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An adaptive clinical trial looks at a specific measurement (patient outcomes, side effects, etc.) during the clinical trial. Based on interim data on the measurement and pre-planned decision rules, the parameters of the protocol may be modified during the trial. The parameters being modified can be anything from dosage to sample size, to patient demographic criteria and they typically enable research teams to shorten trial times and improve the likelihood and speed at which a treatment effect is noted.

The FDA issued draft guidance on adaptive trial design in 2010. In October 2018, this draft guidance was replaced with a new draft that better represented the agency’s current thinking on adaptive designs. Since that time, the industry has continued to witness a rise in the number of adaptive clinical trials being conducted.

Adaptive designs represent a new level of complexity in clinical trials. Simultaneously, they demand a new level of flexibility that is required throughout study conduct. Mid-study modifications are typically based on rather complex computational algorithms. As designed, the changes must be implemented quickly, efficiently and accurately. Response adaptive randomization (RAR) or a sample size reassessment (SSR) are commonly used adaptive designs that require the research team to be able to assess data and formally implement mid-study changes. This new requirement has heightened the tug of war between the need to support greater trial complexity and the need for simultaneously greater user flexibility.

As clinical trial technology vendors try to keep pace with the evolving industry requirements, one thing is for certain: flexibility is key. Traditionally, clinical technologies treated support for mid-study changes as an afterthought, something that was a “nice-to-have” rather than a formal requirement. In modern adaptive trials today, a user must have the ability to identify specific data, evaluate it in real-time and take action on it immediately. The time required to respond impacts the overall trial time, cost and efficiency.

Unified platforms that present trial data in more meaningful ways and enable greater collaboration between team members help to make this possible. When designed with native modules, it enables data entered in one place to be immediately available in other areas of the platform. The combination of actionable real-time data and a common (and simple) user interface helps clinical trial teams to assess and respond to data more quickly without negatively impacting accuracy. Flexibility has to be built into the solution to enable clinical research teams to address the planned changes that are built into an adaptive design.

Adaptive trials create many new technology requirements. They require different levels of access to interim data to ensure trial integrity. From a technology perspective, this translates to role-based permissions that are designed to protect data throughout the clinical trial lifecycle. Adaptive trials may also require more complex drug supply and inventory management as changing demand across sites becomes more difficult to predict. They may also increase the need for a customized randomization process.

As clinical trial teams continue to design and implement adaptive trials, additional opportunities to apply innovative technologies will become apparent. As the industry gains experience, the flexibility of technology used in adaptive clinical trials will continue to grow and expectations for additional flexibility will likely rise. The most sophisticated and experienced users often contribute the most to shaping new tools and technologies. This area will be no exception.

The Mednet team partners with clients across the industry to understand evolving trial design requirements. Mednet’s all-in-one platform is designed to meet the demands of adaptive designs, and our clients are positioned to meet today’s requirements and those of tomorrow. Contact us to learn more about iMednet and schedule a demonstration.