Digital pathology with artificial intelligence analysis provides insight to the efficacy of anti-fibrotic compounds in human 3D MASH model.

Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation and fibrosis. The development of MASH therapies has been hindered by the lack of human translational models and limitations of analysis techniques for fibrosis. The MASH three-dimensional (3D) InSight™ human liver microtissue (hLiMT) model recapitulates pathophysiological features of the disease. We established an algorithm for automated phenotypic quantification of fibrosis of Sirius Red stained histology sections of MASH hLiMTs model using a digital pathology quantitative single-fiber artificial intelligence (AI) FibroNest™ image analysis platform. The FibroNest™ algorithm for MASH hLiMTs was validated using anti-fibrotic reference compounds with different therapeutic modalities-ALK5i and anti-TGF-ß antibody. The phenotypic quantification of fibrosis demonstrated that both reference compounds decreased the deposition of fibrillated collagens in alignment with effects on the secretion of pro-collagen type I/III, tissue inhibitor of metalloproteinase-1 and matrix metalloproteinase-3 and pro-fibrotic gene expression. In contrast, clinical compounds, Firsocostat and Selonsertib, alone and in combination showed strong anti-fibrotic effects on the deposition of collagen fibers, however less pronounced on the secretion of pro-fibrotic biomarkers. In summary, the phenotypic quantification of fibrosis of MASH hLiMTs combined with secretion of pro-fibrotic biomarkers and transcriptomics represents a promising drug discovery tool for assessing anti-fibrotic compounds.

A 3D primary human cell-based in vitro model of non-alcoholic steatohepatitis for efficacy testing of clinical drug candidates.

Non-alcoholic steatohepatitis (NASH) is a progressive and severe liver disease, characterized by lipid accumulation, inflammation, and downstream fibrosis. Despite its increasing prevalence, there is no approved treatment yet available for patients. This has been at least partially due to the lack of predictive preclinical models for studying this complex disease. Here, we present a 3D in vitro microtissue model that uses spheroidal, scaffold free co-culture of primary human hepatocytes, Kupffer cells, liver endothelial cells and hepatic stellate cells. Upon exposure to defined and clinically relevant lipotoxic and inflammatory stimuli, these microtissues develop key pathophysiological features of NASH within 10 days, including an increase of intracellular triglyceride content and lipids, and release of pro-inflammatory cytokines. Furthermore, fibrosis was evident through release of procollagen type I, and increased deposition of extracellular collagen fibers. Whole transcriptome analysis revealed changes in the regulation of pathways associated with NASH, such as lipid metabolism, inflammation and collagen processing. Importantly, treatment with anti-NASH drug candidates (Selonsertib and Firsocostat) decreased the measured specific disease parameter, in accordance with clinical observations. These drug treatments also significantly changed the gene expression patterns of the microtissues, thus providing mechanisms of action and revealing therapeutic potential. In summary, this human NASH model represents a promising drug discovery tool for understanding the underlying complex mechanisms in NASH, evaluating efficacy of anti-NASH drug candidates and identifying new approaches for therapeutic interventions.