Speaker 1: Welcome to Farmer Talk Radio. This podcast is focused on
Speaker 1: lessons learned in the development and introduction of closed loop
Speaker 1: systems from the twenty twenty four pod Partnership Opportunities and
Speaker 1: Drug Delivery Conference. For more information about the pod conference, editorials, podcasts,
Speaker 1: or webcasts, please visit Drug desh Delivery dot org. Thank
Speaker 1: you and enjoy the podcast.
Speaker 2: Good afternoon, everybody. Thank you for sticking around towards the
Speaker 2: end here. It's a privilege to be able to moderate
Speaker 2: this panel today on a topic very near to many
Speaker 2: of our careers and hearts on looking at closed loop
Speaker 2: systems across multiple therapeutic areas. Lessons learned. I'll introduce myself
Speaker 2: first and then ask my fellow panelists to do the same.
Speaker 2: Chris Kovalcik I lead this systems engineering organization within Abbott
Speaker 2: Diabetes Care, responsible for the development and commercialization of the
Speaker 2: entire portfolio of diabetes care products, including the Freestyle Every
Speaker 2: Glucose monitoring system and their associated cloud and mobile application services.
Speaker 3: Hi. Stephen Russell.
Speaker 4: I'm an associated professor at Harvard Medical School and over
Speaker 4: the last few years, the chief medical officer of Beta Bionics,
Speaker 4: which is a company that makes an automated insulin delivery system.
Speaker 3: Hi.
Speaker 5: Am Hindley Pinkson from the bio Innovation Hub nov Ive
Speaker 5: Externally Innovation.
Speaker 6: Hey Ben Lane from Key Technologies. I'm VP of Product Development.
Speaker 6: We've been around for a little over twenty five years,
Speaker 6: and much of that time we've been developing diagnostics and
Speaker 6: drug delivery devices, so we've been in this market for
Speaker 6: quite some time.
Speaker 7: Hi, my name is Louiterritor. I'm a pH Kennedy at
Speaker 7: Harvard Medical School and MIT working with Bob Linger and
Speaker 7: Geo Traversal on this closed loop drug delivery device, which
Speaker 7: we'll be talking about shortly.
Speaker 2: Okay, So to start us off to some common background.
Speaker 2: When we talk about a closed loop system, you generally
Speaker 2: need three or four ingredients to do so. Need to
Speaker 2: be able to measure a metric or variable, diagnose a
Speaker 2: dose or a therapy, deliver that dose, and you also
Speaker 2: need a drug to be able to do that in
Speaker 2: some cases. So if we look at what therapeutic ecosystem
Speaker 2: has been at the forefront of closed loop space for
Speaker 2: the last twenty years or so, it's been diabetes. So
Speaker 2: first question I'd like to ask doctor Russell, why has
Speaker 2: diabetes been so successful in terms of not only development
Speaker 2: of closed loop systems, but commercial uptake and getting it
Speaker 2: out to patients compared to other therapy areas.
Speaker 4: Sure, I think the reason that diabetes has been at
Speaker 4: the forefront is, first of all, you mentioned we have
Speaker 4: to measure something. The physiologically important variable in diabetes is glucose,
Speaker 4: blood glucose, and fortunately blood glucose is in equilibrium with
Speaker 4: interstitial fluid glucose, which then can be measured in a
Speaker 4: minimally invasive way with continuous glucose monitoring devices, and they've
Speaker 4: gotten progressively more accurate and more reliable, to the point
Speaker 4: that now the accuracy is excellent. The next piece is
Speaker 4: that for delivery, we have insulin, which can also be
Speaker 4: delivered subcutaneously.
Speaker 3: It's absorbed very well.
Speaker 4: The pharmacokinetics are pretty good for the ultra rapid insulin analogs,
Speaker 4: and so that means that the control loop isn't too long.
