MOSAICbioacc
MOSAICbioacc calculates bioaccumulation metrics by fitting toxicokinetic (TK) models to accumulation-depuration data to quantify Bioconcentration Factors (BCF), Biota-Media Accumulation Factors (BMF), and Biota-Sediment Accumulation Factors (BSAF) for ecotoxicological assessment.
Key Features:
- Metric calculation: Computes BCF, BMF, and BSAF for species–compound combinations and reports associated uncertainties.
- Toxicokinetic model fitting: Fits toxicokinetic (TK) models to accumulation-depuration data to derive parameter estimates used for metric calculation.
- Handling complex exposure scenarios: Accommodates various routes of exposure, metabolism, and mixtures in the analysis of accumulation-depuration data.
- Uncertainty quantification: Propagates uncertainty from model fitting to the estimated bioaccumulation metrics.
- Transparency and reproducibility: Produces results and metric estimates in a transparent format suitable for reproducibility and validation.
Scientific Applications:
- Ecotoxicological assessment: Provides quantitative bioaccumulation metrics to inform organism and chemical-specific ecotoxicology studies.
- Regulatory decision support: Supports regulatory evaluations and market authorization processes for active substances by supplying BCF, BMF, and BSAF estimates.
- Research on complex exposures: Enables investigation of the effects of multiple exposure routes, metabolism, and mixtures on bioaccumulation.
Methodology:
Automated fitting of toxicokinetic (TK) models to accumulation-depuration data, generation of BCF/BMF/BSAF from fitted TK models, and quantification of uncertainties associated with the estimated metrics.
Topics
Details
- Tool Type:
- web application
- Added:
- 1/18/2021
- Last Updated:
- 10/11/2021
Operations
Publications
Ratier A, Lopes C, Multari G, Mazerolles V, Carpentier P, Charles S. New perspectives on the calculation of bioaccumulation metrics for active substances in living organisms. Integrated Environmental Assessment and Management. 2021;18(1):10-18. doi:10.1002/ieam.4439. PMID:33982382.