Sinopia Biosciences has been awarded a grant from the National Institute of General Medical Sciences (NIGMS), as part of the National Institutes of Health, to further develop and validate their proprietary metabolomics-based high-throughput screening (HTS) platform with an initial focus on rare diseases. To date, Sinopia has received nearly $8 million in grants from the National Institutes of Health and a $450,000 grant from the Michael J. Fox Foundation for Parkinson’s Research (MJFF).
“For the past two decades, phenotypic-based drug discovery, which typically measures a few parameters, has been the most successful approach for discovering therapeutics. Fast forward to today, we can measure hundreds to hundreds of thousands of biomolecular and cellular changes at once cost-effectively and have the ability to successfully generate unbiased hypotheses to discover novel medicines,” said Aarash Bordbar, Co-founder and Chief Technology Officer of Sinopia Biosciences. “At Sinopia, we’re looking to advance these approaches by comprehensively measuring downstream layers, such as metabolites, that may provide a more accurate representation of how best to treat a variety of diseases.”
The $2.2 million grant will support the screening and validation of both chemical and genetic perturbations across multiple cell lines with an initial focus on 50 genetically defined rare diseases – of which there are an estimated 7,000 in the world. In partnership with Omix Technologies, a leader in mass spectrometry-based data generation, Sinopia will use metabolomics data to augment its multi-omics drug discovery engine LEADS (LEarn And DiScover) to develop hypotheses for treating select rare diseases and subsequently validating identified compounds.
“Given the large number of rare diseases, it is difficult to develop drugs using traditional target-based discovery approaches in a time and capital efficient manner,” said Iman Famili, CEO and President of Sinopia Biosciences. “This grant will enable us to dedicate our efforts to building out a metabolomics-based high-throughput screening platform that could help build predictive models for a variety of rare diseases while simultaneously reducing the timelines and cost for discovering novel medicines.”
