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<v Speaker 1>Welcome to Farmer Talk Radio. This podcast is focused on

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<v Speaker 1>lessons learned in the development and introduction of closed loop

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<v Speaker 1>systems from the twenty twenty four pod Partnership Opportunities and

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<v Speaker 1>Drug Delivery Conference. For more information about the pod conference, editorials, podcasts,

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<v Speaker 1>or webcasts, please visit Drug desh Delivery dot org. Thank

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<v Speaker 1>you and enjoy the podcast.

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<v Speaker 2>Good afternoon, everybody. Thank you for sticking around towards the

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<v Speaker 2>end here. It's a privilege to be able to moderate

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<v Speaker 2>this panel today on a topic very near to many

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<v Speaker 2>of our careers and hearts on looking at closed loop

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<v Speaker 2>systems across multiple therapeutic areas. Lessons learned. I'll introduce myself

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<v Speaker 2>first and then ask my fellow panelists to do the same.

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<v Speaker 2>Chris Kovalcik I lead this systems engineering organization within Abbott

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<v Speaker 2>Diabetes Care, responsible for the development and commercialization of the

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<v Speaker 2>entire portfolio of diabetes care products, including the Freestyle Every

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<v Speaker 2>Glucose monitoring system and their associated cloud and mobile application services.

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<v Speaker 3>Hi. Stephen Russell.

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<v Speaker 4>I'm an associated professor at Harvard Medical School and over

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<v Speaker 4>the last few years, the chief medical officer of Beta Bionics,

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<v Speaker 4>which is a company that makes an automated insulin delivery system.

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<v Speaker 3>Hi.

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<v Speaker 5>Am Hindley Pinkson from the bio Innovation Hub nov Ive

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<v Speaker 5>Externally Innovation.

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<v Speaker 6>Hey Ben Lane from Key Technologies. I'm VP of Product Development.

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<v Speaker 6>We've been around for a little over twenty five years,

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<v Speaker 6>and much of that time we've been developing diagnostics and

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<v Speaker 6>drug delivery devices, so we've been in this market for

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<v Speaker 6>quite some time.

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<v Speaker 7>Hi, my name is Louiterritor. I'm a pH Kennedy at

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<v Speaker 7>Harvard Medical School and MIT working with Bob Linger and

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<v Speaker 7>Geo Traversal on this closed loop drug delivery device, which

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<v Speaker 7>we'll be talking about shortly.

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<v Speaker 2>Okay, So to start us off to some common background.

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<v Speaker 2>When we talk about a closed loop system, you generally

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<v Speaker 2>need three or four ingredients to do so. Need to

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<v Speaker 2>be able to measure a metric or variable, diagnose a

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<v Speaker 2>dose or a therapy, deliver that dose, and you also

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<v Speaker 2>need a drug to be able to do that in

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<v Speaker 2>some cases. So if we look at what therapeutic ecosystem

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<v Speaker 2>has been at the forefront of closed loop space for

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<v Speaker 2>the last twenty years or so, it's been diabetes. So

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<v Speaker 2>first question I'd like to ask doctor Russell, why has

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<v Speaker 2>diabetes been so successful in terms of not only development

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<v Speaker 2>of closed loop systems, but commercial uptake and getting it

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<v Speaker 2>out to patients compared to other therapy areas.

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<v Speaker 4>Sure, I think the reason that diabetes has been at

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<v Speaker 4>the forefront is, first of all, you mentioned we have

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<v Speaker 4>to measure something. The physiologically important variable in diabetes is glucose,

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<v Speaker 4>blood glucose, and fortunately blood glucose is in equilibrium with

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<v Speaker 4>interstitial fluid glucose, which then can be measured in a

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<v Speaker 4>minimally invasive way with continuous glucose monitoring devices, and they've

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<v Speaker 4>gotten progressively more accurate and more reliable, to the point

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<v Speaker 4>that now the accuracy is excellent. The next piece is

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<v Speaker 4>that for delivery, we have insulin, which can also be

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<v Speaker 4>delivered subcutaneously.

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<v Speaker 3>It's absorbed very well.

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<v Speaker 4>The pharmacokinetics are pretty good for the ultra rapid insulin analogs,

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<v Speaker 4>and so that means that the control loop isn't too long.

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<v Speaker 4>I mean, if you measure something and then deliver something,

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<v Speaker 4>but then the drug that you deliver doesn't have an

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<v Speaker 4>effect for a day, that's not going to work. Fortunately,

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<v Speaker 4>insulin works within reaches peak and blood within an hour

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<v Speaker 4>or so, and you can get a relatively short control loop.

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<v Speaker 4>And then the reason it's had uptake is that it's

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<v Speaker 4>really hard to control glucose by yourself as a patient.

