Lingfei Huang1, Yixi Liu2, Zheng Jiao3, Junyan Wang1, Luo Fang1, Jianhua Mao4. 1. Department of Pharmacy, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China. 2. Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai 200040, China. 3. Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, West Huaihai Road 241, Shanghai 200030, China. Electronic address: jiaozhen@online.sh.cn. 4. Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China.
Abstract
BACKGROUND: Little is known about the population pharmacokinetics (PPK) of tacrolimus (TAC) in pediatric patients with primary nephrotic syndrome (PNS). In this study, we aimed to compare the predictive performance between nonlinear and linear PK models and investigate the significant factors influencing TAC PK characteristics in pediatric PNS. METHODS: Data were obtained from 71 pediatric patients with PNS, along with 525 TAC trough concentrations at steady-state. Patients' demographic, medical, and treatment details were collected. Genetic polymorphisms of CYP3A4*1G, CYP3A5*3, and ABCB1-C3435T were analyzed. The PPK models were developed using nonlinear mixed-effects model (NONMEM®) software. Two modeling strategies, linear compartmental and nonlinear Michaelis-Menten (MM) models, were evaluated and compared. RESULTS: Body weight, age, daily dose of TAC, co-therapy drugs (including azole antifungal agents and diltiazem), and CYP3A5*3 genotype were the important factors in the final linear model (one-compartment model), whereas only body weight, co-therapy drugs, and CYP3A5*3 genotype were the important factors in the final nonlinear MM model. Apparent clearance and volume of distribution in the final linear model were 7.13 L/h and 142 L, respectively. The maximal dose rate (Vmax) of the nonlinear MM model was 1.92 mg/day and the average concentration at steady-state at half-Vmax (Km) was 1.98 ng/mL. The nonlinear model described the data better than the linear model. Dosing regimens were proposed based on the nonlinear PK model. CONCLUSION: Our findings demonstrated that the nonlinear MM model showed better predictive performance than the linear compartmental model, providing reliable support for optimizing TAC dosing and adjustment in children with PNS.
BACKGROUND: Little is known about the population pharmacokinetics (PPK) of tacrolimus (TAC) in pediatric patients with primary nephrotic syndrome (PNS). In this study, we aimed to compare the predictive performance between nonlinear and linear PK models and investigate the significant factors influencing TAC PK characteristics in pediatric PNS. METHODS: Data were obtained from 71 pediatric patients with PNS, along with 525 TAC trough concentrations at steady-state. Patients' demographic, medical, and treatment details were collected. Genetic polymorphisms of CYP3A4*1G, CYP3A5*3, and ABCB1-C3435T were analyzed. The PPK models were developed using nonlinear mixed-effects model (NONMEM®) software. Two modeling strategies, linear compartmental and nonlinear Michaelis-Menten (MM) models, were evaluated and compared. RESULTS: Body weight, age, daily dose of TAC, co-therapy drugs (including azole antifungal agents and diltiazem), and CYP3A5*3 genotype were the important factors in the final linear model (one-compartment model), whereas only body weight, co-therapy drugs, and CYP3A5*3 genotype were the important factors in the final nonlinear MM model. Apparent clearance and volume of distribution in the final linear model were 7.13 L/h and 142 L, respectively. The maximal dose rate (Vmax) of the nonlinear MM model was 1.92 mg/day and the average concentration at steady-state at half-Vmax (Km) was 1.98 ng/mL. The nonlinear model described the data better than the linear model. Dosing regimens were proposed based on the nonlinear PK model. CONCLUSION: Our findings demonstrated that the nonlinear MM model showed better predictive performance than the linear compartmental model, providing reliable support for optimizing TAC dosing and adjustment in children with PNS.