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Compatibility Study between Physiologically Based Pharmacokinetic (PBPK) and Compartmental PK Model Using Lumping Method: Application to the Voriconazole Case

럼핑법을 이용한 생리학 기반 약물동태모델 및 구획화 약물동태모델 상호 호환 연구: 보리코나졸 적용 연구

  • Ryu, Hyo-jeong (College of Pharmacy, Chungnam National University) ;
  • Kang, Won-ho (College of Pharmacy, Chungnam National University) ;
  • Chae, Jung-woo (College of Pharmacy, Chungnam National University) ;
  • Yun, Hwi-yeol (College of Pharmacy, Chungnam National University)
  • Received : 2021.04.08
  • Accepted : 2021.05.10
  • Published : 2021.06.30

Abstract

Background: Generally, pharmacokinetics (PK) models could be stratified into two models. The compartment PK model uses the concept of simple compartmentalization to describe complex bodies, and the physiologically based pharmacokinetic (PBPK) model describes the body using multi-compartment networking. Notwithstanding sharing a theoretical background in both models, there was still a lack of knowledge to enhance compatibility in both models. Objective: This study aimed to evaluate the compatibility among PBPK, lumping model and compartment PK model with voriconazole PK case study. Methods: The number of compartments and blood flow on each tissue in the PBPK model were modified using the lumping method, considering physiological similarities. The concentration-time profiles and area under the concentration-time curve (AUC) parameters were simulated at each model, assuming taken voriconazole oral 400 mg single dose. After that, those mentioned PK parameters were compared. Results: The PK profiles and parameters of voriconazole in the three models were similar that proves their compatibility. The AUC of central compartment in the PBPK and lumping model was within a 2-fold range compared to those in the 2- compartment model. The AUC of non-eliminating tissues compartment in the PBPK model was similar to those in the lumping model. Conclusion: Regarding the compatibility of the three PK models, the utilization of the lumping method was confirmed by suggesting its reliable PK parameters with PBPK and compartment PK models. Further case studies are recommended to confirm our findings.

Keywords

Acknowledgement

이 논문은 충남대학교 학술연구비 및 2020년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원(No. 2020-0-01441, 인공지능융합연구센터지원(충남대학교))의 지원을 받아 수행된 연구임.

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