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Purpose: The present study aims to explore the effects of tacrolimus on proteinuria in patients with idiopathic membranous nephropathy (IMN) and recommend an appropriate dosage schedule via machine learning method., Methods: The E max model was constructed to analyze the effects of tacrolimus on proteinuria in patients with IMN. Data were mined from published literature and machine learning was built up with E max model, among which the efficacy indicator was proteinuria change rates from baseline. 463 IMN patients were included for modeling, and tacrolimus therapeutic window concentrations were 4-10 ng/ml., Results: In machine learning model, the E max from tacrolimus effecting proteinuria in IMN patients was -72.7%, the ET 50 was 0.43 months, and the time to achieving 25% E max , 50% E max , 75% E max , and 80% (plateau) E max of tacrolimus on proteinuria in patients with IMN were 0.15, 0.43, 1.29, and 1.72 months, respectively., Conclusion: For achieving better therapeutic effects from tacrolimus on proteinuria in patients with IMN, tacrolimus concentration range need to be maintained at 4-10 ng/ml for at least 1.72 months., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Objectives: Cyclosporin has been used for the treatment of pediatric refractory nephrotic syndrome (PRNS). However, the narrow therapeutic window and large pharmacokinetic variability make it difficult to individualize cyclosporin administration. Meanwhile, spironolactone has been reported to affect cyclosporin metabolism in PRNS patients. This study aims to explore the initial dosage optimization of cyclosporin in PRNS based on the impact of spironolactone co-administration., Methods: Monte Carlo simulation based on a previously established cyclosporin population pharmacokinetic model for PRNS was used to design cyclosporin dosing regimen., Results: In this study, the probability of drug concentration reaching the target and the convenience of times of administration were considered comprehensively. The optimal administration regimen in PRNS without spironolactone was 6, 5, 4 and 3 mg/kg cyclosporin split into two doses for the body weight of 5-8, 8-18, 18-46 and 46-70 kg, respectively. The optimal administration regimen in PRNS with spironolactone was 4, 3, 2 mg/kg cyclosporin split into two doses for body weight of 5-14, 14-65, and 65-70 kg, respectively., Conclusion: The cyclosporin dosing regimen for PRNS based on Monte Carlo simulation was systematically developed and the initial dosage optimization of cyclosporin in PRNS was recommended for the first time., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

What Is Known and Objectives: Tacrolimus is used to treat patients with lupus nephritis; however, its time course and dose effect on proteinuria in lupus nephritis patients remain unknown. The purpose of this study was to determine the time course and dose effect of tacrolimus on proteinuria in lupus nephritis patients via model-based meta-analysis (MBMA)., Methods: PubMed, Web of Science, Cochrane Library and ClinicalTrials.gov databases were systematically searched for information on the efficacy of tacrolimus against proteinuria in lupus nephritis patients. Useful data were extracted to build a model for the population studied using a non-linear mixed-effect model (NONMEM). This model was applied to simulate time course of tacrolimus on proteinuria using Monte Carlo simulations., Results: Ten clinical studies that recruited 222 patients with lupus nephritis were included. Based on various diagnostic plots, we found that the established model described the observed data reasonably well. In addition, the typical E max and ET 50 of tacrolimus for 24-hour proteinuria in lupus nephritis patients were -5.88 g and 0.37 months, respectively. The baseline value of 24-hour proteinuria affected E max . No significant dose-response relationship was observed in the range of tacrolimus concentration used in the present study (3-10 ng/mL), indicating that the effect of tacrolimus on proteinuria depends on effective concentration range and not the dose. However, the time course relationship was obvious; the efficacy of tacrolimus increased over time, reaching a plateau (80% E max ) at approximately 1.48 months from the beginning of treatment., What Is New and Conclusion: When the concentration range of tacrolimus is maintained at 3-10 ng/mL, at least 1.48 months of treatment is required to achieve a better outcome with regard to proteinuria in lupus nephritis patients., (© 2020 John Wiley & Sons Ltd.)

The present study aimed to optimize the tacrolimus initial dosing scheme in pediatric refractory nephrotic syndrome patients based on population pharmacokinetics and pharmacogenomics.Demographic characteristics, concomitant medication, laboratory data, pharmacogenomics were collected to build the model and Monte Carlo was used to simulate the optimization of initial dosing scheme.Weight, the polymorphisms of CYP3A5 , and concomitant medication of wuzhi-capsule were included into the covariates affecting tacrolimus clearance. In addition, with the same weight, there was difference in tacrolimus clearance in patients who carry CYP3A5*3/*3 and no coadministration of wuzhi-capsule, patients who carry CYP3A5*1 allele and no coadministration of wuzhi-capsule, patients who carry CYP3A5*3/*3 and coadministration of wuzhi-capsule, patients who carry CYP3A5*1 allele and coadministration of wuzhi-capsule, and their clearance ratios were 1:1.5:0.697:1.0455, respectively. Based on the differences of clearance in the above cases, we simulated different dosing regimens and obtained the optimal initial dose in each case.The present study recommended the tacrolimus initial dosing scheme in pediatric refractory nephrotic syndrome patients based on CYP3A5 genotype and coadministration with wuzhi-capsule.

