Register Now: Beyond EDC: Designing a Connected Data Strategy for Predictive Clinical Development
Commentary|Videos|November 25, 2024

Managing the Chain of Custody for Sample Collection

In this video interview, Mark Melton, vice president of biospecimen data and operations, Slope, highlights the need for improved management of the sample lifecycle.

In a recent video interview with Applied Clinical Trials, Mark Melton, vice president of biospecimen data and operations, Slope, discussed navigating data challenges in clinical trials, emphasizing the need for understanding complex data sources and ensuring a proper chain of custody for samples. Melton highlighted the importance of data mapping to standardize reporting across different labs and the necessity of secure data transfer to protect patient privacy.

A transcript of Melton’s conversation with ACT can be found below.

ACT: What are some of the operational challenges with biospecimen collection and sample tracking? How can they be addressed?

Melton: Then the other part is, you have to imagine, there's hundreds of patients coming in a week, sometimes more, depending on the trial, and it can be less, too, depending on the phase, but the ability to realize that one patient, if I come in for a trial or for a visit, one visit out of, say, 50 visits, I'm going to generate, at a very minimum, double digit samples that come out on that visit, and then one person turns into a multitude of outputs as it relates to samples. Then, how do we take that and have the ability to tie that all back to the patient, and ensure that when we go to submit data and say, “Hey, what we tested, this drug is working, or it's not working.” It's actually not so much about the science at that point, that part's been defined. It's everything that's leading up to that to ensure, again, I said this earlier. Is it the right sample? How often was that sample froze or thawed throughout the process? Did we have the right temperature? Was it sent to the right location? All of that starts from the beginning of the chain of custody, which is at the sites, which are often overlooked. Again, the problem being is there's so many of them. How do you standardize something that's across tens of thousands of different businesses? It's really challenging, so we have to think about it that way and that's the hardest part, in my opinion.

Then the secondary part is you have a lesser number of people who are processing those samples after it leaves the site. In my mind, that should be a little bit easier to regulate, because it's a smaller number of businesses that you have to do, so you impose standards on them around data standards or processing standards, or the availability of the data. I think that's the biggest thing to consider when we're looking at that, is the entire chain of custody and how we fit it together and ensuring that, you know, some of this is bigger than business. While we are treating sick people, all of these are for-profit businesses, so everyone has a right to try to protect their bottom line, but at the end of the day, some of things are bigger than that.

What we try to focus on at Slope, and what we should focus on as an industry is there are certain things that are bigger than business. I think everyone could agree, hey, if these people who are sick, who are coming in, some of them dying, knowing that they want three to five more years, but that their samples are going to contribute to a cure, maybe, or to a treatment that gives longer time span of life, that we should all collectively agree that we need to control that chain of custody from the onset all the way through testing. For me, that's the biggest focus we should have.


Related to this article

Where the Industry Is Headed as Clinical, Operational, and Real-World Data Connect
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, describes the industry’s trajectory toward a unified intelligence orchestration environment—and explains why the future isn’t one model that knows everything, but a trusted system that brings the right evidence to the right human decision.
© photon_photo - © photon_photo - stock.adobe.com
Standardized measurement across five oncology centers found that clinical research coordinators rated eSource-enabled workflows positively (Overall Mean Satisfaction 5.79 of 7), with reduced manual entry and electronic data transfer earning strong marks, while perceived reduction in sponsor and monitor queries lagged as the one domain below threshold.
What Expanding AI Ecosystems Mean for Sponsor Complexity and Oversight
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, argues that CROs must act as orchestrators rather than aggregators—and that the real test of any AI ecosystem is whether it reduces sponsor coordination burden or just hands it back to them.