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Decentralized clinical trials (DCTs) have evolved from a future concept to a present-day necessity. As protocols become more complex, competition for funding increases, and recruitment challenges persist, traditional site-centric models often fail to keep pace.

While clinical research professionals typically understand what has to be submitted to an Institutional Review Board (IRB), the board’s decision-making processes can seem like a ‘black box.’ A mock IRB meeting can be very illuminating, illustrating how regulatory mandates and ethical principles are reconciled with the realities of current clinical research.

Next year is shaping up to be an inflection point in electronic clinical (eClinical) trial technology. As sites, sponsors, contract research organizations, and patients continue to navigate growing protocol complexity and mounting operational pressure, the industry will continue accelerating in 2026 toward solutions that streamline workflows, reduce technological fragmentation, and make research more accessible for the people doing the daily work.

Corporate leaders who make “One Size Fits All” their go-to strategy may find that it’s only convenient right up until blowback arising from its application to real-world situations proves otherwise. This holds true for the onboarding experience in clinical research settings—no “one size” approach to it can possibly cover the organizational and individual needs for every incoming member of the clinical trials team.

With seemingly unavoidable and unceasing headlines such as “FDA Rolls Out Agentic AI for Staffers,” “How AI is Transforming Clinical Trials,” and “New AI System Could Accelerate Clinical Research” hitting the news feeds every day, it’s no wonder some observers from the trenches of the drug and device development industry want to separate the honest hope from the breathless hype when it comes to how artificial intelligence (AI) is being applied to their everyday working lives.