Abstract

REVIEW ON: APPLICATION OF ARTIFICIAL INTELLIGENCE IN PHARMACY

Pooja R. Gawandar*, Swati L. Khedekar and Dr. Kailash R. Biyani

ABSTRACT

Artificial intelligence (AI) has inspired computer-aided drug discovery. The worldwide adoption of machine learning, in deep learning, in multiple scientific disciplines, and the modification in computing hardware and software, among other factors, continue to flourish this development. Much of the initial skepticism regarding applications of AI in pharmaceutical industry discovery has started to vanish, benefitting medicinal chemistry. The recent status of AI in chemical informatics is reviewed. The topics discussed here include quantitative structure-activity/property relationship and structure-based modeling, de novo molecular design, and chemical synthesis prediction. Advantages and limitations of recent deep learning applications are noticed, together with a perspective on next-generation AI for pharmaceutical drug discovery. As per Expert opinion Deep learning-based approaches have only starting to address some fundamental problems in drug discovery. The methodological advances, such as message-passing models, spatial symmetry-preserving networks, hybrid de novo design, and other innovative machine learning paradigms, will likely become commonplace and manage address some of the most challenging problems. Open data sharing and model development will play a crucial role in the advancement of drug discovery with Artificial intelligence.

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