3 Ways Practice Sites Can Utilize AI to Enhance Clinical Trial Strategy

Artificial intelligence (AI), and its impact on our everyday lives, is generating a lot of excitement. There are so many avenues in which generative AI can be applied in healthcare; clinical trials being one of the most compelling. 

Since its inception in 2018, Verana Health has been utilizing these advanced mathematical techniques to help unlock deeper patient care insights at a speed not possible in the past.

Of course, clinical trials have been no stranger to this panacea.^,  Much of the attention has been directed toward drug development and the discovery process, but is there a way research sites can harness this boon to increase efficiency and effectiveness? We think so. Here are 3 innovative, yet practical, ways that we believe research sites could benefit from AI now, and in the near future:

1. Patient Recruitment: On a macro level, AI can aid in identifying potential candidates for clinical trials by analyzing vast amounts of patient data, medical records, and genetic information. Machine learning algorithms (ML) can match potential patients with specific trial criteria, improving the efficiency of participant recruitment. What this means for a busy research center is that under the supervision of the principal investigator, AI can be employed to identify potential candidates already in their database or records. Additionally, AI can help sites craft their marketing messages around trial recruitment. AI can be especially useful in crafting digital media advertising or marketing. Data shows that even seniors are increasing their screen time!
2. Predictive Analytics: AI can help analyze historical trial data to identify patterns and predict outcomes. This information can help practice sites make informed decisions on which trials to undertake, as well as optimal execution strategies. Take the following scenario: a busy research site is approached by two sponsors to undertake a trial in the same indication. The site only has operational capacity for one trial. AI can help the site quickly analyze the study criteria against its electronic health record system to determine which trial is a better fit. Additionally, predictive analytics can assist in estimating the probability of adverse events or patient dropout rates.
3. Real-time Monitoring: AI-powered tools can monitor and analyze patient-generated data, such as wearable devices or mobile health applications. This real-time monitoring helps to promptly detect and respond to any adverse events. This functionality would be extremely valuable in studies using electronic patient-reported outcomes devices to trigger interventions or alterations to a patient’s treatment regimen. AI can help ensure that these “trigger” events are recognized immediately and can help ensure timely implementation of the new regimen. Lastly, AI algorithms can provide alerts and insights based on the collected data, allowing clinical research coordinators (CRCs) to intervene when necessary.

Overall, the integration of AI technologies at practice sites can help streamline trial operations, improve patient recruitment, enhance data management and analysis, and support evidence-based decision-making throughout the trial lifecycle. 

Verana Health is at the forefront of maximizing new technology to benefit sites that are participants of the American Academy of Ophthalmology (Academy) IRIS^® Registry (Intelligent Research in Sight). Verana Health is the exclusive data and analytics partner of the Academy’s IRIS Registry, which is one of the largest specialty society clinical data registries in all of medicine.

Tools, such as our newly introduced VeraSite and Verana Trial Connect (VTC), are two examples of how Verana Health is using technology, including AI, to bring new efficiencies to trial execution. One recent CRC had this to say: “Our site’s recruitment success can largely be attributed to the VTC patient database.”

To learn more about Verana Health’s site solutions, email [email protected].

¹https://www.theguardian.com/commentisfree/2023/jun/26/ai-personalise-medicine-patient-lab-health-diagnosis-cambridge

²https://www.outsourcing-pharma.com/Article/2023/06/08/owkin-invests-50m-in-project-revoltionizing-cancer-research