research is warranted to explore the differences between the two populations in the future, given the potential limitations of this study.

Prediction of the Intra-T Lymphocyte Tacrolimus Concentration after Kidney Transplantation with Population Pharmacokinetic Modeling.

The intracellular tacrolimus concentration in CD3+ T lymphocytes is proposed to be a better representative of the active component of tacrolimus than the whole blood concentration. However, intracellular measurements are complicated. Therefore, the aim of this study was to describe the relationship between intracellular and whole blood tacrolimus concentrations in a population pharmacokinetic model. Twenty-eight de novo kidney transplant recipients, treated with a once-daily oral extended-release tacrolimus formulation, were followed during the first-month post-transplantation. Additional whole blood and intracellular tacrolimus concentrations were measured at day 6 ± 1 (pre-dose, 4 and 8 hours post-dose) and day 14 ± 3 (pre-dose) post-transplantation. Pharmacokinetic analysis was performed using nonlinear mixed effects modeling software (NONMEM). The ratio between intracellular (n = 109) and whole blood (n = 248) concentrations was best described by a two-compartment whole blood model with an additional intracellular compartment without mass transfer from the central compartment. The ratio remained stable over time. Prednisolone dose influenced the absorption rate of tacrolimus, while hemoglobin, CYP3A4*22 allele carrier, and CYP3A5 expresser status were associated with the oral clearance of tacrolimus (P-value < 0.001). Furthermore, the intracellular tacrolimus concentrations were correlated with the intracellular production of interleukin-2 (P-value 0.015). The intracellular tacrolimus concentration can be predicted from a measured whole blood concentration using this model, without the need for repeated intracellular measurements. This knowledge is particularly important when the intracellular concentration is ready to be implemented into clinical practice, to overcome the complexities of cell isolation and analytical methods.