Month: May 2017

Unexpected side-effect of closed looping: Body re-calibrations

by Dana Lewis

It’s fascinating how bodies adapt to changing situations.

For those of us with diabetes: do you remember the first time you took insulin after diagnosis? For me, I had been fasting for ~18 hours (because I felt so bad, and hadn’t eaten anything since dinner the night before) and drinking water, and my BG was still somehow 550+ at the endo’s office.

Water did nothing for my unquenchable thirst, but that first shot of insulin first sure did.

I still remember the vivid feeling of it being an internal liquid hydration for my body, and everything feeling SO different when it started kicking in.

In case the BG of 550+, the A1c of 14+ (don’t remember exact number), and me feeling terrible for weeks wasn’t enough, that’s one of the things that really reinforced that I have diabetes and insulin is something my body desperately needs but wasn’t getting.

Over the last ~14+ years, I’ve had a handful of times that reinforced the feeling of being dependent on this life-saving drug, and the drastic difference I feel with and without it. Usually, it’s been times where a pump site ripped out, or I was sick and high and highly resistant, and then finally stopped being as resistant and my blood sugar started responding to insulin finally after hours of being really high, and I started dropping.

But I’ve had different ways to experience this feeling lately, as a result of having live with a DIY closed loop (OpenAPS) for 2+ years – and it hasn’t involved anything drastic as a HIGH BG or equipment failure. It’s a result of my body re-calibrating to the new norm of my body being able to spend more and more time close to 100% in range, in a much tighter and lower range than I ever thought possible (especially now true with some of the flexibility and freedom oref1 now offers).

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I originally had a brief fleeting thought about how BGs in the low 200s used to feel like the 300s did. Then, I realized that 180 felt “high”. One day, it was 160.

Then one day, my CGM said flat in 120s and I felt “high”. (I calibrated, and turned out that it was really 140). I’ve had several other days where I’d hit 140s and feel like I used to do in the mid-200s (slightly high, and annoying, but no major high symptoms like 300-400 would cause – just enough to feel it and be annoyed).

That was odd enough as a fleeting thought, but it was really odd to wake up one morning and without even looking at my watch or CGM to see what my BGs had been all night, know that I had been running high.

I further classified “really odd” as “completely crazy” when that “running high” meant floating around the 130-140 range, instead of down in the 90-110 range, which is where I probably spend 95% of my nights nowadays.

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Last night is what triggered this blog post, plus a recurring observation that because I have a DIY closed loop that does so well at handling the small, unknown variances that cause disturbances in BG levels without me having to do much work, that as result it is MUCH easier to pinpoint major influences, like my liver dumping glucose (either because of a low or because it’s ‘full up’ and needs to get rid of the excess).

In last night’s case, it was a major liver dump of glucose.

Here’s what happened:

Scott and I went on a long walk, with the plan to stop for dinner on the way home. BG started dropping as I was about half a mile out from the restaurant, but I’m stubborn 😀 and didn’t want to eat a fruit strip when I was about to sit down an eat a burger. So, my BG was dropping low when I actually ate. I expected my BG to flatten on its own, given the pause in activity, so I bolused fairly normally for my burger, and we walked the last .5 miles home.

However, I ended up not rising from the burger like I usually do, and started dropping again. It was quite a drop, and I realize my burger digestion was different because of the previous low, so I ended up eating some fruit to handle the second low. My body was unhappy at two lows, and so my liver decided to save the day by dumping a bunch of glucose to help bring my blood sugar up. Double rebound effect, then, from the liver dump and the fruit I had eaten. Oh well, that’s what a closed loop is for!

Instead of rebounding into the high 300s (which I would have expected pre-closed loop), I maxed out at 220. The closed loop did a good job of bolusing on the way up. However, because of how much glucose my liver dumped, I stayed higher longer. (Again, this probably sounds crazy to anyone not looping, as it would have sounded to me before I began looping). I sat around 180 for the first three hours of the night, and then dropped down to ~160 for most of the rest of the night, and ended up waking up around 130.

And boy, did I know I had been high all night. I felt (and still feel, hours later) like I used to years ago when I would wake up in the 300s (or higher).

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Visuals

recalibration_3 hourHmm, 3 hours doesn’t look so bad despite feeling it.

recalibration_6 hour6 hour view shows why I feel it.

recalibration_12 hour12 hours. Sheesh.

recalibration_24 hour24 hours shows you the full view of the double low and why my liver decided I needed some help. Thanks, liver, for still being able to help if I really needed it!

recalibrating_pebble view of renormalizing Settling back to normal below 120, hours later.

