DILIsym®

Quantitative systems toxicology (QST) software
for modeling drug-induced liver injury (DILI)

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DILIsym - Quantitative systems toxicology (QST) software for modeling drug-induced liver injury (DILI)DILIsym is Quantitative Systems Toxicology (QST) software designed to be used during drug development to provide an indication of the potential drug-induced liver injury (DILI) hazard posed by individual molecules and/or to provide deeper insight into the mechanisms responsible for observed DILI responses at various stages of the development process.

DILIsym simulations integrate compound exposure with compound mediated mechanisms of intrinsic drug toxicity, and with inter-individual variability. The intersection of these is prediction of hepatotoxicity for: DILIsym - Exposure - DILI Mechanisms - Inter-patient Variability Venn Diagram

  • Phase II, III, or IV clinical trials in patients
  • First-in-human clinical trials in healthy volunteers
  • Small preclinical species
  • Large preclinical species

DILIsym is a “middle-out”, multi‑scale representation of drug-induced liver injury. It includes key liver cell populations (e.g., hepatocytes, Kupffer cells), intracellular biochemical systems (e.g., mitochondrial function), and whole body dynamics (e.g., drug distribution and metabolism). DILIsym represents these biochemical and physiological processes for mice, rats, dogs, and humans, based on a substantial amount of publicly-available literature. Through the generation of SimPops™ (a collection of simulated patients forming a simulated population), DILIsym also includes inter‑individual variability.

DILIsym includes a graphical user interface (GUI) to facilitate in silico investigations. The GUI permits the specification of new simulated experiments, including compound, dose, dosing frequency, duration, mechanism(s), and species. Simulations can be performed on individuals or populations. Simulation results can be visualized within the GUI or exported for further analysis in other software.

DILIsym prospectively supports key management decisions by providing information about potential drug-induced liver injury risk in upcoming experimental or clinical study designs, as well as mechanistic rationale for the underlying biochemical events that could cause liver toxicity. DILIsym also supports key management decisions about compounds for which liver transaminase elevations have already been observed by identifying patient screening or dosing protocols to mitigate risk. Additionally, DILIsym can mechanistically interpret existing data on liver transaminase elevations to predict the underlying level of hepatocyte loss and rate of liver recovery, supporting the distinction of innocuous vs. dangerous liver signals.

The current version of the modeling software is DILIsym v7A, which was made available to all DILI-sim Initiative industry members as of January 2018. DILIsym v7A is also available to academic licensees.

DILIsym Sub-Models

DILIsym has been developed within a conceptual framework (Figure 1), wherein liver compound exposure (parent and/or metabolite) can engage various mechanisms of intrinsic toxicity. The mechanisms currently included are: (1) inhibition of bile acid transporters leading to disruptions in bile acid homeostasis, (2) alteration of mitochondrial function, and (3) generation of oxidative stress. Alone or in combination, these mechanisms can lead to hepatocyte cell death via apoptosis or necrosis. Hepatocyte necrosis releases damage associated molecular pattern (DAMP) molecules, capable of activating innate immune cells (e.g., resident Kupffer cells). Activated immune cells produce mediators that may serve to amplify the ongoing injury and/or may promote liver regeneration. Immune cells may also accumulate due to ongoing inflammatory processes. Importantly, while the various elements described thus far can be sufficient to drive liver injury, they may also provide the setting in which an adaptive immune response can develop. Adaptive immune responses are not currently included in DILIsym but are part of ongoing development to be included in future versions of the modeling software.

DILIsym - drug-induced liver injury flow chart

Figure 1. Conceptual framework for DILIsym development.

DILIsym includes multiple sub-models which are solved in an integrated fashion to generate simulation results. Sub-models delineate compound absorption, distribution, metabolism, excretion (ADME) in a PBPK sub-model, various  intracellular biochemical systems that may be impacted by compound exposure (e.g., bile acid homeostasis, mitochondrial function, oxidative stress), the hepatocyte life cycle, and stimulation of innate immune responses. To facilitate comparison with high-level clinical and preclinical readouts, DILIsym includes the release of biomarkers (e.g., ALT, AST) from hepatocytes in the event of cell death, as well as increases in total bilirubin, reflecting compromised liver function due to hepatocyte loss. DILIsym also includes emerging biomarkers (e.g., miR-122, CK-18) that may provide additional dynamic and/or mechanistic information. More detailed descriptions of the sub-models are provided in the links below. Specific data used in design and development are available to licensees through the DILIsym modeling software documentation.

Finally, DILIsym includes SimPops, comprising simulated individuals expressing variability in key parameters related to susceptibility to various mechanisms of toxicity. SimPops permit the researcher to consider the effect of inter-individual variability on drug toxicity. While not a sub-model per se, additional information is similarly provided for SimPops.