Speaker 4: I mean, if you measure something and then deliver something,
Speaker 4: but then the drug that you deliver doesn't have an
Speaker 4: effect for a day, that's not going to work. Fortunately,
Speaker 4: insulin works within reaches peak and blood within an hour
Speaker 4: or so, and you can get a relatively short control loop.
Speaker 4: And then the reason it's had uptake is that it's
Speaker 4: really hard to control glucose by yourself as a patient.
Speaker 3: Diabetes is completely unique, and.
Speaker 4: That we've got this really powerful, really dangerous drug, insulin,
Speaker 4: and then we tell patients to figure out how much
Speaker 4: of it to give themselves multiple times a day, which
Speaker 4: is absolutely crazy and doesn't happen anywhere else in medicine.
Speaker 4: And so there was a real unmet need for changing
Speaker 4: that us the the development of closed loop systems and
Speaker 4: their uptake once they were developed, I think, yeah, so I.
Speaker 5: Would just echo that that the burden of treating yourself
Speaker 5: every day and adjusting many times throughout the day is
Speaker 5: really big. And and then maybe also that the way
Speaker 5: that it came about that we have closed loop today,
Speaker 5: it didn't came in one day. We tried back in
Speaker 5: the seventies where there's something you carried on your back.
Speaker 5: And and then you say, insulin came out and was
Speaker 5: a business in itself. Then the pins were there, pumps
Speaker 5: came out, was a business in the themself. And first
Speaker 5: the ten years after the CDMs came out, we were
Speaker 5: able to get it approved as a closed loop system.
Speaker 2: So going along those lines with the success of diabetes
Speaker 2: and closed loop on it. I'll start with you, what
Speaker 2: are some of the areas we've seen limitations or areas
Speaker 2: for improvement before we segue into other therapy areas.
Speaker 5: Okay, yeah, So then I think if first I will
Speaker 5: just trying to skitch out where we are today, and
Speaker 5: I think Steve did a bit of that with the
Speaker 5: With the you would say that it starts with that
Speaker 5: we are giving a bolus in from from the pump,
Speaker 5: and then when do you see that effect on the
Speaker 5: CTM since you need to wait around one and a
Speaker 5: half hour before it has been throughout the system, so
Speaker 5: there is a big time delay in the system. It works,
Speaker 5: and people are adjusting the meal habits and shows so
Speaker 5: they don't get too much fluctuation there. But then the
Speaker 5: in the we say then what could come that could
Speaker 5: change this? I think the first thing would be to
Speaker 5: get the time to lay down and and the biggest
Speaker 5: element is the insulin. And right now we have a
Speaker 5: dedicated insulin in in clinical trials and that that will
Speaker 5: work so fast that they will not be available in
Speaker 5: pins because they might give a hypoglycemia before you're finished
Speaker 5: with your meal. So so we can cut down a
Speaker 5: lot of time delay on the insulin. Then I would
Speaker 5: say on the pump side, we have an infusion set.
Speaker 5: It sits on for three to seven days. CTMs can
Speaker 5: sit on for fourteen days. Maybe you could picture that
Speaker 5: the infusion set could reach the same level as CDM.
Speaker 5: On the CTM sensors, you see a trend on moving
Speaker 5: from subcutis interstitial liquid measurement and some of the new
Speaker 5: ones going into and when you go into dermal you
Speaker 5: will gain five to ten minutes more in the reduced
Speaker 5: time delay. And then you can say, if you look
Speaker 5: not on the system but the alternatives, then there's cell
Speaker 5: therapy making Bezza cells and putting them in the pocket
Speaker 5: in the in the body, and there's a glucose sensitive
Speaker 5: incident on its way.
Speaker 2: So if we consider everyone sitting in this room, the
Speaker 2: majority of us work for organizations that work across a
Speaker 2: variety of therapy ecosystems. So I'd like to segue into
Speaker 2: to lewis what are if you had to garner a guess,
Speaker 2: what's the next therapy that's right for closed loop infiltration
Speaker 2: outside of diabetes.
