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A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals.

Sasso AF, Isukapalli SS, Georgopoulos PG - Theor Biol Med Model (2010)

Bottom Line: Interaction effects of complex mixtures can be directly incorporated into the GTMM.The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals.The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environmental and Occupational Health Sciences Institute, A joint institute of UMDNJ-Robert Wood Johnson Medical School and Rutgers University, Piscataway, New Jersey, USA.

ABSTRACT

Background: Humans are routinely and concurrently exposed to multiple toxic chemicals, including various metals and organics, often at levels that can cause adverse and potentially synergistic effects. However, toxicokinetic modeling studies of exposures to these chemicals are typically performed on a single chemical basis. Furthermore, the attributes of available models for individual chemicals are commonly estimated specifically for the compound studied. As a result, the available models usually have parameters and even structures that are not consistent or compatible across the range of chemicals of concern. This fact precludes the systematic consideration of synergistic effects, and may also lead to inconsistencies in calculations of co-occurring exposures and corresponding risks. There is a need, therefore, for a consistent modeling framework that would allow the systematic study of cumulative risks from complex mixtures of contaminants.

Methods: A Generalized Toxicokinetic Modeling system for Mixtures (GTMM) was developed and evaluated with case studies. The GTMM is physiologically-based and uses a consistent, chemical-independent physiological description for integrating widely varying toxicokinetic models. It is modular and can be directly "mapped" to individual toxicokinetic models, while maintaining physiological consistency across different chemicals. Interaction effects of complex mixtures can be directly incorporated into the GTMM.

Conclusions: The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals. The GTMM also made it feasible to model toxicokinetics of complex, interacting mixtures of multiple metals and nonmetals in humans, based on available literature information. The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants. As new data become available on interactions of multiple chemicals, the GTMM can be iteratively parameterized to improve mechanistic understanding of human health risks from exposures to complex mixtures of chemicals.

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A schematic depiction of major compartments considered in the generalized PBTK modeling framework (adapted from Georgopoulos, 2008) [4].
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Figure 2: A schematic depiction of major compartments considered in the generalized PBTK modeling framework (adapted from Georgopoulos, 2008) [4].

Mentions: Most PBTK model structures can be considered subsets of the same general "compartmentalized" or "network" physiology shown in Figure 2 (adapted from Georgopoulos, 2008 [4]). Blood flow rates and volumes of physiological compartments are (or at least should be) chemical-independent. Parameters of lumped compartments (e.g. flow rates and volumes of slowly perfused and rapidly perfused tissues) may vary based on the particular model structure and toxic endpoints of interest, and these appear as chemical-dependent. However, even these parameters need to be constrained so as to be consistent with the sum of those quantities for the remaining compartments. The model that is presented here accounts for all major tissues, and absorption and excretion mechanisms. Tissues that are not explicitly modeled in chemical-specific PBTK models can be lumped into rapidly or slowly perfused groups while maintaining overall physiological consistency. Deriving lumped parameter PBTK models from the general framework of Figure 2 reduces an artificial source of intermodel variation, maintains the structure of the original models, and does not require estimation of additional parameters. Chemical-specific PBTK models for toxic metals and nonmetals were mapped to this general formulation in the GTMM, thus allowing for simultaneous toxicokinetic modeling with metabolic interactions.


A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals.

Sasso AF, Isukapalli SS, Georgopoulos PG - Theor Biol Med Model (2010)

A schematic depiction of major compartments considered in the generalized PBTK modeling framework (adapted from Georgopoulos, 2008) [4].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2903511&req=5

Figure 2: A schematic depiction of major compartments considered in the generalized PBTK modeling framework (adapted from Georgopoulos, 2008) [4].
Mentions: Most PBTK model structures can be considered subsets of the same general "compartmentalized" or "network" physiology shown in Figure 2 (adapted from Georgopoulos, 2008 [4]). Blood flow rates and volumes of physiological compartments are (or at least should be) chemical-independent. Parameters of lumped compartments (e.g. flow rates and volumes of slowly perfused and rapidly perfused tissues) may vary based on the particular model structure and toxic endpoints of interest, and these appear as chemical-dependent. However, even these parameters need to be constrained so as to be consistent with the sum of those quantities for the remaining compartments. The model that is presented here accounts for all major tissues, and absorption and excretion mechanisms. Tissues that are not explicitly modeled in chemical-specific PBTK models can be lumped into rapidly or slowly perfused groups while maintaining overall physiological consistency. Deriving lumped parameter PBTK models from the general framework of Figure 2 reduces an artificial source of intermodel variation, maintains the structure of the original models, and does not require estimation of additional parameters. Chemical-specific PBTK models for toxic metals and nonmetals were mapped to this general formulation in the GTMM, thus allowing for simultaneous toxicokinetic modeling with metabolic interactions.

Bottom Line: Interaction effects of complex mixtures can be directly incorporated into the GTMM.The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals.The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environmental and Occupational Health Sciences Institute, A joint institute of UMDNJ-Robert Wood Johnson Medical School and Rutgers University, Piscataway, New Jersey, USA.

ABSTRACT

Background: Humans are routinely and concurrently exposed to multiple toxic chemicals, including various metals and organics, often at levels that can cause adverse and potentially synergistic effects. However, toxicokinetic modeling studies of exposures to these chemicals are typically performed on a single chemical basis. Furthermore, the attributes of available models for individual chemicals are commonly estimated specifically for the compound studied. As a result, the available models usually have parameters and even structures that are not consistent or compatible across the range of chemicals of concern. This fact precludes the systematic consideration of synergistic effects, and may also lead to inconsistencies in calculations of co-occurring exposures and corresponding risks. There is a need, therefore, for a consistent modeling framework that would allow the systematic study of cumulative risks from complex mixtures of contaminants.

Methods: A Generalized Toxicokinetic Modeling system for Mixtures (GTMM) was developed and evaluated with case studies. The GTMM is physiologically-based and uses a consistent, chemical-independent physiological description for integrating widely varying toxicokinetic models. It is modular and can be directly "mapped" to individual toxicokinetic models, while maintaining physiological consistency across different chemicals. Interaction effects of complex mixtures can be directly incorporated into the GTMM.

Conclusions: The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals. The GTMM also made it feasible to model toxicokinetics of complex, interacting mixtures of multiple metals and nonmetals in humans, based on available literature information. The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants. As new data become available on interactions of multiple chemicals, the GTMM can be iteratively parameterized to improve mechanistic understanding of human health risks from exposures to complex mixtures of chemicals.

Show MeSH
Related in: MedlinePlus