Drug Repurposing as an Emerging Field in Drug Designing
Ayooshi Mitra, Shrayana Ghosh, Jutishna Bora, A.H.M. Jaffar Iqbal Barbhuiya · Apple Academic Press eBooks · 2024
With new diseases surfacing and old ones recurring, modern pharmaceutical research is facing a major problem today, with a drop in drug development efficiency and a gap between medicinal demands and available treatments. In a world where computer power is rapidly expanding, in silico approaches can open up a slew of new possibilities in drug research and development. The primary goal of computational approaches is to understand and regulate how medications interact with living systems. This knowledge can help affect the development of better medical therapies as well as improve clinical utilization and eliminate any unpleasant side effects. Drug repurposing, also known as drug repositioning, is one of the intriguing uses of computational pharmacology. It is a method of discovering new uses for previously approved or failed medications in the treatment of other diseases. There are two types of repurposing approaches—drug-based and disease-based. Due to its usefulness over traditional de novo drug development approaches, drug repurposing has sparked considerable interest in pharmaceutical research and industry. However, the data generated by computational methods is frequently complex and high-dimensional, posing new challenges for assimilation in order to advance drug discovery and generate innovative insights into drug mechanisms, side effects, and interactions. Owing to its ability to overcome the limitations and unreliability of traditional statistical approaches, computational drug repurposing, based on data mining, machine learning, and network analysis is becoming increasingly important.