Speaker 7: Definitely, I'd say in chology is a space that really
Speaker 7: is just prime to have close loop therapies start to
Speaker 7: be implemented. So I'm sure many of us have experienced
Speaker 7: someone in our life receiving chemotherapy, but they don't think
Speaker 7: many of us know is how they are dose. So
Speaker 7: chemotherapies have a very narrow therapeutic window, as many of
Speaker 7: us likely know. They work by killing cells through just
Speaker 7: kind of like means that would also kill healthy cells
Speaker 7: as well. But amazingly, the way that they're dose right
Speaker 7: now is on the body service area basis. And what
Speaker 7: that means is if you have Lebron James six nine
Speaker 7: two hundred and five two hundred and fifty pounds and
Speaker 7: happy the.
Speaker 3: Dwarf, if Happy the Dwarf was four six.
Speaker 7: Five hundred pounds, that'd get the same amount of chemotherapy.
Speaker 7: And the reason for that is the basis that they're
Speaker 7: doc on is using ideal body service area that comes
Speaker 7: from this equation from nineteen sixteen.
Speaker 3: So these two cousins to.
Speaker 7: Boy and to Boy, they empirically fit data to nine people.
Speaker 7: They took height and weight and body surface area and
Speaker 7: empirically fit this equation to it. And that's the standard
Speaker 7: of care today for figuring out how to dose patients
Speaker 7: with chemotherapy across the world that the data fire were
Speaker 7: in many other centers. So it really seems like oncology,
Speaker 7: just given the nature of the cytotoxicity of these drugs
Speaker 7: and just the center of characters being in the state
Speaker 7: where it's using this equation from one hundred years ago,
Speaker 7: or an abbreviated version of the pharma that was driving
Speaker 7: in nineteen seventy one when calculators weren't around, so it
Speaker 7: was a much easier way to get to BSA, but
Speaker 7: it was based on the Debois and Dubois parmula. So
Speaker 7: I'd say for those reasons, and the fact that the
Speaker 7: patient's generally in an a fusion care center, so you
Speaker 7: have the infusion pump puck directly up to them, so
Speaker 7: you have a way that you could modulate DELS to
Speaker 7: keep the concentration of drug within the therapeutic window. Really
Speaker 7: makes oncology a very interesting space.
Speaker 6: Yeah, it's interesting to think about these different time constants.
Speaker 6: You know, diabetes is a very very long time constant,
Speaker 6: sensors in there for a couple of weeks, whereas what
Speaker 6: you're talking about is more more acute. Acute maybe the
Speaker 6: wrong word but very short time caused. And there's plenty
Speaker 6: of other applications where you know that's time constant is
Speaker 6: on the treatment windows on the order of hours and
Speaker 6: not you know, days, weeks, years.
Speaker 4: Right, intermittent in that case, whereas somebody with type one
Speaker 4: diabetes has to be under insulin treatment for the entire
Speaker 4: rest of their lives. So whatever system you come up
Speaker 4: with has to be wearable and easily usable, and something
Speaker 4: that somebody can doesn't create more burden than it reduces.
Speaker 2: So going off that thread, the last panel talked a
Speaker 2: lot about considering the user and the development of these systems.
Speaker 2: So if we think across different therapy areas, the user
Speaker 2: plays a different role, right, So we talk about diabetes,
Speaker 2: the user is very intensely aware and often more educated
Speaker 2: on the technology than some of the people that develop
Speaker 2: the systems. If we think about other therapy areas like
Speaker 2: neurodegenerative or on cology, like you mentioned, open question to
Speaker 2: the panel, how do you see the role of these
Speaker 2: user playing in the different close loop applications across these
Speaker 2: therapy areas well.
Speaker 4: One thing I think is that we're trying to reduce
Speaker 4: the role of the user and Type one so.
Speaker 3: The first.
