Exploring the Potential of AI for Clinical Trials
April 30, 2025While AI may be controversial in many industries, its contributions to healthcare, from helping doctors improve their bedside manner to detecting certain types of cancer, are undeniable. As a technology-forward company, Atlantic Research Group (ARG) has formed a committee to explore potential uses of Generative AI for improving clinical trials both clinically and operationally while adhering to our strict AI Usage policy.
“Everyone is very excited and very curious about what AI can do for ARG,” Lynne Lyles, a Clinical Research Associate (CRA) and member of the AI group, explained. “Everyone’s level of AI understanding is different. We’ve been able to bounce ideas off of one another.”
Lyles is a founding member of the team, which first came together this January. As a CRA, she plays a crucial role in conducting visits, maintaining contact with sites and ensuring the success of clinical trials. Lyles is currently involved in training other team members, and LM models have helped her create improved learning tools.
AI as a Training Assistant
This technology has allowed her to take hundreds of pages of a document and, using the right prompts, turn them into podcasts and training materials. This makes the information more accessible and digestible for the target audience, even those who are less technically proficient. Since the material is summarized, she can also fact-check and review everything before sharing it with team members, an essential step when working with these models.
Along with creating training materials, Lyles has used AI tools to create annotations and action items for her visit reports. These tools help her find the information needed to create these points, simplifying the task and ensuring that nothing gets missed. It has also helped ensure she hits the points that need to be covered in every email. By using AI tools this way, Lyles has been able to keep everyone on the same page with access to the same essential information.
Using AI to Create Consistent Processes
As a CRA, she hopes to create a system of processes that can be duplicated so that teams can be more efficient. This can reduce the duplication of work allowing for a stronger focus on medical advancements, which can benefit any trial but has the most profound impact on trials with large numbers of patients and sites.
Despite the benefits of using AI in clinical trials, there are some challenges and ethical considerations. Lyles emphasizes the importance of fact-checking and verifying the information provided by AI tools to ensure accuracy. There’s also an increased need for regulatory approval and oversight when implementing AI in clinical research.
AI in Clinical Trials, Now and in the Future
From Lyles’ perspective, AI has significantly improved the processes of data collection, analysis and reporting. She believes AI has the potential to revolutionize how clinical trials are conducted in the future by providing a standardized and replicable system that can be applied across different studies and sites. However, the AI team at ARG hasn’t solved the problem yet.
“We’re just now scratching the surface,” Lyles said. “We’re in the beginning stages of understanding exactly how we can use AI in clinical trials.”
Looking ahead, Lyles is excited about the possibilities that AI offers in the field of clinical research. She is eager to continue exploring new applications of AI, sharing ideas with colleagues and learning from others in the AI group.
While ARG is only beginning to delve into the world of AI, as a highly focused CRO in neurology, immunology and oncology, we are inspired by seeing the differences it has already made in our industry. In a recent study, mammograms read by AI before being interpreted by a radiologist, as opposed to being read by two radiologists, had 20% more cancers detected. AI has also shown to have a lower rate of false positives, reducing unnecessary biopsies, as well as financial and emotional stress.
AI tools have also impacted other areas of medical research, such as allowing for automated eTMF filing and improving workflows between systems used in clinical research. AI tools have also been used across industries for cost analysis, assistance in the brainstorming process, and creating predictive models based on existing trends. ARG looks forward to uncovering all of the ways AI can improve patient outcomes through clinical trials.
Compliant with ARG's AI usage policy, our team is adopting GenAI to optimize existing processes and pioneer new approaches, given the continually expanding capabilities of these tools.
