We don't plan to have a take-back program, but we have shared in the past that we plan to launch a consumer to consumer resale path in our Marketplace.
Being in the medtech/AI industry (our company, Eyenuk, created the 2nd autonomous AI approved by the FDA), nothing seems too strange here.
I've seen subscriptions supported, and the pricing doesn't seem alarming. If you look at any medical bill that includes lab work, or anything medical related, this is really cheap comparatively.
The cost of everything is required to lure companies into the space. The cost of research, running a clinical trial, the FDA approval, certifications (SOC2, etc.), insurance, etc. still push many companies away. In fact, in the EU, where the cost is lower, the approval process is getting harder (MDR) and many companies are leaving the market.
Why can't companies just charge X price, once, since it's already FDA approved (hence I assume models are validated), and in the future any upgrades cost Y?
It comes across as predatory that users be charged subscriptions for something that seems like it should be fixed.
Aren't other medical devices and drugs sold for a fixed price, regardless of all the FDA approval and marketing they had to go through?
Like, no one pays a subscription fee for an X-ray machine, or a subscription for a course of antibiotics.
Antibiotics are consumables - in a B2B context (it's a medical service provider who is paying the subscription fee), antibiotics are basically a subscription.
Many (most?) diagnostic devices have consumables which is where companies make the bulk of their revenue. Failing that, service contracts are usually in place to lock in some sort of sustained reoccuring revenue.
There is no fundamental reason why a company couldn't do your proposed model, but upgrades are definitely challenging - if you make your model better, or you improve your hardware, or basically do anything that isn't a bug fix or an ancillary upgrade (like I dunno, you made the thing boot up 25% faster), will likely require additional testing and approval from the FDA.
One of the genius medical marketing tactics was to create disposable condoms for thermometers, ear probes, etc., so that you can use one up for each patient and then purchase a whole big box of them on a subscription basis, rather than going through a simple bottle of sanitizer that could clean anything and everything that needs it. (And then of course, nobody cleans the probe underneath, as it just gets slightly grodier with each use.)
That's not why disposables were adopted. A "simple bottle of sanitizer" is less likely to get rid of biofilm and spores, especially given the laziness and error of end-users.
Disposables are inherently safer. Lots of trash, and more expensive, but the best option for wealthy nations that can afford the best care.
I wouldn't pay for a 25% faster bootup unless it was an emergency life-saving device. You'd have to sell me something significantly better and worth my money, like any other seller in the world has to do with their product, from computers, to cars, to fast food.
I'm not sure that a software upgrade would require FDA approval, but product testing is a cost incurred by anyone in any industry. Even a new burger recipe would be tested at the restaurant's own expense. That doesn't seem to justify a subscription model (after paying the initial cost of the device, etc).
There are a lot of ongoing costs as well. Medical insurance is expensive, and there's a lot of process that is ongoing. A lot of effort goes into security, both monitoring and pushing updates. Medical device companies must also undergo regular audits of our quality systems, look up QMS/eQMS, where FDA reps will spend about 1 week a year reviewing everything we've done over the last year. Generating all the documents for those audits takes a lot of time (aka cost). That's not complete list, but this is in addition to regular SaSS costs.
An x ray machine does the same thing all the time, no Software maintenance needed. If you have a product that has a cloud component, any component to it where it needs to be maintenance from a security standpoint, that has cost, you need to cover that cost.
Modern X-ray machines use software to receive the image and view it.
If the models already work, why would it even require a cloud component? That's just risky, complex, and costly. Let the device do its thing, doc writes down the findings, data gets deleted, and device ready for next patient.
They aren't using AI or the cloud component to do what they can already do.
The whole promise that all these companies are pitching is to aggregate patient data over time, tie it to clinically measurable metrics so they can detect, prevent or treat things better. In your example the idea would be the model in the cloud is aggregating all the patient health record data, tying that to the xrays of those same patients, so that in the future the model can see things in x-rays that indicate disease or are predacessors to disease before we humans can even spot them.
Not quite the example I was explaining. In my example the validated/FDA-approved model runs on local hardware, at the physician's energy bill. Need an A6000 GPU? Fine, I'll buy it.
If the vendor wants to improve the model, they can ask for anonymized data from physicians, if they're willing to provide it. That's their cost of developing a better product, just like anyone in any industry pays a price in some way to improve their product.
A bit late here, but I thought I'd mention something in addition - most hospitals and doctors don't want to take on the burden or supporting something new and specialized. They will focus on providing care and buy support. Some have small IT departments, but even IT support is regularly contracted out.
This stuff can't run locally, it's cloud connected by design. It's cloud connected by design because the company's value pitch is on the data, not the hardware. They loose money or break even on the capital hardware. This is always the case, intuitive makes their money on the instruments, others make it on the subscription fee.
If you want it this way, you'll end up paying a lot more for thr capital equipment.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
I'm genuinely curious... If the pizza box is greasy, I tear off the bottom (some boxes are perforated to make this easy even) and toss that in the green bin, which is allowed where I live. I assume anything not greasy/dirty can be recycled. Am I doing it wrong?
Our municipal recycling is clear that pizza boxes with grease staining can still be recycled. Other places are equally clear that cardboard has to be free of grease, so you'll have to check with your local waste collection to be sure.
The thing with programming is that it either works or does not work, but there is a huge window of what can be called art.
With no training, I, or even a 1 year old, could make something and call it art. I wouldn't claim it's very good but I think most people would accept it as art. The same cannot be said for programming.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
Eyenuk | Medical Device (AI) | Los Angeles | Full-Time | hybrid (mostly remote but occasional onsite meetings/events)
About the company: At Eyenuk, we develop AI-based software medical devices for screening, monitoring, and diagnosis of eye disorders such as diabetic retinopathy and glaucoma and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first FDA cleared AI technology for autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada.
About the positions: We are hiring software (full-stack) engineers and CV/ML engineers. We are still a small team, and so we are looking for people who are generalists. Experience with Python is a plus. Experience with cybersecurity or HealthIT is also a plus.
The original article title was a bit click-baity so I put something more appropriate.
I work at the company (Eyenuk) referenced in this article, and have worked with some of the article contributors. I wanted to share because it captures many of the lessons we (us at Eyenuk and our early customers/partners) have learned about the challenges of getting a medical AI product out into the real world.
