Embracing Risk-Based Approaches with Clinical Trial Oversight

In a recent video interview with Applied Clinical Trials, Rob Jones, product manager, TMF practice area, Pharmalex, discussed challenges in the trial master file (TMF) space, highlighting outdated regulations such as ICH E6(R3). When it comes to innovation and compliance in the space, he stressed the importance of a risk-based approach, focusing on critical records and leveraging artificial intelligence for big data analysis. Moving forward, Jones believes the TMF community's collaborative nature can be viewed as a strength in navigating regulatory changes and technological advancements.

ACT: What should leaders in the TMF space be focused on the most in navigating the increased demand for quality and compliance?

Jones: There is a quote that anyone who's ever listened to any of my talks or webinars or blogs or anything. I love this quote, and it's in ICH E8(R1), I've got it written down here. “Perfection in every aspect of activity is rarely achievable, or can only be achieved by use of resources that are out of proportion to the benefit obtained.” Sounds like a Taylor Swift lyric, but realistically, what it's saying is, in order to get perfection, you're going to have to put in far more effort than it's worth, so focus where the focus needs to be. Not all records in your TMF are equal. They're not. A protocol amendment changing the fundamental part of your study because of an endpoint is far more important than the routine chit chat that you have and meeting minutes you kicked out. There's more risk at a high enrolling site that's got 1,000 patients, than there are at another site that's got one, so focusing on where the risk is and really embracing this idea of a risk-based approach, I think that's where we need to focus on. That's where we can really get to this new demand for quality and compliance and being able to say the rest is good enough. It does exactly what we need it to do. It's fit for purpose. The other thing with risk, though, we always need to remember is, I've seen people in the past use risk-based as a way to justify doing less. I think the thing we need to remember is, risk goes both ways. There's some times where the risk drops, and you can say, “Brilliant. Don't need to do as much work as I was doing yesterday. All my metrics are green. I've got everything that I need to. I've just had a call with the rest of the study team. Everything's flying through. Brilliant.” There's other times, though, when you have a bad week and the number's aren’t looking great, and at those times, you have to do more work than you thought, but balancing that being available and being able to pivot where needed, that's really what the leaders in this space need to do. I think again, going back to the AI, this idea of there's people who can really have a first mover advantage. Going to be the same here. There's going to be people who really embrace this and really make a difference to their organization, and there's going to be other people who say, “It's too risky. I don’t want to, and I'm going to check everything twice, just to be safe.” That, to me, is where really the leadership is going to be focused, and again, where quality, compliance, cost, everything that comes into it can really be tackled head on.