Target Safety Assessment

By aggregating information from genetics and genomics, toxicity databases, pathological readouts, clinical trial and scientific literature, our pipeline enables a holistic assessment of target-associated risks. The integration of AI-powered automation enhances efficiency, reproducibility, and scalability, allowing researchers to process vast amounts of data rapidly while minimizing human error. Advanced bioinformatics and machine learning models identify potential liabilities, such as off-target effects, tissue-specific toxicities, and unintended gene interactions, which could compromise drug safety. This proactive approach facilitates early-stage risk mitigation, reducing costly late-stage failures and improving decision-making in target selection and drug design. Additionally, by continuously incorporating new data and refining predictive models, our TSA pipeline evolves over time, increasing the accuracy of safety predictions and accelerating the overall drug discovery process.