DallphinAtoM: Physiologically based pharmacokinetics software predicting human PK parameters based on physicochemical properties, in vitro and animal in vivo data

Computer Methods and Programs in Biomedicine(2022)

引用 0|浏览18
暂无评分
摘要
Background and objectives In silico experiments and simulations using physiologically based pharmacokinetic (PBPK) and allometric approaches have played an important role in pharmaceutical research and drug development. These methods integrate diverse data from preclinical and clinical development, and have been widely applied to in vitro-in vivo extrapolation (IVIVE) of absorption, distribution, metabolism, and excretion (ADME). Methods To develop a user-friendly open tool predicting human PK, we assessed various references on PBPK and allometric methods published so far. They were integrated into a software system named “DallphinAtoM” (Drugs with ALLometry and PHysiology Inside-Animal to huMan), which has a user-friendly platform that can handle complex PBPK models and allometric models with a relatively small amount of essential information of the drug. The models of DallphinAtoM support the integration of data gained during the nonclinical development phase, enable translation from animal to human, and allow the prediction of concentration-time profiles with predicted PK parameters. Results We presented two illustrative applications using DallphinAtoM: (1) human PK simulation of an orally administered drug using PBPK method; and (2) simulation of intravenous infusion following a two-compartment model using the allometric scaling method. Conclusions We conclude that this is a straightforward and transparent tool allowing fast and reliable human PK simulation based on the latest knowledge on biochemical processes and physiology and provides valuable information for decision making during the early-phase drug development.
更多
查看译文
关键词
Physiologically based pharmacokinetics (PBPK),Allometric scaling,In vitro-in vivo extrapolation (IVIVE),Simulation,Population pharmacokinetics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要