Over the past few months, I’ve had the pleasure of attending the Clinical Trials Europe, CNS Summit, and SCDM conferences, listening to excellent speakers and catching up and collaborating with friends and colleagues. At the end of this busy conference season, I’m feeling that 2023 has been an important transition year in clinical trials. So what have I learned, what do I mean by ‘transition’, and is that forward, backwards, or even sideways?

A transition back towards a patient- and solution-first approach

The pandemic drove interest in technology-first ways to continue to deliver studies through decentralized models. Now that we’re in a post-Covid new-normal, I think we’re seeing a reversion or transition back to more standard site-based studies, with selective use of technology to support and empower.  Fortunately there’s increased acceptance of using digital approaches to enhance the trial experience. Equally important is a transition to trial-centric choices, not just technology-driven choices.

This, in my view, is welcome news. The focus first must be on the humans involved in trials – patients, nurses, CRAs, data managers. Technology should support the people involved, and should rarely take center stage.

A transition towards more modern, flexible, integrated technology

While it doesn’t come first, technology is certainly an increasingly important and essential foundation for how clinical trials are operated. Conference speakers highlighted the significant burden on sites imposed by an ever-growing ecosystem of systems. Some sites use upwards of 12 – 15 systems for each trial – meaning that there is an ever-present need to learn multiple technology solutions (or platforms) not to mention a plethora of passwords to remember.  This will only be exacerbated by the datapoint that suggests approximately 70% of trial data now comes from systems outside the EDC.

Another theme raised by sponsors is their frustration with the inability of older technology systems to adapt to their needs – particularly citing mid-study changes as being slow, cumbersome, and expensive to implement.

These understandable frustrations are driving a transition to review and select more modern technology systems – tools with flexibility designed-in and enabled with simpler integrations. This blog post by our Chief Product Officer, Julia Lakeland, expands more on the concept of a modern ePRO platform, addressing these themes.

A transition from AI experiment towards AI value

The clear topic-of-choice for all conferences was, unsurprisingly, AI. As the whole world has switched on to AI (even my Mum is talking about it), the life sciences industry is following suit.

At CNS Summit, there were interesting sessions from Google, Microsoft, and others on AI use cases. Given uMotif’s increasing work powering CNS studies, I’m particularly interested in how AI could help with scoring and quality control of assessments like the MADRS or PHQ-9. These and other use cases could help improve speed and quality, but first they will need to pass stringent quality and validation processes before being ‘match-ready.’

The need for validation and ongoing concerns about the ‘black box’ nature of AI algorithms means that adoption will, quite rightly, take time. So I liked the suggestion from Microsoft’s Junaid Bajwa to start using AI to automate less risky, more mundane tasks in clinical trials, such as:

• Automating medical coding. AI can speed up how conditions are coded, using humans to provide a quality check, rather than doing the laborious first pass. CluePoints is doing some exciting work in this area.
• Speeding up the process of protocol feasibility, study design and site selection. AI can do what humans can’t in looking across millions of data points from ClinicalTrials.gov, publications, and other public sources to more quickly design studies, model trial recruitment and outreach to relevant sites. A company I’ve personally helped – Neuroute  – is launching a ground-breaking software-as-a-service for sponsors to quickly model and execute on their studies using generative AI.

Now, let’s turn our gaze to 2024?  Where might we be going? I am hopeful that the growing focus on patient and human-centered approaches will continue to be a central theme. Making trials more engaging for participants and faster for sponsors benefits all of us by accelerating innovation and the delivery of life-changing new therapies to market.