Speaker 4: Automated insulin delivery technologies are so called hybrid systems, so
Speaker 4: they modulate basil insulin. You need both basil and bolus insulin.
Speaker 4: Basil dealing with the basil insulin needs like overnight, and
Speaker 4: then bowl is dealing with meals and so forth. The
Speaker 4: systems typically manage the basil part and then the user
Speaker 4: is responsible for the bowls part. Our system, the islet
Speaker 4: is designed to take over one hundred percent of the
Speaker 4: insulin dosing and reduce the need for the user to
Speaker 4: get involved. And what we're trying to solve there is
Speaker 4: that only twenty percent of people with type one are
Speaker 4: able to maintain the kind of glucose control they're supposed
Speaker 4: to do because people with really good quantitative skills, really
Speaker 4: good attention to detail, so forth, people with great executive
Speaker 4: function they do fine. Everyone else doesn't. So taking the
Speaker 4: user out of the loop more and more is the
Speaker 4: direction we're trying to move in for diabetes.
Speaker 2: What about a therapy area such as Alzheimer's where the
Speaker 2: user could be the person with cognitive impairment or a caregiver.
Speaker 2: Anybody want to comment on, how do you see closeup
Speaker 2: playing in the Alzheimer's space.
Speaker 6: Yeah, I mean that's a super challenging patient population, right,
Speaker 6: I mean, diabetes has this massive patient population. I think,
Speaker 6: you know, we've done a very good job with the
Speaker 6: vast majority of that group. But there's certain are sub
Speaker 6: certainly are subgroups pediatric, you know, cognitive issues, dexterity issues
Speaker 6: where managing the treatment but then also just applying the pump,
Speaker 6: applying the sensor becomes very challenging for that patient group
Speaker 6: and there's definitely room for improvement there.
Speaker 4: The question with things like you know, neurodegenerative diseases is
Speaker 4: what to measure, right. I'm interested in Parkinson's because my
Speaker 4: mother suffers from that and she has to take this
Speaker 4: complicated regimen of multiple doses. V just I guess recently
Speaker 4: got approval for doodopa, which is an sebt Q infusion,
Speaker 4: so that seems very familiar to me.
Speaker 3: In the insulin space.
Speaker 4: You can infuse this drug supultaneously maintain steady levels. But
Speaker 4: if you were going to try and turn that into
Speaker 4: a closed loop system, what would you measure? You know,
Speaker 4: would you measure interstitial dopamine That's not really where it functions, right,
Speaker 4: So would you measure tremor maybe you could do something
Speaker 4: like that. I think that becomes the challenge for these
Speaker 4: other fields.
Speaker 5: You could say that if it's not a fully closed loop,
Speaker 5: but just some of the components, like using the CDM
Speaker 5: for for other for other things, then I think that
Speaker 5: the that the we have tried out to use a
Speaker 5: CDM for tight trading once weekly insulin to figure out
Speaker 5: quite fast where to go and then go up in
Speaker 5: a few steps. Yeah, so really long acting components getting
Speaker 5: them to the right level fast. Uh. And one other
Speaker 5: element could be to use the CTM sensus for anti
Speaker 5: obesity treatment.
Speaker 2: So segueing to lessons learned, one of the areas we've
Speaker 2: talked about so far as the readiness of the technology.
Speaker 3: So back to the diabetes space.
Speaker 2: A lot of the technologies used to do any of
Speaker 2: these aspects of closed loop development have been readily available
Speaker 2: for the last twenty years. But even still, if you
Speaker 2: look at the companies playing in this game, very few
Speaker 2: if any, develop all of the technology all internally and
Speaker 2: requires a lot of partnership. So if Ben, I'll go
Speaker 2: to you, if we look at focusing on improving technology
Speaker 2: in these other areas, what are some of the advices
Speaker 2: or lessons learned that you've seen that helps not only
Speaker 2: develop this technology, but be able to partner effectively to
Speaker 2: get these solutions out to patients for other areas.
