Population pharmacokinetics of tacrolimus in paediatric systemic lupus erythematosus based on real-world study

Dosage optimization of tacrolimus based on the glucocorticoid dose and pharmacogenetics in adult patients with systemic lupus erythematosus

BACKGROUND

The purpose of the study was to develop a genotype-incorporated population pharmacokinetic (PPK) model of tacrolimus (TAC) in adults with systemic lupus erythematosus (SLE) to investigate the factors influencing TAC pharmacokinetics and to develop an individualized dosing regimen based on the model. In addition, a non-genotype-incorporated model was also established to assess its predictive performance compared to the genotype-incorporated model.

METHODS

A total of 365 trough concentrations from 133 adult SLE patients treated with TAC were collected to develop a genotype-incorporated PPK model and a non-genotype-incorporated PPK model of TAC using a nonlinear mixed-effects model (NONMEM). External validation of the two models was performed using data from an additional 29 patients. Goodness-of-fit diagnostic plots, bootstrap method, and normalized predictive distribution error test were used to validate the predictive performance and stability of the final models. The goodness-of-fit of the two final models was compared using the Akaike information criterion (AIC). The dosing regimen was optimized using Monte Carlo simulations based on the developed optimal model.

RESULTS

The typical value of the apparent clearance (CL/F) of TAC estimated in the final genotype-incorporated model was 14.3 L h-1 with inter-individual variability of 27.6%. CYP3A5 polymorphism and coadministered medication were significant factors affecting TAC-CL/F. CYP3A5 rs776746 GG genotype carriers had only 77.3% of the TAC-CL/F of AA or AG genotype carriers. Omeprazole reduced TAC-CL/F by 3.7 L h-1 when combined with TAC, while TAC-CL/F increased nonlinearly as glucocorticoid dose increased. Similar findings were demonstrated in the non-genotype-incorporated PPK model. Comparing these two models, the genotype-incorporated PPK model was superior to the non-genotype-incorporated PPK model (AIC = 643.19 vs. 657.425). Monte Carlo simulation based on the genotype-incorporated PPK model indicated that CYP3A5 rs776746 AA or AG genotype carriers required a 1/2-1 fold higher dose of TAC than GG genotype carriers to achieve the target concentration. And as the daily dose of prednisone increases, the dose of TAC required to reach the target concentration increases appropriately.

CONCLUSIONS

We developed the first pharmacogenetic-based PPK model of TAC in adult patients with SLE and proposed a dosing regimen based on glucocorticoid dose and CYP3A5 genotype according to the model, which could facilitate individualized dosing for TAC.

Population pharmacokinetic analyses of tacrolimus in non-transplant patients: a systematic review

BACKGROUND AND OBJECTIVES

Tacrolimus (TAC) has been increasingly used in patients with non-transplant settings. Because of its large between-subject variability, several population pharmacokinetic (PPK) studies have been performed to facilitate individualized therapy. This review summarized published PPK models of TAC in non-transplant patients, aiming to clarify factors affecting PKs of TAC and identify the knowledge gap that may require further research.

METHODS

The PubMed, Embase databases, and Cochrane Library, as well as related references, were searched from the time of inception of the databases to February 2023, to identify TAC population pharmacokinetic studies modeled in non-transplant patients using a non-linear mixed-effects modeling approach.

RESULTS

Sixteen studies, all from Asian countries (China and Korea), were included in this study. Of these studies, eleven and four were carried out in pediatric and adult patients, respectively. One-compartment models were the commonly used structural models for TAC. The apparent clearance (CL/F) of TAC ranged from 2.05 to 30.9 L·h^-1 (median of 14.9 L·h^-1). Coadministered medication, genetic factors, and weight were the most common covariates affecting TAC-CL/F, and variability in the apparent volume of distribution (V/F) was largely explained by weight. Coadministration with Wuzhi capsules reduced CL/F by about 19 to 43%. For patients with CYP3A5*1*1 and *1*3 genotypes, the CL/F was 39-149% higher CL/F than patients with CYP3A5*1*1.

CONCLUSION

The optimal TAC dosage should be adjusted based on the patient's co-administration, body weight, and genetic information (especially CYP3A5 genotype). Further studies are needed to assess the generalizability of the published models to other ethnic groups. Moreover, external validation should be frequently performed to improve the clinical practicality of the models.

