Tacrolimus Blood Concentrations Research Articles

Influence of Genetic Polymorphisms in CYP3A5, CYP3A4, and MDR1 on Tacrolimus Metabolism after kidney transplantation

Kidney transplantation stands as the ultimate recourse for restoring vital organ functions, particularly in cases of end-stage kidney disease where alternative treatments, such as dialysis, prove less effective. With over 102,000 kidney transplants conducted globally in 2022, the demand for organ transplantation is ever-increasing, fueled by a rising incidence of end-stage renal disease attributed to causes like diabetes and hypertension.<br /> Despite significant advancements in kidney transplantation, immunosuppressive therapy remains crucial to preventing graft rejection. Tacrolimus (TAC), a calcineurin inhibitor, plays a pivotal role in this regard. Discovered in 1984, TAC inhibits T-lymphocyte activation, preventing acute rejection by disrupting the transcription of crucial genes involved in early T-cell activation. However, the use of TAC is not without challenges. The drug exhibits serious side effects, a narrow therapeutic index, and unpredictable pharmacokinetics. Therapeutic drug monitoring (TDM) becomes imperative in daily practice to maintain TAC blood concentrations within the therapeutic range. This literature review delves into the genetic aspects influencing TAC metabolism, focusing on key polymorphisms in CYP3A5, CYP3A4, and ABCB1 genes. Genetic variations in CYP3A5, a major enzyme in TAC metabolism, impact enzyme activity, necessitating personalized dosing strategies. CYP3A4 polymorphisms, especially CYP3A4*22, demonstrate associations with altered TAC clearance and dose requirements. The ABCB1 gene, encoding P-glycoprotein, another player in TAC pharmacokinetics, also exhibits polymorphisms influencing drug absorption and distribution. The ABCB1 3435C>T variant, in particular, shows potential implications on Tacrolimus bioavailability. Understanding these genetic variations aids in the development of personalized dosing regimens. Studies suggest that tailoring TAC doses based on CYP3A5 genotypes significantly improves the proportion of patients achieving therapeutic concentrations. Additionally, incorporating genetic information, particularly CYP3A4*22, into dosing strategies enhances the precision of TAC therapy, reducing the risk of adverse effects.

Tacrolimus Monitoring in Liver Transplant Recipients, Posttransplant Cholestasis: A Comparative Between 2 Commercial Immunoassays and a Liquid Chromatography-Tandem Mass Spectrometry Method.

Cholestasis commonly occurs after orthotopic liver transplantation. It can be extrahepatic because of mechanical obstruction or intrahepatic because of various causes. During cholestasis episodes, blood concentrations of tacrolimus (TAC) metabolites may increase, potentially affecting TAC concentrations measured by immunoassays. This study aimed to simultaneously evaluate the analytical performance of 2 TAC immunoassays, a quantitative microsphere system (QMS) immunoassay, and chemiluminescence microparticle immunoassay, using liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a reference method in liver transplant recipients. This single-center study included 265 patients who underwent orthotopic liver transplantation. In total, 942 blood samples were collected. TAC trough concentrations were measured using LC-MS/MS and 2 immunoassays in parallel. The plasma concentrations of conjugated bilirubin were measured in all samples. The results were analyzed using Bland-Altman plots and Passing-Bablok regressions. The Bland-Altman plot analysis showed that the TAC QMS immunoassay has a significant bias (+37%) compared with LC-MS/MS, and this bias was higher in patients with cholestasis with hyperbilirubinemia (≤+70% in patients with conjugated bilirubin >150 µmol/L). In comparison, the chemiluminescence microparticle immunoassay showed acceptable analytical performance in patients with hyperbilirubinemia (bias <10%). In agreement with previous findings, the TAC QMS immunoassay showed a positive bias compared with LC-MS/MS. This bias is remarkably high in patients with cholestasis and hyperbilirubinemia, suggesting the cross-reactivity of TAC metabolites with the monoclonal antibody used in the QMS immunoassay.

The efficacy and safety of tacrolimus in treating refractory IgA vasculitis nephritis: a single-center retrospective study on 16 cases.

This study aimed to observe the efficacy and safety of tacrolimus in the treatment of refractory immunoglobulin A vasculitis nephritis (IgAVN). Sixteen patients with IgAVN who had been previously treated with cyclophosphamide shock therapy at least five times, some of whom had also received mycophenolate but still had persistent proteinuria, were enrolled. The clinical and pathological data were collected and analysed. The average (mean±standard deviation) age at the initial assessment for the group of 16 patients was 10±2.7years. Finally, at the end of their respective follow-up time point, 6 of the 16 patients achieved complete remission (37.5%), 5 achieved partial remission (31.2%), and 5 had no remission (31.2%). A significant difference was found in the median proteinuria before and after a 6-month course of tacrolimus treatment [19.2 (11.2, 31.9) vs 7.8 (4.3, 13.9) mg/kg/day] (P<.05). During the first 6months of tacrolimus treatment, all patients' estimated glomerular filtration rate levels remained normal. The mean tacrolimus blood concentration was 6.0±2.6ng/mL. The median prednisone dosage was decreased from 10mg/day to 5mg/day, and prednisone was eventually stopped in three individuals. No drug-related adverse effects were observed during treatment. Tacrolimus has demonstrated efficacy in increasing remission rates, significantly lowering urinary protein levels, and reducing steroid use in children with refractory IgAVN. Further research is required to investigate its optimal blood concentrations, long-term effects and renoprotective properties.

