FDA

Hormones, CGM preferences, DIY, and why so many things are YDMV even when #WeAreNotWaiting

by Dana Lewis

I posted one of my Nightscout graphs yesterday, showing a snapshot of my morning:

Example of how getting out of bed - rather than dawn phenomenon hormones - can increase BG levels.

I hadn’t eaten, and my blood sugar still spiked up. I’ve noticed this happens in the mornings sometimes. When I have mentioned it over the years, people are quick to tell me my basal rates are wrong, and I should adjust them because dawn phenomenon. But actually, this isn’t dawn phenomenon. This happens after I physically get up and start moving for the day, whether that happens at 4am, or 6am, or 10am, or even waking up after noon. So, it’s not a basal thing, and modifying my basal rates doesn’t fix it. (And this is why I wanted to add wake-up mode to my suite of tools, to help address this.)

To me, this is a great example, (as I mentioned in my Twitter thread), of why diabetes is so hard: sooooo many things impact BG levels, and in many cases, we PWDs just have to roll with it and respond the best we can. In my case, #OpenAPS did a great job responding to the spike and bringing me back down within an hour or so.

One of the questions that popped up yesterday in response to that graph, though, was about the BG line: how did I have two BG lines?

The answer: I wear a G4 sensor, and usually have 2 receivers running off the same transmitter and sensor. One receiver is Share-d to my phone, and uploads to NS via the interwebz. The other receiver, although Share-capable, doesn’t (because the company only allows you to pair one receiver and upload via Share). I leave that CGM plugged into a rig to enable it to be a backup for offline looping. When online, this rig with the plugged in CGM uploads BGs from that receiver to NS.

Sometimes, because of different start/stop times and therefore differing calibration records, the receivers “drift” from each other, making it obvious on the graph when that happens.

Because if you give a mouse a cookie, other questions come up, someone had also asked me why I’m using G4, and why not G5. Someone else asked me in a different channel why I’m not using G5 and xDrip+ (a DIY option that doesn’t use Dexcom app or a Dexcom receiver for receiving the data or processing it), or another DIY tool to process my CGM data.

Now, as always, what I chose to use is my personal preference. It’s colored by my preference for what equipment I’m willing to carry; what phone I want to use; what data I want to have; my safety backup preferences; what my insurance covers and what I can afford; where I live; etc. So, just because I use this method, doesn’t mean I expect anyone else to want to do it. It’s just what I do. I don’t try to convince other people to use this method, and I also hope others can share info about what works for them without trying to hammer me over the head because what I’m doing is different. This is where YDMV (your diabetes may vary) comes in. It’s so true, and even within “people who DIY”, there’s a ton of variation – and that’s a good thing! I adore having options to find what works for me, and I want to have other people have options and choices to choose what works for them.

That being said, here’s the answer to how I run my CGMs and some of the things that have factored into my choice to not DIY CGM receivers/data processing most of the time:

  • With two G4 receivers, I can keep one in my pocket, paired to my phone and uploading via Share. When I’m out and about in the city or usually during the day, this is what I carry. When I run, I take the Share receiver.
  • But, I also like emergency back-ups. I like keeping a receiver plugged into an #OpenAPS rig so that if connectivity goes out/down, I can keep looping without a break in my stride. So, I could keep my Share receiver plugged into the rig, but that would involve me unplugging and replugging fairly frequently when I run errands or actually go for a short run, and meh. Hassle. So I keep “non-Share” receiver as the one that’s usually plugged into my ‘offline’ rig.
  • Having the G4 receiver plugged into the rig enables me to see raw data. Raw data is nice for a couple of things: assessing the health of my sensor (if it gets jumpy compared to the filtered data, I know the quality of the sensor is decreasing, and that helps me decide when to change it); giving me a clue to what’s going on when the filtered data goes to ??? or during the start up of a new sensor; and actually being able to run my rig and loop off some* of the raw data when I need to. (*With OpenAPS, you can choose to loop off of it within a certain range, and there’s an option to only set a certain amount of correction for a proportion of what otherwise would be proposed, with a higher level of raw data.)
  • With two receivers running, that also gives me more flexibility around sensor changes. Technically, the sensor is approved for 7 days. At the end of the 7 days, the receiver stops giving you data and forces you to “start” a new sensor session. That could be by inserting a new sensor; or it could be the same sensor on your body. But either way, theoretically it’s a 2 hour ‘warm up’ period from that session where you can’t see data. With 2 receivers, I can stagger the end and start of sensor sessions. I usually set a calendar alarm to restart one of the receivers on the night of the 6th day of the session, allowing me more flexibility on day 7 to choose when to restart or change my sensor.
  • This also means I can choose to “hot swap” when actually changing a sensor. I may choose to not hit ‘stop’ and ‘start’ on a sensor session on one of the receivers, but rather shut it off for about 30 minutes, and just do the stop/start on the other receiver (leaving it plugged into a rig to upload raw data to NS, and be able to see where the new sensor’s readings come in compared to the old one). When I power the non-restarted receiver back on about 30m after swapping the transmitter over to the new receiver (as soon as the raw readings have flattened out), it usually either goes to “no signal” for a few minutes, and then comes back with some data, an hour or more before the restarted sensor allows me to calibrate it and get data. There are downsides to this method: the data on the receiver that didn’t get restarted can be fairly inaccurate, as it’s still using the calibrations from the old sensor. So I don’t always do that, but when it’s more important to me to be able to see relative trend of where BG is (flat, or dropping or spiking), it’s nice to have that option. And since I often soak my new CGM sensors, the data from “day 1” of the sensor after a session “start” on the receiver is often better than if it was truly day 1 of the sensor being in my body.

