How Are Digitized Protocols Accelerating Clinical Research Processes and What’s Next?

Protocols drive every clinical study, guiding research teams from early inception through planning and into the trial’s execution. Clinical trial protocols are also very complex, with detailed schedules of assessments, inclusion/exclusion criteria and scientific reasoning all captured into a single written document.

With so many essential moving parts, it’s no surprise that it’s complex to manage protocols. But what if there was a way to streamline this process, making protocols more dynamic and accessible?

That’s where digitization and artificial intelligence (AI) could step in. In this Xtalks Spotlight, we spoke with Matthew Herod, Director of Enterprise Data Strategy at the PPD Clinical Research Business of Thermo Fisher Scientific, to explore the impact of digitized protocols on clinical research and what lies ahead.

In his role, Matthew champions the drive for rapid adoption of AI in clinical research and provides expertise for applying technology innovations to the clinical product development lifecycle.

Transforming Efficiency and Streamlining Operations

As Matthew explains, protocols impact every aspect of a trial, from initial feasibility assessments to setting up systems like electronic data capture (EDC) and clinical trial management systems (CTMS). These systems, essential for tasks such as scheduling assessments and tracking patient progress, rely on data derived from the protocol.

With conventional protocols, creating the various derivative documents, as Matthew describes them, such as statistical analysis plans and data management plans, can be labor-intensive. Digitized protocols, however, allow information to be quickly and precisely extracted, reducing the manual back-and-forth that often slows down the process.

Matthew outlined three use cases where digitized protocols can lead to greater efficiency:

• Document generation: Digitized protocols simplify the generation of essential documents, reducing the administrative burden associated with trial setup.
• System setup: With digital protocols, components like EDC and CTMS can automatically incorporate protocol information, allowing for faster system configuration.
• Future trial optimization: By digitizing protocols, researchers could analyze data from past trials, identify trends and refine processes for future studies.

According to Matthew, these efficiencies can result in substantial savings in time. “You can start to see how these individual time savings made possible by protocol digitization can start to really cut out a lot of that administrative white space and add up to actual days or weeks being shaved off a trial’s timeline,” he explained.

The potential to compress trial timelines is a game changer, particularly when conducting trials in fast-paced therapeutic areas or those involving complex regulatory landscapes.

Upcoming Xtalks Webinar: Optimizing Clinical Trial Protocols: How Digitized Protocols are Accelerating Clinical Research

Live and On-Demand: Monday, November 4, 2024, at 12pm EST (9am PST)

Register for this free webinar to gain insights into protocol digitization, understand how it can drive efficiencies and discover how it can elevate clinical trials.

Real-World Examples of Digitized Protocol Success

Matthew shared several examples of how digitized protocols are being applied in clinical research. One example is the use of digital systems that standardize data models across various trial components, like scheduling assessments. These standardized protocols can then be used by downstream systems, like EDC platforms and laboratory systems, streamlining data flow.

A specific use case he mentioned was in the field of medical writing, where information is often pulled from unstructured protocol documents. When these protocols are digitized, relevant data points—like inclusion criteria and potential risks—can be automatically extracted, speeding up document drafting processes. While human expertise is still required, digitized protocols enhance efficiency, making it easier to draft high-quality documents quickly.

“It does make the humans doing the work much more efficient, and that’s where you start seeing these time savings start to add up,” Matthew explained.

The Role of AI in Enhancing Digitized Protocols

Clinical protocols are often lengthy, complex documents—traditionally delivered as PDFs—that contain detailed information. Generative AI can help maximize the value of digitized protocols. Unlike structured data systems, generative AI can interpret and interact with protocol content in a flexible manner, substantially reducing the need for manual data preparation.

As Matthew explained, “Large language models, which are part of artificial intelligence, can understand the text of a protocol itself. They can read what’s in there without all that upfront data (preparation) and let you start chatting with it.”

Matthew highlighted the use of retrieval-augmented generation (RAG), a technology that enhances AI’s ability to interact with specific documents. In this setup, the AI references a focused set of documents (e.g., protocols) to generate outputs, allowing researchers to interact with protocol information seamlessly. This approach allows users to access protocol data quickly and efficiently, enabling faster decision-making and document creation.

With AI, digitized protocols become more than static documents—they transform into interactive tools, facilitating quick access to information.

Overcoming Challenges in Digitizing Protocols

While the advantages are clear, transitioning to digitized protocols presents challenges. One of the main obstacles lies in the complexity of protocol documents.

“The ongoing challenge that technology can never eliminate is the need for proper governance and quality controls.”

 

— Matthew Herod

Take, for example, the schedule of assessments—a single table might contain dozens of footnotes and conditional statements. These notes often require detailed cross-referencing with other parts of the protocol, a task that can strain even the most sophisticated AI tools. But as AI continues to evolve, it can become better equipped to handle such details, reducing the need for manual input and making digitized protocols increasingly feasible.

However, Matthew emphasizes that even with sophisticated AI tools, human oversight is necessary to verify outputs, ensure accuracy and maintain data integrity. This governance creates a trusted environment, allowing researchers to confidently use digitized protocols while maintaining high-quality standards.

What’s Next for Protocol Digitization?

Looking to the future, Matthew outlined several key areas where digitized protocols are expected to have the most impact. In the short term, digitized protocols will continue to streamline system setup and document generation, enhancing trial efficiency. However, Matthew is especially excited about how digitized protocols could shape future trials.

As more protocols are digitized, clinical researchers can use these digital repositories for advanced analysis and optimization. Specialized AI systems trained on historical protocol data may reveal new patterns and trends, enabling researchers to anticipate challenges and design more effective trials.

“You can start to imagine using these repositories to identify new areas of risk or optimizations that we wouldn’t otherwise see,” Matthew explained.

In an industry where speed, accuracy and adaptability are vital, digitized protocols offer a glance into a future where clinical trials are faster, and more efficient than ever before.

As Matthew suggests, it’s an exciting time for the industry, with advancements on the horizon that promise to reshape the way we approach clinical trials and ultimately improve patient outcomes worldwide.

This article was created in collaboration with the sponsoring company and the Xtalks editorial team.