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

External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients

OBJECTIVE

Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset.

METHODS

The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting.

RESULTS

Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point.

CONCLUSION

Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Population Pharmacokinetic Analysis for Model-Based Therapeutic Drug Monitoring of Tacrolimus in Chinese Han Heart Transplant Patients

BACKGROUND AND OBJECTIVE

Tacrolimus has become the first-line immunosuppressant for preventing rejection after heart transplantation. The present study aimed to investigate genetic variants and clinical factors affecting the variability of tacrolimus in Chinese Han heart transplant patients using a population pharmacokinetic approach.

METHODS

The retrospective study included 53 hospitalized patients with 547 tacrolimus concentrations for analysis. Nonlinear mixed-effects modeling was used to develop the population pharmacokinetics model for tacrolimus in patients with heart transplants, followed by Monte Carlo simulations to design initial dosing regimens.

RESULTS

In our study, the mutation rate of CYP3A4*18B (C>T) was 27.36%. An oral one-compartment model with first-order absorption and elimination was used to describe the pharmacokinetics of tacrolimus in heart transplant patients. In the final model, the estimated apparent clearance (CL/F) and volume of distribution (V/F) were 532.5 L/h [12.20% interindividual variability, IIV] and 16.87 L (23.16% IIV), respectively. Albumin, postoperative time, and rs2242480 (CYP3A4*18B) gene polymorphisms were the significant covariates affecting CL/F, and creatinine clearance had significant effects on the V/F.

CONCLUSION

The population pharmacokinetic model of tacrolimus in heart transplant patients can better estimate the population and individual pharmacokinetic parameters of patients and can provide a reference for the design of individualized dosing regimens.

Controversial Interactions of Tacrolimus with Dietary Supplements, Herbs and Food

Tacrolimus is an immunosuppressive calcineurin inhibitor used to prevent rejection in allogeneic organ transplant recipients, such as kidney, liver, heart or lung. It is metabolized in the liver, involving the cytochrome P450 (CYP3A4) isoform CYP3A4, and is characterized by a narrow therapeutic window, dose-dependent toxicity and high inter-individual and intra-individual variability. In view of the abovementioned facts, the aim of the study is to present selected interactions between tacrolimus and the commonly used dietary supplements, herbs and food. The review was based on the available scientific literature found in the PubMed, Scopus and Cochrane databases. An increase in the serum concentration of tacrolimus can be caused by CYP3A4 inhibitors, such as grapefruit, pomelo, clementine, pomegranate, ginger and turmeric, revealing the side effects of this drug, particularly nephrotoxicity. In contrast, CYP3A4 inducers, such as St. John’s Wort, may result in a lack of therapeutic effect by reducing the drug concentration. Additionally, the use of Panax ginseng, green tea, Schisandra sphenanthera and melatonin in patients receiving tacrolimus is highly controversial. Therefore, since alternative medicine constitutes an attractive treatment option for patients, modern healthcare should emphasize the potential interactions between herbal medicines and synthetic drugs. In fact, each drug or herbal supplement should be reported by the patient to the physician (concordance) if it is taken in the course of immunosuppressive therapy, since it may affect the pharmacokinetic and pharmacodynamic parameters of other preparations.

Population pharmacokinetics and initial dose optimization of tacrolimus in children with severe combined immunodeficiency undergoing hematopoietic stem cell transplantation

The present study aimed to explore the population pharmacokinetics and initial dose optimization of tacrolimus in children with severe combined immunodeficiency (SCID) undergoing hematopoietic stem cell transplantation (HSCT). Children with SCID undergoing HSCT treated with tacrolimus were enrolled for analysis. Population pharmacokinetics of tacrolimus was built up by a nonlinear mixed-effects model (NONMEM), and initial dose optimization of tacrolimus was simulated with the Monte Carlo method in children weighing <20 kg at different doses. A total of 18 children with SCID undergoing HSCT were included for analysis, with 130 tacrolimus concentrations. Body weight was included as a covariable in the final model. Tacrolimus CL/F was 0.36–0.26 L/h/kg from body weights of 5–20 kg. Meanwhile, we simulated the tacrolimus concentrations using different body weights (5–20 kg) and different dose regimens (0.1–0.8 mg/kg/day). Finally, the initial dose regimen of 0.6 mg/kg/day tacrolimus was recommended for children with SCID undergoing HSCT whose body weights were 5–20 kg. It was the first time to establish tacrolimus population pharmacokinetics in children with SCID undergoing HSCT; in addition, the initial dose optimization of tacrolimus was recommended.