Background: The purpose of our research was to recommend the initial tacrolimus dosage for Chinese pediatric patients undergoing kidney transplantation based on population pharmacokinetics and pharmacogenetics., Methods: Demographic data, laboratory results, drug combinations, and pharmacogenetics from Chinese pediatric patients undergoing kidney transplantation were analyzed using non-linear mixed-effects modeling. A Monte Carlo simulation was performed to evaluate the optimal initial dose of tacrolimus., Results: Body weight and post-transplant days, combined with wuzhi-capsule (WZ, extracted from schisandra sphenanthera, whose primary efficient constituents are schisantherin A, schisandrol B, schisandrin, etc., and often used to treat drug-induced hepatitis in Chinese organ transplant patients) and CYP3A5 polymorphisms, influenced the clearance of tacrolimus in these patients. With same weight and post-transplant days, tacrolimus clearance rates from patients carrying CYP3A5*3/*3 and without WZ, carrying CYP3A5*1 allele and without WZ, carrying CYP3A5*3/*3 and with WZ, carrying CYP3A5*1 allele and with WZ were 1, 1.6, 0.72, and 1.152, respectively. In addition, the initial dose for each condition is recommended., Conclusions: The initial dosage recommendations in the tacrolimus instructions were not individualized, and we have developed more accurate initial doses based on weight and the CYP3A5 genotype. In addition, lower initial doses are recommended with concurrent use of WZ.

1. Numerous tacrolimus population pharmacokinetic (PPK) models in pediatric liver transplantation patients have been established to define an optimal dose schedule. However, the applicability of extrapolating these PPK models to our clinical center remains unknown. The goals of the present study was to evaluate model external predictiveness and establish a new model applicable to traditional therapeutic drug monitoring data.2. Published PPK models were collected from the literature and assessed using our real-world dataset including 41 pediatric liver transplantation patients via the individual prediction error method. The establishment of a new model was characterized using non-linear mixed-effects modeling.3. Nine published pediatric liver transplantation PPK models were identified, three of which could be applied to our real-world dataset. However, these models were dissatisfactory in terms of individual prediction error and hence, inadequate for extrapolation. Finally, a new model applicable to our real-world dataset was established as follows: CL/ F  = 22.9 × (WT/70) 0.75 × (1 - WZ × 0.264) × (1 - FCZ × 0.338) × (1 + ASPI × 0.281) × (POD/41) 0.0486 L/h; V / F  = 906 × (WT/70) L. Where WT, WZ, FCZ, ASPI and POD were weight, Wuzhi capsule, fluconazole, aspirin and post-transplantation day, respectively. In conclusion, published models were inadequate for application to our real-world dataset. The present study produced a new model applicable to our real-world study data.

Hemophagocytic lymphohistiocytosis (HLH) is induced by various triggers, including genetic factors, infections, autoimmune diseases, lymphoma or other malignancies. Cyclosporin is one of the clinical treatments for HLH. However, cyclosporin has considerable inter- and intra-individual variabilities in pharmacokinetics and also displays a narrow therapeutic window, making it difficult to define an optimal dose for HLH treatment. This study is aimed to establish cyclosporin population pharmacokinetic (PPK) model of pediatric HLH patients and formulate an initial dose regimen for personalized medicine.Pediatric HLH patients between June 2014 and March 2019 from Children's Hospital of Fudan University were analyzed using NONMEM. Dose recommended was investigated using Monte Carlo simulations.The final cyclosporin PPK model was: CL/F = 91×(WT/70) 0.75 ×(1+ Piperacillin-Tazobactam × θ P-T ); V/F = 4250×(WT/70), where WT, and θ P-T were weight, and the coefficient of the Piperacillin-Tazobactam, respectively. Based on the simulation results of our model, new initial dosage suggestions were recommended. In conclusion, the first cyclosporin PPK model in pediatric HLH patients was established and the model could be used to predict individualized initial dosing regimens in children with HLH.

Aim: To investigate the effect of the ''minimizing tacrolimus'' strategy on long-term survival of patients after liver transplantation (LT)., Methods: We conducted a retrospective study of 319 patients who received LT between January 2009 and December 2011 at the First Affiliated Hospital of Zhejiang University School of Medicine. Following elimination of ineligible patients, 235 patients were included in the study. The relationship between early tacrolimus (TAC) exposure and survival period was analyzed by Kaplan Meier curves. Adverse effects related to TAC were evaluated by the χ(2) test. Routine monitoring of blood TAC concentration (TC) was performed using the PRO-Trac(TM) II Tacrolimus Elisa Kit (Diasorin, United States)., Results: Of 235 subjects enrolled in the study, 124 (52.8%) experienced adverse effects due to TAC. When evaluating mean TC, the survival time of patients with a mean TC < 5 ng/mL was significantly shorter than that in the other groups (911.3 ± 131.6 d vs 1381.1 ± 66.1 d, 911.3 ± 131.6 d vs 1327.3 ± 47.8 d, 911.3 ± 131.6 d vs 1343.2 ± 83.1 d, P < 0.05), while the survival times of patients with a mean TC of 5-7, 7-10 and 10-15 ng/mL were comparable. Adverse effects due to TAC in all four groups were not significantly different. When comparing the standard deviation (SD) of TC among the groups, the survival time of patients with a SD of 2-4 was significantly longer than that in the other groups (1388.8 ± 45.4 d vs 1029.6 ± 131.3 d, 1388.8 ± 45.4 d vs 1274.9 ± 57.0 d, P < 0.05), while in patients with a SD < 2 and SD > 4, the survival time was not statistically different. Adverse effects experienced in all three groups were not statistically different. In Cox regression analysis, male patients and those with a primary diagnosis of benign disease, mean TC > 5 ng/mL and TC SD 2-4 had better outcomes., Conclusion: The early ''minimizing tacrolimus'' strategy with a mean TC of 5-10 ng/mL and SD of 2-4 was beneficial in terms of long-term survival after LT.