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A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals
Alan F Sasso1, Sastry S Isukapalli, Panos G Georgopoulos
1Environmental and Occupational Health Sciences Institute, A joint institute of UMDNJ-Robert Wood Johnson Medical School and Rutgers University, Piscataway, New Jersey, USA.
Theoretical Biology & Medical Modelling
|June 8, 2010
Summary
A new Generalized Toxicokinetic Modeling system for Mixtures (GTMM) allows consistent study of chemical mixtures. This system enables better understanding of cumulative health risks from environmental contaminants.
Area of Science:
- Environmental Health
- Toxicology
- Computational Biology
Background:
- Humans face concurrent exposure to multiple toxic chemicals, including metals and organics, potentially causing synergistic adverse effects.
- Current toxicokinetic modeling often focuses on single chemicals, leading to incompatible models and hindering synergistic effect analysis.
- A consistent modeling framework is needed to systematically study cumulative risks from complex chemical mixtures.
Purpose of the Study:
- To develop and evaluate a Generalized Toxicokinetic Modeling system for Mixtures (GTMM).
- To enable consistent, physiologically-based modeling of chemical mixtures.
- To facilitate the study of synergistic effects and cumulative risks.
Main Methods:
- Development of a physiologically-based Generalized Toxicokinetic Modeling system for Mixtures (GTMM).
- GTMM utilizes a chemical-independent physiological description for integrating diverse toxicokinetic models.
- The modular system allows direct mapping to individual models and incorporates interaction effects.
Main Results:
- GTMM application to metals and metal compounds validated its ability to explain observational data.
- The system replicated results from individually optimized chemical models.
- GTMM enabled modeling of toxicokinetics for complex, interacting mixtures of metals and nonmetals in humans.
Conclusions:
- GTMM provides a foundational component for a "source-to-dose-to-effect" risk assessment framework.
- The system facilitates mechanistic understanding of human health risks from complex chemical exposures.
- GTMM can be iteratively improved with new data on chemical interactions for enhanced risk modeling.
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