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

Li, Ling; Zhu, Min; Li, Deyi; Guo, Hongli; Hu, Yahui; Xu, Ze-Yue; Xia, Jing; Chen, Feng; Zhao, Fei; Li, Yunman; Xu, Jing; Jiao, Zheng

doi:10.1016/j.intimp.2021.107827

Cited by 8 publications

(5 citation statements)

References 52 publications

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“…Most previously published studies selected the linear compartmental model, aligning with the traditional view that tacrolimus's PK is linear. Even so, the nonlinear tacrolimus kinetics in paediatric patients with primary nephrotic syndrome 62 and refractory nephrotic syndrome 63 have been reported. They found that the nonlinear Michaelis–Menten model was a better fit for the data than the linear model, demonstrating a better individual prediction.…”

Section: Discussionmentioning

confidence: 99%

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review

Khamlek,

Komenkul,

Sriboonruang

et al. 2023

Brit J Clinical Pharma

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AimsThis study aimed to provide up‐to‐date information on paediatric population pharmacokinetic models of tacrolimus and to identify factors influencing tacrolimus pharmacokinetic variability.MethodsSystematic searches in the Web of Science, PubMed, Scopus, Science Direct, Cochrane, EMBASE databases and reference lists of articles were conducted from inception to March 2023. All population pharmacokinetic studies of tacrolimus using nonlinear mixed‐effect modelling in paediatric solid organ transplant patients were included.ResultsOf the 21 studies reviewed, 62% developed from liver transplant recipients and 33% from kidney transplant recipients. Most studies used a 1‐compartment model to describe tacrolimus pharmacokinetics. Body weight was a significant predictor for tacrolimus volume of distribution (Vd/F). The estimated Vd/F for 1‐compartment models ranged from 20 to 1890 L, whereas the peripheral volume of distribution (Vp/F) for 2‐compartment models was between 290 and 1520 L. Body weight, days post‐transplant, CYP3A5 genotype or haematocrit were frequently reported as significant predictors of tacrolimus clearance. The estimated apparent clearance values range between 0.12 and 2.18 L/h/kg, with inter‐individual variability from 13.5 to 110.0%. Only 29% of the studies assessed the generalizability of the models with external validation.ConclusionThis review highlights the potential factors, modelling approaches and validation methods that impact tacrolimus pharmacokinetics in a paediatric population. The clinician could predict tacrolimus clearance based on body weight, CYP3A5 genotype, days post‐transplant or haematocrit. Further research is required to determine the relationship between pharmacogenetics and tacrolimus pharmacodynamics in paediatric patients and confirm the applicability of nonlinear kinetics in this population.

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Section: Discussionmentioning

confidence: 99%

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review

Khamlek,

Komenkul,

Sriboonruang

et al. 2023

Brit J Clinical Pharma

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“…In actual practice, conditional WRES is usually with FOCE-I, and of course this is acceptable. Thus, conditional WRES are all with FOCE-I in the following: Jing et al’s ( 2021 ) pharmacokinetic analysis and dosing guidelines for tacrolimus co-administration with wuzhi capsules in Chinese renal transplant recipients; Li et al’s (2021 ) study of dose tailoring of tacrolimus, based on a non-linear pharmacokinetic model in children with refractory nephrotic syndrome; Yu et al’s (2021 ) study of pharmacokinetics and optimization of polymyxin B dosing in adult patients with various renal functions; Ma et al’s (2020 ) study of the pharmacokinetics of vancomycin in kidney transplant recipients; and Cai et al’s (2020 )model building and parameter optimization in pharmacokinetics and dosing regimen optimization of tacrolimus in Chinese lung transplant recipients.…”

Section: Discussionmentioning

confidence: 99%

Initial sirolimus dosage recommendations for pediatric patients with PIK3CD mutation-related immunodeficiency disease

Chen

Wang²,

Lan³

et al. 2022

Front. Pharmacol.