Speaker 3: Yeah, that's a great question.
Speaker 6: I think, you know, the collaboration of all the partners
Speaker 6: that are involved in this ecosystem, it's a complicated beast
Speaker 6: raight and the ability to rapidly develop and deploy a
Speaker 6: system depends on early engagement between all those parties. So
Speaker 6: you're developing a holistic system from the beginning as opposed
Speaker 6: to disparate development that then gets tied together.
Speaker 3: At the end.
Speaker 6: And it's a very difficult challenge. We see it all
Speaker 6: the time in diagnostics where the you know, the assay
Speaker 6: is developed and then the consumables developed and the instruments developed,
Speaker 6: and there's not that holistic from the beginning viewpoint, and I,
Speaker 6: you know, I don't have a lot of great answers there.
Speaker 6: It's very challenging because very often the pharma company is
Speaker 6: not in the in the hardware space.
Speaker 3: And the drug delivery.
Speaker 6: Company is not in the diagnostic space, and so tying
Speaker 6: all that together early to develop that holistic, efficient system
Speaker 6: is particularly challenging.
Speaker 4: The regulators can help a lot though that's another place
Speaker 4: we haven't discussed that.
Speaker 3: We had an advantage in.
Speaker 4: The diabetes space because the FDA created an it's this
Speaker 4: five ten K pathway for closed loop systems, and they
Speaker 4: created something called interoperable CGM, an ICGM with so it's
Speaker 4: a five to ten K with special controls and essentially
Speaker 4: if it could communicate with one of the devices in
Speaker 4: the x ecosystem and if it met certain accuracy criteria,
Speaker 4: then you could get this ICGM status. And as a
Speaker 4: company making a closed loop device, we are able to
Speaker 4: now do the study with one ICGM and then substitute
Speaker 4: another ICGM into our system without a regulatory filing. We
Speaker 4: just did a letter to file, so that really accelerated
Speaker 4: the whole process tremendously. You know, we launched with one CGM,
Speaker 4: we got the spec for another CGM, and launched four
Speaker 4: months later with a second CGM, and then we got
Speaker 4: the spec for a third and then launched a number
Speaker 4: of months later for that, and now we're we've got
Speaker 4: three CGM sensors that are all available, so it's user
Speaker 4: choice that wouldn't have been possible without the FDA stepping
Speaker 4: in and creating that regulatory framework.
Speaker 5: You could also say that by going through a partner's
Speaker 5: you open up a free, free competition and the BIST,
Speaker 5: the pump company can can pick the BIST CTM company
Speaker 5: and I and you get it even bitter system than
Speaker 5: if they try to do it internal.
Speaker 2: Yeah, this is an interesting space because you have companies
Speaker 2: who are partners and competitors at the same time, sometimes
Speaker 2: even on the same product. Switching to another technology question
Speaker 2: with this for you, So you mentioned oncology, and in
Speaker 2: terms of companion diagnostics, to measure the metric you're proposing
Speaker 2: requires a sophisticated technology in the clinic to be able
Speaker 2: to measure. Do you see start with oncology, Do you
Speaker 2: see that becoming a low cost product eventually? And what
Speaker 2: do you think would it take to get away from
Speaker 2: a diagnostic machine to measure the variable versus a wearable What.
Speaker 3: Are your thoughts there?
