Data Standards Optimize Patient-Centric Clinical Trials
Richard Young
Veeva Systems

ne fundamental challenge facing life scientists is establishing standards for clinical data sharing that enable decentralized or digital trials. During the 30-plus years that the Clinical Data Interchange Standards Consortium (CDISC) has been in place, the ways that the biotechnology and pharmaceutical industries think about data have changed significantly.

Today, standards aren’t seen as intellectual property that must be protected but as a strategic tool that should be open, widely available, and shared. This change in mindset can help industry align on one set of clinical data standards to increase efficiency for study stakeholders and regulators who would receive inspection-ready data faster.

Industry continues to rely on tools like ePRO (electronic patient-reported outcomes) and eCOA (electronic clinical outcome assessments), but we speak about them now as if these applications were brand-new for decentralized trials. The reality is, they don’t fall under that banner because they are being used as siloed applications. We may be using eConsent, but patients still need to come into sites to physically initiate the consent process. This doesn’t qualify as decentralized practice. Meanwhile, most trial protocols have not reached a point where patients have the flexibility to participate based on their preferences, which can change day by day. We have so many applications capturing patient data in so many different ways, but we need simple approaches to integrate and review that data.

Clinical leaders who have experienced the limitations of new technologies initially designed to make studies more patient-centric have also learned that adding more technology to an already complex landscape won’t make the patient journey any easier if it adds to the burden of participating in research. Technology overload can slow down site operations and leave less (not more) time to engage with patients. Embrace modern data management standards and establish processes that bring together different data sources for real-time insights to chart your path toward patient-centric trials.

Critical and Evolving Role of Standards

Industry will advance patient-centric trials by establishing widely accepted standards, working together to leverage real-world data, and building better connections with patients. Widely accepted standards for data transfer would help ensure that data is shared in the correct format. To get there, we’ll need to prioritize two areas designed for two different purposes: clinical data (under CDISC) and healthcare data (under Health Level Seven or HL 7).

Connecting these diverse data sources, types, and aggregations is an ongoing industry effort. As sponsors and researchers make progress toward patient-driven data collection, neither of these options on their own is a practical fit. Trial participants will generate more of their own data, collected through other personal wearables completely unrelated to any clinical trial, which possibly creates an entirely new data category. This will present increased complexity in trials unless we establish innovative approaches first.

Our opportunity for genuine innovation is to develop ways to generate, collate, and distribute data between point solutions that address a specific issue but don’t connect to other systems or otherwise provide seamless connections between researchers and patients. Industry will only be able to apply true scientific precision to clinical data after establishing these connections. If done right, the industry will be able to leverage advanced tools such as artificial intelligence (AI) to clean and format clinical data according to established data standards. This introduces automation and speed, freeing up time so data managers can focus on analysis.

Developing modern standards for clinical trial data sharing will require tremendous effort across stakeholders. Although this work is in its infancy, thought-provoking questions around ethics are surfacing that must be addressed. For example, healthcare providers are proposing giving every patient a unique record ID. This tokenization would enable quicker data sharing but could cause privacy and security concerns.

Another case is publicly publishing final trial data. Sharing study outcomes this way can help physicians better understand the risks and benefits of products and increase society’s trust in medicines and treatments. But even with digital tools that make it easier to share trial outcomes more broadly, some regulations around privacy (such as EU GDPR) haven’t changed to incorporate this new reality where trial data can be publicly shared. Industry is making progress and moving this topic forward, addressing the need to share information efficiently.

Managing the Data Explosion

Today’s clinical trial stakeholders manage far more data from diverse sources than in the past. Most trials today have between 10 and 30 different data sources and ideally should have data ingested in real-time. Most companies must aggregate and clean these sources separately and then combine them into a clinical database, a lengthy and resource-intensive process.
illustration managing the growth in data sources for clinical trials
Managing the growth in data sources for clinical trials is critical to advancing toward more patient-centric trials. (Source: Veeva Systems)
A data workbench platform solution can help aggregate and clean data and connect it with other study data held in a company’s clinical data management system (CDMS). This is critical work since every data point collected can potentially reveal a finding of interest.

These solutions align with data management approaches such as advanced analytics and time-in-motion analyses where a particular process is evaluated for efficiency. We should expect more advancements and collaboration between technology providers specializing in clinical data management and companies applying analytics to that data. Ingestion and aggregation of data would be done in a clinical workbench, storing data in one place and making it accessible to the CDMS. At the same time, other efforts could consider the cost-benefit of increasing the frequency of biomarker analysis or using AI to test the soundness of a trial model or process.

For example, one solution uses AI algorithms to analyze and challenge not only trial results but also the processes and approaches used in the trial. Analyzing all the trial data—clinical, operational, metadata, and audit trail data—offers a complete picture of both the patient and the trial journey. This will allow industry to evaluate and phase out specific processes or jobs that prove unnecessary and replace them with more efficient approaches.