Learn more about the submodels within DILIsym:

DILIsym Development

DILIsym development is supported by a pre-competitive consortium, the DILI-sim Initiative, that includes DILIsym Services and multiple pharmaceutical companies. Member companies have a seat at the table in directing development efforts. The DILIsym development team receives regular feedback from member companies and from the Scientific Advisory Board, which includes key opinion leaders within the field of drug-induced liver injury.

DILIsym Services Home

What are we providing with DILIsym?
DILIsym modeling software functions include:

  • General population samples: The DILIsym software can be used to test compounds in simulated populations, termed SimPops. Simulated individuals within the SimPops express a wide‑range of response to the various exemplar compounds and can be characterized by extensive variability in their underlying biochemistry.
  • DILIsym humans: A middle-out multi-scale representation of human physiology for assessing potential drug-induced liver injury (DILI) hazard in patients. Compound pharmacokinetic (PK) and pharmacodynamics (PD) information can be integrated to predict time profiles of liver enzymes (i.e., alanine aminotransferase, aspartate aminotransferase) and other clinical variables (e.g., bilirubin, prothrombin time, INR), as well as tissue properties (e.g., liver mass, GSH content). Alternate hypotheses regarding the downstream mechanisms of drug action can be investigated, including increased reactive oxygen/nitrogen species, ATP utilization, direct hepatocyte necrosis, and inhibition of bile acid transporters.
  • DILIsym dogs: A middle-out multi-scale representation of Beagle dog physiology for assessing potential DILI hazard in dogs.  Data from Beagle dogs were prioritized among the available datasets to maximize consistency in the representation.
  • DILIsym rats: A middle-out multi-scale representation of Sprague-Dawley rat physiology for assessing potential DILI hazard in rats. Data from Sprague-Dawley rats were prioritized among the available datasets to maximize consistency in the representation. Compound pharmacokinetic and pharmacodynamics information can be integrated to predict time profiles as described above.
  • DILIsym mice: A middle-out multi-scale representation of C57Bl/6 mouse physiology for assessing potential DILI hazard in mice. Data from C57Bl/6 mice were prioritized among the available datasets to maximize consistency in the representation. Compound pharmacokinetic and pharmacodynamics information can be integrated to predict time profiles as described above.
  • Translational research: The ability to integrate your in vitro, small animal, and large animal compound data into a single platform facilitates translational research to better inform program advancement decisions, including experimental design, analyte selection, and timing of sampling.
How is DILIsym being applied?

Key features of the DILIsym modeling software

  • In vitro extrapolation to in vivo predictions (IVIVE) of drug-induced liver injury (DILI) hazard in multiple preclinical species and in humans
  • Predicted DILI hazard can be traced back to its mechanistic source(s)
  • Incorporates inter-individual physiological variability
  • Incorporates PK/PD variability
  • User-friendly GUI to specify in silico experiments and visualize results
  • Direct access to the underlying source code
  • Transparent design and parameterization
  • Inclusive incorporation of the available literature for mechanistic representation of the physiology
  • Regularly updated to include leading edge science
  • Developed and supported by scientific and technical teams
  • Consortium members guide the development of DILIsym and may share data to support model development and improve the collective understanding of DILI
  • Informs drug development decisions and risk mitigation strategies

Key benefits of the DILIsym modeling software

  • Potential DILI hazard posed by specific molecules
  • Impact of alternate pharmacology or experimental protocols on potential DILI hazard
  • Mechanisms contributing to potential DILI hazard
  • Mechanistic differences in cross-species sensitivity
  • Identifies non-standard mechanistically-relevant safety biomarkers of DILI hazard
  • Facilitates maximal use of data by integrating nonclinical and clinical data in a single platform
  • Allows SimPops customization to reflect clinical population characteristics
  • Rapidly realizes implications of “what if” scenarios
  • User-friendly for scientists
  • Customizable code for modelers
What's new in DILIsym version 7A?

A sample of the enhancements include:

  • New validation compounds (ambrisentan, sitaxsentan, phenformin, nelfinavir)
  • New simulated population focused on biomarker variability, SimPops (v6A-1), with variability in alanine aminotransferase (ALT) parameters
  • New capability for population-level PK data input (for enhanced compatibility with Simulations Plus’ GastroPlus and other PBPK programs)
  • Substantial improvements in the PBPK submodel
  • Addition of TNF-α-mediated survival and regeneration for better representation of pleiotropic functionality
  • Updated DILIsym documentation resources, now embedded within the software

View the full DILIsym Version 7A release notes.

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