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There are SO many amazing things about DIY closed looping. Better A1c, better average BG, better time in range, less effort, less work, less worrying, more sleep, more time living your life.

One of the benefits, though, is this bit of double-edged sword: your body also re-calibrates to the new “normal”, and that means the occasional extreme BG excursion (even if not that extreme!) may give you a different range of symptoms than you used to experience.

Different ways to make a difference

by Dana Lewis

tl,dr: There are many ways to make a difference, ranging from donating time/energy/ideas to financially supporting organizations who are making a difference.

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When I was first diagnosed with diabetes (at age 14, three months into high school – ugh), I was stunned. And I didn’t want anyone to know, because I didn’t want to be treated differently. So for the first few months, I learned how to take care of myself, and did that quietly and went about my life: school, color guard, etc. I was frustrated with the idea of having to do all this stuff for the rest of my life, and wanted as little as possible to have to talk/think about it beyond the bare minimum I had to do.

However, after I talked the Latin Club into making our fundraising dollars from the Rake-a-thon go toward the American Diabetes Association, and I saw the reaction of the local staff when I walked in and dropped a check on the desk and turned around and tried to walk out the door. (They didn’t let me just walk out!) I agreed to volunteer and do more, and it changed my life.

I don’t know what first thing I did, but I quickly came to realize that doing things for the broader population of people with diabetes – maybe they had type 2, maybe they lived somewhere else, didn’t matter – made me feel SO much better about my own life with type 1 diabetes. I wasn’t alone. And so my mantra became “Doing something for someone else is more important than anything you would do for yourself.” And it’s proved to be true for me for 14 years.

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Since I grew up in Alabama, that’s where I started getting involved first. Inspired by my parents’ volunteer efforts that I saw growing up, I would volunteer my time and energy for a variety of things:

  • Fundraising for the local walk
  • Actually helping out the day of the walk
  • Joining the planning committee for the walk and spending months helping figure everything out and doing both actual and metaphorical heavy lifting to help make the event happen

Because of my volunteer efforts, I was asked to speak at a fundraising breakfast in Birmingham. It was my first time ever giving a public talk, let alone publicly talking about living with diabetes. And because of the people I met that day, I began doing more volunteer things around the state – and it led me to applying and being selected as the National Youth Advocate for the American Diabetes Association, and later serving on national committees like the National Youth Strategies committee (where we developed and improved the “Wisdom” kits for newly diagnosed kids with diabetes, created a kid-focused section of the ADA website, etc.). And my involvement continued as I graduated college and moved to Seattle, still serving on national committees but also joining the Western Washington Leadership Board and doing the same type of local event volunteering, but now in Seattle. I also have done more around advocacy over the years, beyond my time as NYA. While in college, I was asked to testify before the Senate HELP committee, talking about the need to increase funding for disease research. I’ve also participated regularly in ADA’s Call to Congress, including this year, where Scott and I paid to fly to DC and talk with our Washington state representatives and senators about the critical need for funding NIH & CDC; maintaining critical diabetes programs; and the issues around insulin affordability.

But it was when I was asked to represent the US and attend the World Diabetes Congress in 2006 when my eyes were opened to the issues around insulin access and affordability.

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IDF first did a youth ambassador program in 2006, bringing around two dozen young adults with diabetes to the World Diabetes Congress to participate, train in advocacy activities, etc.

Having grown up in Alabama, where diabetes (particularly type 2) is highly prevalent, I knew that not everyone could afford pumps and CGMs (especially back then, when CGMs were brand new, way less accurate, and still super expensive, even with insurance coverage). I also knew that insulin & supplies were expensive, and some people struggled with gaining access to them. (And I always felt very fortunate that since diagnosis, my parents were able to afford my insulin & supplies.)

However, while in South Africa, I learned from my new friends from other parts of Africa and the rest of the world that this was the tippy top of the ice berg. I learned about:

  • Kids are walking alone on roads for miles and hours to get to a clinic to get a single, daily shot of insulin.
  • They may only test their BGs once a week, or month, or quarter.
  • It’s not just kids – adults would have to stop working and walk for hours, too, choosing to get insulin to stay alive to be able to work another few days to help their family survive.
  • Some people would only get insulin once a week, if that, or once a day – compared to me, where I might have several injections a day, as often as needed to keep my BGs in a safe range.

