As a result of the COVID-19 pandemic, doctors are increasingly engaging with patients on a wide range of topics using digital technologies. This is a fundamental shift in healthcare, and has led to the rising popularity of Decentralized Clinical Trials (DCTs). With an increased patient demand for DCTs, our industry is gaining proof points for what we believe should be an important option when designing clinical trials now and in the future. However, this transition from a site-centric to a patient-centric trial model requires input from patients and insights into their needs in a greater way.  

Our research shows that specific patient profiles rely on, and prefer, direct engagement with their healthcare professional (HCP). With patient cohorts that tend to be more “convenience seeking” and attracted to DCT design, retention risk can be elevated. The operationalization of DCTs cannot be a one-size-fits-all, and will need to balance patient demand, flexibility and practicality. Real success will be achieved when we look at DCTs as a balanced approach. Otherwise, we run the risk of ostracizing large patient cohorts with fully digital and remote approaches that are not grounded in insights about what will work best for patients.

Patient input must be a standard datapoint across the end-to-end clinical development lifecycle. From early development of target patient profiles through to commercial launch, the key to success is ensuring our clinical and commercial design is attractive, high value, and offers a patient experience that meets or exceeds demand. At every step in the process, we must find the balance between patient-led unmet need and biology-led unmet need.

“Clinical trials have the best chance of being attractive to patients when patients are at the center of the process.”

The pharmaceutical industry is increasing its investment in artificial intelligence (AI) and machine learning (ML) as part of its R&D processes. This presents an opportunity to remove the burden from patients. Today, patients are still expected to shoulder unrealistic, rigid schedule requirements—from trial matching and eligibility assessment to rigor in data quality through collection. With the ability to apply more real-world design and digitally transform mHealth and DCT solutions, the heavy lifting can be absorbed by data science. Clinical trials have the best chance of being attractive to patients when patients are at the center of the process.  

Hū has an integrated approach to developing solutions in this area. Our combination of data, technology, and advanced analytics enables a scaled, digital, and representative method of global analysis of patient evidence and insights. Our proprietary models enable clear segmentation of patient cohorts by motivation, preference, lexicon, and propensity to participate in trials. The result is confidence to build DCT and/or hybrid approaches that engage and enable high study participation across the broadest set of patients by determining the optimal levels of optionality in the study design and delivery plan.

At Hū, our approach is one that infuses study design with a balanced DCT approach based on patient insights and evidence. We are committed to leading the charge in designs that offer patients significant convenience in accessing treatments and associated trial procedures, that recognize when and which patients want access to HCPs “on demand,” and that define what warrants an in-person visit. The trend overall is toward patients demanding more control over their treatment journey. DCTs or hybrid trials support these patient needs in ways that traditional clinical trials have not been able to meet. What we are looking at is the democratization of a clinical trial, allowing these often life-saving solutions to be viable care options irrespective of a patient’s zip code or their local physician knowing how to connect them to clinical trials.