Translating human biomonitoring data into quantitative exposure and risk estimates for chloromethylisothiazolinone and methylisothiazolinone using a population pharmacokinetic model.

Human biomonitoring provides direct measures of internal exposure to environmental chemicals, but translating biomarker concentrations into quantitative external exposure and risk estimates remains challenging. Chloromethylisothiazolinone (CMIT) and methylisothiazolinone (MIT) are widely used biocides, and population exposure is typically assessed via urinary biomarkers. However, a quantitative framework connecting biomonitoring data to external dose and health risk is currently lacking. This study aims to quantitatively reconstruct external CMIT/MIT exposures from human urinary biomonitoring data using a population pharmacokinetic (PopPK) model and to assess human health risk via integrating reverse dosimetry with an internal dose-based reference dose (RfD). A human-scale PopPK model capable of quantitatively describing urinary excretion of N-methylmalonamic acid and the mercapturic acid metabolite M-12 following oral CMIT/MIT exposure was developed. Model parameters were estimated using nonlinear mixed-effects modeling and evaluated via bootstrap analysis, visual predictive checks, goodness-of-fit diagnostics, and normalized prediction distribution error analysis. The validated model was then applied to adult biomonitoring data from the German Environmental Sample Bank and to pediatric and adolescent survey data. External exposure doses were reconstructed via reverse dosimetry, accounting for inter-individual PK variability. Human health risk was quantified using the margin of exposure (MOE) approach, referencing an internal dose-derived oral RfD of 0.02 mg/kg/day. The final PopPK model reliably captured urinary biomarker excretion dynamics at population and individual levels. Parameter estimates were robust, with bootstrap medians closely aligned with the final model values. Reconstructed external exposures exhibited no consistent long-term increasing or decreasing trend in adults and no systematic age- or sex-related pattern in pediatric and adolescents. Most exposure scenarios yielded MOE values > 10, while only extreme upper-bound conditions yielded MOEs of approximately 2-5. Even under conservative assumptions, all MOE values remained above 1. This study demonstrates that human biomonitoring data can be quantitatively translated into external exposure and risk metrics using a PopPK-based reverse dosimetry framework. The findings indicate that current CMIT/MIT exposure levels in the general population are unlikely to pose health concerns under typical environmental conditions. The integrated biomonitoring-modeling approach offers a regulatory-relevant framework for linking internal biomarkers to external exposure and health risk assessment.