It was astonishing, saddening, maddening, and terrifying. And living so far away from this part of the world, I wasn’t sure how I could help, until I met Graham Ogle who created the “Life for a Child” program to help tackle the problem, with the vision that no child should die of diabetes. Life for a Child helps less resource-supported countries provide insulin, syringes, other supplies, and education (both for people living with diabetes and healthcare providers). And, they’re a very resource-efficient organization.

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When Scott and I first met, he knew nothing about diabetes (and actually thought my insulin pump was a pager – hah!). And while I volunteered a lot of my time and energy to help organizations, he is also dedicated to finding effective ways to safe lives, and as a result, is a longtime donor to Givewell.org and some of their top charities, like Against Malaria Foundation. Givewell is a nonprofit dedicated to finding giving opportunities and publishing the full details of their analysis to help donors decide where to give. And unlike charity evaluators that focus solely on financials, assessing administrative or fundraising costs, they conduct in-depth research aiming to determine how much good a given program accomplishes (in terms of lives saved, lives improved, etc.) per dollar spent.

Therefore, when Scott and I got married, we decided that in lieu of wedding-related gifts, we would ask people to support our charities of choice, to further increase the impact we would be able to have in addition to our own financial and other resource donations.

However, Life for a Child was not evaluated by Givewell. So Scott and I got on a Skype call with Graham Ogle to crunch through the numbers and try to come up with an idea for how effective Life for a Child is, similar to what Givewell has already done for other organizations.

For example, the Against Malaria Foundation, the recommended charity with the most transparent and straightforward impact on people’s lives, can buy and distribute an insecticide-treated bed net for about $5.  Distributing about 600-1000 such nets results in one child living who otherwise would have died, and prevents dozens of cases of malaria.  As such, donating 10% of a typical American household’s income to AMF will save the lives of 1-2 African kids *every year*.

Life for a Child seems like a fairly effective charity, spending about $200-$300/yr for each person they serve (thanks in part to in-kind donations from pharmaceutical firms). If we assume that providing insulin and other diabetes supplies to one individual (and hopefully keeping them alive) for 40 years is approximately the equivalent of preventing a death from malaria, that would mean that Life for a Child might be about half as effective as AMF, which is quite good compared to the far lower effectiveness of most charities, especially those that work in first world countries.

(And some of the other charities and organizations don’t have clear numbers that can be this clearly tracked to lives saved. It’s not to say they’re not doing good work and improving lives – they absolutely are, and we support them, too – but this is one of the most clear and measurable ways to donate money and have a known life-saving impact related to diabetes.)

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I am asked fairly frequently about what organization I would recommend donating to, in terms of diabetes research or furthering the type of work we’re doing with the OpenAPS community. It’s a bit of a complicated answer, because there is no organization around or backing the OpenAPS community’s work, and there are many ways to donate to diabetes research (i.e. through bigger organizations like ADA and JDRF or directly to research projects and labs if you know of a particular research effort you want to fund in particular).

And also, I think it comes down to seeing your donation make a difference. If you’d ask Scott, he would recommend AMF or other Givewell charities – but he’s seen enough people ask me about diabetes-related donation targets to know that people are often asking us because of wanting to make a difference in the lives of people with diabetes.

So, given all the ways I’ve talked about making a difference with different volunteer efforts (and the numerous organizations with which you could do so), and the options for making a financial donation: my recommendation for the biggest life-saving effort for your dollar will be to donate to Life for a Child, to help increase the number from the 18,000 children and 46 countries they’re currently helping in. (And, they now have a US arm, so if you are in the US your donation is tax-deductible).

You may have a different organization you decide to support – and that’s great. Thank you to everyone who donates money, time, and energy to organizations who are working to make our lives better, longer, and the world in general to be a better place for us all.

This. Matters. (Why I continue to work on #OpenAPS, for myself and for others)

by Dana Lewis

If you give a mouse a cookie or give a patient their data, great things will happen.

First, it was louder CGM alarms and predictive alerts (#DIYPS).

Next, it was a basic hybrid closed loop artificial pancreas that we open sourced so other people could build one if they wanted to (#OpenAPS, with the oref0 basic algorithm).

Then, it was all kinds of nifty lessons learned about timing insulin activity optimally (do eating soon mode around an hour before a meal) and how to use things like IFTTT integration to squash even the tiniest (like from 100mg/dL to 140mg/dL) predictable rises.

