CN Bio has introduced its PhysioMimix ‘in-a-box’ reagent kit for non-alcoholic steatohepatitis (NASH), the most severe form of non-alcoholic fatty liver disease (NAFLD).
Previously only accessible via its contract research services, CN Bio’s best-in-class NASH in vitro model supports the urgent development of therapeutics to treat this emerging global healthcare priority.
Despite research efforts to combat the growing prevalence of NASH, there are no regulatory approved therapeutics due to the inability of traditional in vivo animal experiment approaches to predict the human response to this complex disease. In conjunction with CN Bio’s PhysioMimix MPS, the NASH-in-a-box (NIAB) kit provides researchers with in-house capabilities to gain physiologically relevant insights into the mechanism of disease, human drug efficacy and safety toxicology.
The assay addresses the human-relevance limitations of existing approaches, bridging the gap between human 2D cell culture and expensive animal models, which are ineffective in mimicking the full disease spectrum. This enables NIAB kit users to generate clinically translatable and predictive data that facilitate more insightful, accurate and cost-effective drug development.
Through its ‘in-a-box’ range, CN Bio aims to fast-track the incorporation of MPS into drug discovery workflows by providing a straightforward and quick route to recreating its industry-proven organ-on-a-chip (OOC) assays. Within the NIAB kit, new users are guided through a simple-to-follow software-based protocol for successfully co-culturing internally validated primary human hepatocytes, stellate and Kupffer cells.
The protocol enables the formation of 3D microtissue structures that accurately emulate the microarchitecture of the human liver. By introducing fatty acids, researchers can recapitulate key NAFLD/NASH disease states: intracellular fat accumulation, inflammation and fibrosis. Once created, the model enables the precise mechanistic effects of drugs (of any modality) and disease to be investigated via high-content, clinically translatable end-point measurements.