# Implementing A QSP Platform to Predict and Test Drugs for Metabolic Associated Fatty Liver Disease Genetic Variants in an iPSC-cell Based Human Biomimetic Liver Microphysiology System > **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $695,586 ## Abstract Project Summary: Nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic dysfunction associated fatty liver disease (MAFLD), is a worldwide public health problem. Despite major investments by the pharmaceutical industry, there are no approved drugs for the treatment of MAFLD, reflecting the heterogeneous pathophysiology of this disease. We have implemented a platform focused on a human vascularized liver acinus microphysiology system (vLAMPS) biomimetic that incorporates four human liver cell types and uses genomic, biochemical, and phenotypic metrics, and quantitative systems pharmacology (QSP) to identify mechanisms of disease progression that can be used to inform new or repurposed drugs for MAFLD. Genome- wide association studies (GWAS) have identified several variants that are associated with MAFLD susceptibility, including mutations in PNPLA3, TM6SF2, and MBOAT7. In contrast to these variants that increase MAFLD risk, recent studies have identified two novel protective variants, HSD17B13 and MTARC1, that are linked to lower risk of MAFLD. However, little is currently known regarding the biological function of these protective variants. Thus, our goal is to harness the computational and experimental QSP platform with genome-edited iPSC-derived liver cells to experimentally test probe drugs and drug combinations predicted by computational analysis to normalize key disease phenotypes and to provide mechanistic insight into the role novel protective variants have in both alleviating MAFLD progression and as attractive new pharmacological targets; thus, linking specific genetic variant risk factors with successful intervention on druggable pathways. We will test the following Specific Aims: (1) Implement optimized biomimetic vLAMPS to recapitulate both normal liver function and MAFLD disease progression using iPSC-derived liver cells harboring clinically relevant variants (2); Test the response to drugs predicted to halt or reverse MAFLD disease phenotypes using iPSC-derived high-risk variants in vLAMPS; (3) Test the response to drugs predicted to halt or reverse MAFLD disease phenotypes using iPSC-derived high-risk variants in vLAMPS. The lack of approved drugs for treatment of MAFLD is due to the heterogenous pathology of disease progression and the limitation that animal models do not fully recapitulate the human disease. The use of a combined QSP and iPSC-derived MPS experimental platform to examine mechanistic detail of key disease- related genetic variants and to use for testing predicted drugs serves as a starting point to identify optimized therapeutics that will advance the approach to MAFLD drug discovery. ## Key facts - **NIH application ID:** 10798400 - **Project number:** 1R01DK135606-01A1 - **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH - **Principal Investigator:** Mark T. Miedel - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $695,586 - **Award type:** 1 - **Project period:** 2024-02-01 → 2028-11-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10798400 ## Citation > US National Institutes of Health, RePORTER application 10798400, Implementing A QSP Platform to Predict and Test Drugs for Metabolic Associated Fatty Liver Disease Genetic Variants in an iPSC-cell Based Human Biomimetic Liver Microphysiology System (1R01DK135606-01A1). Retrieved via AI Analytics 2026-06-24 from https://api.ai-analytics.org/grant/nih/10798400. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*