It was also things like displays, button, widgets on the devices of my choice – ranging from being able to “text” my pancreas, to a swipe and button tap on my phone, to a button press on my watch – not to mention tinier sized pancreases that fit in or clip easily to a pocket.

Then it was autosensitivity that enabled the system to adjust to my changing circumstances (like getting a norovirus), plus autotune to make sure my baseline pump settings were where they needed to be.

And now, it’s oref1 features that enable me to make different choices at every meal depending on the social situation and what I feel like doing, while still getting good outcomes. Actually, not good outcomes. GREAT outcomes.

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With oref0 and OpenAPS, I’d been getting good or really good outcomes for 2 years. But it wasn’t perfect – I wasn’t routinely getting 100% time in range with lower end of the range BG for a 24hour average. ~90% time in range was more common. (Note – this time in range is generally calculated with 80-160mg/dL. I could easily “get” higher time in range with an 80-180 mg/dL target, or a lot higher also with a 70-170mg/dL target, but 80-160mg/dL was what I was actually shooting for, so that’s what I calculate for me personally). I was fairly happy with my average BGs, but they could have been slightly better.

I wrote from a general perspective this week about being able to “choose one” thing to give up. And oref1 is a definite game changer for this.

  • It’s being able to put in a carb estimate and do a single, partial bolus, and see your BG go from 90 to peaking out at 130 mg/dL despite a large carb (and pure ballpark estimate) meal. And no later rise or drop, either.
  • It’s now seeing multiple days a week with 24 hour average BGs a full ~10 or so points lower than you’re used to regularly seeing – and multiple days in a week with full 100% time in range (for 80-160mg/dL), and otherwise being really darn close to 100% way more often than I’ve been before.

But I have to tell you – seeing is believing, even more than the numbers show.

I remember in the early days of #DIYPS and #OpenAPS, there were a lot of people saying “well, that’s you”. But it’s not just me. See Tim’s take on “changing the habits of a lifetime“. See Katie’s parent perspective on how much her interactions/interventions have lessened on a daily basis when testing SMB.

See this quote from Matthias, an early tester of oref1:

I was pretty happy with my 5.8% from a couple months of SMB, which has included the 2 worst months of eating habits in years.  It almost feels like a break from diabetes, even though I’m still checking hourly to make sure everything is connected and working etc and periodically glancing to see if I need to do anything.  So much of the burden of tight control has been lifted, and I can’t even do a decent job explaining the feeling to family.

And another note from Katie, who started testing SMB and oref1:

We used to battle 220s at this time of day (showing a picture flat at 109). Four basal rates in morning. Extra bolus while leaving house. Several text messages before second class of day would be over. Crazy amount of work [in the morning]. Now I just have to brush my teeth.

And this, too:

I don’t know if I’ve ever gone 24 hours without ANY mention of something that was because of diabetes to (my child).

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Ya’ll. This stuff matters. Diabetes is SO much more than the math – it’s the countless seconds that add up and subtract from our focus on school/work/life. And diabetes is taking away this time not just from a person with diabetes, but from our parents/spouses/siblings/children/loved ones. It’s a burden, it’s stressful…and everything we can do matters for improving quality of life. It brings me to tears every time someone posts about these types of transformative experiences, because it’s yet another reminder that this work makes a real difference in the real lives of real people. (And, it’s helpful for Scott to hear this type of feedback, too – since he doesn’t have diabetes himself, it’s powerful for him to see the impact of how his code contributions and the features we’re designing and building are making a difference not just to BG outcomes.)

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Thank you to everyone who keeps paying it forward to help others, and to all of you who share your stories and feedback to help and encourage us to keep making things better for everyone.

 

Why guess when you don’t have to? (#OpenAPS logs & why they’re handy)

by Dana Lewis

One of the biggest benefits (in my very biased opinion) of a DIY closed loop is this: it’s designed to be understandable to the person using it.

You don’t have to guess “what did it do at 2am?” or “why did it do a temp basal and not an SMB?”

Well, you COULD guess – but you don’t have to. Guessing is a choice ;).

Because we’ve been designing a system that a person has to decide to trust, it provides information about everything it’s doing and the information it has. That’s what “the logs” are for, and you can get information from “the logs” from a couple of places:

  • The OpenAPS “pill” in Nightscout
  • Secondary logging sources like Papertrail
  • Information that shows up on your Pebble watch
  • The full logs from SSH’ing into a rig (usually what we mean when we ask, “what do your logs say?”)