Phew. Maybe that sounds like a lot of work, but the above setup works well for me for a variety of reasons, and also allows me the flexibility and choice for when I change sensors, when I am forced to be without data or potentially not loop, etc. Given that my schedule varies a lot, it helps since I’m not consistently in the same time zone and what works for starting or changing sensors one week in one part of the world doesn’t always align with convenience exactly 168 hours (7 days) later in another part of the world that I’m in, doing something differently.

Some of the reasons I haven’t switched to G5 include the fact that the transmitters only last for ~3 months instead of 6+ months; I’ve observed many people being frustrated by sensor not talking to the phone even when it’s right beside them; there’s no raw data on G5; you can’t have multiple receivers paired with your transmitter; etc.

Now, you might say, but that’s using Dexcom’s app, etc. With DIY solutions, those limitations don’t apply! And that’s true, to a degree – savvy folks in the community have figured out how to make it so you don’t *have* to use Dexcom’s app to display or process the data; you can replace the batteries on the transmitter; etc. But, just like my method above of using raw data isn’t necessarily going to work for everyone or might not be something someone else choose to do, the DIY options that go with G5 (or even G4 in some cases), aren’t something I believe is the right thing to do for me.

A lot of it comes down to safety. When we first started designing my DIY closed loop, we spent eons discussing how we could do this safely for me. And that evolved into further discussions about how other people could do this safely, too. A core of the OpenAPS Reference Design is that we are using already approved and vetted devices that exist on the market (e.g. existing pumps and CGMs). Those devices include approved and vetted methods for CGM data processing, too, which is even more important when the CGM data is being used to dose insulin as in OpenAPS. Now – this is not a requirement we can enforce: people can do what they want, and some people are even using non-CGMs (such as the Libre, a “Flash Glucose Monitoring” solution, plus a DIY NFC reader) as a CGM source for looping. But, whether it’s a DIY app or algorithm on CGM data, or a different glucose measuring device that’s not a CGM, that’s choice has some safety implications that I hope people are aware of.

First, the background for those who aren’t familiar: the CGM companies display a processed (“filtered”) version of the CGM data. That’s part of their proprietary stuff, but there’s reasons behind it: the raw data can be hectic and weird, and individual readings aren’t the point, anyway. The beauty of CGM is you can see the trends in addition to the estimated BG number.  In some scenarios, such as during sensor starts, during error messages that are displayed as ???, etc, the companies/FDA decided that the CGM should not show data, and instead show an error message/symbol, to help prevent anyone from making incorrect treatment decisions based off of confusing or misleading data.  That’s good enough most of the time.  As mentioned above, there are edge cases when seeing the raw is helpful, but most of the time, I’m happy with the filtered data.

