Personalizing the Trial Experience for Diverse Populations


In this Applied Clinical Trials video interview, Julia Lakeland, Chief Product Officer, uMotif, discusses new technologies that can help personalize the clinical trial experience for diverse patient populations.

How can new technologies personalize the clinical trial experience for diverse patient populations, considering factors like age, access to resources, and cultural needs—while ensuring inclusivity and equitable access to participation?

Increasingly, regulators are requiring more diverse trials. You know, when you look at some of the statistics around who typically participates in a clinical trial, there is there's an imbalance there. So, we have to make sure as a as an industry that we are making clinical research and clinical trials open and accessible to everybody. And there's a whole host of financial barriers associated with trial inclusion. But actually, some of the more common reasons that patients cite around trial participation and dropout rates and the dropout rate in a trial is, is overwhelming, but they include things like you know, inconvenience time commitments, poor communication, a feeling of being underappreciated. And a lot of that, you know, you need to learn from that around how can we, how can we have a personal room so that we can appeal to different patient populations.

Patients are naturally experts in their disease journey. They live with this condition day in and day out and supporting digital health technologies. All of that certainly needs the way to improving diversity. But there are also some practical considerations not just from the technology side of things, but from an actual logistical side of things as well. So is the local infrastructure as you look at a global phase three trial, for example, and you're going to want it in multiple countries, multiple locations, you know, if you go down the route of a digital file with a remote visits and remote data capture, is the local infrastructure there to support that file.

There are practical considerations around the actual infrastructure, for example, in each country, but there are also very more specific things around the actual patient population to take into account. So, for example, font size, and various device controls the size of the screen. The if a wearable is being selected is the sensor is it determined that it is easy to use by that patient population has there been some kind of verification and validation study to ensure that we have that understanding that the sensor is suitable and is practical and is fit for purpose. And so, there is an awful lot to think about. And I think when I look at how we render a clinical outcome assessment where a patient reported outcomes to different patient populations, having the flexibility within the configuration of the app design, so that you can cater to the needs of each different, diverse patient group, that's really important. And you know, I've kind of touched on the, the size of the font, the colors, the contrast, but also the difference in language, you can't underestimate how important language and what a barrier that can be. And so, I think cross culturally, we simply need to understand a lot more than be more responsive to the different perceptions that the individuals have around clinical research and, and how they choose to interact with the technology. And make sure that that is therefore tailored towards their expectations, because it's their data that they are giving for research. And I think we need to be supporting that.

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