Major pharmaceutical companies are turning to artificial intelligence (AI) to accelerate the difficult and costly process of clinical trials. These companies aim to swiftly identify suitable patients and optimize trial designs by leveraging AI.
This will enable them to save millions of dollars and accelerate drug development. An interview with industry experts, regulatory authorities, and AI companies revealed that AI is making significant inroads into clinical trials.
AI: The Key to Faster Clinical Trials
Clinical trials represent the most time-consuming and expensive phase of drug development. Recruiting eligible patients and conducting comprehensive testing always takes years, leading to costs running in billions of dollars.
The latest report suggests that using AI-powered technology has significantly addressed these challenges. According to the report, pharmaceutical giants have explored AI’s potential for years, aiming to discover the next breakthrough drug.
While AI-discovered compounds are already in development, the full impact of these initiatives will take time to materialize.
AI’s Growing Role in Patient Recruitment
Major pharmaceutical companies such as Amgen, Bayer, and Novartis utilize artificial intelligence (AI). This simplifies the analysis of extensive datasets, encompassing public health records, prescription information, and medical insurance claims, including internal data to pinpoint eligible participants for clinical trials.
This approach results in a 50% reduction in the time required for patient recruitment, thereby accelerating the drug development process. During the interview, Jeffrey Morgan, the managing director at Deloitte, agreed that artificial intelligence adoption is on the upswing. He said,
“I don’t believe it’s ubiquitous yet, but we’ve moved beyond the experimental stage.”
Also, the U.S. Food and Drug Administration (FDA) has been active in overseeing the integration of AI and machine learning in drug development processes.
From 2016 through 2022, the FDA received about 300 applications to integrate artificial intelligence into various aspects of drug development. Notably, over 90% of these applications were submitted in the past two years, and many focused on AI’s use in clinical development stages.
Bayer’s Use of AI to Streamline Clinical Trials
Meanwhile, according to a Reuters report, German pharmaceutical company Bayer has employed artificial intelligence (AI) to significantly reduce the number of participants needed for a late-stage trial.
The trial was focused on testing their experimental drug, asundexian, which aims to mitigate the long-term risk of strokes in adults. By leveraging AI, Bayer linked mid-stage trial data with real-world patient data from millions of individuals in Finland and the United States.
This innovative approach allowed Bayer to predict long-term risks in a population similar to the trial’s target group. This enabled the company to conduct the late-stage trial with fewer participants. Without AI, Bayer estimated that it would have incurred millions in costs and a nine-month delay for volunteer recruitment.
Furthermore, Bayer intends to explore this AI-driven methodology further by utilizing real-world patient data. This will enable them to create an “external control arm” for a study testing asundexian in children with the same condition.
This methodology will come in handy in cases where recruiting patients for pediatric trials is challenging due to the rarity of the condition and ethical concerns. Bayer aims to mine anonymized real-world data from children with similar vulnerabilities.
While artificial intelligence holds tremendous promise for the pharmaceutical industry, it also comes with challenges like low regulatory compliance, data privacy, and sorting specialized talents. The industry’s commitment to overcoming these challenges is evident through extensive AI research and development investments.
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