The usage of Digital Health Technologies (DHTs) within clinical trials is growing.
Digital Health Technology: “DHTs that may be worn, implanted, ingested, or placed in the environment allow real-time collection of data from trial participants in their homes or at locations remote from clinical trial sites.”
The usage of Digital Health Technologies (DHTs) within clinical trials is growing. In 2020, approximately 11.4% of clinical trials in neurological disorders had listed a DHT within their protocol (Masanneck et al). It’s further estimated that by 2025 70% of trials for neurological disorders will incorporate some form of DHT. Trials are increasingly utilizing DHTs to provide unprecedented quantification of disease, disease subtypes, patient populations, and treatment efficacy. The increased resolution into disease and human health provided by DHTs holds the promise of reducing clinical trial costs, accelerating trial timelines, reducing the burden on participant populations, and salvaging trials that would have otherwise failed.
Unfortunately, much of this potential value from DHTs is, as of yet, unrealized. Significant logistic, technical, and regulatory challenges are limiting the actual real world value sponsors can derive from these new technologies. The increased complexity of data collected from DHTs does provide powerful new quantifications of disease, but additionally require complex data storage architecture, AI/ML data processing pipelines, and draw increased scrutiny from regulatory bodies. As a result of this increased burden, DHTs are often relegated to exploratory endpoints and post hoc analyses making them more of a burden than a benefit, currently.
To accelerate their adoption as primary endpoints and IE criteria, clinical trial teams need, at the minimum, the ability to compare DHT derived endpoints to traditional TA specific endpoints to establish the necessary clinical burden of evidence to elevate DHTs from a novelty.
Increased data richness and data complexity is a double edged sword, representing a key benefit, and one of the key limitations, when adopting DHTs. Trials incorporating these new technologies often place more burden on sites and sponsors to design and manage new approaches to collect, store, process, quality control, design AI/ML analytic workflows, debug, and analyze these raw and often noisy datastreams. Further, many sponsors are struggling to implement DHTs without increasing burden on participants, which often leads to lower adherence and participant engagement.
The increased complexity of data from DHTs is burying already overworked clinical trial teams under an additional endless burden of spreadsheets, data analytics, and data quality control. These additional workflows are unavoidable as data from DHTs is increasingly fragmented across multiple sources and platforms with unique formats, spanning a diverse set of study endpoints. Accessing and organizing this data requires significant manual effort and customized AI/ML workflows; the teams managing trials don’t have the time and the budget to build and manage the new workflows needed to incorporate DHTs or new analytics on top of DHT data.
As technologies develop, we further need the ability to quickly and reliably incorporate these new workflows and analytics into the workflows used by clinical teams without introducing a cacophony of additional software solutions each time. The burden of this work cannot fall on clinical trial teams. If we, as an industry, want to innovate the way we measure disease and advance human health, we need to lay a new foundation in how clinical trial data is collected and presented to clinical teams.
This new foundation will require clinical trial software vendors to understand both the global and the most granular needs in clinical trial data management. Globally, DHT data streams need to be seamlessly integrated into existing analytics, oversight monitoring, and data management workflows, providing intuitive insight and support to clinical trial teams. This software will need the ability to unify disparate data streams and types into an easy to use and interpret interface thereby providing oversight and monitoring over all data including DHTs.
Diametric to this global need to unify all data is the deep domain expertise and analytic customization required to make data from a DHT useful for an individual trial and therapeutic area. There isn’t a one size fits all solution. Actigraphy data used within cardiovascular health needs to be interpreted very differently than actigraphy used to quantify symptoms within Parkinson’s Disease. Modern clinical trial platforms are under an increasing burden to support domain specific analyses, but on a global scale, to provide the insights sponsors need around DHTs and more complex data sources.
DHTs will struggle to live up to their potential benefit until clinical trial teams have more oversight over data and insights from DHTs and an approach to integrate DHTs within their current workflows with limited additional burden on them. This includes needing a data platform that can automatically process and quality control these novel data streams, integrate their insights with more traditional data sources (labs, COAs, EDC), and visualize their domain specific value. Eliminating the burden these novel data streams place on current clinical trial teams is the largest way to accelerate their adoption and reap the benefits they provide to improve human health.
Our team at OmniScience has helped numerous biopharma sponsors unify, process, and analyze clinical trial data, spanning a breadth of endpoints and inclusion/exclusion criteria, including many trials focused on leveraging DHTs. Our platform, Vivo, unifies and visualizes fragmented data across clinical trials to deliver actionable operational insights, increase collaboration, and facilitate advanced analyses.
We are passionate about lowering the burden new technologies are placing on clinical trial teams to speed their adoption and evolve the way we can fight disease and improve human health. As part of our commitment, we have recently engaged in a strategic partnership with the DiMe Society to better measure these challenges and define a framework to quantify ROI provided by DHTs with the end goal of expanding and accelerating the adoption of DHTs within clinical trials.
If you are running or planning a clinical trial or want to glean more from past clinical trial data, let’s talk about ways our team at OmniScience and our Vivo platform can accelerate your clinical development initiatives.
Vivo is the first control tower for clinical development teams to accelerate trial execution and enable advanced analytics, bringing clinical trial management into the modern era. Vivo allows pharma and biotech to automate and accelerate clinical trials, enabling clinical development teams to manage and unify complex data sets from disparate sources. Vivo provides a single portal to access data summaries and visualizations across all vendor platforms including EDCs, PROs / COAs, labs, imaging, wearables, and more. Vivo enables unprecedented levels of oversight and quality assurance with actionable notifications, smart data management, and conversational search to better monitor and accelerate clinical trials.
