Four ways a holistic ecosystem for clinical trials can help boost ROI

This piece originally appeared on Clinical Leader.

Clinical trials are complex and logistically cumbersome, so it’s easy to assume that the tasks and eClinical platforms supporting them must be equally challenging to manage. In fact, today’s solutions are leaner, modernized, and more user-friendly than the workhorses of the past. When companies are overly focused on one specific use case, they may assume that the tech supporting the use case must also be custom-built and costly.

That’s neither a necessary nor efficient way of deploying clinical trial solutions. To get the most out of these solutions, pharmaceutical and biotech companies should rethink their approach to clinical trial technology – shifting from a mindset of custom, siloed solutions to a broader, more holistic ecosystem of solutions that have been battle-tested across a variety of clinical trials, allowing them to be deployed faster, at a lower cost than bespoke platforms, and more able to boost ROI.

Partner integration

It’s a common assumption that one eClinical solutions provider can or should be able to meet a study’s every need, including custom-made capabilities. But no technology provider can specialize in every conceivable aspect of complex trials. In reality, providers need to focus on their core capabilities, and then work with multiple partners to efficiently cover every clinical trial need. When a provider has spent years honing their expertise in a given area, they are the best option for that specific need. After all, you wouldn’t call a plumber to fix an electrical issue in your home. An intelligently designed, holistic ecosystem for studies allows for a wider degree of choice in selecting expert providers to support your trials.

This integration is possible when the core system is built to handle a variety of solution providers and can adapt to the changing needs of the study or be modified for future studies. For example, a sponsor might need X and Y partners for one study, but for the next, they need Y and Z. If the core platform is flexible, it can be fitted to the next study without starting from scratch with each new project. When adaptability is built into the system, using best-in-class providers for different study aspects becomes the norm. Just as a general contractor coordinates plumbers, electricians, and other experts for a home remodel, the core system collaborates with specialists whose proficiency adds value to the study.

An integrated ecosystem also saves build time and money for studies because it allows providers to leverage their experience to create solutions more efficiently. When sponsors rely on a single provider, developing new, bespoke solutions adds time and labor hours. But how can sponsors procure these specialists? The answer is to look to their current partners for recommendations. If providers are empowered to build partnerships, that gives everyone the opportunity to leverage best-in-class, end-to-end solutions that exist within the same ecosystem.

Unfortunately, examples abound of companies who expect a single provider to reverse engineer solutions rather than relying on numerous specialists with the experience, depth, and breadth of prior studies. In those cases, time and money that could otherwise be used for further research end up being wasted.

To avoid this risk, when evaluating technology solutions for modern clinical research, it’s critical to think about the ecosystem needed and start with a proven, flexible core that supports solutions that will deliver optimized trial outcomes.

Streamlining DCTs and hybrid trials with eConsent

Consent is the first touchpoint with a study participant who may be in a trial for months or years. An eConsent solution that creates a positive user experience and continues to provide educational support throughout the trial increases participation and retention.

This is particularly critical for remote participation in DCTs and hybrid trials. Participants can learn about the protocol remotely and access educational tools, such as video or audio tutorials, interactive quizzes, and other resources in their native language, which they can refer to later as the trial progresses. When a protocol changes, the eConsent platform can further educate participants to keep them informed and engaged.

eConsent is a powerful tool that shapes participants’ perceptions of the trial and creates a framework for engaging them and ensuring compliance throughout the entire trial experience. Successful trials depend on engaged participants; eConsent provides that critical entry point and continuing engagement across the trial. Unlike some solutions on the market where eConsent requires integration, the Zelta platform includes a native eConsent capability (not integration) that makes the design and build process more efficient so that getting a trial up and running becomes seamless.

Whether the trial is on-site or uses DCT elements, deploying eConsent to patients is as simple as using an app. As the study progresses, Zelta updates data from its built-in eConsent in real time, allowing adaptation without retooling if the study’s protocol changes or further consent is needed. However, a sponsor is not restricted to the native Zelta offering. If a sponsor chooses another eConsent provider or leverages the site’s solution, Zelta’s platform can seamlessly integrate participant data into its core system and flow data in near real-time.

Diverse and inclusive trials are possible almost anywhere in the world when the right technology is partnered with the right study execution. eConsent is a powerful tool in the toolbox to reach subjects for clinical research and for executing successful DCTs and hybrid trials. It also delivers improved outcomes in patient accessibility, retention, and overall positive user experiences.