Effect of Voriconazole on Tacrolimus Blood Concentration in Renal Transplant Recipients after Voriconazole Discontinuation

Effect of Voriconazole on Tacrolimus Blood Concentration in Renal Transplant Recipients after Voriconazole Discontinuation

Drug-drug interaction between tacrolimus and caspofungin in Chinese kidney transplant patients with different CYP3A5 genotypes.

The effect of drug-drug interaction between tacrolimus and caspofungin on the pharmacokinetics of tacrolimus in different CYP3A5 genotypes has not been reported in previous studies. To investigate the effect of caspofungin on the blood concentration and dose of tacrolimus under different CYP3A5 genotypes. We conducted a retrospective cohort study in The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital from January 2015 to December 2022. All kidney transplant patients were divided into the combination or non-combination group based on whether tacrolimus was combined with caspofungin or not. Patients were subdivided into CYP3A5 expressers (CYP3A5*1/*1 or CYP3A5*1/*3) and CYP3A5 non-expressers (CYP3A5*3/*3). Data from the combination and the non-combination groups were matched with propensity scores to reduce confounding by SPSS 22.0. A total of 200 kidney transplant patients receiving tacrolimus combined with caspofungin or not were enrolled in this study. Statistical analysis was conducted on the dose-corrected trough concentrations (C0/D) and dose requirements (D) of tacrolimus using independent sample two-sided t-test and nonparametric tests to investigate the impact on patients with different. In this study, the C0/D values of tacrolimus were not significantly different between the combination and non-combination groups (p = 0.054). For CYP3A5 expressers, there was no significant difference in tacrolimus C0/D or D values between the combination and non-combination groups (p = 0.359; p = 0.851). In CYP3A5 nonexpressers, the C0/D values of tacrolimus were significantly lower in the combination than in the non-combination groups (p = 0.039), and the required daily dose of tacrolimus was increased by 11.11% in the combination group. Co-administration of caspofungin reduced tacrolimus blood levels and elevated the required daily dose of tacrolimus. In CYP3A5 non-expressers, co-administration of caspofungin had a significant effect on tacrolimus C0/D values. An approximate 10% increase in the weight-adjusted daily dose of tacrolimus in CYP3A5 non-expressers is recommended to ensure the safety of tacrolimus administration.

Elevation of tacrolimus concentration after administration of methotrexate for treatment of graft-versus-host disease in pediatric patients received allogeneic hematopoietic stem cell transplantation

BackgroundMethotrexate (MTX) is used to treat graft-versus-host disease (GVHD) following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Recently, a case was encountered in which the blood concentration of tacrolimus (TCR) at steady state increased after intravenous MTX administration for GVHD treatment (therapeutic IV-MTX administration). Therefore, this study aimed to investigate the effect of therapeutic IV-MTX administration on the pharmacokinetics of TCR.MethodsThis single-center, retrospective, observational study included patients who underwent allo-HSCT and received therapeutic IV-MTX administration during immunosuppressive therapy with continuous intravenous infusion (CIV) of TCR from April 2004 to December 2021. Here, each therapeutic IV-MTX administration was defined as a case and independently subjected to subsequent analyses. The blood concentration of TCR at steady state (Css), ratio of Css to daily TCR dose (C/D), and clinical laboratory data were compared before and after therapeutic IV-MTX administration. In addition, dose changes in the TCR after therapeutic IV-MTX administration were evaluated.ResultsTen patients (23 cases) were included in this study. The C/D value significantly increased after therapeutic IV-MTX administration (median: 697 vs. 771 (ng/mL)/(mg/kg), 1.16-fold increase, P < 0.05), indicating a reduction in the apparent clearance of TCR. Along with the increase in C/D, significant increases were observed in aspartate transaminase level (median: 51.0 vs. 92.9 U/L, P < 0.01) and alanine aminotransferase level (median: 74.5 vs. 99.4 U/L, P < 0.01) indicating that liver injury after therapeutic IV-MTX administration contributes to the observed C/D increase. In addition, the daily dose of TCR was reduced in 11 cases (47.8%) after therapeutic IV-MTX administration, and the relative frequency of dose reduction tended to be higher than that of dose increase (median: 37.5% vs. 0.0%, P = 0.0519, permuted Brunner-Munzel test). The magnitude of dose reduction was 18.8% (7.4–50.0%) in the 11 cases with dose reduction.ConclusionsTherapeutic IV-MTX administration cause a significant increase in C/D, which requires TCR dose reduction. Careful therapeutic drug monitoring of TCR is needed after therapeutic IV-MTX administration in patients receiving immunosuppressive therapy with TCR after allo-HSCT.

