Review of acute chemical incidents as a first step in evaluating the usefulness of physiologically based pharmacokinetic models in such incidents

Integrated environmental health assessment: Proposed approaches to exposure during chemical incidents

An integrated environmental health exposure assessment (IEHA) refers to the integration of human biomonitoring data (HBM) and environmental measurements and aims to optimize the exposure assessment process. Due to lack of data, this approach remains an issue during chemical incidents. This study aims to explore integrated exposure approaches for assessing human health risks during chemical incidents. Based on the Preferred Reporting Items of Systematic reviews and Meta-Analyses statement, a literature analysis was performed. A level of confidence ranging from 1 to 4 was established to define the quality and strength of data used to undertake an IEHA approach. Twenty-seven articles (n = 18) and texts (n = 9) from Europe (41%) and the United States (37%) were analyzed. Among the 18 scientific articles, 61% (n = 11) presented a quantitative approach and 17% (n = 3) presented a qualitative approach. Quantitative approaches must be based on accurate data, coupled with predictive models. Of all the scientific papers, 40% (n = 7) responded to a confidence level greater than or equal to 2. Uncertainties detected through the integrated exposure approaches were related to input data, analytical methods, and HBM reference value interpretations. During chemical incidents, direct measurements were the most relevant data. Few scientific studies have developed an integrated approach during emergency situations. However, when this was used, they presented a high level of confidence by defining levels of exposure that support decision-making processes. Despite the multiple approaches, there was a lack of guidelines allowing an integrated risk assessment to be performed during an emergency chemical exposure. Integr Environ Assess Manag 2024;20:481-497. © 2023 SETAC.

Evaluation of semi-generic PBTK modeling for emergency risk assessment after acute inhalation exposure to volatile hazardous chemicals

BACKGROUND

Physiologically Based Toxicokinetic Models (PBTK) may facilitate emergency risk assessment after chemical incidents with inhalation exposure, but they are rarely used due to their relative complexity and skill requirements. We aimed to tackle this problem by evaluating a semi-generic PBTK model built in MS Excel for nine chemicals that are widely-used and often released in a chemical incident.

MATERIAL & METHODS

The semi-generic PBTK model was used to predict blood concentration-time curves using inhalation exposure scenarios from human volunteer studies, case reports and hypothetical exposures at Emergency Response Planning Guideline, Level 3 (ERPG-3) levels.(2) Predictions using this model were compared with measured blood concentrations from volunteer studies or case reports, as well as blood concentrations predicted by chemical-specific models. The performances of the semi-generic model were evaluated on biological rationale, accuracy, and ease of use and range of application.

RESULTS

Our results indicate that the semi-generic model can be easily used to predict blood levels for eight out of nine parent chemicals (dichloromethane, benzene, xylene, styrene, toluene, isopropanol trichloroethylene and tetrachloroethylene). However, for methanol, 2-propanol and dichloromethane the semi-generic model could not cope with the endogenous production of methanol and of acetone (being a metabolite of 2-propanol) nor could it simulate the formation of HbCO, which is one of the toxic end-points of dichloromethane. The model is easy and intuitive to use by people who are not so familiar with toxicokinetic models.

CONCLUSION

A semi-generic PBTK modeling approach can be used as a 'quick-and-dirty' method to get a crude estimate of the exposure dose.

An introduction to systems toxicology

Systems toxicology combines novel and historical experimental data to generate increasingly complex models of the biological response to chemical exposure.