DILIsym is the flagship Quantitative Systems Toxicology (QST) software platform from Simulations Plus, designed to predict potential Drug-Induced Liver Injury (DILI) hazards and provide deep mechanistic insight into observed DILI responses during drug development. It is widely used by major pharmaceutical and biotechnology companies and its modeling-based data is assessed by the U.S. Food and Drug Administration's (FDA) DILI team, making it a gold standard for liver safety prediction.
Key Features and Capabilities
DILIsym uses a "middle-out," multi-scale representation of DILI, integrating various biological and physiological processes across multiple scales, from intracellular biochemistry to whole-body dynamics.
- Mechanistic Modeling: Includes sub-models for key mechanisms like mitochondrial toxicity, bile acid homeostasis, oxidative stress, innate immunity, and the hepatocyte life cycle.
- SimPops™ (Simulated Populations): Allows testing compounds in simulated human populations that express a wide range of inter-individual variability in underlying biochemistry, which is essential for identifying susceptible patients and optimizing clinical trial design.
- Multi-Species Support: Represents biochemical and physiological processes for humans, rats, mice, and dogs.
- Biomarker Prediction: Predicts time profiles of classic serum biomarkers (e.g., ALT, AST, bilirubin) and emerging biomarkers (e.g., miR-122, K18).
- User Interface: Features a Graphical User Interface (GUI) for specifying experiments and visualizing results, as well as a command-line version for streamlined workflow integration.
Target Users and Use Cases
DILIsym is primarily used by toxicology, pharmacology, and clinical development teams within the biopharma industry.
- Risk Assessment: Predicting the potential DILI hazard of new drug candidates in preclinical and clinical stages.
- Decision Making: Informing key management decisions, such as go/no-go decisions for drug progression and identifying patient screening or dosing protocols to mitigate risk.
- Regulatory Submissions: Providing QST modeling-based data to support regulatory submissions.
- Dosing Strategy: Aiding in the design of dosing regimens to minimize hepatotoxicity.