Abstract

ARTIFICIAL INTELLIGENCE IS CHANGING THE FACE OF PHARMACOVIGILANCE

Akash R. Tangde*, Gaurav S. Tangade, Sanket S. Khedekar, Vishal K. Patale, Shrikrushna S. Chopade and Prof. Shital G. Dhanmane

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Abstract

Research on drug creation and development is crucial for chemical scientists and pharmaceutical businesses. However, there are obstacles and difficulties that affect medication design and development, such as low efficacy, off-target delivery, time consumption, and excessive cost. Big and complex data from clinical trials, proteomics, microarray, and genomes all represent a challenge to the drug discovery process. Drug development and discovery heavily rely on artificial intelligence and machine learning technologies. Stated differently, pharmacophore modelling, drug repositioning, polypharmacology, quantitative structure–activity connection, artificial neural networks and deep learning algorithms, monitoring and release, and physiochemical activity. Historical data supports the application of deep learning and artificial intelligence in this domain. Furthermore, recently created modelling algorithms received crucial support from innovative data mining, curation, and management strategies. In conclusion, developments in deep learning and artificial intelligence present a great chance for a methodical approach to medication discovery and design that will ultimately benefit humanity.

Keywords: Benefits, Real word in pv, Machine Learning, Regulatory, Machine learning, Supervised Learning, Deep learning, Future Direction, clinical, regulatory.