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<v Speaker 3>Diabetes is completely unique, and.

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<v Speaker 4>That we've got this really powerful, really dangerous drug, insulin,

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<v Speaker 4>and then we tell patients to figure out how much

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<v Speaker 4>of it to give themselves multiple times a day, which

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<v Speaker 4>is absolutely crazy and doesn't happen anywhere else in medicine.

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<v Speaker 4>And so there was a real unmet need for changing

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<v Speaker 4>that us the the development of closed loop systems and

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<v Speaker 4>their uptake once they were developed, I think, yeah, so I.

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<v Speaker 5>Would just echo that that the burden of treating yourself

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<v Speaker 5>every day and adjusting many times throughout the day is

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<v Speaker 5>really big. And and then maybe also that the way

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<v Speaker 5>that it came about that we have closed loop today,

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<v Speaker 5>it didn't came in one day. We tried back in

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<v Speaker 5>the seventies where there's something you carried on your back.

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<v Speaker 5>And and then you say, insulin came out and was

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<v Speaker 5>a business in itself. Then the pins were there, pumps

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<v Speaker 5>came out, was a business in the themself. And first

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<v Speaker 5>the ten years after the CDMs came out, we were

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<v Speaker 5>able to get it approved as a closed loop system.

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<v Speaker 2>So going along those lines with the success of diabetes

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<v Speaker 2>and closed loop on it. I'll start with you, what

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<v Speaker 2>are some of the areas we've seen limitations or areas

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<v Speaker 2>for improvement before we segue into other therapy areas.

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<v Speaker 5>Okay, yeah, So then I think if first I will

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<v Speaker 5>just trying to skitch out where we are today, and

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<v Speaker 5>I think Steve did a bit of that with the

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<v Speaker 5>With the you would say that it starts with that

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<v Speaker 5>we are giving a bolus in from from the pump,

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<v Speaker 5>and then when do you see that effect on the

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<v Speaker 5>CTM since you need to wait around one and a

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<v Speaker 5>half hour before it has been throughout the system, so

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<v Speaker 5>there is a big time delay in the system. It works,

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<v Speaker 5>and people are adjusting the meal habits and shows so

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<v Speaker 5>they don't get too much fluctuation there. But then the

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<v Speaker 5>in the we say then what could come that could

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<v Speaker 5>change this? I think the first thing would be to

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<v Speaker 5>get the time to lay down and and the biggest

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<v Speaker 5>element is the insulin. And right now we have a

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<v Speaker 5>dedicated insulin in in clinical trials and that that will

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<v Speaker 5>work so fast that they will not be available in

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<v Speaker 5>pins because they might give a hypoglycemia before you're finished

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<v Speaker 5>with your meal. So so we can cut down a

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<v Speaker 5>lot of time delay on the insulin. Then I would

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<v Speaker 5>say on the pump side, we have an infusion set.

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<v Speaker 5>It sits on for three to seven days. CTMs can

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<v Speaker 5>sit on for fourteen days. Maybe you could picture that

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<v Speaker 5>the infusion set could reach the same level as CDM.

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<v Speaker 5>On the CTM sensors, you see a trend on moving

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<v Speaker 5>from subcutis interstitial liquid measurement and some of the new

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<v Speaker 5>ones going into and when you go into dermal you

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<v Speaker 5>will gain five to ten minutes more in the reduced

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<v Speaker 5>time delay. And then you can say, if you look

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<v Speaker 5>not on the system but the alternatives, then there's cell

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<v Speaker 5>therapy making Bezza cells and putting them in the pocket

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<v Speaker 5>in the in the body, and there's a glucose sensitive

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<v Speaker 5>incident on its way.

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<v Speaker 2>So if we consider everyone sitting in this room, the

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<v Speaker 2>majority of us work for organizations that work across a

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<v Speaker 2>variety of therapy ecosystems. So I'd like to segue into

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<v Speaker 2>to lewis what are if you had to garner a guess,

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<v Speaker 2>what's the next therapy that's right for closed loop infiltration

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<v Speaker 2>outside of diabetes.

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<v Speaker 7>Definitely, I'd say in chology is a space that really

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<v Speaker 7>is just prime to have close loop therapies start to

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<v Speaker 7>be implemented. So I'm sure many of us have experienced

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<v Speaker 7>someone in our life receiving chemotherapy, but they don't think

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<v Speaker 7>many of us know is how they are dose. So

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<v Speaker 7>chemotherapies have a very narrow therapeutic window, as many of

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<v Speaker 7>us likely know. They work by killing cells through just

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<v Speaker 7>kind of like means that would also kill healthy cells

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<v Speaker 7>as well. But amazingly, the way that they're dose right

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<v Speaker 7>now is on the body service area basis. And what

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<v Speaker 7>that means is if you have Lebron James six nine

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<v Speaker 7>two hundred and five two hundred and fifty pounds and

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<v Speaker 7>happy the.