The Area Under Tacrolimus Concentrations on Day 14-28 Is the Independent Predictor of the Development of Chronic Gvhd in Patients without Severe Acute Gvhd after Unrelated Allogeneic HSCT

Introduction: In unrelated allogeneic hematopoietic stem cell transplantation (UR-SCT), chronic graft-versus-host disease (GVHD) is a critical complication that affects not only patients' quality of life but also post-transplant outcome. Acute GVHD is a major risk factor for the subsequent development of chronic GVHD. The combination of tacrolimus and short-term methotrexate (TAC+sMTX) has been widely used as a GVHD prophylaxis for UR-SCT in Japan. Previous reports have shown that tacrolimus blood concentrations early after transplantation are associated with the development of acute GVHD, but not with that of chronic GVHD. On the other hand, among UR-SCT recipients who did not develop severe acute GVHD, the relationship between tacrolimus blood concentrations and the development of chronic GVHD remains unclear. Methods: To examine the association between tacrolimus blood concentrations and post-transplant outcomes, the area under the tacrolimus concentration on day 0-14 (AUTC 0-14) and day 14-28 (AUTC 14-28) was calculated simply as the sum of the area of the trapezoid for the corresponding period ( Figure). Tacrolimus was initiated by continuous intravenous administration from day -1 in all patients, and no patients were switched to oral administration prior to day 28. Short-term methotrexate was administered at 10 mg/m 2 on day 1 and 7 mg/m 2 on day 3, day 6, and day 11. Among all 151 adult patients with hematopoietic malignancies who underwent first UR-SCT with GVHD prophylaxis of TAC+sMTX between 2010 and 2022 at the Jikei University Hospital, the following were excluded from the analysis: developing grade III-to-IV acute GVHD, using prednisolone or methyl-prednisolone ≥0.5 mg/kg within day 100, engraftment failure, death before day 100, and relapse before day 100. Results: A total of 68 patients were included in the analysis. Median age was 50.5 (range, 16-68) years. Twenty-seven (40%) patients had acute myeloid leukemia, and 18 (27%) had acute lymphoblastic leukemia. Fifty-five (81%) were in complete remission/chronic phase/early stage. The donor source consisted of 42 (62%) bone marrow transplantation (BMT), 20 (29%) cord blood transplantation (CBT), and 6 (9%) peripheral blood stem cell transplantation (PBSCT). BMT recipients transplanted from 22 (52%) HLA 8/8 matched donor, 19 (45%) HLA 7/8 matched donor, and one (3%) HLA 6/8 matched donor. CBT recipients transplanted from 15 (75%) HLA 4/6 matched donor and 5 (25%) HLA 5/6 matched donor. PBSCT recipients transplanted from 5 (83%) HLA 8/8 matched donor and one (17%) HLA 7/8 matched donor. Fifteen (22%) patients were administered additional low-dose anti-thymocyte globulin (ATG) as GVHD prophylaxis. Fifteen male patients transplanted from female donors (22%). Thirty-nine (57%) patients received myeloablative conditioning regimen. The median time from UR-SCT to neutrophil engraftment was 19 days (range, 11-34). Regarding acute GVHD, 46 patients (68%) developed none, 13 patients (19%) developed grade I, and 9 patients (13%) developed grade II. The median observation period for all 68 patients was 48.2 months (4.0 years). The 4-year cumulative incidence (CI) of chronic GVHD was 51%, of which 24% were moderate-to-severe. The CI of moderate-to-severe chronic GVHD was not associated with age, disease status, donor source, HLA incompatibility, ATG use, female to male, intensity of conditioning regimen, and grade I-to-II acute GVHD development. AUTC 14-28 &amp;lt;200 was the only risk factor (AUTC 14-28&amp;lt;200: 32% vs AUTC 14-28≥200: 11%; p=0.047). Multivariate analysis also showed that AUTC 14-28 &amp;lt;200 was the independent factor for development of moderate-to-severe chronic GVHD ( p=0.04). In all 68 patients, 4-year CI of relapse was 20%, 4-year CI of non-relapse mortality was 10%, 4-year GVHD-free, relapse-free, survival (GRFS) was 50%, and 4-year Overall survival was 80%, all of which did not differ between AUTC 14-28 &amp;lt;200 and AUTC 14-28 ≥200 groups. Conclusion: In UR-SCT, our data showed that AUTC 14-28 &amp;lt;200 may be an independent risk factor for developing moderate-to-severe chronic GVHD, even in patients who did not develop severe acute GVHD.

