Not necessarily, at least not via patient input. In the albeit small Inreda studies manual announcement of exercise and meals wasn't required (or an option). Medtronic also has a meal prediction algorithm on their newest offering that's a step towards a fully automated process and currently more or less obviates carb counting but isn't at the point where you don't have to announce a meal (yet).

Rather than integrating external data sources the algorithms are predicting based on historical glucose levels and/or insulin administration and it seems to be working.

https://jamanetwork.com/journals/jamasurgery/article-abstrac...

None of the systems claiming you don't have to do anything in terms of meal announcement are _working_ in the sense of achieving euglycemic parity, which should be the goal. I can say with certainty that the cgm logs from people who don't announce meals on the Inreda device do not look like they are from non-diabetics: there are still often large post-prandial spikes. Inreda likely does better than any single hormone system, but the problem is not solved in any sense.

I'm not going as far as to claim Medtronic's approach (I believe the only one commercially available with so-called meal prediction based on historical CGM and offers full correction boluses) is the optimal one, just that it is an approach that is at least very good (~80% time in target) and while it still requires meal announcements it's just the first step of what they're trying to do. Clearly we can expect further iterations of these algorithms as the technology matures.

> Inreda uses two identical CGMs for noise reduction purposes just so they can get clean data with less of a lag.

Just giving an example that this is possible without external input or data, your statement was that you will need a-priori information which is not necessarily the case. Whether such a system is optimal is a different question.

I haven't seen the raw data and highly doubt enough of it even exists for anyone to make a claim whether or not such a system can be optimized to the point necessary.

> None of the systems claiming you don't have to do anything in terms of meal announcement are _working_ in the sense of achieving euglycemic parity, which should be the goal.

For clarity to any less knowledgeable readers while time spent in euglycemia is a very important outcome measure it cannot come at the expense of severe hypoglycemia or severe hyperglycemia/diabetic ketoacidosis (i.e. an algorithm that improves euglycemia to 95% but has a 2% severe hypo time is less acceptable than 80% euglycemia and 0.5% severe hypo.)

To my knowledge no system on the market/generally available right now is claiming to be completely input free. The closest to my knowledge is again the MiniMed 780G discussed in my first point which will assuredly be iterated on.

Also to be clear I'm not being dismissive of what your company is working on, it's a very interesting and novel approach. It may even be necessary to achieve the optimal product. I look forward to reading about your results when you publish them. I'm just presenting alternatives and a brief overview of what other approaches are for HN readers who are likely unfamiliar with the topic being discussed.

For the record, when I say "Euglycemic Parity" what I really mean is a sort of Turing test (not time in range), where a data-driven Endocrinologist is asked to tell the difference between CGM records from a non-diabetic, and CGM records from a diabetic equipped with some control system. Passing this test should be our long term goal IMO and we will probably have to bring many techniques to bear to eventually achieve it.

The difference between how quickly food and insulin hit your bloodstream make it seem like there is no way to "algorithm your way out of" meal announcements. Food hits almost immediately, and with variable strength depending on macronutrients in it, and insulin takes ~15 minutes to start working, and peaks at 1 hour, with no concern about BG levels. Can you square these 2 for me and make it make sense?

1. Time in severe hypoglycemia - ideally 0%

2. Time in severe hyperglycemia/diabetic ketoacidosis - ideally 0%

3. Time in euglycemia (also called time in target) - clinical target is >70% and for reference the median healthy non-diabetic is in target ~90-95% of the time.

Closed loop systems are very good at #1 and #2 as it takes a while for levels to get to the severe state and insulin can be administered (or withheld) based on CGM.

When we talk about algorithming out of meal announcements it's whether historical patient-specific blood glucose levels and insulin administrations (i.e. a surrogate for what you eat and when) combined with CGM can keep #3 acceptable, not necessarily optimal. Medtronic is using this approach and their newest model more or less eliminates the need for accurate carb-counting but they still require meal announcements. The hope/idea is that this can potentially be eliminated with further iterations.

Another important thing to keep in mind that is sometimes lost in these discussions is that we don't treat numbers we treat patients (i.e. what are the clinical outcomes). Generally speaking, we assume the closer to normal the better but we don't have actual data about how much an extra X% outside of target ranges matters in terms of clinical outcomes and complication rates. We only really started getting this data with CGM and complications in these mild states would require very large cohorts and long (10-20 year) follow-ups to detect differences as they're likely to also be mild.

