Model systems, whether laboratory animals or human cell-based systems, have long been central to the discovery and development of new and better drugs for the treatment of human disease. But some complex diseases, such as non-alcoholic steatohepatitis (NASH), are more difficult to recapitulate in the lab, and standard endpoints may not accurately reflect patient responses in the clinic. InSphero liver expert Sue Grepper recently reviewed some of the limitations of animal models of NASH. Here, she discusses the challenges of developing a truly predictive human in vitro cell model for NASH and how to get it right.
The quest for a more predictive in vitro model system
What model system could be better for predicting the human response than human primary cells? Until recently, human-cell-based model systems held great promise, but weren't ideal for complex disease modeling, for two reasons:
- Scarcity of primary biological materials. Before scientists knew how to successfully isolate and cryopreserve primary liver cells, research was limited to cancer cell lines, such as HepG2 and HUH7, that lack key hepatocellular functions, including cytochrome P50 activity required to metabolize drugs. Isolated cryopreserved primary human hepatocytes have now been available for more than 10 years, but isolated primary Kupffer cells and primary stellate cells emerged on the commercial scene only about 8 and 3 years ago, respectively.
- Lack of model complexity. Since primary liver cells have been available commercially, it has proven very difficult to get the different liver cell types “to get along” in 2D culture. For example, hepatocytes absolutely require a collagen matrix (rat tail vein collagen type 1, to be precise) to attach to plates, whereas Kupffer cells seem to stick to anything. In 2D culture, hepatocytes require specific media containing super-physiological levels of glucose and insulin to remain viable, whereas Kupffer cells prefer a macrophage-optimized media, such as RPMI. Needless to say, it becomes virtually impossible to further include stellate cells in 2D model systems for complex disease research, such as NASH drug discovery.
Simple models for complex diseases fall short
Because of these limitations, most in vitro work with human cells has traditionally been performed in monoculture. Some valuable research can be obtained if the drug being tested targets that one specific cell type (for example, simple steatosis in hepatocytes). But…even the highest quality hepatocyte donor “lot” will contain a substantial percentage of dead cells in each vial, and this typically limits 2D hepatocyte monoculture studies to only ~5 days.
As for stellate cells, almost everyone in the field knows that as soon as you culture quiescent/un-activated stellate cells in 2D, they become activated and myofibroblast-like — not an ideal side effect for negative control. The ultimate downfall to monoculture, however, is that most diseases involve more than a single cell type and require complex cell-cell communications for the disease to progress.
In NASH, for example, there are varying theories around initial lipid accumulation in the hepatocytes triggering inflammation in the macrophages, which further activates the stellate cells to become myofibroblast-like and deposit scarring collagen fibers.
"IHC and confocal imaging are certainly appropriate endpoints for visualizing lipid accumulation and fibrosis — and make for pretty publication images. However, they are low throughput, quantitatively limited, and may not truly mimic clinical pathology."
Modeling the three major hallmarks of NASH with one in vitro system
When InSphero started working on our human liver disease platform, we had a unique advantage in that we had already been perfecting 3D liver co-culture models for almost a decade, and we were able to apply our knowledge and expertise to take on the monumental task of developing a 3D in vitro primary human cell model that highlights all major hallmarks of NASH, within 10 days of physiologically relevant NASH stimuli treatment.
Our new 3D InSight™ Human Liver NASH model includes all the human cell types required to recapitulate the disease pathophysiology. This includes primary hepatocytes, Kupffer cells, endothelial cells, and stellate cells, all of which self-assemble together in a scaffold-free, media-compatible environment.
This in vitro model has been validated with numerous Phase 1/2 clinical NASH therapeutics using clinically relevant endpoints for anti-NASH compound screening. The therapeutics tested in this system target numerous pathways within NASH pathogenesis, ranging from de novo lipogenesis to inflammation and fibrosis. Immunohistochemistry (IHC) and confocal imaging are certainly possible endpoints related to lipid accumulation and fibrosis (and make for pretty publication images). However, they are low throughput, quantitatively limited, and may not truly mimic clinical pathology (no in vitro model can fully recapitulate the exact liver architecture required for defining clinical F3 and F4 fibrosis).
Therefore, our latest model development efforts have focused on clinically relevant and screenable endpoints, such as intracellular triglyceride levels (TAG), secreted cytokines/chemokines, and secreted procollagens. We work closely with our research partners to identify appropriate endpoints for the pathways their therapeutics target to best reflect the patient response to treatment.
Finally, a complex in vitro human model, which can predict an in vivo human response! I'd love to hear your thoughts on this topic. Leave a comment below or look for me at AASLD 2019 in the scientific sessions and at booth 118.
Discover what you can do with 3D InSight™
Watch this video to learn how we applied our scalable Akura™ technology and 10 years of experience in perfecting 3D in vitro human liver models to develop the first automation-compatible 3D in vitro human liver disease platform for NAFLD and NASH. And read about how pharma companies are applying this platform in their drug discovery programs.
Vitruvian Mouse, Microtissue, and Man illustration by David Dean.
