The drug development industry is in the midst of a clinical trial revolution. Patient-centricity is the primary driver — and we should all embrace it.
To be truly patient-centric, we, as an industry, need to invest in ensuring that as we modernize clinical trials, we continue to consider insights and feedback from patients. Giving them a voice, and responding to what they say by designing and adjusting our approach and technologies, is an important first step.
But it also goes beyond that. In fact, I think patient centricity considers three key areas of innovation: trial design, digital biomarkers, and data and advanced analytics.
Trial design: One size does not fit all
Innovative clinical trial design — including remote data collection and decentralization — is aimed at relieving the burden on sites so they can provide better care and make trials more accessible to patients.
When we think about designing a trial, we take a rigorous approach to not only the scientific needs of the study, but also the needs of that specific patient population, investigators, and sites.
For example, we surveyed more than 450 patients and 140 sites and found that half of the respondents said they did not want fully remote visits. Instead, participants and sites were interested in a hybrid approach, with a mix of in-person, virtual, and in-home visits. In this instance, participants wanted an in-person touchpoint with the doctors so they could ask questions and get reassurance.
Not all trials look the same, and thanks to the growing innovation in this space, we have tools available to customize our trials based on patient and site preference.
To ensure we are hearing patient input, we created a patient engagement team to collect insights to better inform our protocols: What do patients expect when they participate in a clinical trial? What support do patients need to lessen any burden from participation? How can we create better patient experiences?
At the same time, we are focusing on inclusivity by designing trials that consider the impacts of age, gender, socioeconomic status, race, and more. Our User Experience Research team collects and incorporates diverse feedback to ensure the technology and protocols are intuitive and consider the real-world context.
Digital Biomarkers: What to wear
Much of traditional clinical trial data is subjective and requires frequent visits to the clinical trial site. Additionally, many trials rely on self-reported questionnaires that ask patients to rate their pain levels, or how they slept last night on a scale of 1 to 10.
As we modernize clinical trials, we are now focusing on how to collect more objective data. Digital biomarkers, collected using digital health technologies (DHTs) such as watches, insoles, eyeglasses, and even home-based Wi-Fi boxes, can amass data in a more seamless fashion. This continuous data collection allows us to increase the amount of unbiased information we receive from participants potentially increasing reliability and reducing variability.
Our Digital Biomarker team assesses DHTs and collaborates with device manufacturers to develop or update devices, as we validate technologies to be utilized as endpoints in our clinical trials. One example: our teams recently worked with a manufacturer to develop insoles and a corresponding algorithm that provides a variety of gait measurements (i.e., balance, swing stance, turning angle, stride length, speed, steps, and other parameters related to walking). The data and modeling we’ve collected from this can inform the designs of new DHTs for other trials and other disease therapeutics.
In early 2023, we are opening a Digital Biomarker Lab, a physical space on our company’s campus that will house specialized facilities and equipment for the verification, design, simulation, and testing of wearable devices and non-contact sensors. Bringing these capabilities in-house allows us to accelerate the development of biomarkers and build our own methods with the hope to advance novel endpoint development, potentially making trial data more robust, reliable and less burdensome for patients.
Data and advanced analytics: The trials of tomorrow
As we look to the future of clinical trials’ data collection, we are investing in data connectivity and data science capabilities. Thanks to national health data standards, we are now embarking on ways to allow study sites to reduce the burden of manual data entry, and directly and securely transmit key information, with faster speed and lower error rates.
Similarly, artificial intelligence and machine learning are improving our data granularity, revealing real-time insights. Finding ways to compliantly link electronic health records to collect and deliver real-world data can inform studies and follow-ups, expand our ability to understand how participants are doing long-term, and accelerate our time to impact by increasing statistical power and precision.
Patient privacy is of the utmost importance, of course, and technology also helps protect privacy by encrypting patient identities for statistical analysis. With patients’ clear consent, we can continue accessing long-term follow-up data without adding burden on patients or study investigators and sites. Privacy-preserved real-world data can be gathered years beyond the official trial end — giving the scientific and medical community richer, more detailed insights about safety, the durability of response, and potential insights on other factors in disease progression.
At Regeneron, our pipeline of more than 30 investigational medicines is comprised of primarily “homegrown” therapeutics covering a broad range of diseases. Our mission is ‘Science to Medicine’ and these innovations and how we incorporate them into our clinical research underscore our passion for maintaining patient-centricity along with cutting-edge clinical science.