The FDA is revolutionizing drug discovery by embracing artificial intelligence (AI) and reducing animal testing. The agency aims to make animal studies the exception for pre-clinical safety and toxicity testing within three to five years, instead relying on AI-driven technologies, human cell models, and computational models.
This shift is expected to cut timelines and costs by at least half, potentially reducing the $2 billion and 15 years it takes to bring a drug to market. AI can process vast amounts of data quickly, predicting drug safety and efficacy more accurately. Companies like Recursion Pharmaceuticals, Certara, and Schrodinger are already leveraging AI to speed up drug discovery.
Recursion's AI-based platform took just 18 months to move a molecule into clinical testing as a cancer drug candidate, far faster than the industry average of 42 months. While animal testing won't disappear entirely, experts predict a hybrid approach will become the norm, combining new methods with animal testing to ensure safety and efficacy.
The new approaches are expected to lead to lower drug prices, making healthcare more accessible. Analysts at TD Cowen and Jefferies estimate AI-driven approaches can cut costs and timelines by more than half. The FDA has released draft guidance outlining a road map for companies to reduce reliance on animal testing, especially for monoclonal antibody drugs.
The agency aims to evaluate AI models' credibility and ability to predict drug outcomes accurately. Overall, the integration of AI in drug discovery has the potential to transform the pharmaceutical industry, making it more efficient, cost-effective, and humane.
