By Shawn M. Schmitt
Communications Specialist, Enzyme
If there’s anyone who understands the power of companies using real-world evidence (RWE) and real-world data (RWD) to support clinical development, it’s Craig Serra. Three years ago, Serra’s daughter was a mere 3 years of age when she was diagnosed with cancer.
Serra was working in Global Development Operations for pharmaceutical manufacturer Novartis at the time and had learned that a researcher in the Netherlands had conducted an investigator-initiated study of patients that had the same type of tumor as his daughter.
“My daughter’s real-world data was included to augment the existing dataset that was used to find another predictive mutation of that tumor type,” Serra said. “A person who has this particular mutation is roughly at triple the risk of getting this particular type of tumor. So, I saw with my own eyes my daughter’s real-world data being combined with other patient data to further the research. It was pretty wild to see that happen – to learn from my daughter’s experience with cancer and see her data married up with an actual real-world use case. That was the cherry on top of my decision to dedicate my time to the oncology world.”
Since then, Serra has gone on to help drive partnerships with leading pharma companies while working within the clinical research business at Flatiron Health. Flatiron is a company that, among other things, packages real-world data for a variety of drug manufacturers to use so they can answer critical questions spanning research, development, and commercialization, and to get lifesaving products into the hands of people who need them faster.
Serra, who has also worked for drug makers Pfizer and Roche, recently spoke with Enzyme about his deeply personal experience with RWD, how such data can be used in novel ways, and whether companies are more open now than ever to the concept of using RWE and RWD. The Q&A below was lightly edited for clarity and brevity.
Enzyme: Let’s talk a bit more about your daughter’s cancer diagnosis. It seems like that, and more specifically, the RWD side of it, has played a role in your professional activities ever since that health scare happened. Would that be accurate?
Craig Serra: Yes, I’d say so. I wanted to work at a company that was dedicated to solving the cancer enigma. It didn’t have to be pediatric cancer, and Flatiron’s focus is not specifically on that. Our real-world data largely come from community cancer clinics. Most parents with children who receive a cancer diagnosis seek out larger academic medical centers with pediatric specialties or children’s hospitals.
But the real-world evidence and real-world data piece of all of this was, I remember having conversations with healthcare professionals after my daughter’s treatment, and one of the things that would pop into my mind on occasion was just thinking about how she has all this data stored that ranges from the most mundane of blood pressures to cutting-edge genomic and proteomic analyses of blood and tissue. And it made me wonder if that could that be used for good and if a researcher could actually use that.
Enzyme: And that’s when you linked up with the researcher in the Netherlands?
Serra: Yes. So, to cut right to it, my background is in the running of clinical trials and all the infrastructure around clinical trials. It wasn’t until fairly recently that using real-world data and real-world evidence to help build and run those trials started happening. Flatiron is the “OG,” if you will, in the collection and use of real-world evidence.
Flatiron has partnered with pharma for a number of years – around 13 years in the oncology space – who typically use it for very specific things. It’s smaller groups of people within these huge companies that use real-world data and real-world evidence. And about three years ago Flatiron decided to launch a clinical research business focused on solving the biggest pain points in clinical research with a focus on using both our new assets – our acquisition of EHR [electronic health record] to EDC [electronic data capture] software Clinical Pipe – as well as our historical assets, which is real-world data and real-world evidence, to better write clinical trial protocols, supercharge site selection, and match patients at the point of care.
So, my background is in the running front of a trial and how we do that. It wasn’t until maybe five or six years ago, during my time at Novartis, that I got into the use of large datasets, specifically real-world data, to better inform how we write protocols. The ability to actually use what’s happening in the market now, whether it’s the standard of care – or not – reflected in the data, to actually design trials better, that’s kind of a novel thing for the running of clinical trials, which is remarkable.
Enzyme: And novel for the pharmaceutical industry, no?
Serra: Oh, yes, I’d would argue that it is relatively novel for pharma. Given that Flatiron is one of the original companies to have collected RWD and generated RWE, and that started a little over a decade ago, that’s not a long time. Some of our customers were formed in the 18th and 19th centuries with trials being run roughly along that same timeline, so 13 years is not very long when we talk about real-world data and the applications of real-world evidence. It’s pretty amazing.
Enzyme: Recently I’ve written other pieces on RWE and RWD, and what I hear most from interviewees is that many companies are still leery about using those. Would you say the same? (Related: “Embrace Real-World Evidence to Avoid Costly Prospective Randomized Trials That can ‘Strangle Innovation,’ RWE Expert Says” – Enzyme, Nov. 15, 2024.)
Serra: I think it’s a couple of things, and I’ll hit on them as quickly as I can. First is money. RWE and RWD collection and use costs money. Larger pharma companies typically have more capital to spend on RWD and RWE; if you’re in a smaller company, you’re probably going to be more bearish than not. But of course, there are exceptions. The second aspect is also related to company size – larger companies typically have functions specifically related to RWD and RWE; smaller companies typically do not have this same infrastructure.
But by and large, what I’m seeing is manufacturer acceptance of RWE and RWD, particularly when you have the FDA, the EMA [European Medicines Agency], and other regulators putting out guidances about how to use these data within the world of drug development.
Enzyme: Now, we have not talked about MedTech manufacturers and their use of RWE and RWD, but obviously those companies are using such data too. And we won’t discuss MedTech today because that’s not necessarily where your experience lies.
But boiled down, what you’re saying to me is this: Manufacturers, in general, are open and willing to using RWE and RWD to supplant the use of standalone studies for drugs, devices, and in vitro diagnostics (IVDs). (Related: “Ex-FDAer Says Real-World Data Just as Good as Clinical Data: ‘I Will Take This to the Grave” – Enzyme, Dec. 4, 2024.)
Serra: I think some consider that to be a binary question – yes or no – but it’s much more nuanced than that.
You need to understand the data you’re looking at. You need to know the outcomes that you’re trying to find are. You need to have really smart people working on this stuff. It’s not, “Here’s a bunch of data and here is your answer to these questions,” and then that’s it. That’s why, to date, there has not been a net new FDA approval of a compound that made it to market by exclusively using real-world data. There have been label expansions and very well-known use cases, and very well-known examples – including palbociclib from Pfizer – that have used real-world data, including Flatiron data, for a male breast cancer approval because that type of cancer is so rare and a clinical trial isn’t feasible or ethical.
In the example of Pfizer, it used pivotal trials in women to show that the compound’s robust safety profile, and then it used real-world data to show that the compound actually worked in off-label prescribing for men with breast cancer, so it got a label expansion from the FDA. This is a great example of RWE and RWD not necessarily replacing anything. Rather, it was adding to a substantial body of evidence. And if people can see that nuance, I think they’re better for it.
