In the process of drug discovery, a crucial step is the assessment of the new compound’s effect on the liver. In the continuing absence of a gold standard for predicting drug-induced liver toxicity, Strand’s novel predictive modeling approach provides an effective tool for pharmaceutical companies to address the following challenges:
Assessing target liabilities: Does the target or similar/homologous targets have the potential of injuring the liver?
Assessing chemical hazard & risk: Test chemicals/series through the platform to understand potential risks.
Solving compound design problems (by understanding toxic mechanisms): Given there exists a problem in a molecule or lead series, the model provides information for understanding what exactly the liability is and the potential to design around it.
Generating testable impact hypotheses: Use "omic" data to generate testable hypotheses for the chemical’s impact on the liver.
Strand's Virtual Liver model has the ability to predict toxicity of three major sources of DILI: Hepatocellular Injury, Drug-Induced Cholestasis, and Steatosis. Thus the platform is capable of predicting the incidence of more than 75% of DILD cases. The platform’s validation set provides proof-of-concept that combining targeted in vitro assays along with a detailed model of liver physiology allows one to predict toxicity as well as generate insights into processes that are affected. There are two options for purchasing Strand’s Liver Toxicity Services:
1) Complete Service Package (includes compound testing, modeling, and assessment) Pharmaceutical companies provide the compounds they want to assess to Strand’s laboratory. There the compounds are run through a set of 14 assays in freshly isolated rat hepatocytes and tested at two concentrations at two time points (4 hours and 16 hours). The in vitro results are entered into Strand’s Virtual Liver model, which provides actionable insight into the in vivo impact of the compound on the rat in terms of its potential for hepatocellular injury, cholestasis and steatosis. The results are summarized in a customized report that provides details on the predicted impact and allow researchers to understand the key biological interaction with the potential for DILD.
2) Virtual Liver Model only Want to find out more? Contact us with your questions.