AI in clinical trials
AI has been making headlines in the last year for its potential use in logistics, business, technology, healthcare, and more. But what about clinical research? We expect sponsors and clinical researchers will leverage AI to improve trials in multiple ways.
Advancements in AI can transform clinical research by simplifying and enhancing the patient experience. Making trials increasingly “patient-centric” will help with a common problem that clinical trials face today—enrolling and retaining patients.
In recent years, 80% of clinical trials fail to meet their enrollment goals on time, and an average of 30% of patients drop out once trials begin. Enrollment and retention problems increase trial timelines and costs and delay getting treatments to people who need them. Technology has the potential to solve many current inefficiencies, making trials simpler for patients and less costly for researchers.
eConsent
Castor, an industry leader in modular, patient-centric clinical trial technology, is developing productive, creative ways to harness AI in clinical trials to reduce trial site burden and improve the patient experience. AI is the next step in the evolution of modern clinical trial technology.
“When it comes to healthcare, people seem comfortable with AI handling simple tasks but want their doctor involved in anything related to treatment. While there’s acceptance for AI in certain areas, trust must be built for more complex tasks. I am a big believer in AI-Assisted vs. AI-Led.” said Derk Arts, MD Ph.D., CEO & Founder of Castor
AI in the clinic
Modern technology is already advancing traditional methods for clinical trials. Consider the informed consent process. Electronic consent tools (eConsent) can replace inefficient paper-based forms. Patients can sign forms remotely instead of traveling to a trial site, and study staff do not have to re-enter data.
AI improves the consent process even further. Study staff can use AI to develop customized interactive elements within the tool and reach wider audiences. Better trial education for patients makes for a more informed and engaged experience—empowering patients and helping further reduce dropout.
AI also helps study staff create materials quicker, freeing them to focus on other tasks that require human creativity and problem-solving. AI has the potential to streamline trials in other ways: automating study builds and data capture, optimizing protocols and site selection, and helping with source data verification.
AI-enabled technology can drastically reduce traditional trial timelines, with applications in study design, start-up, recruitment and enrollment, and close out. Let’s explore this through a real-life example. A health company recently used Castor’s eConsent tool to complete the entire recruitment process for their clinical study in only four months. All 84 patients enrolled in the study completed it—a 100% retention rate. Incorporating AI in the enrollment process could have made it even faster.
Along with the evident benefits of leveraging AI in trial technology, implementation is more complicated than it may initially appear. Establishing trust in the research community is difficult, especially from the institutional review boards (IRBs) that monitor a study’s ethics. IRBs and the FDA already control so many aspects of clinical trials that convincing them of AI’s benefits to patients and trial workflow will take time and work.
Technology enabled research
“Picture AI helping with enrollment and consent processes. It’s not to replace people, but to help them.” We want to see if AI can help patients understand clinical trial details better, make them happier with the tech, and keep them in the trial longer. “AI can take care of the boring stuff, letting people focus on the important ethical parts. This teamwork can make things clearer and smoother,” the story goes on. “It’s not just about speed; it’s about helping patients understand better, stay longer, and be happier by giving them access to a virtual helper all the time during the enrollment and consent steps.”
AI-enabled technology is at a point where it should be considered for use by the clinical research community. Enormous costs, long timelines, non-diverse patient populations, and low success rates are all issues that can find solutions in modernizing trial technology. AI has the potential to be an urgently-needed solution to pressing problems.