So while you're absolutely correct regarding the limitations and that an algorithm cannot outperform accurate carb-counting and meal announcements the missing piece is that it may be sufficient. Particularly if said algorithms result in improved time-in-target for patients who aren't good at managing their diabetes and find meal announcements cumbersome.

I totally get that we "treat the patient" -- that's sort of what I'm hinting at with the demographics. But, in my opinion this thing you said:

> we don't have actual data about how much an extra X% outside of target ranges matters in terms of clinical outcomes and complication rates. We only really started getting this data with CGM and complications in these mild states would require very large cohorts and long (10-20 year) follow-ups to detect differences as they're likely to also be mild.

... is not the same as saying "we know that 70% TIR is safe to live with no complications". I don't think any of the guidelines are that confident, because there's not enough evidence yet. Consider this study (discussed at [1]):

> Overall, increasing time spent with glucose levels in the target range of 70–180 mg/dL (3.9–9.9 mmol/L) was associated with decreasing risk for microvascular complications. For instance, 50.0% of the 10 individuals in the lowest category for TIR (<40%) had at least one microvascular complication, compared with just 27.3% of the 99 people in the highest category for TIR (≥70%).

> Moreover, El Malahi said that the 180 people with microvascular complications had significantly lower average TIR than the 324 individuals without, at 60.4% versus 63.9%.

This suggests to me that a difference of 4% of TIR can seriously affect long-term outcomes. And, by the way, even those with the highest TIR still had microvascular complications higher than the normal population. On top of that, we know that genetic and environmental factors may be at play.

Therefore, my monkey math is that 75%+ as a TIR goal may mean that even if the patient is an order of magnitude more vulnerable to complications, microvascular or otherwise, they have a much better shot.

And, unfortunately, the typical western diet with 3 meals a day and snacks, you have to be "good at managing diabetes" to get to 75%+ TIR. Thanks for reading my ramble.

[1] https://diabetes.medicinematters.com/easd-2020/glycemic-cont...

From Wikipedia:"A proportional–integral–derivative controller (PID controller or three-term controller) is a control loop mechanism employing feedback that is widely used in industrial control systems and a variety of other applications requiring continuously modulated control. A PID controller continuously calculates an error value e(t) as the difference between a desired setpoint (SP) and a measured process variable (PV) and applies a correction based on proportional, integral, and derivative terms (denoted P, I, and D respectively), hence the name."

Getting PID control loops to work has a lot of research behind it, but it's still hard to get right with new hardware. I would imagine a PID control loop involving organics (wetware) would be much order, and harder still a PID control loop in organics with life-threatening failures possible.

The way the Supreme Court recently changed patent law [3] for software has definitely had a positive effect for APS development. [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2769814/ [2] https://patents.google.com/patent/US20150306314 [3] https://en.wikipedia.org/wiki/Alice_Corp._v._CLS_Bank_Intern...

That's good news, right? That means that everything that people now come up with has well-documented prior art?

If you need a really optimal control trajectory minimizing or maximizing for some parameter, you are willing to do the system identification necessary for it to work, and you don't much care whether an electrician can understand how it works model-based controls are much better. as /u/Communitivity mentioned so called 'model based control' (which is an umbrella of techniques) is a much more powerful tool.

Oh my gosh, this is the startup I considered starting last year when this issue became personal to me and I wrapped my brain around the complexity of insulin dosing.

There are a lot of challenges here but we absolutely need an external "brain" to correlate many data points, some trends, and reasonably estimate current insulin sensitivity.

If I was back in that position I'd go low carb high exercise from the start, and do everything I could to reduce my insulin requirements as much as possible. There are cases of new T1s coming of insulin completely, or just a low basal dose for multiple years.

Would love to see/hear more about what you're working on!

    - 1 drug, it works ok, still very patient specific.
    - 2 drugs at the same time, only if you validated correctly at least one alone before.
    - 3 at the same time: clusterfuck/total mess.

I'm a type 1 diabetic on multiple daily injections -- a pump just introduces a lot of inconvenience for me, price aside. You have to track batteries and change tubing and make sure the tubing doesn't snag on things, and unplug the machine before taking a shower or bath, and ... blah blah blah...

All I need for MDI is to carry my syringes and vial around in a cold pack (I live in the tropics, lol) and I don't need to worry about hardware beyond that.