When a sponsor scopes devices for a trial, the decision usually comes down to one of three paths: leave devices out of the protocol to sidestep the complexity, contract directly with a device manufacturer, or hand the device strategy to an end-to-end connected device service provider. For a long time, the first two options looked like the safer bets.
Devices were expensive to procure, difficult to standardize across countries and complex enough to configure that sponsors treated them as a specialized problem to solve late in study planning — once sites were selected, protocols signed and budgets set. Avoiding devices, or going straight to a manufacturer, felt like the lower-risk path.
That’s starting to change. Devices are shrinking, sensors are getting cheaper and most importantly for sponsors weighing a manufacturer relationship against an end-to-end partner, the operational burden of running a global device program is falling fast. As a result, outsourcing the full strategy may now make financial sense, not just operational sense.
Going Directly Comes With a Hidden Operational Bill
Two problems have made going directly to a manufacturer or skipping devices altogether the path of least resistance:
- Global reach means global variability. Device manufacturers often build different models for different markets, because a device is only available in a given country if local payers and regulators support it. That leads manufacturers to field Device A for Europe, Device B for China, Device C for Japan and Device D for Latin America. For a patient, that’s invisible. For a clinical trial, it’s a data problem. Regulators see different part numbers as different products, which complicates pooling and analyzing data across sites. Sponsors going directly to a manufacturer inherit that variability, along with the logistics, training and support burden of running the device themselves.
- Devices were scoped late, which broke outsourcing timelines. Device feasibility was traditionally a conversation that happened after sites were selected and contracts were signed. Sponsors would bolt a connectivity vendor onto a study design that was never built to accommodate one. By the time procurement realized a device program couldn’t scale to a “real world” site that lacked clinical infrastructure, the RFP window had closed. This is exactly the operational layer an end-to-end connected device provider is built to own - logistics, training, support and variability - rather than something a sponsor manages alone or leaves to a single device manufacturer.
Devices Are Now Cheaper, Smaller and Easier to Provision, Which Makes Picking the Right One Harder
What’s changed is device unit economics. When you build global sponsor-vendor relationships around devices, it matters a lot what those devices are. Platforms are appearing from consumer device manufacturers moving aggressively into healthcare. It’s driving down device form factor, cost and complexity. Devices small and simple enough to be supported at “real world” sites can now:
- Plug into wall outlets patients already have at home.
- Send synchronized data over patients’ existing cellular plans.
- Be worn comfortably for days, not hours.
That solves two problems for sponsors considering outsourcing device programs:
- Total cost of ownership. Lower prices for devices means sponsors have more vendor relationships to choose from when evaluating the total cost of outsourcing vs. operating a device program in-house.
- Patient compliance. Devices that look and charge like consumer electronics that patients already own are simpler for patients to use consistently, which means vendors have fewer change orders and touchpoints per site to manage.
Need consistent data captured across dozens of countries? Suddenly, sponsors can get it by design, because either the devices being procured are the same everywhere or the specialized device provider has the logistics experience to successfully import consistent devices globally via complex clinical trial import processes.
That growth cuts both ways. More device options mean more opportunities to match the right sensor to the right protocol and patient population, but only if somebody is tracking the landscape closely enough to know which of the hundreds of available devices is actually right for a given study. That’s the job of a specialized partner continuously scanning the device landscape, rather than a sponsor evaluating options study by study.
Device Feasibility is Now a Vendor-Selection Criterion, Not An Afterthought
When sponsors go through site selection, they’re looking at patient availability, investigator experience and device readiness. Historically, device feasibility was an afterthought. Devices were excluded because regulators didn’t accept the data they captured, or sponsors learned partway through a study that a remote site couldn’t support hardware their protocol required.
Technological advances have flipped that logic, and sponsors are taking advantage. Device readiness is increasingly part of early feasibility scoring. Sponsors who are able to scope device strategy as part of the RFP process are finding realistic opportunities to expand trials that previously weren’t possible. Sites that were never considered before are coming online because sponsors can responsibly support devices in remote locations and can ensure quality, submittable data collection in all corners of the globe.
Consumer and Medical-Grade Devices Are Converging on Primary Endpoints
Clinical research has used consumer devices for years, but mostly for exploratory endpoints or supportive data a study didn’t principally rely on. Wearables, in particular, are now moving from exploratory to primary and secondary endpoints, which raises the stakes considerably. Exploratory data just needs to be interesting. A primary endpoint needs to hold up to full regulatory scrutiny.
