Harness the Power of Generative AI in Pharma: Accelerate Drug Discovery and Development
This advancement in technology is revolutionizing various stages of drug discovery and development, from initial research to clinical trials and regulatory submissions. By leveraging GenAI, pharmaceutical companies have accelerated the drug development process, reduced costs, and improved the accuracy and efficiency of regulatory documentation.
Spending on research and development (R&D) across drug discovery, development, clinical testing, and safety monitoring has significantly increased over time. According to a Deloitte1 study of the top 20 biopharma companies, total reported R&D spending rose by 4.5%, from $139.2 billion in 2022 to $145.5 billion in 2023. In the future, regulatory uncertainty, supply chain concerns, labor shortages, and other complications will likely cause R&D costs to continue to rise. The drug development process is both costly and uncertain, with zero guarantee that a drug will reach the market. On average, it takes 12 years2 to discover and develop a new drug, costing between $1 billion and $2 billion. Throughout this process, only about 10%3 of candidate molecules progress to the clinical phase, and of those, only 10% are eventually approved, resulting in a 1% success rate from start to finish.
Efforts to reduce time and costs in drug development had largely limited success until the rapid release of COVID-19 vaccines. From the public identification of the virus to the first emergency use authorization in December 2020, it took Pfizer and BioNTech 11 months to reach the market. As this specific case demonstrates and drug discovery costs continue to rise, there is a significant opportunity for GenAI to expedite process development and reduce expenses.
The McKinsey Global Institute4 (MGI) estimates that AI technology has the opportunity to generate $60 billion to $110 billion a year in economic value for the pharmaceutical and medical product industries. This value primarily comes from faster identification of new drug compounds, quicker development and approval processes, and enhanced marketing efforts. In clinical development, which accounts for the bulk of costs, Generative AI can reduce expenses by up to 50% by streamlining clinical trial processes and automating trial document drafting. Additionally, it has the potential to shorten trial timelines by over 12 months.
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