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

Abstract

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.

Keywords:

• Model extrapolation
• real-world dataset
• tacrolimus
• population pharmacokinetics
• pediatric liver transplantation

Disclosure statement

The authors report no declarations of interest. The authors alone are responsible for the content and writing of this article.

Additional information

Funding

This work was supported by Clinical Pharmacy Key Specialty Construction Project of Shanghai (No. YZ2017/5); Important Weak Subject Construction Project of Shanghai (No. 2016ZB0305); Scientific research project of Science and Technology Commission of Shanghai Municipality (No. 18DZ1910604); Fudan University Hospital Management Construction Project (No. Fudan medical administration 2018).