Development and validation of an LC-MS/MS method by one-step precipitation for cinacalcet in human plasma

A sensitive, convenient, rapid and economic liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine cinacalcet concentration in human plasma. A stable isotope cinacalcet (cinacalcet-D₃) was selected as internal standard and the analytes were extracted from plasma samples by a one-step precipitation procedure. Chromatography separation was conducted on an Eclipse Plus C18 column by gradient elution with mobile phase of methanol-water-ammonium formate system at a constant flow rate of 0.6 mL/min. Mass spectrometric detection was conducted by multiple reaction monitoring using positive electrospray ionization. Cinacalcet concentrations in human plasma were determined over the concentration range of 0.1-50 ng/mL. The accuracies of lower limit of quantification (LLOQ) and quality control samples were all within the range of 85-115%, and the inter- and intra-batch precisions (CV%) were all within 15%. The average extraction recovery rates were 95.67-102.88%, and the quantification was not interfered by the matrix components. The validated method was successfully applied to determined cinacalcet concentrations in human plasma from secondary hyperparathyroidism patients.

Population Pharmacokinetics of Tacrolimus in Pediatric Patients With Umbilical Cord Blood Transplant

Tacrolimus was frequently used in pediatric patients with umbilical cord blood transplant for the prevention of graft-versus-host disease. The aim of the present study was to evaluate the population pharmacokinetics of tacrolimus among pediatric patients with umbilical cord blood transplant and find potential influenced factors. A total of 275 concentrations from 13 pediatric patients were used to build a polulation pharmacokinetic model using a nonlinear mixed-effects modeling approach. The impact of demographic features, biological characteristics, and concomitant medications, including sex, age, body weight, postoperative day, white blood cell count, red blood cell count, hemoglobin, platelets, hematocrit, blood urea nitrogen, creatinine, aspartate transaminase, alanine transaminase, total bilirubin, albumin, and total protein were investigated. The pharmacokinetics of tacrolimus were best described by a 1-compartment model with first- and zero-order mixed absorption and first-order elimination. The clearance and volume of distribution of tacrolimus were 1.93 L/h and 75.1 L, respectively. A covariate analysis identified that postoperative day and co-administration with trimethoprim-sulfamethoxazole were significant covariates influencing clearance of tacrolimus. Frequent blood monitoring and dose adjustment might be needed with the prolongation of postoperative day and coadministration with trimethoprim-sulfamethoxazole.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Tacrolimus Population Pharmacokinetic Model in Adult Chinese Patients with Nephrotic Syndrome and Dosing Regimen Identification Using Monte Carlo Simulations

BACKGROUND

The study aimed to establish a population pharmacokinetic (PPK) model of tacrolimus for Chinese patients with nephrotic syndrome using the patient's genotype and Wuzhi capsule dosage as the main test factors.

METHODS

Ninety-six adult patients with nephrotic syndrome, who were receiving tacrolimus treatment, were enrolled. A nonlinear mixed-effects model was used to determine the influencing factors of interindividual tacrolimus metabolism variation and establish a PPK model. To optimize the tacrolimus dosage, 10,000 Monte Carlo simulations were performed.

RESULTS

The 1-chamber model of first-order absorption and elimination was the most suitable model for the data in this study. The typical population tacrolimus clearance (CL/F) value was 16.9 L/h. The percent relative standard error (RSE%) of CL/F was 12%. Increased Wuzhi capsule and albumin doses both decreased the tacrolimus CL/F. In CYP3A5 homozygous mutation carriers, the CL/F was 39% lower than that of carriers of the wild-type and heterozygous mutation. The tacrolimus CL/F in patients who were coadministered glucocorticoids was 1.23-fold higher than that of the control. According to the patient genotype and combined use of glucocorticoids, 26 combinations of Wuzhi capsule and tacrolimus doses were matched. The Monte Carlo simulation identified the most suitable combination scheme.

CONCLUSIONS

An improved tacrolimus PPK model for patients with nephrotic syndrome was established, and the most suitable combination of Wuzhi capsule and tacrolimus doses was identified, thus, facilitating the selection of a more economical and safe administration regimen.