How to Establish Durable and Satisfying Connections with Patients and Sites

Industry sponsors are accelerating their use of digital tools as they design and execute more hybrid trials. Today’s question is whether applications like eConsent or eCOA will continue to grow because of the adoption of digital or decentralized trial strategies or because clinical leaders simply want access to real-time data. Using these technologies shouldn’t be confused with delivering and executing a proper digital strategy, which consists of connected processes and technologies across the clinical ecosystem.

It is important to remember that decentralization will push more of the daily trial processes away from a research site and into the patient’s home. This is not just about collecting greater volumes of data but also about transforming the core thinking behind data collection.

Progress has brought clinical research closer to the patient-centric ideal where participants have greater choice in how they participate in a study. As one example, a patient could provide consent from the comfort of home by downloading an application, seamlessly becoming part of the trial, and then choose whether to use at-home or remote monitoring or to travel to a clinic for an in-person visit on a daily basis.

Although this may not be feasible with MRI or other procedures that must be conducted on-site, the underlying vision is that patients will be in the driver’s seat to determine how much decentralization they prefer. Clinical study teams must accept this model before offering and delivering it to study participants.

It is critical for sponsors who are proactively evaluating digital technologies for clinical trials to consider that for each problem a new application seems to address, new challenges could be created. Think about the other stakeholders such as research sites, whose burden can increase when more technology or tools are deployed to them. When I meet with sponsors and industry partners, I advise them to “wear the hat of a patient or a site” before writing the protocol, because introducing a new technology at the final trial design stage is too late and inefficient.

Patient convenience is also critical for continued participant compliance and trial enrollment. Many of today’s digital patient-facing technologies still require patients to do too much work. These recommendations can help drive the development of digital tools that are a win for all trial stakeholders: patients, research sites, sponsors, and CROs.

Consider the interests of every stakeholder. What are the requirements and interests of each constituent group, and how are you delivering them? Are you adopting tools that solved a specific problem but presented unanticipated challenges? The ecosystem will function better if we can introduce less burden to a patient’s life and to research site staff. Establishing repeatable, viable, and defensible processes is essential for sponsors.

Determine the impact on each stakeholder and the overall cost. Consider how likely auditors are to accept the data, how patients will respond to a new approach, and how easily sites can execute it. Upfront and long-term costs must be measured to determine if a tool makes sense. If patients like the model, accept it, and comply with its requirements, they’ll be more likely to return for future trials.

Don’t burden sites with technology that turns them into a Help Desk. Unfortunately, some patient-focused applications add workload and slow down processes for clinical staff. Many research sites now report spending significantly more time with each patient to train them on how to use clinical applications like ePRO. Sponsors must think about the site burden of bringing on new technology and ensure that these tools strengthen the site’s engagement with patients. This doesn’t mean that the trial will require more in-person patient visits; instead, it means that patients can engage in the way they prefer.

Deliver one seamless experience for patients. A connected technology ecosystem allows site staff to easily access patient health and treatment records. Think about how people engage in the real world and provide a similar experience for participating in a trial. For example, integrate applications into the tools patients already use, like smartphones or Fitbits, to make them easier to use. Companies sometimes require patients to download multiple applications, which makes it harder (not easier) for patients to keep up. Could sponsors one day provide patients with a QR code that can complete registration and carry over patient details, automatically creating data flows into other processes—to connect everything at once instead of asking patients to navigate a 20-step checklist?

Build in a more holistic healthcare environment. A scorecard or dashboard approach can be extremely helpful for study participants because it provides an “at a glance” information summary. Patients with diabetes who are overweight could benefit from receiving a personalized message from their physician with a diagnostic on the amount of insulin taken, HbA1c lab results, and positive reinforcement to help them remain motivated in their care. This would also make patient-physician interactions a more seamless part of the trial, advancing toward a more holistic medical care approach. These types of improvements in how we work together are precisely the benefits that digital clinical trial technology should deliver.

Looking Ahead to Patient-Centric Digital Trials

Industry continues to explore how new digital tools can enable a more patient-centric and efficient trial. Adaptive trials will be a test for digital technologies because they change continuously in response to trial results, requiring a central control point and seamless data transfer. Another issue to monitor is how the sponsors and data providers will work together to make it easier to aggregate, ingest, and clean new data sources to supplement clinical trial data.

Broadly established data standards would streamline this process by ensuring that all parties are aligned in how data is formatted and submitted. This presents a significant opportunity for the life sciences: Delivering the right data in the right format at the right time can reveal insights or correlations much faster and accelerate clinical development, too.

Patient-focused decentralized trials have taken center stage in life sciences as technology providers and early adopters share initial experiences in an evolving space. It is essential to keep in mind that companies are at the early phases of digital clinical trial development, and more work and innovation lie ahead. These approaches are still formative and need more collaboration to make flexible patient-centered digital trials a reality.