Population Pharmacokinetic Evaluation with External Validation of Tacrolimus in Chinese Primary Nephrotic Syndrome Patients

PURPOSE

The generalizability of numerous tacrolimus population pharmacokinetic (popPK) models constructed to promote optimal tacrolimus dosing in patients with primary nephrotic syndrome (PNS) is unclear. This study aimed to evaluate the predictive performance of published tacrolimus popPK models for PNS patients with an external data set.

METHODS

We prospectively collected 223 concentrations from 50 Chinese adult patients with PNS who were undergoing tacrolimus treatment. Data on published tacrolimus popPK models for adults and children with PNS were extracted from the literature. Model predictability was evaluated with prediction-based and simulation-based diagnostics and Bayesian forecasting.

RESULTS

In prediction-based evaluation, none of the 11 identified published popPK models of tacrolimus had met a predefined criteria of a mean prediction error ≤  ± 20%, and the prediction error within ± 30% of the identified models didn't exceed 50%. Simulation-based diagnostics also indicated unsatisfactory predictability. Bayesian forecasting demonstrated amelioration in the model predictability with the inclusion of 2-3 prior observations. Moreover, the predictive performance of nonlinear models was not better than that of one-compartment models.

CONCLUSIONS

The prediction of tacrolimus concentrations for patients with PNS remains challenging; published models are not applicable for extrapolation to other hospitals. Bayesian forecasting significantly improved model predictability and thereby helped to individualize tacrolimus dosing.

Population pharmacokinetics and dosage optimization of tacrolimus coadministration with Wuzhi capsule in adult liver transplant patients

1. This study aimed to establish a population pharmacokinetic model of tacrolimus coadministration with Wuzhi capsule and optimize the dosage regimen in adult liver transplant patients.2. Totally 1327 tacrolimus trough concentrations from 116 adult liver transplant patients were obtained for model development. A one-compartment model with first-order absorption and elimination was used to analyse the data, and the final model was internally verified using a goodness-of-fit diagnostic plot, bootstrap methods, and visual prediction test. A total of 29 patients with 250 tacrolimus trough concentrations was used for external validation via prediction-based diagnostics. Additionally, the simulation was used to optimize the recommended dose of tacrolimus and Wuzhi capsules.3. The estimated apparent clearance and volume of the distribution of tacrolimus were 15.4 L/h and 1210 L, respectively. The tacrolimus daily dose, Wuzhi capsule daily dose, postoperative time, alanine transaminase, haemoglobin, total bilirubin, direct bilirubin, estimated glomerular filtration rate, and urea, concomitant with voriconazole and fluconazole, were identified as significant covariates affecting the pharmacokinetic parameters. Internal and external validation showed that the final model was stable and reliable for predicting performance.4. The final model could provide guidance for dosage optimization of tacrolimus coadministered with Wuzhi capsules in adult liver transplantation patients.

Effects of Posaconazole on Tacrolimus Population Pharmacokinetics and Initial Dose in Children With Crohn’s Disease Undergoing Hematopoietic Stem Cell Transplantation

