In the pharmaceutical industry, artificial intelligence (AI) is revolutionizing individualized therapy, research, and drug development. Artificial intelligence (AI) technologies, such machine learning (ML) and deep learning (DL), are used to read enormous amounts of data, spot mysterious patterns, and find possible medication candidates more quickly. AI is also improving clinical trials through better patient recruitment, real-time data monitoring, and trial outcome prediction. AI's capacity to customize care according on a person's genetic composition, lifestyle, and environmental factors is also supporting personalized medicine, a novel approach to healthcare. AI is also simplifying medicine production procedures, enhancing quality control, and streamlining supply chain management. This comprehensive review studies the different impacts AI-enabled technologies have on each stage of the pharmaceutical life cycle. It demonstrates that machine learning, data analytics and predictive modelling can accelerate drug discovery, improve manufacturing processes, streamline quality processes, enhance formulation approaches, and transform post-marketing surveillance, drug repurposing, precision medicine, and nanobots.
Debnath et al. (Wed,) studied this question.
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