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<v Speaker 3>Dwarf, if Happy the Dwarf was four six.

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<v Speaker 7>Five hundred pounds, that'd get the same amount of chemotherapy.

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<v Speaker 7>And the reason for that is the basis that they're

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<v Speaker 7>doc on is using ideal body service area that comes

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<v Speaker 7>from this equation from nineteen sixteen.

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<v Speaker 3>So these two cousins to.

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<v Speaker 7>Boy and to Boy, they empirically fit data to nine people.

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<v Speaker 7>They took height and weight and body surface area and

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<v Speaker 7>empirically fit this equation to it. And that's the standard

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<v Speaker 7>of care today for figuring out how to dose patients

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<v Speaker 7>with chemotherapy across the world that the data fire were

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<v Speaker 7>in many other centers. So it really seems like oncology,

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<v Speaker 7>just given the nature of the cytotoxicity of these drugs

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<v Speaker 7>and just the center of characters being in the state

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<v Speaker 7>where it's using this equation from one hundred years ago,

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<v Speaker 7>or an abbreviated version of the pharma that was driving

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<v Speaker 7>in nineteen seventy one when calculators weren't around, so it

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<v Speaker 7>was a much easier way to get to BSA, but

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<v Speaker 7>it was based on the Debois and Dubois parmula. So

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<v Speaker 7>I'd say for those reasons, and the fact that the

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<v Speaker 7>patient's generally in an a fusion care center, so you

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<v Speaker 7>have the infusion pump puck directly up to them, so

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<v Speaker 7>you have a way that you could modulate DELS to

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<v Speaker 7>keep the concentration of drug within the therapeutic window. Really

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<v Speaker 7>makes oncology a very interesting space.

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<v Speaker 6>Yeah, it's interesting to think about these different time constants.

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<v Speaker 6>You know, diabetes is a very very long time constant,

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<v Speaker 6>sensors in there for a couple of weeks, whereas what

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<v Speaker 6>you're talking about is more more acute. Acute maybe the

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<v Speaker 6>wrong word but very short time caused. And there's plenty

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<v Speaker 6>of other applications where you know that's time constant is

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<v Speaker 6>on the treatment windows on the order of hours and

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<v Speaker 6>not you know, days, weeks, years.

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<v Speaker 4>Right, intermittent in that case, whereas somebody with type one

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<v Speaker 4>diabetes has to be under insulin treatment for the entire

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<v Speaker 4>rest of their lives. So whatever system you come up

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<v Speaker 4>with has to be wearable and easily usable, and something

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<v Speaker 4>that somebody can doesn't create more burden than it reduces.

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<v Speaker 2>So going off that thread, the last panel talked a

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<v Speaker 2>lot about considering the user and the development of these systems.

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<v Speaker 2>So if we think across different therapy areas, the user

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<v Speaker 2>plays a different role, right, So we talk about diabetes,

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<v Speaker 2>the user is very intensely aware and often more educated

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<v Speaker 2>on the technology than some of the people that develop

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<v Speaker 2>the systems. If we think about other therapy areas like

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<v Speaker 2>neurodegenerative or on cology, like you mentioned, open question to

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<v Speaker 2>the panel, how do you see the role of these

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<v Speaker 2>user playing in the different close loop applications across these

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<v Speaker 2>therapy areas well.

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<v Speaker 4>One thing I think is that we're trying to reduce

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<v Speaker 4>the role of the user and Type one so.

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<v Speaker 3>The first.

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<v Speaker 4>Automated insulin delivery technologies are so called hybrid systems, so

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<v Speaker 4>they modulate basil insulin. You need both basil and bolus insulin.

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<v Speaker 4>Basil dealing with the basil insulin needs like overnight, and

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<v Speaker 4>then bowl is dealing with meals and so forth. The

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<v Speaker 4>systems typically manage the basil part and then the user

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<v Speaker 4>is responsible for the bowls part. Our system, the islet

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<v Speaker 4>is designed to take over one hundred percent of the

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<v Speaker 4>insulin dosing and reduce the need for the user to

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<v Speaker 4>get involved. And what we're trying to solve there is

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<v Speaker 4>that only twenty percent of people with type one are

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<v Speaker 4>able to maintain the kind of glucose control they're supposed

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<v Speaker 4>to do because people with really good quantitative skills, really

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<v Speaker 4>good attention to detail, so forth, people with great executive

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<v Speaker 4>function they do fine. Everyone else doesn't. So taking the

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<v Speaker 4>user out of the loop more and more is the

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<v Speaker 4>direction we're trying to move in for diabetes.

