Applicability analysis and evaluation of aglycones in single-pass intestinal perfusion technique based on PBPK model / 中国中药杂志

Single-pass intestinal perfusion( SPIP) is the common carrier of biopharmaceutics classification system( BCS) to study compound permeability. With the application and deepening study of BCS in the field of traditional Chinese medicine( TCM),SPIP model is becoming more and more common to study the intestinal absorption of TCM ingredients. Based on the limitations of the SPIP model in some researches on TCM permeability,it was speculated in this study that aglycone may be more suitable than the glycoside to study the intestinal absorption problem by using SPIP model. Furthermore,applicability of aglycone components was analyzed and evaluated. In this study,with quercetin,daidzein,formononetin,genistein and glycyrrhetinic acid used as research objects,the quantitative study of SPIP was used to evaluate the intestinal permeability of these aglycones and to predict the effective permeability coefficient( Peff) and absorption fraction( Fa) in human body. By combining studies comparison and analysis on multiple permeability research methods and prediction of human body absorption of aglycones in physiological-based pharmacokinetic models,this paper can further illustrate that the SPIP model is a good tool for studying the permeability of aglycones and predicting human absorption,which can provide data foundation and theoretical reference for researches on SPIP technique and BCS in intestinal absorption of TCM ingredients.

Application of physiologically based pharmacokinetic models to drug evaluation:research progress / 中国药理学与毒理学杂志

Currently,a physiologically based pharmacokinetic(PBPK)model plays a key role in pharmaceutical research,which has been widely used at each stage of drug discovery and develop?ment. In the process of drug discovery,the selection of drug candidates is finished using the PBPK model to predict the pharmacokinetic properties of the drugs. In the process of preclinical development , through a combination of in vitro and physiological data amplification coefficient,the PBPK model can be used to predict not only the overall pharmacokinetic behavior of drug candidates in humans and animals and in vitro metabolism experiments,but also drug-drug interactions(DDI). In the course of clinical development,the PBPK model can help predict the difference between reference populations (age,different disease state,and polymorphism),especially the dosage and sampling time of the children. At present,the input parameters of PBPK model are mostly the mean values of the population,making it difficult to serve individuals. It is hoped that the input parameters of the model can reflect more of the individual characters according to the individual requirement,and that the time parameters of the input accord more with the actual physiological condition. In this article ,we briefly introduced the characteristics of common PBPK software,and reviewd the principle and feature of the PBPK model,as well as its application to drug discovery,preclinical development and clinical development,DDI,and individualized medication.

Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol / 대한마취과학회지

BACKGROUND: We investigated how one pharmacokinetic (PK) model differed in prediction of plasma (Cp) and effect-site concentration (Ceff) using a reproducing simulation of target-controlled infusion (TCI) with another PK model of propofol. METHODS: Sixty female patients were randomly assigned to TCI using Marsh PK (Group M) and TCI using Schnider PK (Group S) targeting 6.0 microg/ml of Cp of propofol for induction of anesthesia, and loss of responsiveness (LOR) was evaluated. Total and separate cross-simulation were investigated using the 2 hr TCI data (Marsh TCI and Schnider TCI), and we investigated the reproduced predicted concentrations (MARSHSCH and SCHNIDERMAR) using the other model. The correlation of the difference with covariates, and the influence of the PK parameters on the difference of prediction were investigated. RESULTS: Group M had a shorter time to LOR compared to Group S (P < 0.001), but Ceff at LOR was not different between groups. Reproduced simulations showed different time courses of Cp. MARSHSCH predicted a higher concentration during the early phase, whereas SCHNIDERMAR was maintained at a higher concentration. Volume and clearance of the central compartment were relevant to the difference of prediction, respectively. Body weight correlated well with differences in prediction between models (Rsqr = 0.9821, P < 0.001). CONCLUSIONS: We compared two PK models to determine the different infusion behaviors during TCI, which resulted from the different parameter sets for each PK model.