Chung Hee Lee, Thi Quyen Tran, Woo Jin Jung, Seon Jong Park, Thi Lien Ngo, Sung Yoon Yang, Jung-Woo Chae*, Hwi-yeol Yun*
College of pharmacy, Chungnam National University
Objectives: : In vitro–in vivo extrapolation(IVIVE) is the process by which organ clearance is scaled up using in vitro data.[1] IVIVE approaches was based on physiologically based scaling approaches, different with empirical allometric scaling approaches, so many of researchers was used it to predict systemic exposure with in-vitro drum metabolism and pharmacokinetic studies.[2] Nevertheless of its advantages, the process can be cumbersome, and there are also various assumptions about that. This study is to develop user-friendly IVIVE platform using R shiny and confirm performance to predict organ clearance in comparison with real clearance.
Methods: The IVIVE approaches established to date have been obtained from the reference literature.[2] Estimate the in vitro intrinsic hepatic clearance based on Vmax and Km, or half-life of drug disappearance in in vitro metabolism studies. Extrapolate CLint, in vitro to in vivo intrinsic hepatic clearance with proper scaling factors. Calculate in vivo CLh, according to hepatic clearance models with estimates of CLint,h, Qh, and fu.
The functional equations for hepatic clearance (e.g., well-stirred model, parallel tube mode and dispersion model) were implemented to be able to calculate the mathematical equations with R program. Differences in the estimates of CLh from well-stirred model and parallel tube model are less important for lower-clearance drugs, drugs with fu·CLi,h<<Qh.
Consequently, using R Shiny, several approaches were applied at once using the parameters obtained from in vitro to implement in vivo hepatic clearance for each approach in comparison. The evaluation was conducted for the reliability of the program through comparison with the drug-specific hepatic clearance by drug obtained from the literature.[3]
Results: There was no significant difference between the values of hepatic clearance obtained from references and the outcomes produced from the program. The results obtained were applied to each of the comparative approaches to intuitively represent all the results for each approach. User-friendly interface was made on open-platform of R Shiny.
Conclusions: The program performed validation well. This is likely to be a tool for many researchers to obtain in vivo hepatic clearance through in vitro. R shiny package was firmly built between various R packages, many possibilities of application is secured.
Acknowledgement: This research was supported by a grant (18182MFDS405 and 19182MFDS427) from Ministry of Food and Drug Safety in 2018 and 2019, respectively.
References:
[1] Khojasteh, S.C., H. Wong, and C.E. Hop, Drug metabolism and pharmacokinetics quick guide. 2011: Springer Science & Business Media.
[2] Zou, P., et al., Applications of human pharmacokinetic prediction in first-in-human dose estimation. AAPS J, 2012. 14(2): p. 262-81.
[3] Ito, K. and J.B. Houston, Comparison of the use of liver models for predicting drug clearance using in vitro kinetic data from hepatic microsomes and isolated hepatocytes. Pharm Res, 2004. 21(5): p. 785-92.
Reference: PAGE () Abstr 9418 [www.page-meeting.org/?abstract=9418]
Poster: Methodology - Estimation Methods