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<v Speaker 2>What about a therapy area such as Alzheimer's where the

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<v Speaker 2>user could be the person with cognitive impairment or a caregiver.

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<v Speaker 2>Anybody want to comment on, how do you see closeup

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<v Speaker 2>playing in the Alzheimer's space.

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<v Speaker 6>Yeah, I mean that's a super challenging patient population, right,

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<v Speaker 6>I mean, diabetes has this massive patient population. I think,

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<v Speaker 6>you know, we've done a very good job with the

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<v Speaker 6>vast majority of that group. But there's certain are sub

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<v Speaker 6>certainly are subgroups pediatric, you know, cognitive issues, dexterity issues

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<v Speaker 6>where managing the treatment but then also just applying the pump,

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<v Speaker 6>applying the sensor becomes very challenging for that patient group

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<v Speaker 6>and there's definitely room for improvement there.

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<v Speaker 4>The question with things like you know, neurodegenerative diseases is

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<v Speaker 4>what to measure, right. I'm interested in Parkinson's because my

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<v Speaker 4>mother suffers from that and she has to take this

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<v Speaker 4>complicated regimen of multiple doses. V just I guess recently

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<v Speaker 4>got approval for doodopa, which is an sebt Q infusion,

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<v Speaker 4>so that seems very familiar to me.

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<v Speaker 3>In the insulin space.

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<v Speaker 4>You can infuse this drug supultaneously maintain steady levels. But

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<v Speaker 4>if you were going to try and turn that into

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<v Speaker 4>a closed loop system, what would you measure? You know,

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<v Speaker 4>would you measure interstitial dopamine That's not really where it functions, right,

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<v Speaker 4>So would you measure tremor maybe you could do something

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<v Speaker 4>like that. I think that becomes the challenge for these

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<v Speaker 4>other fields.

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<v Speaker 5>You could say that if it's not a fully closed loop,

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<v Speaker 5>but just some of the components, like using the CDM

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<v Speaker 5>for for other for other things, then I think that

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<v Speaker 5>the that the we have tried out to use a

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<v Speaker 5>CDM for tight trading once weekly insulin to figure out

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<v Speaker 5>quite fast where to go and then go up in

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<v Speaker 5>a few steps. Yeah, so really long acting components getting

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<v Speaker 5>them to the right level fast. Uh. And one other

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<v Speaker 5>element could be to use the CTM sensus for anti

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<v Speaker 5>obesity treatment.

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<v Speaker 2>So segueing to lessons learned, one of the areas we've

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<v Speaker 2>talked about so far as the readiness of the technology.

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<v Speaker 3>So back to the diabetes space.

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<v Speaker 2>A lot of the technologies used to do any of

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<v Speaker 2>these aspects of closed loop development have been readily available

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<v Speaker 2>for the last twenty years. But even still, if you

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<v Speaker 2>look at the companies playing in this game, very few

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<v Speaker 2>if any, develop all of the technology all internally and

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<v Speaker 2>requires a lot of partnership. So if Ben, I'll go

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<v Speaker 2>to you, if we look at focusing on improving technology

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<v Speaker 2>in these other areas, what are some of the advices

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<v Speaker 2>or lessons learned that you've seen that helps not only

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<v Speaker 2>develop this technology, but be able to partner effectively to

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<v Speaker 2>get these solutions out to patients for other areas.

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<v Speaker 3>Yeah, that's a great question.

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<v Speaker 6>I think, you know, the collaboration of all the partners

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<v Speaker 6>that are involved in this ecosystem, it's a complicated beast

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<v Speaker 6>raight and the ability to rapidly develop and deploy a

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<v Speaker 6>system depends on early engagement between all those parties. So

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<v Speaker 6>you're developing a holistic system from the beginning as opposed

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<v Speaker 6>to disparate development that then gets tied together.

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<v Speaker 3>At the end.

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<v Speaker 6>And it's a very difficult challenge. We see it all

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<v Speaker 6>the time in diagnostics where the you know, the assay

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<v Speaker 6>is developed and then the consumables developed and the instruments developed,

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<v Speaker 6>and there's not that holistic from the beginning viewpoint, and I,

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<v Speaker 6>you know, I don't have a lot of great answers there.

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<v Speaker 6>It's very challenging because very often the pharma company is

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<v Speaker 6>not in the in the hardware space.

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<v Speaker 3>And the drug delivery.

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<v Speaker 6>Company is not in the diagnostic space, and so tying

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<v Speaker 6>all that together early to develop that holistic, efficient system

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<v Speaker 6>is particularly challenging.

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<v Speaker 4>The regulators can help a lot though that's another place

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<v Speaker 4>we haven't discussed that.

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<v Speaker 3>We had an advantage in.