Dose tailoring of tacrolimus based on a non-linear pharmacokinetic model in children with refractory nephrotic syndrome

The population pharmacokinetics (PPK) of tacrolimus (TAC) in children with refractory nephrotic syndrome (RNS) have not been well-characterized. This study aimed to investigate the significant factors affecting the TAC PPK characteristics of children with RNS and to optimize the dosing regimen. A total of 494 concentrations from 108 children were obtained from routine therapeutic drug monitoring between 2016 and 2018. Information regarding the demographic features, laboratory test results, genetic polymorphisms of CYP3A5 (rs776746) and co-therapy medications were collected. PPK analysis was performed using the nonlinear mixed-effects modelling (NONMEM) software and two modelling strategies (the linear one-compartment model and nonlinear Michaelis-Menten model) were evaluated and compared. CYP3A5 genotype, weight, daily dose of TAC and daily dose of diltiazem were retained in the final linear model. The absorption rate constant (Ka) was set at 4.48 h^-1 in the linear model, and the apparent clearance (CL/F) and volume of distribution (V/F) in the final linear model were 14.2 L/h and 172 L, respectively. CYP3A5 genotype, weight and daily dose of diltiazem were the significant factors retained in the final nonlinear model. The maximal dose rate (V_max) and the average steady-state concentration at half-Vmax (K_m) in the final nonlinear model were 2.15 mg/day and 0.845 ng/ml, respectively. The nonlinear model described the pharmacokinetic data of TAC better than the linear model in children with RNS. A dosing regimen was proposed based on weight, CYP3A5 genotype and daily dose of diltiazem according to the final nonlinear PK model, which may facilitate individualized drug therapy with TAC.

Population pharmacokinetics and pharmacogenomics of tacrolimus in Chinese children receiving a liver transplant: initial dose recommendation

BACKGROUND

In order to improve the precision of treatment with tacrolimus in Chinese patients undergoing pediatric liver transplantation, the optimum initial dose of tacrolimus was determined based on population pharmacokinetics and pharmacogenomics.

METHODS

Demographic data, clinical parameters, drug combinations and pharmacogenomics were integrated to build a population pharmacokinetic model using NONMEM. Additionally, Monte Carlo simulations were used to optimize the recommended initial dose.

RESULTS

Weight, patient cytochrome 450 3A (CYP3A)5 genotype, and co-administration with wuzhi-capsule (WZ) were incorporated into the final model. For children with a CYP3A5*3/*3 genotype not co-administered WZ, 0.10 mg/kg/day split into two doses was recommended for patients weighing 5-17 kg, and 0.05 mg/kg/day split into two doses was recommended for patients weighing 17-60 kg. For children with a CYP3A5*1 allele not co-administered WZ, 0.25 mg/kg/day for patients weighing 5-10 kg, 0.20 mg/kg/day for patients weighing 10-17 kg, 0.15 mg/kg/day for patients weighing 17-36 kg, and 0.10 mg/kg/day for patients weighing 36-60 kg; all split into two doses was recommended. For children with a CYP3A5*3/*3 genotype co-administered WZ, 0.10 mg/kg/day for patients weighing 5-11 kg, and 0.05 mg/kg/day for patients weighing 11-60 kg; both split into two doses was recommended. For children with a CYP3A5*1 allele who were co-administered WZ, 0.20 mg/kg/day for patients weighing 5-10 kg, 0.15 mg/kg/day for patients weighing 10-22 kg, and 0.10 mg/kg/day for patients weighing 22-60 kg all split into two doses was recommended.

CONCLUSIONS

The optimal initial dose of tacrolimus was determined based on population pharmacokinetics and pharmacogenomics in Chinese patients undergoing pediatric liver transplantation.

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

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

Population pharmacokinetic analysis of linezolid in patients with different types of shock: Effect of platelet count

Linezolid was approved by the Food and Drug Administration for the treatment of serious infections. However, patients with serious frequently develop shock, and it is currently elusive whether shock affects the pharmacokinetics of linezolid. The aim of the present study was to explore whether the pharmacokinetics of linezolid are different among patients with various types of shock or patients without shock and whether potential confounders are involved in their outcomes. A population pharmacokinetic analysis using a non-linear mixed-effects model was performed to examine the pharmacokinetics of patients with different types of shock or patients without shock. The pharmacokinetics of linezolid in patients with different types of shock or patients without shock was described by a one-compartment model. In our results, the patients with different types of shock or patients without shock demonstrated no differences in pharmacokinetics, whereas the platelet count was identified as a significant influencing factor. The results demonstrated that the pharmacokinetics of linezolid exhibited no significant differences among patients with different types of shock or patients without shock, whereas the platelet count significantly affected the clearance rate of linezolid.

Population pharmacokinetics and initial dosing regimen optimization of cyclosporin in pediatric hemophagocytic lymphohistiocytosis patients

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.