But to me, there’s a difference between using raw or DIY-calibrated data for edge cases, vs. using them all the time. I’ve seen several cases in just the past few days with a newer “DIY CGM app”, which uses its own calibration algorithm for processing the unfiltered CGM readings.  These people have reported the app displaying normal BGs (say, 90 mg/dL), while they found themselves in the 40’s (rather low). It’s not clear whether that is due to the app’s calibration algorithm, something the user did in testing and calibrating, or if it’s just a bad sensor, and since most of them are not using the official receiver/app in parallel, that’s difficult to figure out.  But regardless, it’s happened enough times across numerous people for me to be concerned about a DIY CGM app being used as the primary source of CGM data. There are limitations to using company-built apps or physical devices for CGMs, but in the case where people can afford it, for safety I think it is important to at least use the approved and vetted receiver/app in parallel, to provide a backup and baseline level of alerting and alarming. The FDA & the companies have worked to create something that can be reliable for alarming when your BG is actually low (say <55 mg/dl) and alerting a human that something is going on. This is important regardless of whether people are looping or not, but it’s perhaps even more important when people are looping, since that data is driving insulin dosing decisions. Additionally, the company-created devices have been designed to deal with miscalibrations that aren’t in line with what the data from the receiver is showing, and have safety measures in place to “reject” calibrations and request new ones when necessary. Sure: there are times where that’s frustrating, but those features truly are “there for safety”, and are important for avoiding the rare but potentially serious outcomes that could be caused by incorrect CGM readings. Since safety is what we prioritize and design around in DIY closed looping, I hope people will consider that ,and prioritize safety first when choosing what to use as their primary data source.

—

Tl;dr – YDMV. I currently use G4 with two receivers, for the reasons described above. I think it’s important to prioritize safety over convenience most of the time, and understand the limitations of the solution that you choose (DIY or commercial). But everyone’s different, and their situation, preferences, etc. may drive different decision making. And did I mention YDMV?

More open innovation coming soon?

by Dana Lewis

This is a big deal: JDRF just announced funding for companies to open up their device protocols, with an explicit mention of projects including OpenAPS.

This is something we’ve been asking companies for over many years, but even the most forward-thinking diabetes device companies are still limiting patients to read-only retrospective access to the patient’s own data. That’s a start, but it isn’t enough.  We need all device makers to take the next step toward full and open interoperability: participating in open-protocol development of pumps and AP systems. If funding from a major organization like JDRF is what will be needed to prioritize this, great: we’re really excited to see them doing so.

Many of us in the diabetes community have chosen to accept the risk of a flawed device, because of the net risk reduction -and quality of life improvements – that come from being able to DIY closed loop. But that doesn’t mean we’re 100% happy with that.

  • We shouldn’t have to bandaid our pumps – literally – with tape.
  • We shouldn’t have to buy them second hand.
  • We should be able to use in-warranty devices that aren’t physically broken.

In order to use our medical devices in the safest and most effective way possible, we need the ability to remotely and safely control our devices – and understand them – as we see fit.  That means the makers of the medical devices we rely on need to openly document the communications protocols their devices use, so that any informed patient, or any company or organization operating on their behalf, can safely interact with the device.

It’s a big deal for JDRF to put resources into helping companies figure out how to do this, and ease liability and regulatory concerns. Thanks to everyone who’s been a vocal advocate in the DIY community; in organizations like JDRF; and individuals advocating at the medical device companies as well.  And props to the FDA, who last month released official guidance encouraging device makers to “design their devices with interoperability as an objective” and “clearly specify the relevant functional, performance, and interface characteristics to the user.”

We all have the same goals – to make life better, and safer, for those of us living with type 1 diabetes. I’m excited to see more efforts like this that further align all of our activities toward these goals.

To the diabetes device companies: we’ve long said we are happy to help if you want to figure out how to do this. Hopefully, you already have ideas about how to do this smartly and safely. But if you need help, let us know – we’re happy to help, because #WeAreNotWaiting and neither should you.

 

Half life

by Dana Lewis

I have now lived with diabetes for more than half of my life.

That also means I have now lived less than half of my life without diabetes.

This somehow makes the passing of another year living with diabetes seem much more impactful to me. Maybe not to you, or to someone else with a different experience of living with diabetes and a different timeline of life before and after diagnosis…but to me this is a big one.

I’m happy to have context, though, to help me keep things in perspective. For example, I’ve now lived with a closed loop artificial pancreas (or automated insulin delivery) system for almost two full years.

(That’s almost as significant a marker of a “with” vs. “without” comparison as living “with” vs. “without” diabetes.)

And because I ended up with type 1 diabetes, I found out that doing things for other people and the communities you’re a part of is a powerful way to help yourself, both in the short term and the long term. That’s what drove me to figure out a way to take #DIYPS closed loop and make it something open source. And by doing that, I learned so much more about open source, and have been able to partner with incredible people innovating in hardware and software. These collaborations have resulted in an incredibly rich community of passionate people I like to call #OpenAPS-ers.

