The aim of machine learning algorithm (ML) is to recognize the pattern from a given data and thus create statistical models for data analysis and prediction. Therefore, the ML models are robust and time efficient. ML models nowadays widely used in all stages of drug discovery starting from protein structure prediction, hit identification, etc. My research interest in ML method development includes hit identification, lead optimization, xenobiotics metabolism and toxicity prediction.
I have already employed ML methods to developed a few modules using which it is possible to accelerate the lead molecule design process. A brief description of these methods can be found here.