Scientists at IIT-Bombay have used Machine Learning to quicken drug discovery. ML helped the scientists to generate the more promising leads for discovery of molecules, cutting short the elaborate process of trial and error. Scientists, Prof Sunoj Raghavan and Dr P Balamurugan, who led this study, used ML techniques like ‘random forest and decision tree’ for this purpose.
“A ML-based mathematical model is trained on known catalysts, which then helps to predict the effectiveness of other catalysts. After multiple training runs with additional data of catalysts, the model was validated with some test sets,” says Prof Raghavan.
“We believe that the leads emerging through machine learning on what combination of catalysts and substrates has better propensity to be successful and could be coupled with automated experimental protocols. Our approach can also be exploited in a broad range of asymmetric reactions and thus can open up promising avenues toward a cost-effective and efficient design of asymmetric catalysts,” he says.
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