Invent: Health

Diabetes Monitoring: Human out of the loop - Transcript

Speakers: Matt Parker, Chris Dawson & Andrew Chapman

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Matt: Hello, and welcome to the second series of Invent Health, a podcast from technology and product development company TTP.
I'm your new host, Matt Parker. I'm an engineer here at TTP and have been working across novel healthcare technologies for the past six years.
The pace of innovation in the healthcare space has never been higher, and I'm fascinated by the role technology has to play in enabling the future of healthcare.
Over the course of this season, we're going to be exploring the fascinating future of health technologies from continuous monitoring devices that are changing the way we think about epilepsy treatment, to how rapid innovation could hold the key to solving healthcare's most pressing problems.
Today, in this inaugural episode of our second season, we're looking into diabetes, and asking when it comes to diseases with a high burden of treatment, how can we take humans out of the loop?
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Designing treatment regimens for diseases requires vision over all aspects of the creation process. But even the most sophisticated treatments built on the latest pharmaceutical evidence and using the latest technology will fail if you're unable to effectively engage the patients themselves.
Ensuring patients are able to adhere to a full course of treatment or even simply administer their drugs correctly is notoriously difficult. Despite the advances in monitoring and delivery technologies, the burden of continuously tracking and adjusting your treatment is greater than you might think.
So, what if you are able to take this challenge away from patients? What if you are able to create a closed loop system, one where monitoring and treatment was fully automated?
For serious conditions like diabetes, this is something that healthcare practitioners have been battling for decades. Patients have to monitor their blood glucose level and take frequent daily injections of insulin. The cumulative impact being out of the ideal blood glucose range can have really significant health impacts.
Speak to any one of the world's 415 million diabetic patients and they will tell you what a burden this constant level of monitoring and delivery can be. So, I wanted to find out what technologies there are out there, which could take them out of the loop, automating the process entirely.
To find some answers, I went to speak with one of our top engineers here at TTP, Chris Dawson.
Chris is a mechanical engineer who after working in F1 Motorsport and aero engineering, now leads the biosensing team at TTP. If you listened to our first season of Invent Health, you’ll remember Chris speaking about the fascinating neuromodulation devices that are changing the way we think about neuro diseases.
But today, we're focusing on diabetes, and I started off by asking Chris about why when it comes to treatment adherence and the burden of constant monitoring and delivery, diabetes is the big one.
Matt (Interview): Hi Chris, welcome to the show. Do you want to tell us a little bit about the work that you do at TTP?
Chris: Thanks very much, Matt. So, I am the team lead for the biosensing team here at TTP. We tend to work in developing complex, difficult biosensing solutions to detect and measure valuable analytes in real time.
Matt: And what kind of things does that end up being?
Chris: So, anything where a continuous measurement gives you valuable, useful information about a disease state.
Matt: And why is diabetes the big one in this space?
Chris: Oh, for many reasons, I think. First of all, it's very widespread disease state. There's a significant proportion of the population that have it. It needs to be continuously managed. So, there's a lot of patient involvement in the management of that disease state.
And getting it wrong is critical. If you have a significant hyper or hypo-excursion, then you are at high risk of fatality, maintain your blood glucose level within a set range is critical to your state of health.
Matt: So, run me through what would a patient have to do in a standard day to manage their condition?
Chris: If you're a really, really, really good patient, really well-behaved and do exactly what you're told which none of us are, you should take a minimum of four finger stick tests per day, generally on waking, before bed, and then a couple around mealtimes.
So, that involves finger pricking yourself, putting some blood onto a test strip, and taking a reading from that and recording that, all of which is a very manual process for the patient.
Matt: And what makes that so difficult to manage? What aspect of that is hard?
Chris: Well, so if you are taking a single point measurement, which might be incredibly accurate, you are still only taking four measurements a day. So, if you have a hypo event at night, you completely miss that.
If you go out for a big meal and a few drinks, then you can have an excursion that's abnormal. And so, what lots of people end up doing is kind of getting a feel for do I feel bad or not.
The problem with that is generally, you don't start feeling unwell until you're quite far out of the recommended glycemic range.
Matt: What are the challenges, I guess, if you are outside of that range? What is the kind of effect can that have in the long-term?