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Eliminating silos

Twenty years ago, when the first-gen systems were launched, clinical trial solutions were segmented into separate systems, and each system involved dedicated roles and workflows. But as trials have become more complex, this segmented approach has resulted in silos and, consequently, inefficiency and increased costs, both in resource and spending. Legacy systems requiring outdated procedures aren’t translating well to modern clinical trials.

Clinical trial workflows can only do so much when they’re constrained in silos. If we apply data silos to a machine learning scenario, we would need to start with the principle that your ML use case is only as good as the data set being used by the algorithm. If that data set is limited to just one study, then the algorithm will treat that one study as if it exists in a vacuum. That's a narrow set of inputs that will result in a narrow, possibly inaccurate set of outputs that could be missing crucial information from other sources (e.g., outside research). The same is true if the data source is too broad and not curated, increasing the risk of erroneous answers and erroneous data correlations. Not only does that affect the results, but it could also lead to duplicate work across the company because not all of the right data and analysis were taken into account from the start.

Like any other tools, machine learning and AI are meant to help save time and make work more efficient – not by reinventing the wheel, but by building on the knowledge of others. Likewise, eClinical platforms that put studies and data into silos are inevitably limited in their scope, limited in their data sets, and burdensome to operate. That narrow use can lead to unintended bias, inefficiency, and unnecessary spending.

Eliminating technology and data silos opens up more opportunities to optimize processes, roles, and responsibilities and for more effective applications of solutions like advanced automation and machine learning. Well-curated, real-time access to data within and across a clinical trial portfolio is critical to improved decision-making and insights.

Applying advanced automation and machine learning

As companies incorporate more modern technology solutions for clinical research, there is a greater opportunity for leveraging advanced automation and machine learning to drive improved efficiency and outcomes. As data silos are reduced and eliminated, the access to, and ability to curate and leverage, broader sets of data improves the ability to apply machine learning in new and exciting ways. In addition, the elimination of technology silos and reevaluating people and processes increases the opportunity to use advanced automations and visualizations to deliver improved insights and streamlined workflows.

It's important to start with well-thought-out and structured use cases that are critical of existing ways of working. When advanced automations are applied to inefficient and broken processes, the return on investment will be lacking and the improved outcomes are put at risk. In addition, machine learning with too narrow or too broad of a use case can cost a significant amount of development time with limited ROI.

Driving the best outcomes starts with the ability to clearly articulate the desired, measurable outcome and then define what evolution of the solution is needed and expected to deliver those outcomes. Too often, these solutions are not well defined upfront and thus not well understood. It’s hard to measure ROI if it’s unclear what outcome is expected, how to measure success, and when the outcomes should begin to be realized.

Companies need seamless, fully integrated solutions to streamline their studies within and across the portfolio and apply advanced solutions to use cases that will deliver measurable outcomes. And this requires rethinking technology, processes, and people with a critical eye toward silos that are leading to suboptimal processes and associated roles and responsibilities. Updating technology and implementing advanced solutions without also rethinking processes and people will continue to lock companies into outdated methods and missed opportunities for optimization.

There is a real opportunity for these advanced solutions to drive tangible, measurable change within studies and across portfolios. Well-thought-out and well-executed solutions enhance human capabilities and experiences. Seamlessly integrating these solutions into the workflow and experience will help deliver these real, concrete outcomes.

Creating real ROI

Streamlined eClinical solutions can increase ROI by creating more efficient ways of building, running, and managing change within clinical research. It’s important to acknowledge that ROI can be difficult to measure for clinical trials. To calculate ROI, companies must clearly define success measures, understand responsibilities, implement process changes, and evaluate the results based on these metrics. When companies increase efficiency, they accelerate speed-to-market timelines and eliminate labor-heavy tasks that reduce workload burden, free staff to focus on higher-value tasks, and reduce the need for ever-growing pools of resources as the portfolio grows and research becomes more complex. Given that clinical trials are already so complex and logistically cumbersome, streamlining them through modern technology solutions, brought together with an intelligent ecosystem approach, can lead to measurable outcomes and real ROI.

Zelta is an eClinical solution that can help you streamline complexity in your clinical trials and drive real ROI. Book a demo to see for yourself.

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