The research and development of pharmaceuticals is a costly, lengthy, and high-risk venture, spread over four stages of studies: drug discovery, preclinical research, clinical research, and post-marketing studies on safety and effectiveness. The journey of a new drug to the market is estimated to take approximately 10 years and cost billions of US dollars, says Dr Nicola Davies in her exclusive article on the US Food and Drug Administration.1
A modern approach for overcoming these challenges is the use of artificial intelligence (AI) in drug development. The coming of AI is a boon for the pharma industry because it can significantly cut the cost of development and time-to-market for new drugs. For example, in the race to develop vaccines and other therapeutics for COVID-19, AI-based virtual screening of both new and repurposed molecules can accelerate discovery.2
The FDA defines AI as “the science and engineering of making intelligent machines, especially intelligent computer programs.”3 In recent years, AI has been increasingly used in drug repurposing, which involves developing an already approved drug for a different indication or different population; optimizing and expediting patient recruitment in trials; and, post-approval safety surveillance.1 However, AI holds huge benefits not only for pharma but also for the FDA; AI can facilitate the agency’s regulatory activities related to drug development and approval.
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