Decentralized clinical trials, or DCTs, looked to be a slow-moving trend for much of the 2010s. Here and there, certain aspects would appear in trials, be it healthcare wearables, virtual site visits, or remote patient monitoring. Suddenly, the onset of the global pandemic forced the pharma industry’s hand, resulting in an overnight conversion of all clinical trials into DCTs to allow clinical research to continue.
The problem: our data management systems weren’t ready.
Remote data collection, processing, and analysis weren’t part of the previous clinical trial infrastructure. Even several years later, data collection systems still lag– and numerous data privacy concerns exist.
How do we solve this ongoing healthcare data challenge? Let’s find out.
The 5 Data Challenges Facing DCTs
According to a comprehensive survey of research professionals by Informa Engage, 76% of clinical trial teams say they’re fast-tracking their use of DCT methods1. The more DCTs become the norm, the more we see glaring data challenges. These include:
1. Data Quantity
Previously, traditional clinical trials captured only a fraction of the data DCTs do. In a single site visit, an investigator might check a person’s core vital signs, take a blood sample, and ask the participant to complete a questionnaire.
Even sleep studies collected data for at most a single night. That led to data sets that were discrete and relatively small.
DCTs now rely on healthcare wearables to do the heavy lifting of data collection. Continuous 24/7 monitoring leads to colossal data sets previously unimaginable using conventional techniques. Storing, accessing, and processing this quantity of information presents an (as yet) unsolved healthcare data challenge.
Furthermore, sifting through the vast amounts of data collected every minute to identify what is essential and relevant is a considerable challenge. Distinguishing between valuable information and unnecessary details remains a persistent issue. However, advancements in machine learning offer a promising solution, helping to identify patterns in the noise.
2. Data Privacy Concerns
DCTs, by their nature, involve the collection of sensitive patient data remotely. Transmitting, collecting, and storing this data securely is an immense problem.
Already, the pharmaceutical industry finds itself beset by cybercriminals. In the UK, a report by OCISIA (in collaboration with BAE Systems Detica) found that the pharmaceutical and biotech industry was the hardest hit by cybercrime, losing £9.2 billion in intellectual property2.
Often, this information isn’t released – the cybercriminal threatens to remove the data from a clinical trial database to blackmail the organization. Companies usually capitulate – paying the extortion fee is better than facing a lengthy legal battle.
In one case, hackers sent a UK medical firm files of former patients alongside the ransom demand3. The group responsible, Maze, conducted the attack at the height of the pandemic.
3. Data Integrity and Quality
From health wearables to patient-reported outcomes, DCTs rely on a combination of data sources. Ensuring consistent, accurate, and high-quality data is a top concern for decentralized clinical trials.
Without trained investigators to verify its authenticity and correctness, data errors can undermine a clinical trial’s results.
Data integrity in clinical trials is critical to establishing the efficacy and safety of treatments. Compromising in this area could lead to misguided conclusions and significant patient risks.
4. Standardizing Data Collection
Unlike traditional clinical trials, where standard protocols and equipment were easily enforced, DCTs often involve a selection of different devices and methodologies. Managing this variability and standardizing data collection is a fundamental hurdle for the uptake of DCTs. Pharmaceutical companies, contract research organizations, and the relevant authorities have only begun considering the problem.
For instance, heart rate monitored by one wearable device may use a different algorithm or sampling frequency than another. These differences can make direct comparisons or aggregations of results tricky, if not downright misleading.
Moreover, as participants increasingly come from diverse geographic locations, environmental and contextual variables become increasingly challenging to control. For instance, walking five miles in 70°F heat in downtown Chicago differs significantly from a 100°F hike in the Colorado Rockies.
5. Regulatory Compliance
Decentralized clinical trials are a frontier in medical research – as such, the regulatory framework is still being established. Hangovers from the centralized era persist illogically in trials with little relevance to ten years ago.
For starters, DCTs allow trials to be more global, spanning multiple jurisdictions, each with its own regulatory environment. Take pharmacovigilance – reporting a SUSAR (Suspected Unexpected Adverse Reaction) can differ considerably from one country to another. And with more data being collected, we can expect more SUSARs to be identified4. Are pharmaceutical companies and contract research organizations ready for this deluge of reporting?
Furthermore, complex data laws, like GDPR or CPRA, can sometimes contradict each other, making collecting participant data a mind-boggling tangle of legalities and collection systems.
Solving DCT’s Healthcare Data Challenges
Some of the data challenges facing DCTs will take global collaboration. Lobbying from big pharma will, hopefully, standardize some data laws and reporting systems, ensuring they can adapt to handle the data volume.
One promising solution to cut through these labyrinthine data challenges is a centralized data platform tailored for DCTs. Imagine a single, unified system that seamlessly collects, aggregates, and analyzes data from various sources, regardless of the location of origin.
Such a platform would offer:
- Unified Data Collection: Standardizing input from diverse data sources, from wearable tech to patient self-reports, ensuring data is collected in a universally compatible format and stored safely on a clinical trial database.
- Enhanced Data Security: Leveraging state-of-the-art encryption techniques and multi-layered security protocols, the platform would ensure patient data remains confidential, minimizing vulnerabilities to cyber threats.
- Advanced Analytics: The platform could employ AI and machine learning algorithms to sift through the vast datasets, detecting anomalies, ensuring data quality, and even potentially predicting adverse events before they manifest.
- Regulatory Compliance Integration: Keeping updated with the evolving regulatory landscape, this platform would have built-in features that ensure compliance, from patient consent management to reporting protocols across different jurisdictions.
- Scalability and Flexibility: Designed to evolve with the times, such a platform can be updated to accommodate emerging devices, new data sources, or changing regulations without overhauling the entire system.
Closing Thoughts
Data challenges or not, decentralized clinical trials are here to stay. More affordable, efficient, and convenient than their predecessors, we can expect their continued rollout. However, developing a comprehensive data platform would be a significant piece of the puzzle.
Introducing CDConnect™ – a centralized data platform explicitly created for decentralized trials.
From rapid device authentication to in-depth, customizable dashboards, our platform streamlines the entire research process. Harness real-time data insights, compare participants seamlessly, and uphold the highest standards of confidentiality.
Dr. Anat Ben-Shlomo, a distinguished endocrinologist at a top hospital in Los Angeles, routinely utilizes wearables in her clinical research. She stresses the importance of having a robust, user-friendly, and reliable tool for conducting high-quality health wearable-based decentralized research. In a recent discussion, she highlighted how CDConnect™ effectively tackles numerous challenges associated with decentralized clinical trials, particularly its capability to handle vast volumes of data and extract the most significant information.
Check out CDConnect™ today and see the difference for yourself!
Sources:
- https://go.oracle.com/LP=103091?elqCampaignId=257896&src1=:ex:bad::::&SC=:ex:bad::::&pcode=BUMK200701P00094
- https://www.pharmaceutical-technology.com/features/featurecybercrime-pharmaceutical-industry-biotech/
- https://www.computerweekly.com/news/252480425/Cyber-gangsters-hit-UK-medical-research-lorganisation-poised-for-work-on-Coronavirus
- Vayena E, Blasimme A, Sugarman J. Decentralized clinical trials: ethical opportunities and challenges. The Lancet Digital Health. 2023 Apr 25.