Chris: So, there are many, many comorbidities that sit alongside diabetes. Your chance of dying early increases drastically with poorly managed diabetes, as do the risks of all of the comorbidities that sit alongside diabetes.
So, managing it well is tricky, challenging, and hugely important for good standard of care.
Matt: So, you talked a little bit there around some of the things that you have to do, some of the processes. Is that a completely manual process or is there an element of automation and support that exists already for patients in this space?
Chris: So, there are lots of different technologies out there, and each technology will be relevant to a different subset of the diabetes population.
The most exciting tool that's come up in the last 10 years is continuous monitoring. So, this is instead of having to finger stick yourself four times a day, you are able to wear a continuous blood glucose monitor, which lasts for well, up to two weeks now.
They started off lasting several days, then a week, and now, we're up to a couple of weeks. And these can effectively give continuous readout of what your blood glucose is doing.
So, they take a measurement every five minutes and do some analytics on it, and tell you not only what your measurement is, but what direction it's headed in. And so, that allows you to intervene before you go outside of your glycemic range.
Matt: And so, once you've got a reading from one of these systems, as a patient, what do you have to do with that? How does that change your behavior?
Chris: So, depending on what that reading is, if you’re going up or going down, you might either have to go and have a suitable snack to pull yourself out of going into a hypoglycemia or you might have to administer insulin to stop you going hyperglycemic.
Matt: So, in this context, what do we mean by treatment adherence? Why is it so important?
Chris: So, it's really critical in diabetes because if you get it wrong, the outcomes can be pretty poor.
But it basically means the patient buying into and engaging with the treatment that they've been prescribed. And that seems a really glib obvious answer, but for a disease state like diabetes, it can involve many, many interactions across the course of a day worrying about lots of things moderately, continuously, and even worrying about what happens when you're asleep.
So, it's really not straightforward. It requires a lot of user effort, and it can be quite tiring from both an intellectual and physical standpoint to ensure that all of the things that you're supposed to do, you're doing and doing well.
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Matt: Chris is right when he talks about the many interactions with a disease that someone with diabetes would have to deal with. It really is extraordinarily high.
Some estimates suggest that someone with diabetes will make 180 more health-related decisions each day than someone without diabetes.
So, it's clear the huge and tangible benefits that would be available to someone with diabetes if these processes of monitoring and injection were fully automated with devices living for months or even years in the body.
So, next, I wanted to learn more about how we can go about monitoring and treating diabetes, what are the most effective technologies on the market now in terms of sensing glucose levels, and ultimately, delivering insulin.
I got in touch with another expert working in this field to find out.
Alright, so Andy, thanks for joining us today.
Andrew: It's a pleasure. Thanks for the invite.
Matt: Dr. Andrew Chapman is a scientist and entrepreneur who for over a decade, has designed and led interdisciplinary commercial and academic programs across a whole range of different scientific disciplines.
He’s currently the CEO and co-founder of Carbometrics, a company whose revolutionary biomimetic glucose binding molecules have made them one of the most exciting companies working in this space.
Their glucose binding molecules are helping Novo Nordisk to develop new cutting-edge glucose reactive insulins, and in the meantime, enabling the next generation of glucose sensors.
I sat down with Andy to find out some more about his work with Carbometrics, and just what it is that their binding molecules are able to do for people with diabetes.
I guess, to keep it at the high level, how important is it to keep the patient at the center of any solution, any technology that we're trying to propose to help them manage their condition?
Andrew: Well, yeah, absolutely. You know, it’s really important. So, I suppose you have to really understand what any treatment is going to do to fit into their life. I think we're a long way from where it was life or death, it was take this big insulin or it's probably fatal.
I think now, there are different treatment options and mixtures of treatment options, which mean we can be a lot more targeted in what we prescribe to certain patients, not just in small molecule drugs, in peptide drugs, but in technologies that compliment them.
And one solution that be good for another patient may not be for another. And I think getting adherence to treatment and getting them to constantly stay very true to whatever treatment regime they're supposed to be doing, has got to be of paramount importance.
Matt: I'd love to dive into that a little bit more. Maybe to start, could you tell me a little bit about Carbometrics?
Andrew: Yeah, sure. Carbometrics is really a spin-out from a spin-out, and the parent company, if you like, is Ziylo.