Clinical Effects of Tacrolimus Blood Concentrations Early after Allogeneic Hematopoietic Stem Cell Transplantation

Tacrolimus (TAC) plus short-term methotrexate (stMTX) is used for graft-versus-host disease (GVHD) prophylaxis after allogeneic hematopoietic stem cell transplantation (allo-HSCT). TAC blood concentrations are frequently adjusted to enhance the graft-versus-leukemia/lymphoma effect or attenuate severe GVHD. Limited information is available on the clinical impact of these adjustments and the optimal time to perform them in order to achieve good clinical outcomes. We retrospectively analyzed 211 patients who underwent allo-HSCT at our institutes. Higher TAC concentrations in week 3 correlated with a significantly higher cumulative incidence of relapse (CIR) (p=0.03) and lower non-relapse mortality (p=0.04). The clinical impact of high TAC concentrations in week 3 on CIR was detected in the refined disease risk index: low/intermediate (p=0.04) and high (p&amp;lt;0.01), and conditioning regimens other than cyclophosphamide/total body irradiation and busulfan/cyclophosphamide (p=0.07). Higher TAC concentrations in week 1 correlated with a lower grade 2-4 acute GVHD rate (p=0.01). Higher TAC concentrations in weeks 2 and 3 correlated with slightly lower (p=0.05) and significantly lower (p=0.02) grade 3-4 acute GVHD rates, respectively. Higher TAC concentrations in weeks 1 and 3 were beneficial for severe acute GVHD in patients with a human leukocyte antigen-matched donor (p=0.03 and p&amp;lt;0.01, respectively), not treated with anti-thymocyte globulin (p=0.02 and p=0.02, respectively), and receiving three stMTX doses (p=0.03 and p=0.02, respectively). The clinical impact of TAC concentrations varied according to patient characteristics, including disease malignancy, conditioning regimens, donor sources, and GVHD prophylaxis. These results suggest that TAC management needs to be based on patient profiles.

Influencing factors of post-transplantation diabetes mellitus in kidney transplant recipients and establishment of a risk prediction model.

The aim was to explore the influencing factors of post-trans-plantation diabetes mellitus (PTDM) in kidney transplant recipients and to es-tablish a risk prediction model. A retrospective analysis was performed on the clinical data of 408 patients subjected to kidney transplantation from May 2015 to March 2022. With the simple random sampling method, they were divided into a training set (n=306) and a test set (n=102) at a ratio of 3:1. According to the occurrence of PTDM, the training set was further classified into PTDM and non-PTDM groups. The influencing factors of PTDM were identified by least absolute shrinkage and selection operator and multivariate logistic regression analysis. A nomogram prediction model was constructed and validated. Non-PT-DM and PTDM groups had significantly different preoperative body mass index (BMI), family history of diabetes mellitus, 2-h preoperative and postprandial blood glucose, 2-hpreoperative and postprandial peptide index, postoperative hypomagnesemia, whole blood concentration of tacrolimus, triacylglycerol, glycated albumin and fasting blood glucose (P&lt;0.05). BMI, family history of diabetes mellitus, 2-h preoperative and postprandial blood glucose, and post-operative whole blood tacrolimus concentration were independent risk factors for PTDM. In contrast, the 2-h preoperative and postprandial peptide index was an independent protective factor (P&lt;0.05). The incidence of PTDM in patients receiving kidney transplantation correlates with the family history of diabetes mellitus, preoperative BMI, 2-h postprandial blood glucose, 2-h postprandial peptide index, and postoperative whole blood tacrolimus concentration.

Effects of CYP3A5 Genotypes on Thrombocytopenia in Liver Transplantation Patients Treated with Tacrolimus.

