Contributing Expert: Nicole Latimer, CEO of Medrio
In this executive interview, Chris Hayden of Fierce Biotech interviews Medrio’s CEO, Nicole Latimer. You’ll hear about how Medrio is providing a stable base for clinical researchers amidst uncertainty and why standardization is key to success.
Below, find an edited transcript featuring the highlights of the conversation. To hear the entire discussion, listen to the full interview by watching the video.
The clinical trial industry is full of disruptions. How do you stay focused on solving the real challenges?
[2:15]
We focus on our mission to save a hundred million annual lives. We do that by helping life sciences companies to streamline their clinical research and create accurate data that supports their ability to raise additional funding, get regulatory approval, and commercialize their therapies.
I also share stories with my team about our customers having success with using our software, finishing their trials, and using the data from those trials to get regulatory approval. I share some of the success stories about how they’ve been able to commercialize and save patients’ lives. It really helps with minimizing some of those external distractions, and it helps with thinking through: “How do you handle the change? How do you bring changes in and incorporate them in a way that stays true to your mission?”
How can an organization maintain stability while also evolving with the industry?
[4:25]
At Medrio, we value supportive, long-term relationships since these are foundational for stability. We love to work with customers who are just starting out in their clinical trials. It also gives us an opportunity to stay with them throughout their clinical research journey. As you know, very often clinical research is a seven to 15-year journey for many organizations, from the moment you go into the clinic for the first time to the time you get approval. We know we want to work with them over that long period of time and support them to make sure that they can be as efficient and effective as possible.
The second thing we do is we also focus on standardization and efficiencies. We think that a lot of clinical research has the possibility of being overly complicated or overly delayed. We take it upon ourselves to provide best practices and ideas to our customers on how they can be more efficient and what they can do that’s more effective. We share techniques and tips that other people have used in order to streamline their clinical research.
The third thing we do is equip our team and our customers to be empowered to make decisions to do what they need to do. That’s part of what we call our guided autonomy approach. We make software that’s easy enough to use that our customers can use it themselves. But we also have a wide variety of experts—people with decades of experience who can work with our customers to ensure that they are optimizing the use of that technology.
What strategies have been most effective in maintaining financial stability while continuing to deliver value?
[8:20]
Having financial stability is fundamental in this industry. Whether you’re a biotech that’s out seeking funding or you’re a technology company like Medrio, you know that good financial, good economic stewardship is critical to surviving here. We really look at making sure that we are using our economic resources well, not only for ourselves but also for our customers.
We also stay laser-focused on solving our customers’ needs. When [industry] trends come up, we look at those trends and determine if they are actually going to help with resolving or serving those customer needs.
A great example is AI. There is no limit to how you could use generative AI in clinical research. But a lot of it is not necessarily going to meet the needs of our customers. Our core customers at Medrio have said that speed and flexibility are the most important things that we can deliver in terms of our technology. When we’re applying AI, we’re doing so in a way that expedites clinical research. We’re applying it in a way that allows us to automate the database builds, which is a precursor for clinical research, and we’re using AI to enable our reporting.
Scaling clinical trials efficiently is a major challenge. What do you want those running trials to know to make it a little bit easier?
[15:15]
It really has to do with how you set those trials up from the beginning. There are two things that you can do to make it a lot easier to scale. The first is data standardization. Having some standard forms that you’re going to use in every trial makes it easier to standardize that data and to then compare data as you continue to scale your trials.
It also helps to then standardize your processes. One of the processes that we think is critically important is looking through your data and understanding which data is truly necessary —an absolute must-have—and what doesn’t quite meet that standard. What we’ve seen is that over the last six to seven years, there’s been a 35% increase in the number of clinical variables associated with Phase I studies. It’s adding to the complexity, it’s adding to the time, it’s adding to the cost, and we see our sponsors streamlining their effort.
How can clinical research continue to evolve over the next 20 years, and what strategies will help ensure stability amongst all this change?
[19:25]
The first thing is greater technology adoption. Many organizations today are still using paper-based data collection as part of their overall clinical research process. Paper is a second-rate, second level of quality of data, when it’s compared to electronic capture. We’ve got to migrate to higher-quality data.
The second thing is the ability to directly bring in source data into clinical trial data systems. Right now, we’ve got a lot of information and data coming in from different sources. People are then pulling up that source and transcribing that information into the clinical trial data systems. That then requires verification and monitoring, and introduces the possibility of errors. We’ve got to really think about how we look at some of that source data—not only to enhance the quality, but also to make it much more efficient.
Want to learn more about what to look for in a stable EDC/CDMS partner? Read this CDMS/EDC vendor guide.