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<v Speaker 4>The diabetes space because the FDA created an it's this

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<v Speaker 4>five ten K pathway for closed loop systems, and they

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<v Speaker 4>created something called interoperable CGM, an ICGM with so it's

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<v Speaker 4>a five to ten K with special controls and essentially

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<v Speaker 4>if it could communicate with one of the devices in

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<v Speaker 4>the x ecosystem and if it met certain accuracy criteria,

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<v Speaker 4>then you could get this ICGM status. And as a

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<v Speaker 4>company making a closed loop device, we are able to

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<v Speaker 4>now do the study with one ICGM and then substitute

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<v Speaker 4>another ICGM into our system without a regulatory filing. We

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<v Speaker 4>just did a letter to file, so that really accelerated

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<v Speaker 4>the whole process tremendously. You know, we launched with one CGM,

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<v Speaker 4>we got the spec for another CGM, and launched four

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<v Speaker 4>months later with a second CGM, and then we got

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<v Speaker 4>the spec for a third and then launched a number

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<v Speaker 4>of months later for that, and now we're we've got

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<v Speaker 4>three CGM sensors that are all available, so it's user

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<v Speaker 4>choice that wouldn't have been possible without the FDA stepping

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<v Speaker 4>in and creating that regulatory framework.

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<v Speaker 5>You could also say that by going through a partner's

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<v Speaker 5>you open up a free, free competition and the BIST,

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<v Speaker 5>the pump company can can pick the BIST CTM company

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<v Speaker 5>and I and you get it even bitter system than

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<v Speaker 5>if they try to do it internal.

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<v Speaker 2>Yeah, this is an interesting space because you have companies

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<v Speaker 2>who are partners and competitors at the same time, sometimes

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<v Speaker 2>even on the same product. Switching to another technology question

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<v Speaker 2>with this for you, So you mentioned oncology, and in

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<v Speaker 2>terms of companion diagnostics, to measure the metric you're proposing

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<v Speaker 2>requires a sophisticated technology in the clinic to be able

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<v Speaker 2>to measure. Do you see start with oncology, Do you

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<v Speaker 2>see that becoming a low cost product eventually? And what

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<v Speaker 2>do you think would it take to get away from

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<v Speaker 2>a diagnostic machine to measure the variable versus a wearable What.

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<v Speaker 3>Are your thoughts there?

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<v Speaker 7>Yeah, absolutely, So for context, we've developed this closed loop

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<v Speaker 7>drug delivery system to control of the concentration of chemotherapy

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<v Speaker 7>and we've shown it in vivo we published it earlier

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<v Speaker 7>this year. So in the system, we draw a blood

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<v Speaker 7>from the animal or eventually a patient and then we

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<v Speaker 7>do this raptive the blood preprocessing step to then put

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<v Speaker 7>it onto a high performance to liquid chromatography MasSpec or

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<v Speaker 7>HBOCMS system, which has been as many of the people

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<v Speaker 7>in this audience likely know, a gold standard by the

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<v Speaker 7>FDA to determine the concentration of drug for many many

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<v Speaker 7>different clinical trials over the years. So we really wanted

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<v Speaker 7>to design the sensor or the overall system around the

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<v Speaker 7>sensor because of the development and the trust and to

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<v Speaker 7>the points that we're mentioned earlier, the fact that you

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<v Speaker 7>really need this sensor, and that's one of the things

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<v Speaker 7>that really helped in the diabete space to enable closer

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<v Speaker 7>the control. So we designed this overall system around LCMS,

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<v Speaker 7>and then the loop gets closed by taking that concentration

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<v Speaker 7>reading and put it into the control algorithm. So with that,

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<v Speaker 7>that's one of the major questions we always get is

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<v Speaker 7>LCMS is very expensive. The high end ones that you'd

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<v Speaker 7>likely want in the clinic are just shy of about

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<v Speaker 7>a million dollars, So the upfront cost is large, But

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<v Speaker 7>when you start thinking about the lifetime of these types

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<v Speaker 7>of devices, they'd likely last with good maintenance on the

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<v Speaker 7>order of about a decade. You can imagine you can

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<v Speaker 7>do about two maybe three patients a day with the

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<v Speaker 7>system comes down to about one thousand uses over a year,

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<v Speaker 7>ten thousand over a decade, So the cost per patient

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<v Speaker 7>is approximately one hundred dollars if you work it out

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<v Speaker 7>according to that way. Of course, there's many other variables

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<v Speaker 7>that go into account with it. You'd have to have

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<v Speaker 7>personal cost, but the cost of the system isn't as

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<v Speaker 7>large as you'd initially think, and there's likely if this

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<v Speaker 7>system were ever to reach it to the clinic, they'd

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<v Speaker 7>likely be work continuing to bring the cost of the

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<v Speaker 7>LCMS device down. So definitely opportunity i'd say is the

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<v Speaker 7>ability to make low cost LCMS devices is definitely something

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<v Speaker 7>that's interesting, and that's just one of many different types

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<v Speaker 7>of approaches you get take for the censor, But we

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<v Speaker 7>really decided to focus on that just because it is

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<v Speaker 7>very well trusted, able to be applied to multiple different drugs,

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<v Speaker 7>and there's allowed of us to develop this system and

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<v Speaker 7>apply it to a chemotherapy space.

