We offer AI-assisted, expert-driven ICH S1B(R1) carcinogenicity assessments aligned with the current regulatory guideline. Our AI-supported workflows streamline data gathering and evaluation, enabling a comprehensive, weight-of-evidence approach that integrates literature, preclinical data, mechanistic insights, ‘omics datasets and regulatory documentation. Combined with expert review, this approach delivers robust, regulator-ready carcinogenicity reports grounded in scientific rigor and reproducibility.
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Our AI-enabled target safety assessment workflows integrate advanced automation with expert toxicological interpretation to identify and evaluate potential safety risks associated with target modulation. Leveraging AI for intelligent data extraction and analysis, we combine peer-reviewed literature, prescribing information, regulatory documentation, omics datasets (e.g., genomics and proteomics), and cheminformatics resources into a unified evaluation framework. This AI-driven, expert-led approach enables early detection of on-target and off-target risks, supporting informed decision-making and proactive risk mitigation throughout the development lifecycle.
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We apply AI-assisted workflows to accelerate and improve the derivation of safe exposure limits, including PDEs. Our AI-assisted, expert-driven approach supports rapid literature analysis and data evaluation, providing a transparent and reproducible foundation for expert toxicological interpretation. The outcome is a scientifically robust, regulator-ready assessment, reviewed and signed by our European Registered Toxicologist (ERT).
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Our AI-supported, protocol-driven workflows enable structured and comprehensive systematic reviews of toxicological data. AI automation enhances search efficiency and coverage, while expert oversight ensures accurate interpretation and traceability throughout the process. This combination delivers well-structured, evidence-based syntheses that support regulatory submissions and risk assessments.
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Our AI-enhanced read-across services integrate toxicological expertise with computational analysis across structural, physicochemical, metabolic, and toxicological domains. AI supports analog search, similarity assessment, and the automated collection and evaluation of analogue data, ensuring efficient and comprehensive data coverage. This process is complemented by expert toxicological review and uncertainty analysis, resulting in transparent, regulator-ready justifications that provide robust, science-based alternatives to traditional testing.
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Our specialized AI-assisted service applies our software technology to accelerate toxicological risk assessment. The approach can be tailored to specific project needs, enabling targeted support where automation provides the greatest value. Through controlled use of large language models, we support search, literature review, data extraction, and evidence summarization, while toxicologists retain full control of knowledge sources and task execution. A human-in-the-loop approach ensures expert validation throughout, improving efficiency without compromising accuracy, reproducibility, or accountability in final decisions.
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Whether you want to explore the Onesum Platform or engage our expert consultants, we’d love to learn about your thoughts and challenges.
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