I have often highlighted this to clinical, industry, and CRO colleagues – maybe to anyone who would listen. Clinical trials are important. They are harder and more expensive to do, and finding patients to participate can be tough. 

This means that trials take longer to start and longer to complete and report, with the utility and value of results often diminishing by the time of publication – a situation that is wholly unfavourable to all involved.

Risk-based monitoring (RBM) is a modern approach to clinical trials, shifting from the traditional frequent, on-site monitoring toward a more targeted and flexible strategy. Critically, RBM is designed to enhance the efficiency and effectiveness of trials while still maintaining data integrity and patient safety.

With an increase in its adoption over recent years in light of the introduction of new regulatory requirements, the emergence of supportive technologies, and the decentralisation of clinical trials, there is a key question for the multi-disciplinary teams responsible for these trials: how can we best apply technology and innovative approaches to enhance success and reshape the trial landscape?

Tackling the Issue of Patient Matching and Recruitment in Clinical Trials

Digital ecosystems, utilised well, have the potential to arm teams conducting clinical trials with solutions that target the key issues around data access and patient recruitment at a retrospective and prospective level. Such technology provides the ability to create integrated pools of patient data across sites, sources, and disease areas, from which the critical inclusion and exclusion criteria can be matched for trial cohorts. With this, teams are equipped not only with the ability to drive recruitment of the right patients during study set-up, but also to create “trial-like” external comparator arms when contextualising existing output.

Beyond the data, critical parts of our day-to-day span from driving engagement with the clinical teams and treatment sites that support the signposting of patients to potential studies of relevance, to engagement with patients and patient organisations themselves. Bridging the gap between patients, research, and a better understanding of their disease is a core part of our ongoing work, and a vital component in any approach to boosting recruitment for clinical trials.

Indeed, my conversations with clinicians and patients alike, supported by internal research through digital patient surveys, have flagged time and again the need for better patient education and engagement regarding trials. Even in the case of a recently approved therapeutic innovation, we found that little more than a quarter of potential patients were aware that any clinical trials were taking place within the space, and even fewer had heard of this specific treatment.

Central to tackling these challenges is the rise of patient matching software, which uses AI-driven technology to meet the demands of recruitment at scale and beyond the capabilities of manual trial matching. Targeting longstanding barriers to recruitment at multiple pain points, these solutions can support accelerated enrolment not only through automated trial matching from an investigator perspective, but also at a clinician and patient level.

For clinical teams, this can help to streamline the matching process and reduce the time needed to manually assess their patients’ eligibility, providing physicians with an easier opportunity to refer potential patients to a clinical trial. Meanwhile, patients can utilise these technologies to search for potential trials they could participate in against their medical histories and basic demographics – removing the need to parse increasingly complex eligibility criteria and empowering patients to take charge of their own care by identifying potential trials of interest and suitability.

In the past, low accrual rates have been highlighted as the most common reason for trial termination, with enrolment timelines missed in 86% of trials, and almost one-third of Phase III trial failures resulting from slow recruitment. As such, it is all too clear that enhanced methods of connecting patients with trials that could potentially benefit both them and the wider patient population are vital in this ever-changing landscape, and future trials will need to utilise the supporting technology at hand to ensure their success.

Innovations in Action | Utilising Digital Innovations Across the Trial Pipeline

Sanius has the solution to support rapid recruitment and retention of patients to trials, while also helping recruited patients by providing pre-, peri-, and post-trial support.

Each stage of the trial is supported by the enrichment of the core database – from the integration of retrospective data, to the capture of prospective real-time physiological metrics and patient-driven quality of life insights. As incredible fonts of information, we have also seen first-hand the value of incorporating existing and often disease-specialised registry data alongside that captured from medical records, wearables, and digital patient-reported outcomes (PROs).

Upon utilising our expertise in data science to access, clean, and integrate data from across these sources, sense-checking of the resulting aggregated database and translation into real-world insights and evidence is supported by our network of dedicated clinical specialists – ensuring everything we do is validated through a clinical lens. Not only does this help at a post-trial level to produce RWE for regulatory submissions that is guided by clinical expertise and the true patient experiences, but this also ensures that the data feeding into pre-trial processes of patient-matching are of the standard needed to ensure accurate eligibility assessments.

Once enrolled, ongoing challenges often remain. Ensuring that a trial’s end comes with generated evidence of sufficient quality and data endpoint completeness is vital in supporting regulatory submissions that meet the requirements to bring innovation to the patient populations that need them. A key part of our work, once patients are enrolled, therefore revolves around ongoing support from a dedicated patient engagement and coaching team. This team focuses on the day-to-day of the patient experience, ensuring that the devices and digital components in a trial are understood and working well, while also supporting retention and adherence to ongoing data capture and study procedures.

From pre-trial engagement, patient matching, and recruitment, to peri-trial support that drives the generation of powerful real-world evidence, our ongoing focus is to tackle the challenges that too often lead to clinical trial failure. For colleagues who wish to learn more about our ecosystem and capabilities within the trial space, we welcome you to reach out here or through [email protected].