Artificial Intelligence in Drug Discovery and Diagnosis: Challenges, Opportunities, and Strategies

Artificial Intelligence (AI) is going to revolutionize the drug discovery process by far accelerating the development of new drugs and making the discovery process much more accurate and cheaper. This work carries out a thorough analysis of more than 50 recent works, investigating the issue of AI as an aid in drug discovery and diagnosis. The research methodology will include summarizing the existing sources of literature concerning the application of AI in drug development, specifically on the machine learning and deep learning methods applied in terms of analyzing large amounts of data, predicting the toxicity of a drug, and finding potential drug candidates. There are several main findings in the study, which include that AI can increase the efficiency of the drug development processes and that AI can pre-determine the safety and effectiveness of drug compounds. Nonetheless, AI does not have an ethical role to play in relation to drug development, especially in terms of using novel chemicals and drugs, which must be in the hands of human beings. The study ends with a listing of a number of future directions of study, including making AI more transparent, finding solutions to data privacy, and developing AI to be applicable in personalized medicine. Regulators, policymakers, and researchers should proactively involve themselves in ensuring that ethics are inculcated in drug discovery that is driven by artificial intelligence.