Predictive toxicology involves using computational tools, database searches, and chemo-informatics approaches to assess the potential toxicity of individual compounds and compound clusters across various domains.
We analyse toxicity risks in plastics, drug formulations, environmental/ecological systems, and botanical extracts (e.g., foods and herbal medicines). By integrating machine learning models, structure-activity relationship (SAR) analysis, and toxicity prediction software, we identify hazardous compounds, detect patterns of toxicity, and assess safety profiles.
These predictive methods help in early risk assessment, reducing reliance on animal testing, streamlining regulatory compliance, and improving the development of safer pharmaceuticals and consumer products.
