Coupling of computer modeling with in vitro methodologies to reduce animal usage in toxicity testing

Area of Science:

• Toxicology
• Pharmacokinetics
• Computational Biology

Background:

• In vitro data are increasingly used to inform physiologically based pharmacokinetic (PBPK) models.
• Reducing in vivo animal testing is a key goal in chemical risk assessment.
• PBPK models integrate biological and chemical data for predicting chemical behavior in the body.

Purpose of the Study:

• To demonstrate the utility of in vitro data in developing PBPK models.
• To showcase how PBPK models supported by in vitro data can reduce the need for in vivo studies.
• To illustrate the application of PBPK modeling in human risk assessment for specific chemicals.

Main Methods:

• Utilized in vitro studies to characterize metabolism, tissue partitioning, and enzyme inhibition for PBPK model parameterization.
• Integrated in vitro human metabolism data into PBPK models for refined risk assessments.
• Developed PBPK models for polychlorotrifluoroethylene, organophosphate esters, and methylene chloride.

Main Results:

• In vitro data enabled definitive human risk assessment for polychlorotrifluoroethylene without additional primate in vivo studies.
• A PBPK model for organophosphate esters accurately described enzyme inhibition across species (mice, rats, humans) after acute and chronic exposures.
• Incorporation of in vitro human metabolism data refined the carcinogenic risk assessment for methylene chloride.

Conclusions:

• In vitro data are crucial for developing robust PBPK models.
• PBPK models parameterized with in vitro data can effectively reduce reliance on in vivo testing.
• PBPK modeling integrating in vitro data enhances the accuracy and efficiency of chemical risk assessment.