The present study explored the effects of posaconazole on tacrolimus population pharmacokinetics (PPK) in children with Crohn’s disease (CD) undergoing hematopoietic stem cell transplantation (HSCT). Tacrolimus concentrations, physiological and biochemical factors, and concomitant medications from 51 CD children undergoing HSCT were used to establish a PPK model based on a nonlinear mixed-effect model. Steady-state concentrations of tacrolimus for children weighing less than 20 kg treated with different dose regimens were simulated by the Monte Carlo method. Weight and concomitant medications were included as covariates. At the same weight, the relative tacrolimus clearance was 1:0.43 in children without or with posaconazole. Compared to children not receiving posaconazole, the simulated tacrolimus steady-state concentrations at different doses for different body weights were all higher in children receiving posaconazole (p &lt; 0.01). Furthermore, in children not receiving posaconazole, the dosage regimen with the best probability of achieving the target concentration was 0.6 mg/kg/day for children weighing 5–8.2 kg and 0.5 mg/kg/day for children weighing 8.2–20 kg, while for children receiving posaconazole, the best probability of reaching the target concentration of tacrolimus was a dosage regimen of 0.5 mg/kg/day for children weighing 5–20 kg. In conclusion, the PPK for tacrolimus was determined in children with CD undergoing HSCT for the first time. Co-treatment with posaconazole significantly increased tacrolimus concentrations, and we recommend a specific initial dose regimen for tacrolimus.

Population pharmacokinetics of tacrolimus in Chinese adult liver transplant patients

Tacrolimus is widely used in organ transplantation to prevent rejection. However, the narrow therapeutic window and the large inter-and intra-individual variability in the pharmacokinetics (PK) of tacrolimus make it difficult for individualization of dosing. This study aimed at developing a population pharmacokinetic model for estimating the oral clearance of tacrolimus in Chinese liver transplant patients, and identifying factors that contribute to the PK variability of tacrolimus. Data of 151 liver transplant patients who received tacrolimus were analyzed in this study. The population PK model was analyzed and the covariates including population demographic and biochemical characteristics, drug combination, and genetic polymorphism were explored using non-linear mixed-effects modeling approach. A single-compartment population PK model was developed, and the final model was CL/F = (14.6-2.38 × cytochrome P450 (CYP) 3A5-3.72 × WZC+1.04 × (POD/9)+2.48 × COR) × Exp(η_i ), where CYP3A5 was 1 for CYP3A5*3/*3, Wuzhi Capsule (WZC) was 1 when patients took tacrolimus combined with WZC, otherwise it was 0, corticosteroids (COR) was 1 when patients take tacrolimus combined with COR, otherwise, it was 0, POD was the post-operative day. Visual inspection and bootstrap indicated that the final model was stable and robust. In this study, we developed the first tacrolimus population PK model in Chinese adult liver transplant patients. We first determined the influence of WZC on tacrolimus in these people, which could provide useful PK information for the drug combination of tacrolimus and WZC. We also revealed the influence of genetic polymorphism of CYP3A5, POD, and a combination of COR on tacrolimus PK. Therefore, these significant factors should be taken into consideration in optimizing dosage regimens.

The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate

In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.

Effects of voriconazole on population pharmacokinetics and optimization of the initial dose of tacrolimus in children with chronic granulomatous disease undergoing hematopoietic stem cell transplantation

Background

This study aimed to explore the effects of voriconazole on population pharmacokinetics and optimization of the initial dose of tacrolimus in children with chronic granulomatous disease (CGD) undergoing hematopoietic stem cell transplantation (HSCT).

Methods

Thirty-four children with CGD undergoing HSCT were assessed to establish a population pharmacokinetic model (PPM) using the non-linear mixed effect. Tacrolimus concentrations were simulated by the Monte Carlo method in children weighing <25 kg at different doses.

Results

In the final model, weight and concomitant use of voriconazole were included as covariates. With the same weight, the relative value of tacrolimus clearance was 1:0.388 in children not taking voriconazole: children taking voriconazole. Compared with children not taking voriconazole, the measured tacrolimus concentrations were all higher in children taking voriconazole (P<0.01); however, these were not corrected by dose or body weight for concentration differences. Thus, we simulated the tacrolimus concentrations using different body weights (5–25 kg) and different dose regimens (0.1–0.8 mg/kg/day) for the same body weight and dose. Tacrolimus concentrations in children taking voriconazole were higher than those in children not taking voriconazole (P<0.01). Also, in children with CGD undergoing HSCT who were not taking voriconazole, the initial dose regimen of 0.5 mg/kg/day was recommended for body weights of 5–10 kg, and 0.4 mg/kg/day was recommended for body weights of 10–25 kg. In children with CGD undergoing HSCT who were taking voriconazole, an initial dose regimen of 0.3 mg/kg/day was recommended for body weights of 5–25 kg.