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Sirolimus is used to treat pediatric patients with PIK3CD mutation-related immunodeficiency disease. However, the initial dosages of sirolimus remain undecided. The present study aims to explore initial dosages in pediatric patients with PIK3CD mutation-related immunodeficiency disease. Pediatric patients with this disease were analyzed using the population pharmacokinetic (PPK) model and the Monte Carlo simulation. Body weight and concomitant use of posaconazole were included in the final PPK model, where, under the same weight, clearances of sirolimus were 1 : 0.238 between children without and children with posaconazole. Without posaconazole, the initial dosages of sirolimus were 0.07, 0.06, 0.05, and 0.04 mg/kg/day for body weights of 10–14, 14–25, 25–50, and 50–60 kg, respectively. With posaconazole, the initial dosages of sirolimus were 0.02 mg/kg/day for body weights of 10–60 kg. This is the first attempt to build a sirolimus PPK model for recommending initial dosages in children with PIK3CD mutation-related immunodeficiency disease, thereby providing a reference for individualized clinical drug administration.

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“…A one-compartment model of first-order absorption and elimination was used to fit the data. The absorption rate constant (Ka) was fixed at 4.48 h −1 based on reports in the literature and suitability for pediatric populations ( Wang D. et al, 2019a ; Chen et al, 2020 ; Huang et al, 2020 ; Li et al, 2021 ). Inter-individual variation was described using an exponential model.…”

Section: Methodsmentioning

confidence: 99%

“…Currently, methods for predicting pharmacokinetics in different individuals mainly include traditional multiple linear regression methods, population pharmacokinetic (PPK) methods, and machine learning methods ( Agrawal et al, 2020 ; Li et al, 2021 ; Woillard et al, 2021 ). Multiple linear regression methods are simple to operate, but they cannot distinguish inter-and intra-individual variability.…”

Section: Introductionmentioning

confidence: 99%

Tacrolimus pharmacokinetics in pediatric nephrotic syndrome: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction

et al. 2022

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Background and Aim: Tacrolimus (TAC) is a first-line immunosuppressant for the treatment of refractory nephrotic syndrome (RNS), but the pharmacokinetics of TAC varies widely among individuals, and there is still no accurate model to predict the pharmacokinetics of TAC in RNS. Therefore, this study aimed to combine population pharmacokinetic (PPK) model and machine learning algorithms to develop a simple and accurate prediction model for TAC.Methods: 139 children with RNS from August 2013 to December 2018 were included, and blood samples of TAC trough and partial peak concentrations were collected. The blood concentration of TAC was determined by enzyme immunoassay; CYP3A5 was genotyped by polymerase chain reaction-restriction fragment length polymorphism method; MYH9, LAMB2, ACTN4 and other genotypes were determined by MALDI-TOF MS method; PPK model was established by nonlinear mixed-effects method. Based on this, six machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Extra-Trees, Gradient Boosting Decision Tree (GBDT), Adaptive boosting (AdaBoost) and Lasso, were used to establish the machine learning model of TAC clearance.Results: A one-compartment model of first-order absorption and elimination adequately described the pharmacokinetics of TAC. Age, co-administration of Wuzhi capsules, CYP3A5 *3/*3 genotype and CTLA4 rs4553808 genotype were significantly affecting the clearance of TAC. Among the six machine learning models, the Lasso algorithm model performed the best (R2 = 0.42).Conclusion: For the first time, a clearance prediction model of TAC in pediatric patients with RNS was established using PPK combined with machine learning, by which the individual clearance of TAC can be predicted more accurately, and the initial dose of administration can be optimized to achieve the goal of individualized treatment.

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

Cited by 8 publications

References 52 publications

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review

Initial sirolimus dosage recommendations for pediatric patients with PIK3CD mutation-related immunodeficiency disease

Tacrolimus pharmacokinetics in pediatric nephrotic syndrome: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction

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