Major pharmaceutical companies are turning to artificial intelligence (AI) to revolutionize the process of conducting clinical trials. By employing AI technologies, these Big Pharma firms aim to expedite patient recruitment for trials and potentially save millions of dollars by reducing the number of participants needed to test new drugs.
Human research, which is the most expensive and time-consuming phase of drug development, can take several years and cost over a billion dollars. To speed up the process of finding suitable participants for trials, pharmaceutical companies have been experimenting with AI for years. Although it will take time for these efforts to pay off, executives from various companies, including Amgen, Bayer, and Novartis, have confirmed that AI is playing an increasingly significant role in human drug trials.
Traditionally, pharmaceutical companies have faced challenges in finding the right individuals for clinical trials. They had to rely on surveys, connections with medical facilities, and physicians to identify potential participants. However, AI has changed this approach. For example, Amgen has developed an AI engine called ATOMIC, which leverages vast amounts of internal and public data to assess the historical success of hospitals and physicians in enrolling patients for clinical trials. This process helps to identify suitable trial sites and shorten the time it takes to enroll participants.
Similar approaches are being adopted by other pharmaceutical companies, showcasing the growing influence of AI in the industry. Novartis, for instance, has utilized an AI tool to streamline patient enrollment in trials, making the process quicker, more cost-effective, and efficient. However, the effectiveness of these AI tools heavily relies on the availability of quality data. Typically, less than 25% of health data is publicly available for research purposes, which poses a challenge for AI implementation.
Moreover, pharmaceutical companies are eyeing the use of real-world patient data to create external control arms for studies. Bavarian pharmaceutical giant Bayer aims to utilize real-world data from young patients to eliminate the need for placebos in a pediatric trial. This approach raises ethical questions regarding the administration of placebos to trial participants when effective treatments are unavailable. However, such external control arms have been used occasionally, particularly for rare diseases or when the number of patients is limited.
While the use of AI in clinical trials holds promises, regulators emphasize the importance of adhering to evidence-based standards for drug safety and efficacy. The U.S. Food and Drug Administration (FDA) has received around 300 applications involving the use of AI in medication development, with the majority submitted in the past two years. Regulators want to ensure that AI is utilized responsibly and that patients’ well-being and the accuracy of trial results are not compromised.
In conclusion, AI is increasingly revolutionizing the landscape of clinical trials in the pharmaceutical industry. Companies are leveraging AI technologies to expedite patient recruitment, enhance the efficiency of trial enrollment, and potentially save costs. While the application of AI holds great potential, it is crucial to balance innovation with the adherence to rigorous scientific standards and ethical considerations.
