The Promise and Perils of Artificial Intelligence in Pharmaceutical Industries and Healthcare System

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Deepak Rawat, Arpita Yadav, Neha Gupta, Harish Kumar Singh, Upama singh, Sneh Lata Verma, Preeti Pandey, Sonali Shaw, Rahul Kumar, Shivangni Raj, Mohit Shrivastava, Dheeraj Dubey


Artificial intelligence is quickly changing the pharmaceutical and healthcare businesses. AI improves medicine research, development, and delivery and personalizes patient care. AI screens vast libraries of chemicals for drug candidates in drug development. AI can automate this laborious operation. AI can also forecast drug candidate toxicity and effectiveness, reducing the number of clinical trials. Clinical trials employ AI to choose the best patients. Clinical studies are costly and time-consuming, so selecting people most likely to benefit from the therapy is crucial. AI can design more efficient and successful clinical trials. AI is used in personalized medicine to discover disease-related genetic alterations. This data may be utilized to create patient-specific therapies. A patient's medication response may also be predicted by AI. AI in pharmaceutical and healthcare research is still developing, but it might transform these sectors. AI can automate jobs, enhance decision-making, and provide new insights to produce more effective disease therapies, speed up clinical trials, and give personalized medicine. The present article explores the use of artificial intelligence (AI) in drug research and development, drug repurposing, pharmaceutical productivity, and clinical trials, among other areas, to minimize human effort and fulfill deadlines. We also look at how AI tools and processes interact, present difficulties and solutions, and the future of AI in the pharmaceutical industry.

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