When Speed Isn’t Enough: Designing Clinical Trials That Don’t Leave People Behind

Clinical trials are moving faster than ever. AI is helping us accelerate recruitment, automate protocol designs, identify the most promising sites, and monitor incoming data with impressive efficiency. For sponsors and research teams, the pace of progress is both real and welcome.

But in this transformation of how trials are designed and implemented, we must pause to ask:

Are we just moving faster - or are we actually moving better?

As someone working at the intersection of technology, research, and public health, I believe this is a critical question one we must address as we integrate AI more deeply into the trial ecosystem.

There’s no denying that AI has been a game changer for many operational aspects of clinical research. It brings tremendous value in:

• Matching patients to trials using real-world data.

• Automating site feasibility, selection, and planning.

• Enhancing monitoring through real-time alerts and predictive analytics.

For sponsors and CROs, this can mean shorter timelines, lower costs, and better alignment with regulatory expectations.That’s worth celebrating. But operational speed must be matched by thoughtful design, especially when people are at the heart of the process.

Risk of Gaps Beneath the Gains

At the same time, AI introduces new risks:

• Digital consent platforms that assume literacy and smartphone access, leaving behind those less tech-savvy.

• Recruitment engines trained on biased datasets, underrepresenting underserved or rural populations.

• Monitoring systems that catch protocol deviations but overlook participant distress or dropout risk.

Without intentional design, AI can deepen existing inequities - even while giving the illusion of greater efficiency.

Automation with Empathy

This is a critical design challenge - and a timely opportunity.

We don’t need to choose between speed and quality. We must design trials that move faster while ‘honoring participant agency, context, and comprehension’.

AI needs to be leveraged to:

• Tailor the consent process dynamically, based on a participant’s language, literacy level, and preferred communication style.

• Create real-time feedback loops to check comprehension and emotional readiness at each stage of participation.

• Help sponsors and research teams anticipate and address barriers to inclusion -not at the recruitment stage, but earlier, during protocol development.

At DSDC, we’ve been exploring some of these possibilities - designing tech that’s not just efficient, but deeply participatory.

The Next Generation of Trials

The goal isn’t just automation. It’s automation with empathy. This is where sponsors, CROs, and research teams have a unique opportunity - to shape the next generation of clinical trials that are not only smarter and faster, but also fairer, more responsive, and deeply human.