Thrombocytopenia is a complication after liver transplantation. This study's aims were to evaluate the role of CYP3A5 genotypes on tacrolimus-induced thrombocytopenia after orthotopic liver transplantation. In this retrospective case-control study, data from 100 patients who underwent deceased-donor liver transplantation (DDLT) were divided into CYP3A5*3 genotype (donor/recipient) tacrolimus fast- (A*/A*, n = 22), intermediate- (A*/GG, n = 20; GG/A*, n = 31) and slow-metabolizer (GG/GG, n = 27) groups. Platelet count changes and prognosis for 180 days after surgery were compared. Platelet counts declined significantly after DDLT, especially on postoperative day (POD) 3, and continued at low levels for a week thereafter in all groups. In the GG/GG group, platelet counts on POD3 (50.29 ± 5.44 × 109/L) were the lowest among the groups (A*/A*, 71.00 ± 6.22 × 109/L; A*/GG, 57.95 ± 6.21 × 109/L; GG/A*, 75.90 ± 5.56 × 109/L) (p = 0.006). Compared with the A*/A* genotype, tacrolimus nadir levels were significantly higher in GG/GG genotype patients, who also exhibited a higher incidence of hemorrhage (22.2%, p = 0.011). A combination of a nadir blood concentration of tacrolimus ≥ 4.74 ng/mL and spleen size ≥ 165.5 mm was a risk factor for increased thrombocytopenia after DDLT on POD3, with an AUC of 0.735 (sensitivity, 77.2%; specificity, 41.7%). A high blood concentration of tacrolimus after the early stage of DDLT is a major risk factor for hemorrhage. For the CYP3A5 genotype (GG/GG), controlling the blood concentration of tacrolimus below the target concentration until POD3 can avoid thrombocytopenia-related complications.

Machine Learning Models for Predicting Personalized Tacrolimus Stable Dosages in Pediatric Renal Transplant Patients

Tacrolimus, characterized by a narrow therapeutic index, significant toxicity, adverse effects, and interindividual variability, necessitates frequent therapeutic drug monitoring and dose adjustments in renal transplant recipients. This study aimed to compare machine learning (ML) models utilizing pharmacokinetic data to predict tacrolimus blood concentration. This prediction underpins crucial dose adjustments, emphasizing patient safety. The investigation focuses on a pediatric cohort. A subset served as the derivation cohort, creating the dose-prediction algorithm, while the remaining data formed the validation cohort. The study employed various ML models, including artificial neural network, RandomForestRegressor, LGBMRegressor, XGBRegressor, AdaBoostRegressor, BaggingRegressor, ExtraTreesRegressor, KNeighborsRegressor, and support vector regression, and their performances were compared. Although all models yielded favorable fit outcomes, the ExtraTreesRegressor (ETR) exhibited superior performance. It achieved measures of −0.161 for MPE, 0.995 for AFE, 1.063 for AAFE, and 0.8 for R2, indicating accurate predictions and meeting regulatory standards. The findings underscore ML’s predictive potential, despite the limited number of samples available. To address this issue, resampling was utilized, offering a viable solution within medical datasets for developing this pioneering study to predict tacrolimus trough concentration in pediatric transplant recipients.

Tacrolimus-associated sinusoidal obstruction syndrome after living-related liver transplantation

Sinusoidal obstruction syndrome (SOS), previously known as hepatic veno-occlusive disease, is manifested by obliterating inflammation of the terminal hepatic veins, characterized by hepatomegaly, right upper quadrant pain, jaundice and ascites, and most often occurs in patients after hematopoietic stem cell transplantation and usually in those who received platinum-based drugs. Cases of SOS development in patients after transplantation of solid organs (lungs, pancreas, liver) are also reported in the world literature. These incidents are rare, and isolated and poorly studied after living-related liver lobe transplantation. The diagnosis is based on clinical signs, imaging techniques (according to ultrasound and radiological methods of examination), histological assessment of liver biopsy. Tacrolimus has been reported to be a causative agent that potentially plays a role in the pathophysiological mechanism of SOS. Aim. To study the relationship between the use of prolonged-release tacrolimus and the development of SOS in patients after living-related liver transplantation. Clinical case. In this article, we present a case of SOS after living-related liver transplantation which was associated with a toxic effect of prolonged-release tacrolimus (“Envarsus”). In a 55-year-old man, after living-related liver transplantation, high blood concentrations of tacrolimus associated with uncontrolled drug intake were detected. When performing a number of laboratory and instrumental methods of examination due to a massive ascites manifestation, the diagnosis of SOS was made. The study was carried out in accordance with the principles of the Helsinki Declaration. The informed consent was obtained from the patient for conducting the studies. Conclusions. By ruling out other possible contributing factors, including an acute rejection crisis, it was concluded that prolonged-release tacrolimus (“Envarsus”) was the cause of SOS.

B-320 Development of Two-step Sandwich CLEIA Kit for Tacrolimus With Automated Sample-Pretreatment Process, LUMIPULSE Presto® iTACT® Tacrolimus