While #OpenAPS is by no means a cure, and no artificial pancreas will be a cure, they provide an immeasurably improved quality of life that a lot of us didn’t realize was possible with diabetes. Someone told me he can get the same results for his child living with diabetes, but with #OpenAPS it requires about 85% less work. And given the enormous time and cognitive burden of diabetes, this is a HUGE reduction.

And now doors are opening for us collectively to make even more of a significant impact on the diabetes community, and our fellow patient communities. Yesterday, while at the White House Frontiers conference, NIH Director Dr. Francis Collins was in the audience during my panel. At the end of the day, he stopped me to ask questions about my experiences and perspective on the FDA and what we need from the government. I was able to talk with him about the need for FDA & other parts of the government to help foster and support open source innovation. We talked about the importance of data access for patients, and the need for data visibility on commercially approved medical devices.

Showing former NIH Director Francis Collins my OpenAPS rig and talking about data interoperability.

This is not just a need of people with diabetes (although it’s certainly very applicable for all of the manufacturers with pipelines full of artificial pancreas products): these are universal needs of people dealing with serious health conditions.

Given what I heard yesterday, it’s working. The #WeAreNotWaiting spirit is infusing our partners in these other areas. We are planting seeds, building relationships, and working in collaboration with those at the FDA, NIH, HHS in addition to those in industry and academia. I know they were working toward these same goals before, but social media has helped raise up our collective voices about the burning need to make things better, sooner, for more people.

So if I have to live the rest of my life at a ratio where more than half of it has been spent living with diabetes, I look forward to continuing to work to get to an 85% reduction in the burden of daily life with diabetes for everyone.

 

Old news alert: FDA is monitoring the DIY community

by Dana Lewis
There was a news article today that got a lot of people to react strongly. In that sense, the article did it’s job, to get people talking. But that doesn’t mean it got all the details right, as an insider to the DIY community would know.

What am I talking about?

There was an article posted today in “Clinical Endocrinology News” with the titillating headline of “FDA Official: We’re monitoring DIY artificial pancreas boom”.

Guess what, though? This is NOT news. We’ve been talking to the FDA, and they’ve in fact been “monitoring” us (especially if monitoring includes reading this blog, DIYPS.org ;)) since the summer of 2014, before we even turned our eyes toward closing the loop. Definitely since we, while they were in the room at a D-Data in 2015, announced we would close the loop. And even more so after we closed the loop and then decided to go the #OpenAPS route and find a way to make closed loop technology open source. And others from the community, like Ben West, have been talking with the FDA for even longer than we have.

What the article got right:

Recently at AADE, Courtney Lias from FDA (who gave a similar presentation at D-Data a month ago) gave a presentation talking about AP technology. She addressed both how the FDA is looking at the DIY community (they believe that they have enforcement discretion, even though no one in the DIY community is distributing a medical device, which is legally where FDA has it’s jurisdiction) and how it’s looking at the commercial vendors with products in the pipeline.

Courtney highlighted questions for CDE’s to ask patients of theirs who may be bringing up (or bringing in) DIY closed loops. They are good questions – they’re questions we also recommend people ask themselves and are a critical part of the safety-first approach the DIY community advocates every day.

(It was not mentioned in this article, but Aaron Kowalski’s presentation at AADE also highlighted some critical truths that I think are key about setting and managing expectations regarding closed looping. I often talk about these in addition to pointing out that it should be a personal, informed choice in choosing to closed loop. I hope these points about setting expectations and our points about the stages of switching from standard diabetes tool to closed looping becomes a bigger part of the conversation about closed loop safety and usability in the future.)

Where the article linked together some sentences that caused friction today:

The end of the article had a statement along the lines of an FDA concern about what happens if an AP breaks and you have a newly diagnosed person who doesn’t have old school, manual diabetes methods to fall back on. The implication appeared to be that these concerns were solely about the DIY looping “boom”. However, we know from previous presentations that Courtney/FDA usually brings this up as a concern for commercial/all AP technology – this isn’t a “concern” unique to DIY loops.

And that’s the catch – all of the concerns and questions FDA has, the DIY community has, too!

In fact, we want FDA to ask the same questions of commercial vendors, and we are going to be reaching out to the FDA to ask how they will ensure that we, as patients, can ask and get answers to these questions as end users when the FDA is approving this technology.

