Several methods are employed to fill data gaps in toxicology:
1. Read-Across: This method involves using data from similar chemicals to predict the properties of the substance in question. It relies on the assumption that similar chemical structures will exhibit similar toxicological properties.
2. Quantitative Structure-Activity Relationship (QSAR) Models: QSAR models use mathematical equations to predict the toxicity of a chemical based on its molecular structure. These models can be highly effective in predicting various toxicological endpoints.
3. In Silico Modeling: These computer-based models simulate biological processes to predict the potential toxicity of chemicals. They can be used for both hazard identification and dose-response assessment.
4. In Vitro Testing: Laboratory tests using cell cultures or isolated tissues can provide valuable data on the toxicity of substances. These tests are often used as alternatives to animal testing.
5. Weight of Evidence (WoE) Approach: This method integrates data from multiple sources, including experimental studies, computational models, and expert opinions, to provide a comprehensive assessment of a chemical's toxicity.