Abstract Background Tacrolimus (The other name: FK506) is an immunosuppressive drug used for preventing rejection of allotransplantation and treating atopic dermatitis or rheumatoid arthritis. The complex consisting of Tacrolimus and FK506 binding protein binds to calcineurin and suppresses expression of Interleukin-2 (IL-2) and IL-2 induced immune response. Although tacrolimus is a useful immunosuppressive drug, this medicine causes serious side effects, such as renal dysfunction, opportunistic infections due to the excessive immunosuppression, and so on. Therefore, the measurement of the tacrolimus concentration in blood is required to obtain the maximum tacrolimus therapeutic effect without side effects. It is known that 95 percent of tacrolimus in blood localizes in the inside of erythrocyte, and this localization imposes cumbersome pretreatment process of whole blood. Almost all diagnostic reagents for tacrolimus need the manual whole blood pretreatment process that defaces the reliability of measurement values. And the existing diagnostic reagents often show the high cross-reactivity against the metabolite products of tacrolimus. To solve these inconveniences, we developed a highly-specific chemiluminescence enzyme immunoassay (CLEIA) for tacrolimus using a new automated sample-pretreatment process on a fully automated LUMIPULSE® L2400 analyzer. In this study, we report the basic performance of this new tacrolimus assay named as LUMIPULSE Presto® iTACT® Tacrolimus. Methods LUMIPULSE Presto® iTACT® Tacrolimus is the two-step sandwich CLEIA with the on-board sample-pretreatment process. All evaluations were executed on LUMIPULSE® L2400 analyzer (FUJIREBIO INC.). The on-board sample-pretreatment process is performed simultaneously with the first immune-reaction in sandwich CLEIA, and the total reaction time is 20 min. Limit of detection (LoD) and Limit of quantification (LoQ), within-run precision, day-to-day reproducibility, linearity, endogenous interferences, anticoagulative interferences, tacrolimus metabolites interferences and the correlation with current tacrolimus assay were evaluated in LUMIPULSE Presto® iTACT® Tacrolimus. Results Both of LoD and LoQ of LUMIPULSE Presto® iTACT® Tacrolimus were 0.12 ng/mL. Within-run precisions (% CVs) using three control samples were 0.4%–2.5%. Day-to-day reproducibility in five days were 0.4%–1.9%. We determined the linearity ranged from 0.29 to 48.80 ng/mL. Up to 19.7 mg/dL of conjugated bilirubin, 18.8 mg/dL of free bilirubin, 1620 FTU of chyle, 2000 mg/dL of triglycerides, 1000 IU/mL of RF, and 1010 ng/mL of HAMA, and 4–12 g/dL of proteins including albumin did not affect tacrolimus measurements. In addition, there was no influence by EDTA 2K and EDTA 2Na up to 10 mg/mL. The cross-reactivities of four tacrolimus metabolites (M-I, M-II, M-III, and M-IV) were respectively 0.4%–1.0%, 0.0%–0.8%, -0.7%–0.2%, and 0.7%–1.6%. Comparing to the existing chemiluminescence immunoassay (CLIA) with 128 specimens, the correlation coefficient was 1.0, and the slope calculated by Passing-Bablok method is 1.04. Comparing to the existing electrochemiluminescence immunoassay (ECLIA) with 137 specimens, the correlation coefficient was 1.0, and the slope calculated by Passing-Bablok method is 1.07. Conclusion The fundamental performance of LUMIPULSE Presto® iTACT® Tacrolimus is satisfactory and the on-board sample-pretreatment process of this assay is expected to contribute to reducing the burden and inconvenience of laboratory personnel.

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

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

Viral rebound and safety of nirmatrelvir/ritonavir for lung-transplant recipients infected with SARS-CoV-2

Data on the viral rebound and safety of nirmatrelvir/ritonavir in lung transplant (LTx) recipients are limited. The study prospectively followed four LTx recipients. Clinical characteristics, viral RNA dynamic in throat swabs, and tacrolimus blood concentration were monitored regularly. All four LTx recipients, aged 35–74 years, were not vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). They got coronavirus disease 2019 (COVID-19) after more than one week of admission during the era of Omicron. All cases received nirmatrelvir/ritonavir (NM/r) within two days of infection, and the relative viral RNA copies dropped quickly. Viral load rebound was observed in all four cases after discontinuation of the first five days of NM/r treatment. Three of them received another 5-days antiviral therapy with NM/r. The duration of positive viral PCR testing was 25-28 days. None of them progressed into severe or critical COVID-19. Tacrolimus was stopped 12 h before NM/r and held during the 5-day course of antiviral therapy. Blood concentration of tacrolimus were maintained at a baseline level during these five days. Tacrolimus was re‐initiated at its baseline daily dose 3-4 days after NM/r therapy. However, during the second round of antiviral therapy with NM/r, the concentration of tacrolimus fluctuated wildly. In conclusion, the 5-day course of NM/r treatment was not sufficient for LTx recipients and the viral rebound was common. More data are needed to clarify whether LTx recipients with SARS-CoV-2 viral rebound could benefit from additional treatment with NM/r.

