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Conventional drug discovery ignores the spatial relationships between cells when assessing the effects of drugs. I talk with Imran Haque, VP of Data Science at Recursion Pharmaceuticals, about their data-first approach that combines "cell painting" with deep learning to assess changes in cellular morphology, thus providing a crucial lens into the molecular wirings of a given drug's mechanism of action. We discuss his team's work in repurposing therapies to tackle COVID-19 and what it takes to successfully merge deep learning with cellular images in a way that yields therapies.
Check out the glossary of terms, definitions, and resources (and get a sneak peak of the future conversations lined up!) here: bit.ly/datapulse-glossary
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Conventional drug discovery ignores the spatial relationships between cells when assessing the effects of drugs. I talk with Imran Haque, VP of Data Science at Recursion Pharmaceuticals, about their data-first approach that combines "cell painting" with deep learning to assess changes in cellular morphology, thus providing a crucial lens into the molecular wirings of a given drug's mechanism of action. We discuss his team's work in repurposing therapies to tackle COVID-19 and what it takes to successfully merge deep learning with cellular images in a way that yields therapies.
Check out the glossary of terms, definitions, and resources (and get a sneak peak of the future conversations lined up!) here: bit.ly/datapulse-glossary