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अमूर्त

Computational Insights into Drug Repurposing: A Brief Review

Surajit Bal, Rathi Dasgupta

The COVID-19 pandemic has triggered a surge in the reutilization of established medications, albeit the underlying evidentiary foundation varies. Drug reutilization involves repurposing known drugs or drug combinations for unforeseen medical contexts. Consequently, it plays a crucial role in expediting the pre- clinical phase of developing novel drugs, offering time and cost savings compared to traditional drug discovery. Given that drug reuse relies on extensive data from existing drugs and diseases, the substantial proliferation of publicly accessible, large-scale machine learning techniques represents cutting-edge data science applications for disease identification, therapeutics and target discovery, minimizing errors. In this write-up, we have explored different computational databases, techniques and methodologies, as well as possibilities, for harnessing machine learning methods to expedite the process of drug repurposing.