A model-based pharmacokinetic assessment of drug–drug interaction between tacrolimus and nirmatrelvir/ritonavir in a kidney transplant patient with COVID-19

We experienced a patient with a remarkable and prolonged increase in tacrolimus blood concentrations when nirmatrelvir/ritonavir was concomitantly used. The inhibitory intensity and duration of nirmatrelvir/ritonavir on tacrolimus pharmacokinetics were examined using a model-based analysis. A renal transplant patient taking oral tacrolimus continuously was treated with nirmatrelvir/ritonavir for 5 days. The baseline tacrolimus trough blood concentration was 4.2 ng/mL. Tacrolimus was discontinued on Day 6 after the concomitant administration of nirmatrelvir/ritonavir, and the trough concentration increased to 96.4 ng/mL on Day 7. The model-based analysis showed that tacrolimus clearance decreased to 35% and bioavailability increased by 18.7-fold after the coadministration of nirmatrelvir/ritonavir, compared with before the coadministration. Therefore, nirmatrelvir/ritonavir drastically decreased both the apparent clearance and apparent volume of distribution. Simulated tacrolimus concentrations could be best fitted to the observed concentrations when the inhibitory effects of nirmatrelvir/ritonavir were modeled to disappear over about 10 days by first-order elimination. In conclusion, nirmatrelvir/ritonavir greatly increases tacrolimus concentrations by not only reducing clearance, but also increasing bioavailability. Interactions between nirmatrelvir/ritonavir and low-bioavailability drugs which are substrates for CYP3A and P-glycoprotein, such as tacrolimus, are harmful, and concomitant use of these medicines should be avoided.

Artificial Neural Network Analysis of Determinants of Tacrolimus Pharmacokinetics in Liver Transplant Recipients.

The efficacy and toxicity of tacrolimus are closely related to its trough blood concentrations. Identifying the influencing factors of pharmacokinetics of tacrolimus in the early postoperative period is conducive to the optimization of the individualized tacrolimus administration protocol and to help liver transplant (LT) recipients achieve the target blood concentrations. This study aimed to develop an artificial neural network (ANN) for predicting the blood concentration of tacrolimus soon after liver transplantation and for identifying determinants of the concentration based on Shapley additive explanation (SHAP). In this retrospective study, we enrolled 31 recipients who were first treated with liver transplantation from the Department of Liver Transplantation and Hepatic Surgery, the First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) from November 2020 to May 2021. The basic information, biochemical indexes, use of concomitant drugs, and genetic factors of organ donors and recipients were used for the ANN model inputs, and the output was the steady-state trough concentration (C0) of tacrolimus after oral administration in LT recipients. The ANN model was established to predict C0 of tacrolimus, SHAP was applied to the trained model, and the SHAP value of each input was calculated to analyze quantitatively the influencing factors for the output C0. A back-propagation ANN model with 3 hidden layers was established using deep learning. The mean prediction error was 0.27 ± 0.75 ng/mL; mean absolute error, 0.60 ± 0.52 ng/mL; correlation coefficient between predicted and actual C0 values, 0.9677; and absolute prediction error of all blood concentrations obtained by the ANN model, ≤3.0 ng/mL. The results indicated that the following factors had the most significant effect on C0: age, daily drug dose, genotype at CYP3A5 polymorphism rs776746 in both recipient and donor, and concomitant use of caspofungin. The predicted C0 value of tacrolimus in LT recipients increased in a dose-dependent manner when the daily dose exceeded 3 mg, whereas it decreased with age when LT recipients were older than 48 years. The predicted C0 was higher when recipients and donors had the genotype CYP3A5*3*3 than when they had the genotype CYP3A5*1. The predicted C0 value also increased with the use of caspofungin or Wuzhi capsule. The established ANN model can be used to predict the C0 value of tacrolimus in LT recipients with high accuracy and good predictive ability, serving as a reference for personalized treatment in the early stage after liver transplantation.

A highly sensitive method for determination of tacrolimus in peripheral blood mononuclear cells by nano liquid chromatography–high resolution accurate mass spectrometry

The determination of intracellular tacrolimus concentration in peripheral blood mononuclear cells (PBMCs) is crucial for assessing the effect-site concentration of tacrolimus. Analytical methods previously reported required a minimum of 3 mL of whole blood sample for measuring the tacrolimus concentration. In this study, we developed a highly sensitive method using EASY nLC 1200 combined with Q Exactive orbitrap mass spectrometer for detecting tacrolimus in PBMCs, requiring only 0.5–2 mL of sample. Furthermore, we compared two primary normalization methods for PBMCs tacrolimus concentration using Passing–Bablok regression, Bland–Altman analysis, Spearman's rank correlation, and Mountain plot. The newly established method was employed to compare tacrolimus concentrations in whole blood and PBMCs among 194 lung transplant recipients. The developed method exhibited high sensitivity with a lower limit of quantitation at 5 pg/mL, and excellent intra- and inter-days accuracy and precision. The comparison between different normalization methods for PBMCs tacrolimus concentration revealed a strong correlation between PBMCs count and intracellular protein amount within these cells. This finding suggests that both PBMCs count and intracellular protein amount can be used for normalizing intracellular tacrolimus levels and can be mutually converted. However, a weaker correlation was observed between PBMCs and whole-blood tacrolimus concentrations in lung transplant recipients, warranting further investigation. The method reported herein enables the quantification of PBMCs tacrolimus concentration using smaller volumes of whole blood samples, which has significant implications for both patients and laboratory personnel.

