Beyond the Label: How Drugs and Devices Diverge Across the Product Lifecycle
By: Dr. Steven Farmer - Senior Partner, ABIG Health
When it comes to healthcare innovation — new treatments and products that could improve lives, or even lengthen and save them — we often group pharmaceutical developments and medical devices under one umbrella: therapeutics. But the truth is, these innovations follow very different development, approval, and post-market trajectories.
Indeed, while pharmaceutical innovations are typically static in form and effect once they are approved by the U.S. Food and Drug Administration (FDA), high-risk medical devices are dynamic. How they work — actually, whether they work — depends heavily on clinician expertise, settings in which they are delivered, and how the devices hold up over time.
This post will explore the differences between drugs and devices when it comes to the premarket phase, delivery, and post-market variability. It also will articulate the role real-world evidence (RWE) plays in approval and payments processes.
Premarket Development: Fixed vs. Evolving Interventions
If you have picked up a prescription at the pharmacy, you have seen the voluminous list of instructions, warnings, and other disclaimers that are printed in miniscule font on a paper that, once unfurled, rivals the size of a world atlas.
Despite the length of these instructions, pharmaceutical development actually follows a linear, well-defined three-step pathway toward approval. And once approval is granted, the target indication, doze, and delivery are fixed by the FDA. (That is, the map of instructions, warnings, and other disclaimers rarely, if ever, changes.)
Device development, especially for novel, high-risk Class III devices, is far different.
It is iterative and dependent on design. Premarket trials often involve or require operator involvement, training, and procedural components. (For a drug, no one is monitoring how a patient ingests a pill.) Additionally, the device risk-benefit analysis is less fixed and more context-dependent. Finally, while FDA approval pathways for devices emphasize safety and effectiveness, they may not capture post-approval variability. Specifically, because FDA trials try to gauge safety and effectiveness for the population as a whole, they often do not generate enough data to show whether, for example, a device presents a good option for an 80-year-old man with a history of heart disease.
Delivery and Performance: Skill, Setting, and System Matter
The delivery and performance of a device for certain populations and in certain settings does matter, of course, particularly to insurers. No shareholder or taxpayer wants to pay for a treatment that is not likely to work or, worse, may harm a patient.
When it comes to delivery and performance, outcomes are generally the same for drugs once they are in the supply chain. Risks and efficacy are largely independent of provider skill or care setting — a patient with a blood clot may have the choice of a few drugs, but that drug can be prescribed via telehealth or in person (once the existence of clot has been confirmed, of course) and does not have to be administered by a specialist.
With medical devices — and, again, especially for those that are high-risk and novel — outcomes are highly influenced by all sorts of factors, including a provider’s training, credentialing, and specialty.
It is unlikely any patient would allow their general practitioner to implant a pacemaker, for example. At that brings up another difference between drugs and devices: with devices, there is a volume-outcome relationship. Especially in cardiology, orthopedic, and neurosurgery, outcomes improve the more experience a clinician has. (Unless, of course, you are a character on a Thursday night ABC medical dramas. Doctor Odyssey and Dr. Meridith Grey can perform a procedure they have only read about flawlessly.) This difference is exacerbated by the fact that academic centers often lead adoption with diffusion occurring over time to community settings. It is much less likely a device implantation will be reproducible in settings with fewer resources.
Post-Market Reality: Devices Continue to Evolve
Added to these roadblocks is the fact that devices are not static products. The pacemaker that was introduced in the mid-20th century is not the pacemaker that clinicians implant today. (That is fortunate since the first implanted cardiac pacemaker lasted only three hours. The patient had to have multiple surgeries over the next 43 years of his life in order to survive.)
Obviously this iterative process can alter the device’s performance characteristics, which is why FDA approval are product-specific instead of provider-specific.
To account for all of these factors, it is important for device manufacturers to track and assess how their innovations work in the real world. Premarket studies cannot only be conducted at high-performing academic centers under ideal conditions and for the ideal patient. Manufacturers must look at hard cases and they must aim to represent the broader patient population or the type of practice variability that will happen after devices are launched into the marketplace.
Real-World Data: Essential for Device Evidence Generation
Fortunately, real world data (RWD) studies are uniquely suited to the evaluation of medical devices. First, they capture the diversity of providers, patients, and care settings in which the device may be used.
Second, RWD studies track longitudinal performance as devices evolve and diffuse. These studies also help to identify rare events, learning curves, and practice gaps that may influence a devices utility and efficacy.
All of these factors are why regulators like the FDA and payers are increasingly looking at RWD studies to evaluate a device. These entities know RWD complements premarket data for lifecycle evidence development. In the future, I believe RWD will be absolutely essential for building payer confidence in effectiveness beyond controlled settings.
As innovators move forward, they must recognize one truth: Drugs are fixed and devices are dynamic. Especially for high-risk, novel devices, manufacturers must look at the total product lifecycle and plan for RWD studies from the outset. These tools are not optional add-ons — they are necessary to understand long-term benefit and risk and to secure payer, patient, and clinician trust.
If innovation is ongoing, evaluation must be too.
If you need help designing a RWD strategy, ABIG Health can help. Learn more.