And Ziylo was spun out of Professor Tony Davis’s group in University of Bristol who's just a world-leading super molecular chemist, and in around 2014, he made a really significant discovery, his first glucose binding molecule discovery.
Which really, got the company Ziylo out, like got going, the startup, but it was really the second discovery of the second-generation glucose binding molecule by Tony and Rob Tromans, who's now our Head of Research.
It was the most selective and fantastic discovery that had come out of this group. And that really pivoted Ziylo into what it became, which is when I joined and Ziylo became about taking this molecule forward for its application in glucose sensitive insulin.
Matt: I ask this some hesitancy — could you tell me how the glucose binding molecules work?
Andrew: Yeah, it's actually remarkably simple. It’s really the design principles that Tony was building on decades of thoughts around there, they're just inspired by nature.
We take the active site of an enzyme or the binding site of a protein for a particular molecule, and what that is, is the right orientation of molecular motifs, if you like. If we think of these north and south parts of a magnet, so the right bits of molecule, the right shape of hole that you make, the cleft that's in there.
And so, what emerged was this really beautiful symmetric design for glucose (symmetry’s really useful for chemists for building something) that is the exact size and shape for glucose, the exact molecular complement of chemical bits, we want to point in the right direction of glucose.
And it results in really exquisite selectivity for glucose as the only molecule it binds. And now, there are lots of things that really look like glucose. I mean, problem is water looks a lot like glucose really from a high level, and it's very hard to distinguish between these things in water, and particularly, amongst the sugars.
I mean, the proteins get all the attention, but really, the carbohydrates that have just as much, if not more complexity within them, and the structures they can form. And so, huge amount of … you look at the inside of our body, it's painted with carbohydrates.
So, it's a very tough challenge to pick out something that will only bind just that right size and shape of glucose. In fact, it's so exquisitely selected for glucose.
Glucose exists in two forms, in dissolved in solution: the alpha and the beta anime. And really, this molecule only binds the beta anime, so only one form of … and that's of the keys to its selectivity really.
Matt: That's absolutely fascinating. So, Carbometrics’ focus now is long-term implantable glucose sensing. So, maybe could we talk a little bit around, I guess, the current state of sensing in diabetes treatment?
Andrew: So, the advent is continuous glucose monitoring where the patient wears sensor permanently, which is always taking their blood glucose every five minutes, which is virtually always.
It really just provides much, much better actionable data for the patient, and overall, gives you a much better way of assessing their general state of controlling their blood glucose.
And I think now, it's really becoming widely accepted that the gold standard of long-term blood glucose control has, and is the HbA1c test. So, how much of your hemoglobin has got basically glucose stuck on the end of it. It acts like a really long-term marker for how well your blood glucose is being controlled over a reasonably long period of time.
But the continuous glucose monitors been able to say, “Well, I can actually just look at the data and I can see what percentage of time you were in range” and that is really amazing. So, I think that it provided much better data for the patients.
And types of sensors that are there really exist around the form factor they say of a small, no bigger than an inch type circle that's worn on the arm or the abdomen and a very, very small wire poke through skin into the subcutaneous layer, so a few millimeters down into the skin.
These are worn for about two weeks maximum, and it wasn't the same as the blood draw from the finger. And there are some reasons. It's a hard task to make a sensor that goes inside and lives in the body, basically inside the body for 14 days.
As things have improved in the sense side, the glue side, the algorithms, these things are now really chasing the accuracy down to well within what you can get from taking capillary blood glucose draws from a finger stick monitor.
But the problem remains that by no means, all patients have this one. By nowhere near means all patients have this. And so, there's a price, there's a particular usability issue. You know, some patients don't want to have a visible sensor on them at all.
So, there is always this need to have other form factors of glucose sensors. There's only really one decent example of it, is a fully implantable sensor. The one's that’s in the market from Senseonics can be worn for 180 days. And I know there's plenty of data to show that it goes out to longer time.
But the sort of disadvantage of that, the current status of that is that the patient, although they have an implant which is just inserted by a simple inpatient procedure, they still have to wear something on the outside, the transmitter, which reads the data from this implanted sensor.
So, all these things, they're certainly getting there, and their accuracy has become really phenomenal.