A Joint Pharmacokinetic Model for the Simultaneous Description of Plasma and Whole Blood Tacrolimus Concentrations in Kidney and Lung Transplant Recipients.

Historically, dosing of tacrolimus is guided by therapeutic drug monitoring (TDM) of the whole blood concentration, which is strongly influenced by haematocrit. The therapeutic and adverse effects are however expected to be driven by the unbound exposure, which could be better represented by measuring plasma concentrations. We aimed to establish plasma concentration ranges reflecting whole blood concentrations within currently used target ranges. Plasma and whole blood tacrolimus concentrations were determined in samples of transplant recipients included in the TransplantLines Biobank and Cohort Study. Targeted whole blood trough concentrations are 4-6 ng/mL and 7-10 ng/mL for kidney and lung transplant recipients, respectively. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. Simulations were performed to infer plasma concentration ranges corresponding to whole blood target ranges. Plasma (n=1973) and whole blood (n=1961) tacrolimus concentrations were determined in 1060 transplant recipients. A one-compartment model with fixed first-order absorption and estimated first-order elimination characterised observed plasma concentrations. Plasma was linked to whole blood using a saturable binding equation (maximum binding 35.7 ng/mL, 95% confidence interval (CI) 31.0-40.4 ng/mL; dissociation constant 0.24 ng/mL, 95% CI 0.19-0.29 ng/mL). Model simulations indicate that patients within the whole blood target range are expected to have plasma concentrations (95% prediction interval) of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively. Whole blood tacrolimus target ranges, currently used to guide TDM, were translated to plasma concentration ranges of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively.

[Correction model of the sampling time error on the blood trough concentration of tacrolimus in non-sustained-release dosage form for renal transplant recipients].

Objective: To establish correction model of the sampling time error on the blood trough concentration of tacrolimus in non-sustained-release dosage form for renal transplant recipient and improve the accuracy of drug dose assessment and clinical adjustment in renal transplant recipients. Methods: Visit records of 206 outpatients in the Department of Transplantation, Nanfang Hospital, Southern Medical University were retrospectively collected from October 15, 2022 to October 30, 2022. The distribution of sampling time of tacrolimus blood drug concentration was described and the time range of correction was determined. Twenty inpatients after renal transplantation in the Department of Transplantation, Nanfang Hospital, Southern Medical University from October 1, 2022 to November 30, 2022 were prospectively included, and their demography data, laboratory test results during follow-ups, and CYP3A5 genotype were collected. The patients took tacrolimus in non-sustained-release dosage form every 12 h starting from 19∶30 on the day of admission. Peripheral blood samples were collected from the patients on the second day of admission at 7∶30 and on the third day at 6∶00-10∶00 every 30 minutes to test the blood concentration of tacrolimus. Using the collection time as the independent variable and the blood tacrolimus concentration as the dependent variable, a simple linear regression was performed to fitting a linear model of tacrolimus blood concentration-sampling time. Multiple linear regression was performed to analyze the influencing factors of the tacrolimus metabolic rate within a specific period and generate the regression equation. Results: The 206 outpatients aged (46±13) years, including 131 males (63.6%). The time gap [M (Q1, Q3)] between the sampling time of the follow-up outpatients and standard C12 was 24 (13.0, 46.5) min, and the maximum time gap was 135 min. The 20 enrolled inpatients aged (45±12) years, including 15 males (75.0%). There was no significant difference in the blood concentration of tacrolimus collected at 7∶30 on the second (7.87±2.21)ng/ml and third days (7.84±2.33)ng/ml after admission of the enrolled inpatients (P=0.917), and the blood tacrolimus concentration rhythm was stable in the trial. The plasma concentration of C10.5-C14.5 was linearly related to the time, with R2 [M (Q1, Q3)] 0.88 (0.85, 0.92) and all P<0.05. The metabolic rate of tacrolimus during C10.5-C14.5=0.984+0.090×basic concentration of tacrolimus (ng/ml)-0.036×body mass index+0.489×CYP3A5 genotype-0.007×hemolobin(g/L)-0.035×alanine aminotransferase (U/L)+0.143×total cholesterol (mmol/L)+0.027×total bilirubin (μmol/L), with R2=0.85. Conclusion: This study propose a correction model for tacrolimus (non-sustained-release dosage form) trough concentration around C12, which is helpful for clinicians to easily and accurately assess renal transplant recipients' tacrolimus exposure.