Here’s an example of the information the OpenAPS pill provides me in Nightscout:

Example OpenAPS pill info in Nightscout

This tells me that at 11:03 am, my BG was 121; I had no carbs on board; was dropping a tiny bit as expected and was likely going to end up slightly below my target; and the current temporary basal rate running was about equivalent to what OpenAPS thought I needed at the time. I had 0.47 netIOB, all from basal adjustments. It also specifies some of the eventual numbers that are what trigger the “purple line predictions” displayed in Nightscout, so if you can’t tell where the line is (90 or 100?), you can use the pill information to determine that more easily.

(Here’s the instructions for setting up Nightscout for OpenAPS)

Here’s an example of a log from Papertrail and what it tells us:

Example papertrail usage for OpenAPS

This example is from Katie, who described her daughter’s patterns in the morning: when Anna leaves her rig in the bedroom and went to take a shower, you can see the tune change at around 6:55, meaning she’s out of range of the rig. After the shower, getting dressed, and getting back to the rig around 7:25, it goes back to “normal” tuning (which means reading and writing to the pump as usual).

Papertrail is handy for figuring out if a rig is working or not remotely and high level why it might not be, especially if it’s a communication or power problem. But I generally find it to be most helpful when you know what kind of problem it is, and use it to drill down on a particular thing. However, it’s not going to give you absolutely all the details needed for every problem – so make sure to read about how to access the traditional logs, too, and be able to do that on the go.

(Here’s the instructions for getting Papertrail going for OpenAPS)

Here’s what the logs ported to my Pebble tell me:

OpenAPS logs on Pebble watch @DanaMLewis example

There’s several helpful things that display on my watch (using the excellent “Urchin” watchface designed by Mark Wilson, which you can customize to suit your personal preference): BGs, basal activity, and then some detailed text, similar to what’s in the OpenAPS pill (current BG, the change in BG, timestamp of BG, my netIOB, my eventual BGs, and any temp basal activity). In this case, it’s easy for me to glance and see that I was a bit low for a while; am now flat but have negative net IOB so it’s been high temping a bit to level out the netIOB.

(I’ve always preferred a data-rich watchface – even back in the days of “open looping” with #DIYPS:)

https://twitter.com/danamlewis/status/652566409537433600/photo/1

(Here’s more about the Urchin watchface)

Here’s what the full logs from the rig tell me:

Example OpenAPS logs from the rig

This has a LOT of information in it (which is why it’s so awesome). There are messages being shared by each step of the loop – when it’s listening for “silence” to make sure it can talk successfully to the pump; refreshing pump history; checking the clocks on devices and for fresh BGs; and then processing through the math on what the BG is, where it’s headed, and what needs to happen. You can also see from this example where autosensitivity is kicking in, adjust basals slightly up, target down, and sensitivity down, etc. (And for those who aren’t testing oref1 features like SMB and UAM yet, you’ll get a glimpse of how there’s now additional information in the logs about if those features are currently enabled.)

(Here are some other logs you can watch, and how to run them)

Pro tip for OpenAPS users: if you’re logged into your rig, you just have to type l (the letter “L” but lower case) for it to bring up your logs!

So if you find yourself wondering: what did OpenAPS do/why did it do <thing>? Instead of wondering, start by looking at the logs.

And remember, if you don’t know what the problem is – the full logs are the best source of information for spotting what the main problem is. You can then use the information from the logs to ask about how to resolve a particular problem (Gitter is great for this!)– but part of troubleshooting well/finding out more is taking the first step to pull up your logs, because anyone who is going to help you troubleshoot will need that information to figure out a solution.

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And if you ever see someone say “RTFL”, instead of “read the manual” or “read the docs”, it means “read the logs”. 😉 :)

Choose One: What would you give up if you could? (With #OpenAPS, maybe you can – oref1 includes unannounced meals or “UAM”)

by Dana Lewis

What do you have to do today (related to daily insulin dosing for diabetes) that you’d like to give up if you could? Counting carbs? Bolusing? Or what about outcomes – what if you could give up going low after a meal? Or reduce the amount that you spike?

How many of these 5 things do you think are possible to achieve together?

  • No need to bolus
  • No need to count carbs
  • Medium/high carb meals
  • 80%+ time in range
  • no hypoglycemia

How many can you manage with your current therapy and tools of choice?  How many do you think will be possible with hybrid closed loop systems?  Please think about (and maybe even write down) your answers before reading further to get our perspective.