Because that’s the missing piece.
Right now, with the current technology on the market, we don’t get answers or insight into how these systems and devices work. This is even MORE critical when we’re talking about devices that automate insulin delivery, as the #OpenAPS community has learned from our experiences with looping. Getting the right level of data access and visibility is key to successful looping, and we expect the same from the commercial products that will be coming to market – so the FDA has a role to play here.

What we can do as a result
And we have a role, too. We’ll play our part by communicating our concerns and questions directly to the FDA, which is the only way they can officially respond or react or adjust what they’re doing. They unfortunately can’t respond to tweets. So I’m drafting an email to send to FDA, which will include a compilation of many of the questions and concerns the community has voiced today (and previously) on this topic.

Moving forward, I hope to see others do the same when concerns and questions come up. You don’t need to work for a commercial manufacturer, or be a part of a formal initiative, in order to talk to the FDA. Anyone can communicate with them! You can do that by sending an email, submitting a pre-submission, responding to draft guidances, and more. And we can all, in our informal or formal interactions, ask for clarity and push for transparency and set expectations about the features and products we want to see coming from commercial manufacturers.

Feedback on proposed FDA guidance on interoperable medical devices

by Dana Lewis

Our friend Anna McCollister-Slipp first alerted us to the proposed draft guidance recently released from the FDA, covering medical device interoperability. (You can read the draft guidance linked here.) We were subsequently among those asked by Amy Tenderich, and others, to share our initial thoughts and comments in response to the draft guidance. We wanted to publicly share our initial thoughts as a draft comment in response to the proposed guidelines (which we plan to officially submit as well), in hopes of encouraging subsequent discussion and additional commentary submitted in response to the draft guidance. We’d love to hear your thoughts after you read the linked guidance, as well as our comment below, and also encourage you to consider submitting a comment to the FDA regarding the guidance.

Draft comment response by Scott Leibrand & Dana Lewis:

The proposed FDA guidance on medical device interoperability is a gesture in the right direction, and is clearly intended to encourage medical devices to be designed with interoperability in mind. However, in the current draft form, the proposed guidance focuses too much on *discouraging* manufacturers from including the kinds of capabilities necessary to allow for continued innovation (particularly patient-led innovation as seen from the patient-driven #WeAreNotWaiting community).  Instead, much of the guidance assumes that manufacturers should only provide the bare minimum level of interoperability required for the intended use, and even goes so far as to suggest they “prevent access by other users” to any “interface only meant to be used by the manufacturer’s technicians for software updates or diagnostics”.  There is also much note of “authorized users”, which is language that is often currently leaned upon in the real world to exclude patients from accessing data on their own medical devices – so it would be worthwhile to further augment the guidance and/or more specifically review the implications of the guidance with an eye toward patients/users of medical devices.  The focus on including information on electronic data interfaces in product labeling is a good inclusion in the guidance, but it would be far more powerful (and less likely to be interpreted as a suggestion to cripple future products’ interoperability capabilities) if manufacturers were encouraged to properly include interface details for *all* their interfaces, not just those for which the manufacturer has already identified an intended use case.

Specific suggestions for improving the proposed guidance on medical device interoperability:
  • The guidance needs to more explicitly encourage manufacturers to design their products for *maximum* interoperability, including the ability for the device to safely interoperate with devices and for use cases that are not covered by the manufacturer’s intended uses.
  • Rather than designing device interoperability characteristics solely for intended uses, and withholding information related to non-intended uses, manufacturers should detail in product labeling the boundaries of the intended and tested use cases, and also provide information on all electronic data interfaces, even those with no manufacturer-intended use.  Labeling should be very clear on the interfaces’ design specifications, and should detail the boundaries of the uses the manufacturer intended, designed for, and tested.
  • The guidance should explicitly state that the FDA supports allowing third parties to access medical devices’ electronic data interfaces, according to the specifications published by the manufacturers, for uses other than those originally intended by the manufacturer.  They should make it clear that any off-label use by patients and health care professionals must be performed in a way that interoperates safely with the medical device per the manufacturer’s specifications, and it is the responsibility of the third party performing the off-label use, not the manufacturer, to ensure that they are making safe use of the medical device and its electronic data interface.  The guidance should make clear that the manufacturer is only responsible for ensuring that the medical device performs as specified, and that those specifications are complete and accurate.
With these kinds of changes, this guidance could be a powerful force for improving the pace of innovation in medical devices, allowing us to move beyond “proprietary” and “partnership” based solutions to solutions that harness the full power of third-party innovation by patients, health care professionals, clinical researchers and other investigators, and startup technology companies.  The FDA needs to set both clear rules that require manufacturers to document their devices capabilities as well as guidance that encourages manufacturers to provide electronic data interfaces that third parties can use to create new and innovative solutions (without introducing any new liability to the original manufacturer for having done so).  If the FDA does so, this will set the stage to allow innovation in medical devices to parallel the ever-increasing pace of technological innovation, while preserving and expanding patients rights to access their own data and control their own treatment.

