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Pharma Tech Outlook | Wednesday, October 27, 2021
A technology that can significantly contribute to resolving the pain points of the drug development process will rapidly grow into a multibillion-dollar industry.
FREMONT, CA: Pharmaceutical drug development is a time-consuming and costly process. Pharmaceutical and biotechnology companies typically spend more than one billion dollars to bring a drug to market, a process that can take up to ten to 15 years. Furthermore, the drug development process is risky; up to 90 percent of drug candidates are eventually dropped due to issues like safety and efficacy, leading to massive losses for companies. Any technology that can significantly contribute to resolving any of these three pain points of the drug development process will rapidly grow into a multibillion-dollar industry.
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The use of artificial intelligence (AI), namely machine learning and deep learning algorithms, to enhance the drug discovery process is one such technology that has arisen in recent years. Compounds of interest are identified and improved to have drug-like properties in this early stage of the drug development process before being tested in animals and, later, humans. While computers have been used to aid pharmaceutical research and development for decades, and AI has been employed for more than ten years, it has only lately begun to gain traction. For example, over 80 percent of funding for AI in drug discovery has been increased in the last three years, with spending in 2020, at the peak of the COVID-19 epidemic, exceeding that of 2018 and 2019.
Companies that are commercializing AI drug discovery platforms and AI-discovered pharmaceuticals have demonstrated that using algorithms can cut a multi-year process down to a few months. This considerable reduction in development time and the quantity of compounds that must be manufactured for laboratory testing provides significant cost savings, addressing two critical challenges in pharmaceutical R&D.
While AI drug discovery businesses have not proven that their technologies can bring a drug to market (that is, pass clinical trials) with higher success rates than traditional drug discovery methods, the rapid timelines and potential cost savings are compelling enough for pharmaceutical companies around the world to invest internally to grow their own AI capabilities, or to partner with AI companies in multibillion-dollar deals.
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