Two trends are converging to make that possible. Consumer devices from manufacturers like Apple and Samsung are getting more compliant, with the validation and data quality needed to be taken seriously in a clinical trial. At the same time, medical-grade devices - historically accurate but difficult to use and requiring extensive training - are designed for consumer-grade user experience: intuitive apps, simple Bluetooth or cellular connectivity and the ability to batch and resend data after a lost connection instead of losing it outright. The result is a much larger, more complex landscape of viable devices, which is exactly why evaluating and selecting the right one has become a specialized skill of its own.
Two things you’ll find when you buy a validated device program:
- Device programs built on consumer-grade hardware are far cheaper and easier to operate than clinical-grade hardware with dedicated facilities and training requirements. The vendor math for “buy” starts to favor vendors because device programs are simply cheaper to operate.
- Sponsors are increasingly interested in hybrid and fully remote clinical trial models. Many of those models are predicated on outsourcing device programs in the first place. But they run far more smoothly if the devices capturing data are already validated by regulators, because it eliminates one of the riskier discussion points in vendor contracts.
From Point-In-Time Data to Continuous, Composite Endpoints
Clinical trials used to capture data like blood pressure and weight in repeated visits to a clinic. Connected devices are letting researchers capture those types of data continuously, which opens up all kinds of new digital endpoints previously impossible to measure because sensors weren’t small or low-power enough to exist.
Multimodal digital endpoints are one of the clearest examples. A diabetes study used to rely on a fingerstick blood glucose reading a few times a day - a single point-in-time value.
Now sponsors have a continuous glucose monitor logging ketone data and insulin delivery data for patients on an insulin pump, all on a single dashboard. More devices and more data sources produce a far richer picture than any one of them could alone, but only if the data streams can actually be connected and used together.
Body composition data is a good example of what’s now possible. The gold standard, a DEXA scan, is expensive, disruptive to patient scheduling and only available at specific facilities. A high-end, FDA-validated bioimpedance analysis (BIA) scale can now deliver DEXA-comparable, submittable data on skeletal muscle mass, fat composition and subcutaneous fat - not just weight and BMI - and some of that technology is now small enough to ship to a patient’s home. That matters beyond convenience. Skeletal muscle mass is a known area of concern in GLP-1 trials, and a BIA scale offers a noninvasive way to monitor it without bringing the patient back to a site or specialty lab.
Shipping a device to a home introduces its own risk, though, namely, making sure the right person is actually using it. Newer devices address that with built-in biometric validation: The patient’s phone confirms it’s actually them stepping on the scale, not a family member or anyone else in the household, before the reading is logged. That single check prevents a meaningful source of bad data. Just a few years ago, vendors couldn’t support this model across an entire program because devices varied widely and the patient experience was fragmented. Devices alone don’t resolve that; the right vendor does.
Multiple devices used to mean multiple login portals and dashboards for sites, patients and sponsors to manage, and sites feel that burden acutely. A site running a handful of devices across a handful of studies can end up juggling more than a dozen logins and a stack of laptops, with no clear sense of which system is causing which problem. Platforms have started consolidating around single sign-on, common training materials and a single help desk, so a site calls one number whether the issue is a laptop, a CGM device or an ECG machine and gets an answer either way. Given how selective sites can afford to be about which trials they take on, reducing that burden is now a meaningful factor in site retention, not just a convenience.
The same logic applies on the patient side. A mobile-first experience that feels like a consumer app, not a clinical instrument, is what keeps patients compliant. If a device is difficult to use, patients simply won’t use it, and the data the trial depends on is put at risk. Continuous, real-time data streaming adds another layer of protection: If a patient’s device goes offline unexpectedly, the platform can flag it immediately so the site can check in before the gap becomes a permanent loss of data, even for patients in remote locations far from a site.
Why This Matters for Sourcing Decisions Now
Sponsors are making device strategy decisions right now that will directly impact how they approach vendor partnerships for the next 3-5 years. Interest in real-world body composition data is exploding in the GLP-1 and obesity clinical space. Device agnostic data capture is table stakes for global rare disease research. Device privacy and security standards are being evaluated by regulators in key geographies around the world, and in some cases, diverging in ways that future vendors will have to comply with, not debate, once a contract is signed. Underneath all of it is the same throughline: Richer data from continuous and multimodal endpoints, higher patient retention from a consumer-grade experience and lower site burden from a common platform combine to produce faster outcomes, fewer patients needed to power a study and lower overall trial costs.
Sponsors making decisions about device programs this year are setting more than just cost expectations for device procurement. They’re deciding whether devices will be a limiting factor on representative data or whether a partner who owns the full device strategy — not just the hardware — can enable broader, more diverse trials than would be possible by going directly to a manufacturer or managing it internally.