Use of in vitro data in developing a physiologically based pharmacokinetic model: Carbaryl as a case study
Miyoung Yoon1, Gregory L Kedderis2, Grace Zhixia Yan1
1Center for Human Health Assessment, The Hamner Institutes for Health Sciences, Research Triangle Park, NC, USA.
Abstract:
In vitro-derived information has been increasingly used to support and improve human health risk assessment for exposure to chemicals. Physiologically based pharmacokinetic (PBPK) modeling is a key component in the movement toward in vitro-based risk assessment, providing a tool to integrate diverse experimental data and mechanistic information to relate in vitro effective concentrations to equivalent human exposures. One of the challenges, however, in the use of PBPK models for this purpose has been the need for extensive chemical-specific parameters. With the remarkable advances in in vitro methodologies in recent years, in vitro-derived parameters can now be easily incorporated into PBPK models. In this study we demonstrate an in vitro data based parameterization approach to develop a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model, using carbaryl as a case study. In vitro experiments were performed to provide the chemical-specific pharmacokinetic (PK) and pharmacodynamic (PD) parameters for carbaryl in the PBPK model for this compound. Metabolic clearance and cholinesterase (ChE) interaction parameters for carbaryl were measured in rat and human tissues. These in vitro PK and PD data were extrapolated to parameters in the whole body PBPK model using biologically appropriate scaling. The PBPK model was then used to predict the kinetics and ChE inhibition dynamics of carbaryl in vivo. This case study with carbaryl provides a reasonably successful example of utilizing the in vitro to in vivo extrapolation (IVIVE) approach for PBPK model development. This approach can be applied to other carbamates with an anticholinesterase mode of action as well as to environmental chemicals in general with further refinement of the current shortcomings in the approach. It will contribute to minimizing the need for in vivo human data for PBPK model parameterization and evaluation in human risk assessments.
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