Conclusions

We established, for the first time, a PPM of tacrolimus in children with CGD undergoing HSCT in which voriconazole significantly increased tacrolimus concentrations. In addition, the initial dose of tacrolimus in children with CGD undergoing HSCT was recommended.

Initial dose recommendation for sirolimus in paediatric kaposiform haemangioendothelioma patients based on population pharmacokinetics and pharmacogenomics

Objective

Sirolimus has been used to treat paediatric kaposiform haemangioendothelioma patients. However, there is considerable pharmacokinetic variability among individuals, and it is difficult to develop an initial dosing regimen. The goal of the present study is to recommend an initial sirolimus dose in paediatric kaposiform haemangioendothelioma patients based on population pharmacokinetics and pharmacogenomics.

Methods

This was a retrospective clinical study. A population pharmacokinetics model was established and population characteristics, laboratory test results, drug combinations, and pharmacogenomics were considered as potential covariates. The Monte Carlo method was used to simulate the optimal initial dosage.

Results

The final covariates that affect sirolimus clearance include weight and the CYP3A5 genotype. The initial dosage of sirolimus for individuals with CYP3A5*3/*3 was 0.20 mg/kg split into two doses for 5 to 60 kg body weight. For individuals with CYP3A5*1, the initial dose was 0.23 mg/kg split into two doses for 5 to 30 kg body weight and 0.20 mg/kg split into two doses for 30 to 60 kg body weight.

Conclusion

The recommendation for the initial sirolimus dose in paediatric kaposiform haemangioendothelioma patients was based on population pharmacokinetics and pharmacogenomics. This study may provide practical value for sirolimus clinical use in paediatric kaposiform haemangioendothelioma patients.

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.

Analysis of time course and dose effect of tacrolimus on proteinuria in lupus nephritis patients

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 ET₅₀ 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.

Initial Dosage Optimization of Tacrolimus in Pediatric Patients With Thalassemia Major Undergoing Hematopoietic Stem Cell Transplantation Based on Population Pharmacokinetics

BACKGROUND

Hematopoietic stem cell transplantation (HSCT) is an effective treatment for hematological disorders. Tacrolimus is widely used after HSCT, but it has highly interindividual variable pharmacokinetics. Population pharmacokinetics (PPK) researches of tacrolimus in children with β-thalassemia major (β-TM) undergoing HSCT are insufficient.

OBJECTIVE

To establish a PPK model of tacrolimus in children with β-TM and optimize initial dosing regimen for achieving target concentration of 5 to 15 ng/mL.

METHODS

Data on patients aged <18 years were retrospectively collected from January 2017 to December 2018. PPK analysis and Monte Carlo simulations were performed using nonlinear mixed-effects modeling.

RESULTS

A data set of 55 patients with 332 concentrations was included. A 2-compartment model could best describe the pharmacokinetics of tacrolimus. The body surface area and gender were significant covariates in the final model. The typical value of clearance, the distribution volume of the central room, the distribution volume of the peripheral room, and the intercompartmental clearance were 5.05L/h, 4.33L, 155L, and 6.22L/h, respectively. The optimal initial dosing regimen of 0.03, 0.04, 0.05, 0.06, and 0.10 mg/kg were appropriate for female children with a weight (WT) of 50 to 10 kg. The regimen of 0.04, 0.05, 0.06, 0.07, and 0.12 mg/kg is suitable for male children with a WT of 50 to 10 kg. The probability of target attainment (PTA) of each regimen reached 91%.

CONCLUSION AND RELEVANCE

A stable PPK model of tacrolimus was established. The proposed dosage regimen reached a good PTA, which could provide a reference for tacrolimus therapy.