Speaker 7: Yeah, absolutely, So for context, we've developed this closed loop
Speaker 7: drug delivery system to control of the concentration of chemotherapy
Speaker 7: and we've shown it in vivo we published it earlier
Speaker 7: this year. So in the system, we draw a blood
Speaker 7: from the animal or eventually a patient and then we
Speaker 7: do this raptive the blood preprocessing step to then put
Speaker 7: it onto a high performance to liquid chromatography MasSpec or
Speaker 7: HBOCMS system, which has been as many of the people
Speaker 7: in this audience likely know, a gold standard by the
Speaker 7: FDA to determine the concentration of drug for many many
Speaker 7: different clinical trials over the years. So we really wanted
Speaker 7: to design the sensor or the overall system around the
Speaker 7: sensor because of the development and the trust and to
Speaker 7: the points that we're mentioned earlier, the fact that you
Speaker 7: really need this sensor, and that's one of the things
Speaker 7: that really helped in the diabete space to enable closer
Speaker 7: the control. So we designed this overall system around LCMS,
Speaker 7: and then the loop gets closed by taking that concentration
Speaker 7: reading and put it into the control algorithm. So with that,
Speaker 7: that's one of the major questions we always get is
Speaker 7: LCMS is very expensive. The high end ones that you'd
Speaker 7: likely want in the clinic are just shy of about
Speaker 7: a million dollars, So the upfront cost is large, But
Speaker 7: when you start thinking about the lifetime of these types
Speaker 7: of devices, they'd likely last with good maintenance on the
Speaker 7: order of about a decade. You can imagine you can
Speaker 7: do about two maybe three patients a day with the
Speaker 7: system comes down to about one thousand uses over a year,
Speaker 7: ten thousand over a decade, So the cost per patient
Speaker 7: is approximately one hundred dollars if you work it out
Speaker 7: according to that way. Of course, there's many other variables
Speaker 7: that go into account with it. You'd have to have
Speaker 7: personal cost, but the cost of the system isn't as
Speaker 7: large as you'd initially think, and there's likely if this
Speaker 7: system were ever to reach it to the clinic, they'd
Speaker 7: likely be work continuing to bring the cost of the
Speaker 7: LCMS device down. So definitely opportunity i'd say is the
Speaker 7: ability to make low cost LCMS devices is definitely something
Speaker 7: that's interesting, and that's just one of many different types
Speaker 7: of approaches you get take for the censor, But we
Speaker 7: really decided to focus on that just because it is
Speaker 7: very well trusted, able to be applied to multiple different drugs,
Speaker 7: and there's allowed of us to develop this system and
Speaker 7: apply it to a chemotherapy space.
Speaker 3: You also have to think about the value.
Speaker 4: So in the diabetes space, you know, these devices are
Speaker 4: not nearly as expensive as that, but there are a
Speaker 4: lot of people because each person needs one and multiple
Speaker 4: over their lifetime. Usually, but we're reducing the risk of
Speaker 4: long term complications, and you, I believe would be reducing
Speaker 4: the risk of chemotherapy related complications because of overdosing or
Speaker 4: inadequate treatment of a cancer from underdosing. So I think
Speaker 4: you can easily make the argument that a one hundred
Speaker 4: dollars is worth the reduction to an insurance company is
Speaker 4: worth the reduction of those those complications.
Speaker 3: Yeah.
Speaker 7: Absolutely, There's been this additional approach that's been developed therapeutic
Speaker 7: drug monitoring, where you take the concentration of the end
Speaker 7: of one around of chemotherapy and then don't suggest for
Speaker 7: the next round of chemotherapy. And even with that, which
Speaker 7: if you think about it, that's the closed system. It's
Speaker 7: a sampling rate in the case of five few of
Speaker 7: once per two weeks. It's a very basic control algorithm
Speaker 7: that's normally for five few. The clinical trials I'm aware
Speaker 7: of that have been done, it's a rule spase algorithm,
Speaker 7: so if you're a certain percent above, you decrease by
Speaker 7: x percent of the dose. So even within those trials,
Speaker 7: they've shown benefit in terms of tox and efficacy. So
Speaker 7: I completely agree with you, and in the paper we
Speaker 7: put out, we did some preliminary analysis on that with
Speaker 7: certain assumptions of how much benefit we could apply based
Speaker 7: on those TDM studies, and it does when you take
Speaker 7: everything into account, does appear that it could be cost effective,
Speaker 7: even given the high costs involved.
