Artificial intelligence (AI) is revolutionising early drug discovery, particularly in clinical trials, which have long been a bottleneck in the pharmaceutical industry. Recent applications of AI technologies are enhancing efficiencies in clinical research.
Only 14% of drugs entering clinical trials are ultimately approved by the FDA, according to the Congressional Budget Office (CBO). The drug development process is complex and can cost over $2 billion. AI-driven modelling and simulations are being developed to improve success rates by simulating expensive clinical trials before they occur. While industries like aerospace use extensive simulations, biology presents unique complexities.
QuantHealth, an AI-focused clinical trial design company based in Tel Aviv, has completed over 100 simulated clinical trials, achieving an impressive 85% accuracy rate. CEO Orr Inbar highlights that their proprietary AI simulator uses over 1 trillion data points to optimise clinical development. This technology enables scientists to model trials rapidly, assessing variables like success rates and commercial viability.
AI can also predict phase 2 trial outcomes with 88% accuracy, compared to the actual success rate of 28.9%. For phase 3 trials, the accuracy is 83.2%, significantly higher than the industry average of 57.8%. This predictive capability allows companies to make informed decisions on trial progression and drug repurposing.
Certara is another company using AI to enhance drug development. Their technology integrates simulations with other methods to model dosing based on previous studies. The FDA collaborates with Certara to review drug applications and expand predictive models, aiming to make drug development faster and safer.
AI also assists in managing vast amounts of data, extracting useful information from millions of documents. This capability enables researchers to build biological maps and better understand drug physiology.
Overall, AI's role in drug development is expanding, with applications ranging from improving trial designs to accurately predicting clinical outcomes. These innovations could save the pharmaceutical industry billions of dollars and significantly reduce the time needed to bring new drugs to market.