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

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

Initial dosage optimization of ciclosporin in pediatric Chinese patients who underwent bone marrow transplants based on population pharmacokinetics

Bone marrow transplants (BMT) are an established therapeutic strategy for patients with severe aplastic anemia, acute lymphoblastic leukemia, acute myeloid leukemia or chronic myeloid leukemia. However, the successful application of BMT is limited by graft-vs.-host disease (GVHD). Ciclosporin has been widely used for treating GVHD in pediatric patients who underwent BMT. The present study aimed to optimize the dosage of ciclosporin for safety and effectiveness based on population pharmacokinetics. A non-linear mixed-effects model was used to analyze the clinical data of pediatric patients who underwent BMT between September 2016 and September 2019 at the Children's Hospital of Fudan University. Monte Carlo simulations were used to identify the optimal dose of ciclosporin. The final population pharmacokinetic model indicated that body weight and days post-transplant influenced the clearance of ciclosporin in pediatric patients who underwent BMT. The present study indicated that the optimal initial dose of ciclosporin for pediatric patients weighing 5-30 kg who underwent BMT was 6 mg/kg/day split into 2 doses.

Population pharmacokinetics of riociguat and its metabolite in patients with chronic thromboembolic pulmonary hypertension from routine clinical practice

Pharmacokinetic data for riociguat in patients with chronic thromboembolic pulmonary hypertension (CTEPH) have previously been reported from randomized clinical trials, which may not fully reflect the population encountered in routine practice. The aim of the current study was to characterize the pharmacokinetic of riociguat and its metabolite M1 in the patients from routine clinical practice. A population pharmacokinetic model was developed in NONMEM 7.3, based on riociguat and its metabolite plasma concentrations from 49 patients with CTEPH. One sample with riociguat and M1 concentrations was available from each patient obtained at different time points after last dose. Age, bodyweight, sex, smoking status, concomitant medications, kidney and liver function markers were tested as potential covariates of pharmacokinetic of riociguat and its metabolite. Riociguat and M1 disposition was best described with one-compartment models. Apparent volume of distribution (Vd/F) for riociguat and M1 were assumed to be the same. Total bilirubin and creatinine clearance were the most predictive covariates for apparent riociguat metabolic clearance to M1 (CL_f,M1/F) and for apparent riociguat clearance through remaining pathways (CL_e,r/F), respectively. CL_f,M1/F, CL_e,r/F, Vd/F of riociguat and M1, and clearance of M1 (CL_e,M1/F) for a typical individual with 70 mL/min creatinine clearance and 0.69 mg/dL total bilirubin were 0.665 L/h (relative standard error = 17%)), 0.66 (18%) L/h, 3.63 (15%) L and 1.47 (19%) L/h, respectively. Upon visual identification of six outlying individuals, an absorption lag-time of 2.95 (6%) h was estimated for these patients. In conclusion, the only clinical characteristics related to riociguat exposure in patients with CTEPH from routine clinical practice are total bilirubin and creatinine clearance. This confirms the findings of the previous population pharmacokinetic studies based on data from randomized clinical trials.

Population pharmacokinetics of tacrolimus in pediatric patients with systemic-onset juvenile idiopathic arthritis: Initial dosage recommendations

Pediatric patients with systemic-onset juvenile idiopathic arthritis (SOJIA) may be treated with tacrolimus. However, the therapeutic range for tacrolimus is narrow with considerable inter- and intra-individual variability, making it difficult to formulate an ideal dosage regimen for personalized treatment. The purpose of the present study was to set up a population pharmacokinetics (PPK) model of tacrolimus treatment for SOJIA to determine the optimal initial dosage. Patients with SOJIA were analyzed using non-linear mixed-effects modeling. Different regimens were analyzed using Monte Carlo simulation with concentration profiles. A first-order absorption and elimination one-compartment model was selected as the most appropriate model for SOJIA. Based on initial dosage recommendations, the regimen of 0.5 mg every 24 h (q24h) appeared to be most suitable for subjects with a body weight of 5 kg, while the 0.5 mg q12h regimen was most suitable for subjects with a body weight of 15–25 kg, the 1/0.5 mg q24h regimen was appropriate for the 26–35 kg group and the 1 mg q12h regimen was suitable for the subjects with a body weight of 36–50 kg. To the best of our knowledge, the present study established the first PPK model of tacrolimus treatment that may be used for the selection of the initial dose based on body weight of pediatric patients with SOJIA.