University of Pittsburgh researchers present an integrated quantitative systems pharmacology (QSP) platform, combining computational algorithms for drug prediction with a human biomimetic liver acinus microphysiological system (LAMPS) for candidate drug testing. This system identifies both potential repurposable drugs and potential novel therapeutics that could help treat metabolic-dysfunction associated steatoic liver disease (MASLD).
Description
MASLD is a major public health concern, comprising of many complex symptoms. The researchers analyzed patient-derived hepatic RNAseq data to generate 12 gene signatures associating molecular phenotypes with MASLD progression and pathophysiology, such as lipotoxicity, insulin resistance, and inflammation. Using connectivity mapping, drugs predicted to invert the expression of MASLD-associated signatures were identified. This innovative method identified multiple drugs for testing through independent prioritization approaches, thus providing a foundation for novel therapeutics for this disease.
Applications
Metabolic-dysfunction associated steatoic liver disease (MASLD) • Liver disease (Steatosis, Fibrosis, Cirrhosis)
Advantages
A challenge in developing targeted therapies for MASLD include the large number and diversity of differentially expressed genes and pathways, as well as the uncertainties regarding their individual contributions to MASLD pathogenesis across a heterogeneous patient population. The adoption of systems-based approaches, such as QSP, to predict disease progression and response to therapies identifies and prioritizes candidate drugs for experimental testing using a mechanistically unbiased approach. This provides an opportunity to create highly personalized therapeutics for liver disease.
Invention Readiness
In limited proof of concept experimental studies, the authors identified the HDAC inhibitor, vorinostat, as a drug that reduced stellate cell activation, secretion of pro-fibrotic and inflammatory markers, and protected against disease-induced cell death in the LAMPS model of MASLD progression. They also observed complementary effects of other drugs in the experimental model, supporting the potential of complementary drug combinations as a therapeutic strategy.
IP Status
https://patents.google.com/patent/WO2023034381A1