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With just pump and CGM, it’s possible to get good time in range with proper boluses, counting carbs, and eating relatively low-carb (or getting lucky/spending a lot of time learning how to time your insulin with regular meals).  Even with all that, some people still go low/have hypoglycemia.  So, let’s call that a 2 (out of 5) that can be achieved simultaneously.

With a first-generation hybrid closed loop system like the original OpenAPS oref0 algorithm, it’s possible to get good time in range overnight, but achieve that for meal times would still require bolusing properly and counting carbs.  But with the perfect night-time BGs, it’s possible to achieve no-hypoglycemia and 80% time in range with medium carb meals (and high-carb meals with Eating Soon mode etc.).  So, let’s call that a 3 (out of 5).

With some of the advanced features we added to OpenAPS with oref0 (like advanced meal assist or “AMA” as we call it), it became a lot easier to achieve a 3 with less bolusing and less need to precisely count carbs.  It also deals better with high-carb meals, and gives the user even more flexibility.  So, let’s call that a 3.5.

A few months ago, when we began discussing how to further improve daily outcomes, we also began to discuss the idea of how to better deal with unannounced meals. This means when someone eats and boluses, but doesn’t enter carbs. (Or in some cases: eats, doesn’t enter carbs, and doesn’t even bolus). How do we design to better help in that safety, all while sticking to our safety principles and dosing safely?

I came up with this idea of “floating carbs” as a way to design a solution for this behavior. Essentially, we’ve learned that if BG spikes at a certain rate, it’s often related to carbs. We observed that AMA can appropriately respond to such a rise, while not dosing extra insulin if BG is not rising.  Which prompted the question: what if we had a “floating” amount of carbs hanging out there, and it could be decayed and dosed upon with AMA if that rise in BG was detected? That led us to build in support for unannounced meals, or “UAM”. (But you’ll probably see us still talk about “floating carbs” some, too, because that was the original way we were thinking about solving the UAM problem.) This is where the suite of tools that make up oref1 came from.  In addition to UAM, we also introduced supermicroboluses, or SMB for short.  (For more background info about oref1 and SMB, read here.)

So with OpenAPS oref1 with SMB and floating carbs for UAM, we are finally at the point to achieve a solid 4 out of 5.  And not just a single set of 4, but any 4 of the 5 (except we’d prefer you don’t choose hypoglycemia, of course):

  • With a low-carb meal, no-hypoglycemia and 80+% time in range is achievable without bolusing or counting carbs (with just an Eating Soon mode that triggers SMB).
  • With a regular meal, the user can either bolus for it (triggering floating carb UAM with SMB) or enter a rough carb count / meal announcement (triggering Eating Now SMB) and achieve 80% time in range.
  • If the user chooses to eat a regular meal and not bolus or enter a carb count (just an Eating Soon mode), the BG results won’t be as good, but oref1 will still handle it gracefully and bring BG back down without causing any hypoglycemia or extended hyperglycemia.

That is huge progress, of course.  And we think that might be about as good as it’s possible to do with current-generation insulin-only pump therapy.  To do better, we’d either need an APS that can dose glucagon and be configured for tight targets, or much faster insulin.  The dual-hormone systems currently in development are targeting an average BG of 140, or an A1c of 6.5, which likely means >20% of time spent > 160mg/dL.  And to achieve that, they do require meal announcements of the small/medium/large variety, similar to what oref1 needs.  Fiasp is promising on the faster-insulin front, and might allow us to develop a future version of oref1 that could deal with completely unannounced and un-bolused meals, but it’s probably not fast enough to achieve 80% time in range on a high-carb diet without some sort of meal announcement or boluses.

But 4 out of 5 isn’t bad, especially when you get to pick which 4, and can pick differently for every meal.

Does that make OpenAPS a “real” artificial pancreas? Is it a hybrid closed loop artificial insulin delivery system? Do we care what it’s called? For Scott and me; the answer is no: instead of focusing on what it’s called, let’s focus on how different tools and techniques work, and what we can do to continue to improve them.

Being Shuttleworth Funded with a Flash Grant as an independent patient researcher

by Dana Lewis

Recently, I have been working on helping OpenAPS’ers collect our data and put it to good use in research (both by traditional researchers as well as using it to enable other fellow patient researchers or “citizen scientists). As a result, I have had the opportunity to work closely with Madeleine Ball at Open Humans. (Open Humans is the platform we use for the OpenAPS Data Commons.)