Matt: Yeah, it's fantastic. And so, Carbometrics’ goal here is to replicate that long-term implantable sensor with the same accuracy. Which aspect are we tackling? Are we also looking at that transmission phase, having to wear the external sensor?
Andrew: So, our principle, USP, if you like here is that the fundamental technology behind this glucose detection principle is based on glucose binding to our glucose-binding molecule. And the molecule itself is so stable that we’ve never seen anything chemically degrade it or oxidatively degrade it.
And the body, I heard it said, I think it's a great way of framing it, is that it's easier to put something in space for a year than its inside a human body.
So, the engineering challenges that Senseonics must have faced to get their glucose-binding molecule, or the glucose-binding molecule used in it, which is another synthetic one, which is not as selective to glucose. It’s actually really chemically unstable. It's very fragile.
And so, they’ve had to do some really clever things to try and get this molecule to last inside the body up to a year, approved for six months but could sure go longer. But then all of the peripheral stuff that is around that has resulted in the distillation of this form factor, which is an implantable device which be on the outside, powered from the outside.
We believe we have the opportunity to make something that can last even longer and be fully implanted so that the patient is not seeing this device.
The great hope here would be that you can insert something via a simple procedure and forget about it for two years or more, and still have accurate readings which are not sensitive to environmental things you may take.
We're starting from a really good point that we really just have built something so selective for glucose. We have much less of a worry that some other random molecule you may see will cause a false reading in the sense.
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Matt: I was really surprised by just how fundamentally simple the glucose binding molecules Andy described are, and equally, by the challenges of implementing them in glucose sensors.
But sensing glucose levels is only one half of the problem. The other half is interpreting the data they’re giving, to select the right dose of insulin to deliver. Some patients are now tackling this problem themselves by hacking their devices to close this part of the loop; to automatically deliver insulin in response to the sensor data.
They're creating custom software that does it for them. It's an example of how much patients want to take themselves out of the loop, the weight it takes off their shoulders.
So, why aren’t these systems available from the major manufacturers? Are there inherent risks here?
I asked Chris about the benefits and risks of hacking your own system before moving into some of the alternative treatments available outside of this sensing and delivery approach.
And we've heard how patients are hacking their own systems to enable these closed loop systems, what's allowing them to do it, which has been so difficult for the large manufacturers.
Chris: I suspect there's two things happening. First of all, they're taking on their own risk and they are happy doing that, but they're also early adopters, so they're probably incredibly invested and interested in what the sensor's doing, what the algorithm's doing, and what their pump is doing.
So, actually, in terms of hands-off use, they're probably a very poor set of people to look at because they're interested and motivated and invested in setting up their own hybrid closed loop system.
Whereas, if a large medical device manufacturer were to sell that as a system to an untrained, possibly less-interested user who understandably wants to use that system to minimize their interactions, then there are much greater opportunities for it to go wrong.
And when it does, I would imagine the large medical device manufacturer would be eminently suable.
Matt: And do you think that's affecting the innovation process?
Chris: Yes. This is a difficult thing to have a strong view on because I can absolutely understand it. I don't have a strong conviction either way.
But there is an argument to be made that implementing fully closed loop systems could save more lives, but there is a high probability that it would also result in people losing their lives.
Matt: Which I guess is a reminder to the importance of getting it right in the hardware design wherever possible, and these are high stakes.
Chris: Oh, absolutely. In the technology, and the implementation of the technology and the ease of use of the technology, and in the minimization of user burden of the technology — all of these things are important to ensure that we get good outcomes.
Matt: So, we’ve talked about some of the challenges and the opportunities provided by automating this closed loop, this process, but I guess this is not entirely without risk. What are some of the things that could go wrong?
Chris: So, the biggie here is you under or overdose yourself with insulin without knowing it. You've completely allowed the algorithm to determine your treatment course and the algorithm gets it wrong either because the algorithm gets it wrong or because it gets a wrong input from a sensor.
So, as soon as you take the human out the loop, you make the patient's life much easier because the human in the loop is them, but because they are not interacting often with the system, you lose the ability to adjust based on experience, based on them knowing themselves, and based on taking a reading and occasionally going, “Well, that reading's clearly incorrect.”
Whereas when you've got your algorithm doing all of that, it assumes that all of the data that gets is right, and does its algorithmic magic and infuses you with insulin.
