Toxic drugs detected with AI – Srijit Seal leads study
Srijit Seal, a PhD student in Chemistry at Clare Hall, University of Cambridge, has led a team to build a machine learning model that takes measurements from human cells, making predictions about drug safety.
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The discovery of new drugs can be a complex process, so any tools that help to accelerate the process are critical. According to this study by the Bender Group, published in Communications Biology, a machine learning model developed uses Cell Painting* and gene expression data to make predictions of mitochondrial toxicity 60% better than using compound structures only.
On publication of this study, Srijit comments:
Pharmaceutical companies and academics can use this model to determine whether you have mitochondrial toxicity in a compound, which is a leading cause of late-stage drug withdrawals. This saves time and resources by identifying good, non-mitotoxic candidates before scientists start clinical tests.
*Cell Painting is when a cell is flooded with different dyes that stick to different features of the cell. This colourful cell is then profiled with a lot of detail and the results of this profiling are stored in a digital library. It is useful for general investigations and spotting patterns in large amounts of data. The model developed by the Bender Group spotted patterns in these data – for example, certain types of granular in the cell painting data indicated mitochondrial toxicity.
This model is now publicly accessible to researchers who aim to predict mitochondrial toxicity of compounds.
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Srijit’s PhD research is supported by a Cambridge International Scholarship from the Cambridge Trust, the Jawaharlal Nehru Memorial Fund, a Trinity Henry Barlow Scholarship from Trinity College, and his MPhil research was supported by the Clare Hall India Innovation Master’s Studentship.
He recently won a Student Poster Award from the Society for Laboratory Automation and Screening (SLAS), and was Clare Hall Graduate Student Body Committee (GSB) President 2021/22.
Story queries: communications.manager@clarehall.cam.ac.uk