The Challenge and Opportunity Presented by Clinical Trial Regulation EU 536/2014

Article

New regulations offer opportunity for simplification in strategic planning.

Elvin Thalund

Elvin Thalund

Since 2007, the European Union (EU) has seen a decline in the number of clinical trials and clinical trial applications. In an effort to reverse this trend, the EU has enacted a new clinical trial regulation—EU 536/2014, that greatly simplifies and enforces one clinical trial application process, to foster greater innovation and more trial applications.

While it presents a great opportunity to expand the clinical trial landscape, the new regulation also represents a huge shift in study planning and preparation—a shift that could lead to excessive delays and millions in lost revenue if not managed accordingly. Previously, each EU country had their own laws for clinical trial regulation. This meant more than 100 regulatory and ethical submissions across 30 countries (27 EU members and 3 conforming states) involved in setting up a study, which created obvious issues and bottlenecks. The new regulation greatly streamlines this process, but at the expense of content and timing flexibility. Now, any missing content about any investigative site in the submission could delay the trial enrollment by months.

To combat these challenges and realize the opportunity EU 536/2014 offers, sponsors and CROs alike need to rethink their approach to clinical trials.

Timing is crucial

January 2022 kicked off a three-year transition period in which the clinical trial directive, the existing process for handling submissions, will still apply for any studies underway. Companies will have a one-year grace period, during which initial clinical trial applications can be submitted under the new regulatory infrastructure but do not have to be. However, beginning in January 2023, all new submissions must be submitted under the new regulator infrastructure, and all ongoing studies have until January 2025 to either complete or convert to the new regulation.

Some organizations will no doubt want to submit under the new regulation right away to experience the system, likely testing it out on early-stage trials. Given the typical 6 to 8 months needed to ready a study, mid-2022 (now!) is the crucial deadline for all companies to prepare for the new regulation and the January 2023 deadline.

Overall, this new regulation establishes a thoughtful process from the very beginning and ensures high quality of and a more predictable timeline for studies. Until now, patient enrollment tasks could be planned and managed independently with minimal coordination between study, country, and site project managers. The focus has been on the first activity (e.g., first country and site approved) knowing additional activities would follow. This has allowed for decentralized planning and management, with only oversight for global and EMEA project managers.

With EU536/2014 all of the planning has to be done as one phase, and there are only two key parts to the submission process—Part I (study content) with the reporting country and Part II (country and site content) with the member states concerned. It has gone from 100+ submissions to just one, however, Part I and II are now fixed and aligned. This gives organizations clear timelines, but this alignment also means that the study startup is much less agile, as new sites can only be added four times a year. This strictly timed, single submission process is a paradigm shift that will require a great deal more up-front planning and coordination.

The role of machine learning in driving the process

As organizations try to manage this paradigm shift, having siloed systems and disparate data will be impossible given the need for upfront coordinated planning. To be successful, systems with underlying data structures must be coded, normalized, and de-identifiable. This will enable the application of advanced analytics and machine learning, which in turn, produces early, fast, and accurate insights for project management for submission.

Automating trial builds can minimize obstacles like protocol quality, human errors, and other issues that ultimately delay getting drugs/therapies to market. For example, using machine learning, systems can review all available historical data quickly and efficiently, uncovering all the problems created from prior protocol changes to fully optimize protocol design and building—ensuring steps aren’t missed and past problems aren’t repeated.

The new regulations provide an immense opportunity for organizations to be much more strategic with their planning. First, the thoughtful move to upfront planning will enable organizations to take a streamlined and holistic view of the planning process. Second, machine learning will give scientific insight into which indicators have the most impact on these models, so organizations can focus on those indicators to refine their models and learn from these insights. Ultimately, these changes can drive organizational and behavioral changes, such as earlier accurate predictions and less reliance on later subjective decisions, to optimize business processes. This can allow organizations to continuously improve and have a direct impact on timelines and associated costs of clinical trials. Now is the time to move ahead and embrace the opportunity EU536/2014 brings to clinical trials.

Elvin Thalund, director, industry strategy, Oracle Health Sciences

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