Our overall strategy is to screen existing drugs for their unexpected ability to abrogate key aspects of SARS- CoV-2 infection. The proposal will leverage the infrastructure we have created as part of the LINCS Consortium to use gene expression profiling to discover existing drugs that either block the cellular mechanisms required for viral infection, or block the cellular response to infection that causes disease. While there is much biological learning to be done, the focus of this proposal is not basic biology, but rather on the discovery of drugs that could be rapidly tested in patients. For this reason, we emphasize existing drugs (those that are either FDA-approved, EMA-approved, or are in clinical development) because of the pace at which they can be advanced to clinical trials. Our proposed approach leverages capabilities developed under our Common Fund-supported LINCS Center for Transcriptomics. First, we have created a ?shovel-ready? production-scale data generation capability that can now be brought to bear on COVID-19. Second, we have assembled a drug repurposing library with ~10,000 drugs that are either FDA-approved or are in clinical development. Third, through our LINCS experience, we have learned that real power comes from unleashing the world?s scientific community by creating public resources that can be utilized by others. In this project, we will screen ~10,000 drugs in lung epithelial cells and monocytic immune cells, using gene expression profiling as the readout. We will make this Drug Repurposing LINCS dataset immediately publicly available, so that anyone in the research community can query it with relevant signatures -- including those that have yet to be discovered. High priority drugs identified through analysis of these data will be subjected to orthogonal tests of antiviral and immune function. An important aspect of this proposal will be the creation of a COVID-19 Drug Repurposing Portal which will house all of the raw and processed data generated by this proposal, together with biologist-friendly analytical and visualization tools that will enable the entire COVID-19 research community to identify top priority drugs for pre-clinical and eventually clinical testing as anti-COVID-19 therapies.
We will identify existing drugs for their unexpected ability to either block the cellular mechanisms required for SARS-CoV-2 infection, or block the cellular response to infection through the generation and analysis of gene expression signatures from ~10,000 drugs in lung epithelial cells and monocytic immune cells
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