Matt: Is this the only approach that's currently being trialed?
Chris: No. One approach is glucose reactive insulin. In its very basic form, glucose reactive insulin is engineered in a way so that you can dose a consistent amount of the drug into yourself every day and it reacts with the glucose in your blood, and you’ll only use the amount of insulin that's required.
So, no measurement is required because all of this is dealt with by the glucose reactive insulin. And so, this leaves the patient just dosing themselves with a set amount of glucose every day, and never having to worry about measuring their blood glucose. The pharmaceutical kind of deals with it for you. So, that's one approach.
The other area, I guess, is less in pharmaceuticals and more in biology. And there are multiple teams that are working on engineering beta cells, which are the cells in your pancreas that secrete insulin and being able to do beta cell transplants back into your pancreas, meaning that you can effectively produce your own insulin.
Matt: How would that work?
Chris: That's as far as I'm concerned, is magic. So, there are a couple of teams working on it at the moment. There's a team in Harvard that are using stem cells to grow beta cells, effectively grow beta cells in the lab and then people have undertaken implants of these beta cells.
So, there's lots of work going on in understanding how we can protect the beta cells from immune attack. Then the challenge becomes what happens if these cells become cancerous?
So, you need to have this protection for the beta cells that can be turned off so that if beta cells become cancerous, your immune system can then respond to them. So, that's a super exciting area.
There's an even longer-term play in biology, which is can we take standard cells out of people, reprogram them back a few steps, and then turn them into beta cells? So,
then you would effectively have produced beta cells that align with the patient's own genetics.
Matt: Wow.
Chris: Yes. So, that's effectively a cure for diabetes as with many things. It's super exciting. There's lots of research and work going into it. I think it's a little while off.
Matt: I think that’s a very sci-fi future where it's a cure by implanting your own cells back into you.
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Matt: Hacking your own insulin device is not something I would recommend all of our listeners do, but it's certainly has had some startling results for those bold enough to try it. And you can see why.
While unregulated, there are examples of patients who have hacked their way to something that closely resembles the closed loop system that would benefit so many struggling with diabetes.
But Chris also mentioned another field which has the potential to entirely change the lives of people with diabetes; stem cell therapies. This is one of the most hyped fields in healthcare at the moment, and for good reason. Do have a listen to our two-parter on this in the last season of Invent Life Sciences to find out more.
I asked Andy about his thoughts on this as a future treatment for diabetes, and about some of the timelines he sees for getting all of this implemented at scale.
And I guess, there's a handful of other approaches to that dream, as the technology solution with the fantastic sensing and closing the loop in terms of delivery, but there's some interest as well around sort of cell therapy treatments for diabetes.
Andrew: There's a lot of interest and they are really just … if I'm honest, they're the one I'd back. I back them fully for technology. But I think the issue is like cost and availability as a general solution.
So, huge challenge is around being able to give yourself cells which are not from you. They also got to be in the right place. I mean, they're located in the pancreas near the portal vein where they are for a reason, and we don't really have the option of sticking them back there easily. So, we've got to give them somewhere else.
And I believe we infuse them into the liver, for example, in one example of this cell therapy, and that's not bad. That's kind of where they need to be, where the insulin needs to be.
The cells are not particularly robust as I understand it. Some cells grow really well and don't mind being cultured. I understand beta cells are particularly strappy about how much oxygen and nutrients they have. And so, they're just not very robust things to be delivering.
And so, there's been these huge challenges around encapsulating them, so isolating them from the immune system, providing them with the right matrix to be in so that they can grow and secrete insulin and the right nutrients, so the nutrients can diffuse to them. And the products i.e. insulin, diffuse away from them well.
But when they're in there, I mean, they do an incredible job. Obviously, they sense glucose perfectly, exactly what you'd need, and they make the insulin you need so you don't have to carry it around, and it just comes straight from you, and it's going to a site where it's supposed to be in most cases. Rather than being injected peripherally in the abdomen, it's usually given into the circulation.
Matt: Yeah, it's another fascinating technology. I think in, I guess, my experience there, that feels further away, or at least, it certainly, feels further away before that's broadly adopted.
