Download Center

Bayesian analysis of physiologically based pharmacokinetics modelling of perchloroethylene in humans
Mathematics and Computer Sciences Journal (MCSJ), Volume 2, Aug 2017

View Abstract   Hide Abstract
Abstract
This study is to estimate population distributions of PBPK model parameters and to make a dose reconstruction with clinical data from uncontrolled studies. Perchloroethylene (PCE) is a widely distributed pollutant in the environment. The cancer risks of PCE at low exposures are uncertain. PCE occurs widely in the dry cleaning establishments and also can be found in indoor air. However, the concentrations of PCE are mostly below 1ppm. Therefore, it is very important to assess cancer risks at these low concentrations. A human physiologically based pharmacokinetics (PBPK) model was used to quantify tissue doses of PCE and its key metabolite, Trichloroacetic Acid (TCA) after inhalation exposures. This PBPK model was integrated with a statistical hierarchical model to acknowledge variations due to intraindividual variation, interindividual variation, measurement error and difference between study methods. A Bayesian approach, Markov chain Monte Carlo analysis, was employed to analyze clinical data obtained from controlled studies. The data are on alveolar or exhaled breath concentrations of PCE, blood concentrations of PCE and TCA, urinary excretion of TCA. The posterior distributions of PBPK model parameters were obtained. Predictive ability of posteriors was satisfactory. Posterior predictions are much better than prior fit.

Author(s): Junshan Qiu
Choose an option to locate/access this article/journal

Check if you have access through your login credentials or your institution

Members Login Panel

To Complete the Process of Article Purchasing, Please click on Payment Button. You can make a credit card payment through the highly secure payment system, you can now pay your bill online 24 hours a day;

Journals
Authors

 

Click on the above icon to go to the OASP Web-based Submission System

Editorial

The process of peer review involves an exchange between a journal editor and a team of reviewers, also known as referees. A simple schematic of OASP's Peer-Review process has been shown in this section.