The role of AI in clinical trials

Artificial Intelligence (AI) is revolutionising the healthcare sector, with one of its most promising applications being clinical trials. The global clinical trials market, valued at over USD 50 billion, is undergoing a transformative shift as sponsors, CROs, and healthcare providers seek smarter, faster, and more scalable ways to identify, recruit, and retain participants. AI stands at the forefront of this evolution, and at Clinrol, we’re deploying AI-driven solutions that make patient recruitment more accurate, ethical and accessible.

How AI improves efficiency in clinical trials

Traditionally, clinical trials are hampered by delays—80% are delayed due to difficulties in recruitment, and nearly one-third of research sites fail to enroll a single participant (Tufts Center for the Study of Drug Development). AI changes that by introducing automation, predictive modelling and smart targeting.

Through machine learning algorithms, Clinrol’s platform can analyse a combination of real-world data (RWD), electronic health records (EHRs), and patient-reported outcomes to match individuals to trial criteria with unmatched precision. NLP (Natural Language Processing) is used to process and understand unstructured clinical notes, enabling deeper patient profiling beyond surface-level demographics (NIH on NLP in clinical research).

This technology also supports site selection, forecasting which locations are likely to recruit faster and yield higher retention. By identifying patterns in historical performance data, AI helps sponsors optimise trial placement, reducing costs and improving speed to market.

Smarter recruitment with AI

AI-powered recruitment campaigns can adapt in real time. At Clinrol, our algorithms analyse engagement data from digital ads, landing pages and pre-screening forms. This allows us to refine targeting continuously and ensure messaging resonates with diverse patient populations.

A study by McKinsey & Company highlighted how AI-based tools can reduce recruitment timelines by up to 30% (McKinsey Health Tech Insights). Clinrol takes this further by using AI to build lookalike audiences based on patient behaviour, health history, and digital interactions, ensuring better quality leads and higher conversion rates.

Can AI help me find a clinical trial?

Absolutely. With Clinrol’s AI-matching tool, patients no longer have to sift through irrelevant studies. By entering basic health data, users are presented with studies that are best suited for their profile and location. The system also learns from user input to offer more personalised suggestions over time.

This approach is especially useful for patients with rare or complex conditions, where eligibility criteria are highly specific. Visit our find a study page to get started. Or if you're a sponsor or site looking to find patients or participants, we offer AI tools designed to improve communication, boost engagement and reduce the burden on site staff.

Real-world impact

Our AI solutions have helped increase referral rates by over 200% in under-represented patient groups. This is crucial as diversity in trials is essential for generating generalisable results, a concern highlighted by the FDA and other global regulatory bodies (FDA: Enhancing Diversity in Clinical Trials).

As the healthcare industry continues to embrace digital transformation, AI is proving to be not just a helpful tool, but a game-changing force. At Clinrol, we’re proud to be pioneering this space ethically and transparently.