The chief operating officer of RUCDR Infinite Biologics at Rutgers University looks like he'd be just as comfortable on a Florida golf course as he is analyzing sample datasets. In truth, Andrew Brooks, PhD, is at ease given any opportunity to discuss the benefits of the work he and his team do to advance biobanking standards. We caught up with Brooks in August to discuss RUCDR's sample identification process using the Fluidigm® SNP Trace™ panel—and found ourselves treated to a lesson in pride and passion.
Q: How did the adoption of SNP Trace throughout the RUCDR (Rutgers University Cell and DNA Repository) come about?
A: The history of identifying samples for us and assessing functional quality control has been going on for about four or five years. When we started to expand a lot of our collections and experiment and implement new analytical technologies, it was clear that understanding the quality and the identity of the sample was extremely important. Although you could put a lot of best practices and SOPs in place that deal with sample collection, they can't catch or address a lot of the potential errors in small and large biobanking projects. So we started working on an idea with respect to ensuring sample quality as well as identity, which ultimately developed into the implementation of SNP Trace throughout the entire RUCDR. SNP Trace is run on every sample we extract or collect in order to ensure sample quality and identity.
Q: Why do you feel sample identification is so important?
A: Implementing a quality program like this was really critical for us, because we distribute and analyze large numbers of DNA samples. Over time sample collection had started to grow and technologies for analysis started to accommodate larger samples to be run. We were starting to see errors in those samples that directly affected the analysis and interpretation of that data. So for instance, if we would distribute 10,000 samples, 100 or 200 would come back with either the wrong gender or the sample failed analysis. These kinds of losses are expensive and directly affect the analysis that people are doing. So what we decided was if we can control for that up front and provide a level of functional quality control on every sample, not only would we be able to make those data sets tighter and more robust, not only would we be able to decipher any data discrepancies for collections or errors that happen in the field, but also we would be able to provide a higher quality research product that allowed people to get more out of every analysis they do.
Q: You get excited discussing the possibilities of improving research, like you're quite proud of what you do.
A: I think everybody wants to be able to take pride in their work. What we do requires a different level of dedication in that our pride directly reflects the quality of the work we do and the quality of the samples we're generating, which goes well beyond our own personal feelings. Myself included, the people who work within the RUCDR take a different level of pride only because of what's at stake. The future of diagnostics, the future of cures for a lot of genetic diseases is really in our hands, so to speak, with respect to being able to provide the materials that are critical to finding those answers. It makes you think just about every day of the importance of what we do and the level of pride that's needed to be successful.
Q; That's a lot to hold in your hands. What does it mean to you personally to know the value of what the RUCDR does?
A: The value of what we do means a lot, not just to me, but to everybody that's part of the RUCDR team. We're constantly reminded that in every tube and every sample we collect, there's a person who's given that sample. And likely there's a person struggling with a disease or something that's led them to a clinical trial or to being part of a disease-related collection. So the quality that we take in handling these samples and making sure they're quality samples has a lot to do not just with the outcome of a study but the responsibility we have to the patients and the subjects who have contributed to these really important studies.
Q: It seems like passion for your work is as important a credential as any degree.
A: I have a lot of passion in everything I do, whether it's at work or at home with my family. It's the kind of person I am. I've always wanted to be a scientist. I always enjoyed science throughout school and into college. Certainly making the decision to go into molecular neuroscience was a very conscious choice. During my graduate career, I experienced a very exciting time because there were a lot of developing technologies—really the birth of genomics and genetic medicine. I did my PhD in molecular medicine and gene therapy, which exposed me to a lot of very cool technologies. Working with the RUCDR and coming here about nine years ago really gave me the opportunity to take my love and passion for technology, really a drive for understanding the molecular mechanism of disease, and combine it into a program that really has no peers currently and allows us to do things that other labs can't do.
Q: Would cost be a challenge to biobanks considering adding a sample identification process?
A: Given the challenges associated with working in a biobank setting, accuracy is really the leading quality that we have to follow. There's only so much we can do to accurately identify a sample, so implementing new tools and new technologies to make sure we're doing the absolute best job fits with what we're all trying to accomplish.
The benefit of implementing SNP Trace in our lab far outweighs the cost. When we look at the cost of sample collection, most of it is in the recruitment of the subject, any clinical analysis or assessments that are done, and the actual collection of the sample. The biobanking component is a very small fraction. So if we were to lose a sample, having to reconsent a patient is a far larger cost than actually having to process that sample. And if you break that down further and look at the cost of processing a sample, by the time you're done with extraction and then the cost of downstream analysis—sequencing exomes at several hundred dollars or sequencing genomes at several thousand dollars—the cost of SNP Trace for a few dollars to qualify that sample and make sure the right sample is being run for downstream analysis is inconsequential.
Q: How did your team respond to adding SNP Trace to the sample processing workflow?
A: Our quality control group really embraced this technology from the get-go, because it made their job a whole lot more efficient. They're able now to make measurements and assessments of sample quality instead of having to deal with them after the fact. So what SNP Trace does is allow us to be very proactive about sample quality. In the past we were reactive—when there were problems with sample quality or sample identity, we would do all the kinds of analysis and testing and looking at stock samples that we needed to do to present that sample again for analysis. With our current approach, what the quality control team does is proactively assess every sample so the number of failures and misidentifications on the back end now is almost nonexistent because those samples don't make it onto analysis. So there's no wasted time or cost. And the automation of this approach allows the quality control team to do things much more efficiently.
As chief operating officer, my job is to implement new technologies, make sure we're operationally sound, make sure we're efficient, but also to make sure that we're staying true to our mission. And our mission of identifying answers to complex diseases and genetic anomalies really requires us to use a quality sample. So I think from many perspectives—operationally, financially, even scientifically—having this kind of program in place doesn't just make us a better program or a better company, but it actually makes us better scientists.