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<v Speaker 3>You also have to think about the value.

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<v Speaker 4>So in the diabetes space, you know, these devices are

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<v Speaker 4>not nearly as expensive as that, but there are a

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<v Speaker 4>lot of people because each person needs one and multiple

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<v Speaker 4>over their lifetime. Usually, but we're reducing the risk of

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<v Speaker 4>long term complications, and you, I believe would be reducing

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<v Speaker 4>the risk of chemotherapy related complications because of overdosing or

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<v Speaker 4>inadequate treatment of a cancer from underdosing. So I think

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<v Speaker 4>you can easily make the argument that a one hundred

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<v Speaker 4>dollars is worth the reduction to an insurance company is

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<v Speaker 4>worth the reduction of those those complications.

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<v Speaker 3>Yeah.

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<v Speaker 7>Absolutely, There's been this additional approach that's been developed therapeutic

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<v Speaker 7>drug monitoring, where you take the concentration of the end

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<v Speaker 7>of one around of chemotherapy and then don't suggest for

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<v Speaker 7>the next round of chemotherapy. And even with that, which

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<v Speaker 7>if you think about it, that's the closed system. It's

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<v Speaker 7>a sampling rate in the case of five few of

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<v Speaker 7>once per two weeks. It's a very basic control algorithm

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<v Speaker 7>that's normally for five few. The clinical trials I'm aware

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<v Speaker 7>of that have been done, it's a rule spase algorithm,

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<v Speaker 7>so if you're a certain percent above, you decrease by

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<v Speaker 7>x percent of the dose. So even within those trials,

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<v Speaker 7>they've shown benefit in terms of tox and efficacy. So

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<v Speaker 7>I completely agree with you, and in the paper we

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<v Speaker 7>put out, we did some preliminary analysis on that with

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<v Speaker 7>certain assumptions of how much benefit we could apply based

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<v Speaker 7>on those TDM studies, and it does when you take

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<v Speaker 7>everything into account, does appear that it could be cost effective,

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<v Speaker 7>even given the high costs involved.

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<v Speaker 2>An area like to go into a little bit is

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<v Speaker 2>around access. So when the first hybrid closed loop technology

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<v Speaker 2>is launched in the diabetes space, if you purely look

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<v Speaker 2>at the physics and the technology, it's a no brainer

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<v Speaker 2>that every single person with diabetes would therapeutically benefit from

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<v Speaker 2>this system. However, if you look at the percent of

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<v Speaker 2>the population of persons with diabetes that are on such

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<v Speaker 2>a system is incredibly low, a single digit percent. How

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<v Speaker 2>do we increase access to these technologies by building patient

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<v Speaker 2>trust not only a diabetes space, but in other therapeutic

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<v Speaker 2>areas where the concept of a closed loop system would

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00:23:33.920 --> 00:23:36.880
<v Speaker 2>be completely foreign to an individual receiving the therapy.

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00:23:37.920 --> 00:23:41.200
<v Speaker 4>Well, I'm going to mention one thing, which is that

403
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<v Speaker 4>percentage being that low. That may be true for diabetes

404
00:23:43.920 --> 00:23:45.599
<v Speaker 4>as a whole, but if you look at type one

405
00:23:45.839 --> 00:23:49.319
<v Speaker 4>we're we're at about thirty percent, So it's really pretty

406
00:23:49.359 --> 00:23:52.400
<v Speaker 4>substantial adoption in the type one space. The other thing

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<v Speaker 4>is that it's kind of a unique situation because, as

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<v Speaker 4>was mentioned, CGM was always already available. Insulin pumps were

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<v Speaker 4>already of aailable Obviously, the insulins were already available and

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00:24:04.000 --> 00:24:06.920
<v Speaker 4>the people were using them, they just weren't using them together.

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00:24:07.519 --> 00:24:11.759
<v Speaker 4>And when the closed loop devices came out, they used

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<v Speaker 4>the same billing codes as the dumb pumps, right, So

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00:24:15.920 --> 00:24:19.720
<v Speaker 4>the the insurer was getting increased value for no increase

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00:24:19.759 --> 00:24:23.480
<v Speaker 4>in cost. So the value proposition was pretty compelling in

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00:24:23.480 --> 00:24:26.079
<v Speaker 4>that case. I don't know if that's that's probably not

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00:24:26.119 --> 00:24:27.839
<v Speaker 4>going to be the case for some of these other ones.