Speaker 2: An area like to go into a little bit is
Speaker 2: around access. So when the first hybrid closed loop technology
Speaker 2: is launched in the diabetes space, if you purely look
Speaker 2: at the physics and the technology, it's a no brainer
Speaker 2: that every single person with diabetes would therapeutically benefit from
Speaker 2: this system. However, if you look at the percent of
Speaker 2: the population of persons with diabetes that are on such
Speaker 2: a system is incredibly low, a single digit percent. How
Speaker 2: do we increase access to these technologies by building patient
Speaker 2: trust not only a diabetes space, but in other therapeutic
Speaker 2: areas where the concept of a closed loop system would
Speaker 2: be completely foreign to an individual receiving the therapy.
Speaker 4: Well, I'm going to mention one thing, which is that
Speaker 4: percentage being that low. That may be true for diabetes
Speaker 4: as a whole, but if you look at type one
Speaker 4: we're we're at about thirty percent, So it's really pretty
Speaker 4: substantial adoption in the type one space. The other thing
Speaker 4: is that it's kind of a unique situation because, as
Speaker 4: was mentioned, CGM was always already available. Insulin pumps were
Speaker 4: already of aailable Obviously, the insulins were already available and
Speaker 4: the people were using them, they just weren't using them together.
Speaker 4: And when the closed loop devices came out, they used
Speaker 4: the same billing codes as the dumb pumps, right, So
Speaker 4: the the insurer was getting increased value for no increase
Speaker 4: in cost. So the value proposition was pretty compelling in
Speaker 4: that case. I don't know if that's that's probably not
Speaker 4: going to be the case for some of these other ones.
Speaker 5: You can say that I tried to look up how
Speaker 5: much longer would a person live if if they go
Speaker 5: from a pin system to a closed loop system, and
Speaker 5: I might not have got all the data right, but
Speaker 5: what it's all around the too too too quality adjusted
Speaker 5: life years in And then I think in in US
Speaker 5: we were most insurance are willing to pay fifty two
Speaker 5: hundred thousand per year quality adjusted lifespan improvement. And so
Speaker 5: you will say this should be enough recent enough science
Speaker 5: to YE to get it out there.
Speaker 2: We have about three and a half minutes left, so
Speaker 2: I like to open it up for questions from the floor.
Speaker 8: Either.
Speaker 9: My name is Sheldon Oberg and with bets to biomedical
Speaker 9: but in a former life I used to head the
Speaker 9: Electronic Diabetes Insulin Delivery System Electronic Mini Men. The last
Speaker 9: panel was on digital health, and as we know, the
Speaker 9: insulin industry has been using connected systems for well over
Speaker 9: two decades. I'm curious on your insights on how digital
Speaker 9: health has helped and improved that patient barka, So I'll start.
Speaker 2: So, I think one area is providing access to information.
Speaker 2: So by having connected applications or just having the data
Speaker 2: stored in a cloud, it's made life easier for not
Speaker 2: only the persons with diabetes using the systems, but also
Speaker 2: they're endocrinologists that they see. We could spend a whole
Speaker 2: panel talking about the difficulty with the minimum amount of
Speaker 2: time that a patient gets with an endocrinologist, and I'm
Speaker 2: hoping you can.
Speaker 3: Talk about that.
Speaker 2: But having access to this information, getting feedback on how
Speaker 2: to create these reports and graphs and how to make
Speaker 2: it very available is very helpful for people. Also simplicity,
Speaker 2: I think one of the dangers, as was mentioned in
Speaker 2: the last panel, is sometimes we connect devices for connection
Speaker 2: sake rather than actually thinking about what's needed, and the
Speaker 2: reality is a lot of people that are on closed
Speaker 2: loop diabetes systems don't want to have it in true life,
Speaker 2: so providing them with every single bell and whistle and
Speaker 2: alarm and alert actually is a high level of dissatisfaction
Speaker 2: for the user. So I think it's important that we're
Speaker 2: mindful of, yes, we can have these digital companion applications,
Speaker 2: but being cognizant of how to use them effectively to
Speaker 2: provide a wealth of information while having limited intrusion to
Speaker 2: the user base.