Population pharmacokinetics of sirolimus in pediatric patients with kaposiform hemangioendothelioma: A retrospective study

Numerous studies have established population pharmacokinetics (PPK) models of sirolimus in various populations. However, a PPK model of sirolimus in Chinese patients with pediatric kaposiform hemangioendothelioma (PKHE) has yet to be established; therefore, this was the purpose of the present study. The present study was a retrospective analysis that utilized the trough concentration data obtained from traditional therapeutic drug monitoring-based dose adjustments. A total of 17 Chinese patients with PKHE from a real-world study were characterized by non-linear mixed-effects modeling. The impact of demographic features, biological characteristics and concomitant medications was assessed. The developed final model was evaluated via bootstrap and a prediction-corrected visual predictive check. A one-compartment model with first-order absorption and elimination was used for modeling of data for PKHE. The typical values of apparent oral clearance (CL/F) and apparent volume of distribution (V/F) in the final model were 3.19 l/h and 165 liters, respectively. Age, alanine transaminase levels and sex were included as significant covariates for CL/F, while the duration of treatment with sirolimus was a significant covariate for V/F. In conclusion, the present study developed and validated the first sirolimus PPK model for Chinese patients with PKHE.

Model extrapolation to a real-world dataset: evaluation of tacrolimus population pharmacokinetics and drug interaction in pediatric liver transplantation patients

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.

Transcriptomics analysis of sirolimus treatment in lupus nephritis

Lupus nephritis (LN) is one of the principal causes of mortality and disability in patients with systemic lupus erythematosus. Sirolimus has been used to treat patients with LN; however, the effects and mechanism of sirolimus in these patients remains unclear. The present study aimed to elucidate the therapeutic effects and mechanisms of sirolimus in LN mice using low, medium and high doses of sirolimus (0.1, 0.3 and 1 mg/kg, respectively). The survival probability and kidney index were calculated, and renal fibrosis was determined using Masson's Trichrome staining. The expression levels of E-cadherin, α-smooth muscle actin (α-SMA) and vimentin were assessed via immunofluorescence analysis. Transcriptome analysis of control and sirolimus-treated LN mice was performed using RNA-sequencing, differentially expressed gene (DEG) identification and annotation, and Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The results suggested that a medium dose of sirolimus alleviated renal fibrosis and increased the survival rates of mice with LN (P<0.05). Furthermore, transcriptome analysis revealed 334 DEGs associated with LN, 176 of which were upregulated and 158 were downregulated. Following GO functional enrichment, ‘biological process’, ‘molecular function’ and ‘cellular component’ terms were identified. A total of 10 KEGG pathways were enriched, with ‘cytokine-cytokine receptor interaction’ and ‘interleukin-17 signaling pathway’ being significantly enriched (P<0.05). To the best of our knowledge, the present study is the first to conduct transcriptome analysis of LN mice treated with sirolimus, and demonstrated that a dose of 0.3 mg/kg exerted the greatest therapeutic effects.

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

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

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

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

Cyclosporin population pharmacokinetics in pediatric refractory nephrotic syndrome based on real-world studies: Effects of body weight and spirolactone administration

Different models of population pharmacokinetics (PPK) of cyclosporin have been established in various populations. However, the cyclosporin PPK model in patients with pediatric refractory nephrotic syndrome (PRNS) has yet to be constructed. The present study aimed to establish the cyclosporin PPK model in PRNS, and to identify factors that may account for any variability. Chinese patients with PRNS treated with cyclosporin between June 2014 and June 2018 at the Children's Hospital of Fudan University (Shanghai, China) were retrospectively analyzed. The impact of demographic features, laboratory parameters and concomitant medications was evaluated. A total of 18 PRNS patients from real-world studies were analyzed by non-linear mixed-effects modeling. A one-compartment model with first-order absorption and elimination was selected as the appropriate model in PRNS. Body weight (WT) and spirolactone intake were included as significant covariates for the apparent oral clearance (CL/F), and the WT was revealed to significantly influence the apparent volume of distribution (V/F). The final covariate models were as follows: CL/F=80.7 × (WT/70)^0.75 × (1-0.265×θ_spirolactone), and V/F=2,030 × (WT/70), where θ_spirolactone is the coefficient of spirolactone. The inter-individual variability in CL/F and V/F was 44.6 and 53.1%, respectively. In conclusion, in the present study, a cyclosporin PPK model for patients with PRNS was successfully constructed, and the presence of a clinically significant interaction between spirolactone and cyclosporin in PRNS patients was determined based on real-world studies, indicating that concomitant medication with spirolactone was able to reduce cyclosporin clearance in the patients with PRNS.