Artificial intelligence (AI) has made significant strides in revolutionizing early drug discovery, but human clinical trials have remained a bottleneck in the pharmaceutical industry. However, recent applications of AI technology are beginning to bring efficiencies to clinical research.
AI-powered modeling and simulations have shown promise in improving the success rates of novel drugs entering human trials. The complexity of drug development often results in high failure rates, with only 14% of drugs that enter clinical trials ultimately receiving approval from the FDA. The cost of developing a single drug can exceed $2 billion, making it imperative for the industry to find ways to improve efficiency and success rates.
Modeling software in clinical research aims to simulate costly clinical trials, similar to how other technical industries use simulations for complex items like semiconductors and fighter jets. While modeling biology poses unique challenges due to its systemic complexity, simulations hold the potential to enhance drug development by pre-emptively modeling trials, improving success probabilities, and increasing predictability.
QuantHealth, an AI-focused clinical trial design company, has reported an 85% accuracy rate in simulating over 100 clinical trials. The company's AI-based Clinical-Simulator system utilizes vast amounts of data to optimize clinical development, offering a holistic approach to trial design and outcome prediction. By partnering with health systems and acquiring proprietary data sources, QuantHealth has been able to train its AI models effectively and achieve high accuracy rates in predicting trial outcomes.
Similarly, Certara is using AI to accelerate the drug development process by predicting appropriate dosing based on prior non-human studies. The FDA has collaborated with Certara to enhance regulatory review processes and improve product development for complex generics and novel drugs.
Overall, AI-based clinical simulation systems have the potential to transform the pharmaceutical industry by significantly improving success rates and reducing costs. By predicting trial outcomes with higher accuracy and optimizing trial design, AI technologies are poised to revolutionize drug development and streamline the path to FDA approval.