How Are Computational Models Transforming Toxicological Studies?
The advent of computational toxicology has introduced powerful models that simulate the effects of chemicals on biological systems. These models, including Quantitative Structure-Activity Relationship (QSAR) models, help predict the toxicity of new compounds, reducing the reliance on animal testing. Machine learning algorithms further enhance these predictions by analyzing vast datasets to identify patterns and potential hazards.