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<v Speaker 5>You can say that I tried to look up how

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00:24:35.359 --> 00:24:39.359
<v Speaker 5>much longer would a person live if if they go

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00:24:39.480 --> 00:24:43.319
<v Speaker 5>from a pin system to a closed loop system, and

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<v Speaker 5>I might not have got all the data right, but

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<v Speaker 5>what it's all around the too too too quality adjusted

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00:24:54.680 --> 00:25:00.519
<v Speaker 5>life years in And then I think in in US

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<v Speaker 5>we were most insurance are willing to pay fifty two

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00:25:05.799 --> 00:25:11.680
<v Speaker 5>hundred thousand per year quality adjusted lifespan improvement. And so

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00:25:11.680 --> 00:25:16.759
<v Speaker 5>you will say this should be enough recent enough science

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<v Speaker 5>to YE to get it out there.

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<v Speaker 2>We have about three and a half minutes left, so

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<v Speaker 2>I like to open it up for questions from the floor.

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<v Speaker 8>Either.

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<v Speaker 9>My name is Sheldon Oberg and with bets to biomedical

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<v Speaker 9>but in a former life I used to head the

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<v Speaker 9>Electronic Diabetes Insulin Delivery System Electronic Mini Men. The last

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<v Speaker 9>panel was on digital health, and as we know, the

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<v Speaker 9>insulin industry has been using connected systems for well over

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<v Speaker 9>two decades. I'm curious on your insights on how digital

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<v Speaker 9>health has helped and improved that patient barka, So I'll start.

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<v Speaker 2>So, I think one area is providing access to information.

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<v Speaker 2>So by having connected applications or just having the data

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00:26:13.960 --> 00:26:16.680
<v Speaker 2>stored in a cloud, it's made life easier for not

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00:26:16.720 --> 00:26:19.200
<v Speaker 2>only the persons with diabetes using the systems, but also

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<v Speaker 2>they're endocrinologists that they see. We could spend a whole

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<v Speaker 2>panel talking about the difficulty with the minimum amount of

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<v Speaker 2>time that a patient gets with an endocrinologist, and I'm

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<v Speaker 2>hoping you can.

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<v Speaker 3>Talk about that.

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00:26:32.799 --> 00:26:37.799
<v Speaker 2>But having access to this information, getting feedback on how

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00:26:37.839 --> 00:26:40.799
<v Speaker 2>to create these reports and graphs and how to make

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<v Speaker 2>it very available is very helpful for people. Also simplicity,

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<v Speaker 2>I think one of the dangers, as was mentioned in

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<v Speaker 2>the last panel, is sometimes we connect devices for connection

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00:26:50.240 --> 00:26:53.000
<v Speaker 2>sake rather than actually thinking about what's needed, and the

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00:26:53.039 --> 00:26:56.079
<v Speaker 2>reality is a lot of people that are on closed

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<v Speaker 2>loop diabetes systems don't want to have it in true life,

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00:27:00.720 --> 00:27:03.200
<v Speaker 2>so providing them with every single bell and whistle and

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00:27:03.240 --> 00:27:07.240
<v Speaker 2>alarm and alert actually is a high level of dissatisfaction

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<v Speaker 2>for the user. So I think it's important that we're

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<v Speaker 2>mindful of, yes, we can have these digital companion applications,

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<v Speaker 2>but being cognizant of how to use them effectively to

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<v Speaker 2>provide a wealth of information while having limited intrusion to

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<v Speaker 2>the user base.

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<v Speaker 4>One thing that I think is pretty interesting about the

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<v Speaker 4>digital health applications for this use case is that so

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<v Speaker 4>called follow apps are really impactful, which means that somebody

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<v Speaker 4>can have their CGM glucose information followed by another person,

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<v Speaker 4>often a parent, if it's a child, or a spouse,

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00:27:46.319 --> 00:27:49.640
<v Speaker 4>or even just another friend with diabetes, and so they

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00:27:49.720 --> 00:27:53.119
<v Speaker 4>watch out for each other and if some you know,

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00:27:53.119 --> 00:27:56.440
<v Speaker 4>if an hypo alarm for your friend goes off, and

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<v Speaker 4>you know.

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<v Speaker 3>You can call them up and say, hey, are you okay?

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<v Speaker 4>You seeing this? And I think that that's tremendously valuable.

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<v Speaker 4>It kind of expands the network of caregivers beyond the

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<v Speaker 4>people who are immediately present to any anyone you want.

