Accumulation-depuration data collection in support of toxicokinetic modelling

Area of Science:

• Environmental Science
• Toxicology
• Computational Biology

Background:

• Chemical bioaccumulation evaluation is crucial for assessing toxic risks by regulatory bodies.
• Toxicokinetic (TK) data link chemical exposure to organismal accumulation and depuration, aiding risk assessment.
• Existing TK data are often inaccessible, primarily presented as plots in scientific literature, hindering TK modeling.

Purpose of the Study:

• To develop an accessible database of toxicokinetic (TK) data extracted from scientific literature.
• To support the development and application of TK models for predicting chemical concentrations in organisms.
• To enhance the availability, findability, accessibility, interoperability, and reusability (FAIR principles) of TK data.

Main Methods:

• Systematic extraction of TK data from published scientific literature.
• Development of a novel database to store and organize extracted TK data.
• Implementation of a dynamic data model to allow for continuous updates and contributions from researchers.

Main Results:

• Creation of a freely available database containing extracted TK data.
• The database facilitates the use of TK data for TK modeling and bioaccumulation metric calculation.
• Established a platform for researchers to share data, promoting collaborative and cumulative scientific advancement.

Conclusions:

• The developed database significantly improves access to crucial TK data for regulatory and research purposes.
• Enhanced data accessibility supports more accurate toxicological risk assessments and predictive modeling.
• The initiative promotes data sharing and reusability within the scientific community, fostering advancements in chemical safety.