Speaker 4: One thing that I think is pretty interesting about the
Speaker 4: digital health applications for this use case is that so
Speaker 4: called follow apps are really impactful, which means that somebody
Speaker 4: can have their CGM glucose information followed by another person,
Speaker 4: often a parent, if it's a child, or a spouse,
Speaker 4: or even just another friend with diabetes, and so they
Speaker 4: watch out for each other and if some you know,
Speaker 4: if an hypo alarm for your friend goes off, and
Speaker 4: you know.
Speaker 3: You can call them up and say, hey, are you okay?
Speaker 4: You seeing this? And I think that that's tremendously valuable.
Speaker 4: It kind of expands the network of caregivers beyond the
Speaker 4: people who are immediately present to any anyone you want.
Speaker 3: Frankly, yeah, I would second that.
Speaker 6: My five year old niece is Type one and the
Speaker 6: connected ability to have her parents be able to monitor
Speaker 6: is just tremendous.
Speaker 3: It really is.
Speaker 2: Is there an there one more question?
Speaker 8: I work for a design agency and we'll be looking,
Speaker 8: in fact, for the last sort of a year or so
Speaker 8: into biosensing and.
Speaker 3: The closed loops.
Speaker 8: I mean, in fact, I came across a company it's
Speaker 8: only down the road. Then they created this sensor where
Speaker 8: you put in just a plastic cube coming out from
Speaker 8: a wound after an operation. You would tell you about
Speaker 8: the chemistry of the liquid coming out. That will tell
Speaker 8: you how well is the actually you know the hill
Speaker 8: that is taking place, which is fantastic and it's also
Speaker 8: a throwaway center if you like. So I was I
Speaker 8: want to ask the panel, how where are we going
Speaker 8: with a biosensing I think we are there. There are
Speaker 8: sort of many examples out there, but I haven't seen
Speaker 8: a lot of the sort of like closed loop systems.
Speaker 8: I mean, we kept talking about which is great about
Speaker 8: type one diabetes and so on, how can biosensing help
Speaker 8: us move into other bigger areas and bigger applications.
Speaker 2: Thank you, Eric, Do you want to take this?
Speaker 5: Yeah, So, I think there's a that they'll becoming a
Speaker 5: number of new symstotypes and some day they call it
Speaker 5: electronic nose, a sensor that can that can sense a
Speaker 5: number of different things and then by looking a little
Speaker 5: bit on on the fingerprick from then then they can
Speaker 5: then they can miss a lot of metabolics and key
Speaker 5: tones and and other stuff. And yeah, so so I
Speaker 5: think there's a lot of UH since US on its way.
Speaker 5: Also the CTM since US are trying to build in
Speaker 5: more sensors within the existing system.
Speaker 4: So yeah, there's a lot of interest in a key
Speaker 4: tone sensor for type one diabetes space so you can
Speaker 4: detect failure of insulin delivery, but also for lactate for
Speaker 4: the UH, the lifestyle UH or or athletic improvement. So
Speaker 4: having lactate sensors measurements of lactate is really something that's
Speaker 4: only done by pro athletes or or high level athletes now,
Speaker 4: but you could conceivably have c g M like measurements
Speaker 4: of lactate which could potentially improve athletic endeavors.
Speaker 3: And it's yet to be seen.
Speaker 4: I mean, both of the major CGM companies have launched
Speaker 4: direct to consumer devices for people without diabetes, with the
Speaker 4: idea that being able to see what particular types of
Speaker 4: food due to your blood glucose would change your habits.
Speaker 3: And I can tell you that it's done that for me.
Speaker 4: After seeing what some of my favorite breakfast foods did
Speaker 4: to my glucose, I changed my habits considerably, So I
Speaker 4: think there definitely is a role for this.
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