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<v Speaker 3>Frankly, yeah, I would second that.

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<v Speaker 6>My five year old niece is Type one and the

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00:28:18.640 --> 00:28:22.319
<v Speaker 6>connected ability to have her parents be able to monitor

477
00:28:22.480 --> 00:28:23.640
<v Speaker 6>is just tremendous.

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<v Speaker 3>It really is.

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<v Speaker 2>Is there an there one more question?

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<v Speaker 8>I work for a design agency and we'll be looking,

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<v Speaker 8>in fact, for the last sort of a year or so

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<v Speaker 8>into biosensing and.

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<v Speaker 3>The closed loops.

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<v Speaker 8>I mean, in fact, I came across a company it's

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<v Speaker 8>only down the road. Then they created this sensor where

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<v Speaker 8>you put in just a plastic cube coming out from

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<v Speaker 8>a wound after an operation. You would tell you about

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<v Speaker 8>the chemistry of the liquid coming out. That will tell

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<v Speaker 8>you how well is the actually you know the hill

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00:29:00.160 --> 00:29:02.880
<v Speaker 8>that is taking place, which is fantastic and it's also

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<v Speaker 8>a throwaway center if you like. So I was I

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<v Speaker 8>want to ask the panel, how where are we going

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<v Speaker 8>with a biosensing I think we are there. There are

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<v Speaker 8>sort of many examples out there, but I haven't seen

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<v Speaker 8>a lot of the sort of like closed loop systems.

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<v Speaker 8>I mean, we kept talking about which is great about

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<v Speaker 8>type one diabetes and so on, how can biosensing help

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<v Speaker 8>us move into other bigger areas and bigger applications.

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<v Speaker 2>Thank you, Eric, Do you want to take this?

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<v Speaker 5>Yeah, So, I think there's a that they'll becoming a

501
00:29:37.359 --> 00:29:46.799
<v Speaker 5>number of new symstotypes and some day they call it

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00:29:47.599 --> 00:29:52.920
<v Speaker 5>electronic nose, a sensor that can that can sense a

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00:29:53.000 --> 00:29:56.839
<v Speaker 5>number of different things and then by looking a little

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00:29:56.839 --> 00:30:02.720
<v Speaker 5>bit on on the fingerprick from then then they can

505
00:30:03.240 --> 00:30:07.920
<v Speaker 5>then they can miss a lot of metabolics and key

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00:30:08.000 --> 00:30:13.759
<v Speaker 5>tones and and other stuff. And yeah, so so I

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00:30:13.839 --> 00:30:17.680
<v Speaker 5>think there's a lot of UH since US on its way.

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<v Speaker 5>Also the CTM since US are trying to build in

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<v Speaker 5>more sensors within the existing system.

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<v Speaker 4>So yeah, there's a lot of interest in a key

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00:30:30.839 --> 00:30:35.039
<v Speaker 4>tone sensor for type one diabetes space so you can

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<v Speaker 4>detect failure of insulin delivery, but also for lactate for

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00:30:40.559 --> 00:30:47.400
<v Speaker 4>the UH, the lifestyle UH or or athletic improvement. So

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00:30:47.519 --> 00:30:51.960
<v Speaker 4>having lactate sensors measurements of lactate is really something that's

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00:30:51.960 --> 00:30:54.960
<v Speaker 4>only done by pro athletes or or high level athletes now,

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00:30:55.440 --> 00:30:59.319
<v Speaker 4>but you could conceivably have c g M like measurements

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00:31:00.359 --> 00:31:05.279
<v Speaker 4>of lactate which could potentially improve athletic endeavors.

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00:31:07.559 --> 00:31:09.799
<v Speaker 3>And it's yet to be seen.

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00:31:09.920 --> 00:31:12.480
<v Speaker 4>I mean, both of the major CGM companies have launched

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00:31:12.559 --> 00:31:16.599
<v Speaker 4>direct to consumer devices for people without diabetes, with the

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00:31:16.640 --> 00:31:21.920
<v Speaker 4>idea that being able to see what particular types of

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00:31:21.960 --> 00:31:26.000
<v Speaker 4>food due to your blood glucose would change your habits.

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<v Speaker 3>And I can tell you that it's done that for me.

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<v Speaker 4>After seeing what some of my favorite breakfast foods did

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<v Speaker 4>to my glucose, I changed my habits considerably, So I

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<v Speaker 4>think there definitely is a role for this.

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<v Speaker 1>We hope you enjoyed the podcast. For more information about

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00:31:44.079 --> 00:31:48.359
<v Speaker 1>the pod, conference, editorials, podcasts, or webcasts, please visit drug

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00:31:48.400 --> 00:31:50.720
<v Speaker 1>desh Delivery dot org. Thanks for listening.