It’s been awesome to collaborate with Madeleine on many fronts. She’s proven herself really willing to listen to ideas and suggestions for things to change, to make it easier for both individuals to donate their data to research and for researchers who want to use the platform. And, despite me not having the same level of technical skills, she emits a deep respect for people of all experiences and perspectives. She’s also in general a really great person.

As someone who is (perhaps uniquely) utilizing the platform as both a data donor and as a data researcher, it has been fantastic to be able to work through the process of data donation, project creation, and project utilization from both perspectives. And, it’s been great to contribute ideas and make tools (like some of my scripts to download and unpack Open Humans data) that can then be used by other researchers on Open Humans.

Madeleine was also selected this year to be a Shuttleworth Fellow, applying “open” principles to change how we share and study human health data, plus exploring new, participant-centered approaches for health data sharing, research, and citizen science. Which means that everything she’s doing is in almost perfect sync with what we are doing in the OpenAPS and #WeAreNotWaiting communities.

What I didn’t know until this past week was that it also meant (as a Shuttleworth Fellow) that she was able to make nominations of individuals for a Shuttleworth Flash Grant, which is a grant made to a collection of social change agents, no strings attached, in support of their work.

I was astonished to receive an email from the Shuttleworth Foundation saying that I had been nominated by Madeleine for a $5,000 Flash Grant, which goes to individuals they would like to support/reward/encourage in their work for social good.

Shuttleworth Funded

I am so blown away by the Flash Grant itself – and the signal that this grant provides. This is the first (of hopefully many) organizations to recognize the importance of supporting independent patient researchers who are not affiliated with an institution, but rather with an online community. It’s incredibly meaningful for this research and work, which is centered around real needs of patients in the real world, to be funded, even to a small degree.

Many non-traditional researchers like me are unaffiliated with a traditional institution or organization. This means we do the research in our own time, funded solely by our own energy (and in some case resources). Time in of itself is a valuable contribution to research (think of the opportunity costs). However, it is also costly to distribute and disseminate ideas learned from patient-driven research to more traditional researchers. Even ignoring travel costs, most scientific conferences do not have a patient research access program, which means patients in some cases are asked to pay $400 (or more) per person for a single day pass to stand beside their poster if it is accepted for presentation at a conference. In some cases, patients have personal resources and determination and are willing to pay that cost. But not every patient is able to do that. (And to do it year over year as they continue to do new ground-breaking research each year – that adds up, too, especially when you factor in travel, lodging, and the opportunity cost of being away from a day job.)

So what will I use the Flash Grant for? Here’s so far what I’ve decided to put it toward:

#1 – I plan to use it to fund my & Scott’s travel costs this year to ADA’s Scientific Sessions, where our poster on Autotune & data from the #WeAreNotWaiting community will be presented. (I’m still hoping to convince ADA to create a patient researcher program vs. treating us like an individual walking in off the street; but if they again do not choose to do so, it will take $800 for Scott and I to stand with the poster during the poster session). Being at Scientific Sessions is incredibly valuable as researchers and developers, because we can have real-time conversations with traditional researchers who have not yet been introduced to some of our tools or the data collected and donated by the community. It’s one of the most valuable places for us to be in person in terms of facilitating new research partnerships, in addition to renewing and establishing relationships with device manufacturers who could (because our stuff is all open source MIT licensed) utilize our code and tools in commercial devices to more broadly reach people with diabetes.

#2 – Hardware parts. In order to best support the OpenAPS community, Scott and I have also been supporting and contributing to the development of open source hardware like the Explorer Board. Keeping in mind that each version of the board produced needs to be tested to see if the instructions related to OpenAPS need to change, we have been buying every iteration of Explorer Board so we can ensure compatibility and ease of use, which adds up. Having some of this grant funding go toward hardware supplies to support a multitude of setup options is nice!

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There are so many individuals who have contributed in various ways to OpenAPS and WeAreNotWaiting and the patient-driven research movements. I’m incredibly encouraged, with a new spurt of energy and motivation, after receiving this Flash Grant to continue to further build upon everyone’s work and to do as much as possible to support every person in our collective communities. Thank you again to Madeleine for the nomination, and to the Shuttleworth Foundation for the Flash Grant, for the financial and emotional support for our community!