Mike Hollan

Pharmaceutical ExecutivePharmaceutical Executive: May 2024

Mike Hollan, Assistant Managing Editor, Pharmaceutical Executive

When it comes to developing new drugs and therapies, there is obviously nothing more important than data. Countless bits of data are collected for each medication before it hits the market, and researchers continue to collect data after that. Even before the modern technology boom, data was a key component of the life sciences industry.
In the modern world, data is more valuable than ever. New technologies, such as AI and machine learning algorithms, are capable or collecting, sorting, and analyzing bits of data at a faster rate than ever before. Researchers across almost every industry are seeing the benefits and discovering new ways to innovate based on these discoveries. In the life sciences industry, this data is being used for everything from drug development, market analysis, and even scheduling sales reps calls.
It’s undeniable that data is important, yet there are still aspects of the life science industry that have yet to catch up to the modern world. For example, a shocking number of processes in the industry still rely on physical paper. In a digital world, waiting for a physical document to be delivered can cause unnecessary delays. It’s also easier to back-up, store, and retrieve digital documents.
I recently spoke with Mark Melton, customer advocacy executive at Magnolia, about an issue he calls the “first-mile problem.”
“The first mile refers to the first part of the journey of samples we’re collecting from patients and the physicians at the clinical trial to where the samples, and, therefore, the data that’s associated with the samples, must go,” he explains. “The first mile is the clinical trial site to the actual destination lab. Usually, they are not local. The data that travels with the sample is all paper. What they do is they fill out a requisition form, usually a three-piece carbon copy structure. Essentially, that’s the data that goes with the samples.”
Obviously, this can trigger a multitude of issues that going digital could solve. For example, Melton explains that labs may receive up to 500 pieces of paper containing the data for up to 1,000 samples. Due to the data being on physical pieces of paper, it takes much longer to simply sort it.
“That first-mile journey right now, in 2024, is all paper-based,” says Melton. “That’s where all the problems start. The second and third miles are where they aggregate all that data from the different labs and sites. If you can solve the first-mile issues, then everything in the subsequent miles in the journey becomes much easier.”
I also spoke with Bob Zambon, PhD, vice president of technology strategy and strategic partnerships at Syneos Health, about another data issue that modern technology can help solve.
“When you look across the landscape of the various data formats (such as R&D, and even just general healthcare data), a lot of times it gets subsided into different groups,” he says. “For example, there’s real-world data, and then you can buy further research data; so things along those lines. Where we’re looking at the total value perspective, it requires all of them to interplay in one way or another.”
Zambon continues, “You look at different standard approaches for things like real-world data that are starting to move down that pathway. It means putting data into a format that can be universally understood and is standardized. You do this so that every time you do a research project, you’re not having to re-standardize, re-baseline, and remaster all your data.”
New technologies have opened the door to a number of innovative ways of using data. Unfortunately, the first step often still requires researchers to spend time translating physical documents into digital files. As Zambon explains, this process can be much more complicated than it first appears to be.
“Even something as simple as [optical character recognition] and translating physical documents into a digital format using [natural language processing] to start the process can still be difficult,” says Zambon. “There are differences to account for, such as what some of the open text fields mean in different types of health records. You might have data saying someone was just diagnosed with cancer, or this particular lab test came back with this particular result. This is all part of moving down that path of taking all that data and making it more accessible so you can apply additional algorithms, machine learning, and AI.”
It’s long past time for the industry to fully embrace the digital age. It’s fine to keep paper back-ups of data, but using physical documents as the primary source of data for research is keeping a tighter grasp of new technologies out of reach for the life sciences.
Mike Hollan is Pharm Exec’s Assistant Managing Editor. He can be reached at mhollan@mjhlifesciences.com.