Does the FDA care more about safety than people with diabetes do?

by Dana Lewis

Today my inbox was suddenly flooded with links to a video with some commentary about artificial pancreas technology at a conference by a representative of the U.S. FDA. The implication many people are getting after watching the video clip is that this FDA representative is implying that people are being unsafe by building their own artificial pancreas. He mentions it is consumer prerogative to build an artificial pancreas – which is correct. The implication of his analogy is that changing your car and killing yourself is similar to a DIY artificial pancreas effort.

The scary takeaway from the video, in my opinion, as well as other public comments in the past, is the implication that the FDA cares more about the potential harms of taking action than the almost certain harms of inaction. And it’s increasingly frustrating that the FDA appears to imply publicly that those of us in the #wearenotwaiting community are doing things unsafely as a result of taking action.

Safety is what drives the #wearenotwaiting movement. In my case, I refuse to sleep another night with the fear that I won’t wake up in the morning because there’s not an FDA-approved system on the market that will wake me up if my life is in danger, let alone a system that can take action and change the situation to be more safe. So I built my own (#DIYPS), because the current FDA-approved CGM devices were not (and still are not) loud enough to wake me up at night, putting me at risk of dying in my sleep. And yes, it ultimately turned into an artificial pancreas – with the same goal of ensuring I wake up every morning, safely (alive). That is my prerogative for sure.

But I fail to see why the FDA, which collectively has no particular knowledge of these systems (especially as they have no jurisdiction, acknowledged on all fronts, over what I do myself – it’s my prerogative), is making public statements implying that these types of systems are categorically unsafe.

As a matter of fact, every DIY system I’ve seen is safer than the FDA-approved standard of care available for people with diabetes. The thousands of people using Nightscout, which is currently a DIY remote view-only monitoring system? Provides more safety and security for people with diabetes, not to mention it is helping achieve better outcomes for people with diabetes than they were able to achieve before with the standard of diabetes care as it exists today. (This was originally for the most part because of restricted access to data, although while that has improved there’s still interoperability issues getting access to real-time data in the same place from the 3+ average devices a person with diabetes uses…unless they have Nightscout or another DIY tool running.) The dozens of people working on their DIY version of an artificial pancreas system (many of whom are collaborating and sharing data in the #OpenAPS community)? These systems are safer than the standard of care, which is to let an insulin pump continue to overdose you if you are dangerously low while you sleep.

(You can see some of my personal data from #DIYPS, before we closed the loop, here and more about outcomes after we closed the loop and had #OpenAPS here. My closed loop artificial pancreas system continues to work excellently nine plus months in, and you can continue to watch my outcomes as I post them to Twitter regularly using the #DIYPS and #OpenAPS hashtags. I’ve also shared the other powerful lessons that DIY tech has helped me learn about diabetes care that helps all people with diabetes, regardless of technology.)

Are there risks to DIY efforts? Yes. But there’s risks to living with diabetes regardless. And as a person with diabetes, I am well aware of the risks that I choose to take. Diabetes is a disease in which you carry around large amounts of a lethal drug in your pocket that you are supposed to inject daily in order to save your life. As a person with diabetes, we are nothing but aware of the multitude of risks of living with this chronic disease 24/7/365.

In fact, even without a DIY artificial pancreas system, I am at risk every day simply from using my FDA-approved insulin pump that does not accurately track how much insulin I am given. (Read more here about how most insulin pumps on the market calculate IOB only from boluses, and often do not provide a record let alone incorporate any temporary adjustments to your basal rates and do not in any case track the impact of suspending your pump completely.)

And as someone who has founded the #OpenAPS movement, with the goal of an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of type 1 diabetes…..we approach it with safety first in mind, and is a big part of why the DIY part is critical and is a part of our number one priority of safety.

Not everyone will choose to go the DIY route. In fact, most people do not and I am told all the time “Oh, I would never do that.” And that’s fine! Everyone can choose what they want for themselves.

But technology has made it increasingly feasible for those of us who want to improve our own safety to do so, because the industry and the FDA are not moving quickly enough to meet our needs.

That, indeed, is our prerogative – to increase our own safety.