Andrew: Yeah, I think that's probably right. I mean, if you look at the costs you see from oncology, like in CAR T-cell therapy, like I mean, it's a bonkers solution.
It's incredibly inventive and it works really well for certain types of cancer, which may be its limitation. But just the cost involved in treating a patient with that is just staggering.
Matt: And comparing that to the other technologies we've discussed, do you think you could give us a rough timeline for when we’re going to see these rolled out to patients: the full closed loop systems, the glucose reactive insulin. Where does that stand on a timeline? Is it years away? Is it decades?
Andrew: Well, I think there are pumps now already with versions of at least hybrid closed loop, which are basically doing that. So, I think that's sort of there.
Matt: Glucose reactive insulin, is that a similar timeframe or is that something that seats between those two extremes maybe?
Andrew: Well, Nove Nordisk, we started working with them in 2018. It was a research collaboration for three years, and then went in-house.
And so, this is going from normal drug discovery effort, let's say 10 years on this. We had to completely discover the concept from scratch, and when they would expect that to be at market, we'll be in the less than 10 year timeframe.
Matt: We've talked a lot about sensing, and I guess, the advances in biosensing technology have very much been driven by diabetes. And I wonder if there's anything we can learn from sort of automating, improving the sensing and treatment there that we could apply to other disease areas or other disease states?
Andrew: Absolutely. Yeah, I think the idea that we go towards monitoring blood glucose in anyone is … whether it's like immediately got some clinical benefit is obviously very dubious.
But I think there's been a lot of interest in how blood glucose might affect someone's general diet and behavior, in fact, when wearing them. And I can speak from my own experience with this, it has a bizarre effect on your behavior wearing them because it will give you a spike on a screen when you eat a donut, you avoid eating donuts. I did anyway. And it's got a behavioral change associated with it.
So, I think the area that's commonly cited around it is around exercise and I'm not sure that it has a huge benefit to anyone to monitor it.
But what you couldn't overlook would be the holistic monitoring of glucose, lactate, ketones. But I think what might be interesting is as we get more analytes that we can routinely measure, when you look at what can be done with machine learning, is what might we know about a patient from just monitoring their temperature, blood pressure — all of these things at once, I think has got to be loads of good stuff in that data.
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Matt: The interoperability these kinds of technologies could have is such an important point, because continuous monitoring for not just glucose, but everything from ketones to lactates has so much potential as well.
It mirrors the new popularity in wearable devices like Smart watches, which have become not just a niche accessory, but a must-have for people concerned with their own health.
The more we allow for patients to track their own health data, the more burden is lifted from healthcare services the world over. This epitomizes what these closed loop systems for diabetes are trying to do.
Scale is the thing which is needed for it. And at the moment, closed loop systems, unlike the much less scalable stem cell treatments, could well provide the answer. But are we going to reach the point of widespread adoption anytime soon? Are we going to be able to take the human out of the loop in diabetes care in the next 10, 20 years, or more?
I asked both guests the same question, and I'll leave you today with their answers.
So, final question: will we be able to take the human outta the loop in diabetes and beyond?
Chris: I hope so. It feels to me in the short-term that we can minimize their interventions. We've got to the point where we've got hybrid closed loop systems that attempt to minimize the user intervention.
And I think that the technology will continue to move on a pace, and eventually, we'll get to a point where we have enough data and have enough confidence that we can have fully closed loop systems. So, yes, I absolutely think that's somewhere we'll get to.
Further off into the future, will we get to a point where patients don't need to wear any of this hardware? I also hope that's the case, where we're able to treat the disease directly and not require the patient to do anything, effectively leveraging the body's own sensing algorithms and infusion to do what it does in non-diabetics
Matt: And for Andy?
Andrew: Yeah, I do, definitely, yeah. I mean, what I want to see though, is before that is just that the access to all of the … I'm always reminded when you're looking at the kind of market options, the addressable market for glucose sensing, barely anyone has any sense.
You look at the numbers of it, the first thing is sensing at all. Being able to measure it from a finger prick is still just not available to lots and lots of people. We could get that done first – airdropping these things onto people, these strips, these simple technologies.
Matt: Thank you, Andy, for taking us through that.
Andrew: Thank you very much for having me, Matt.
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Matt: Thanks so much for listening to this week's episode of Invent Health from TTP, and a big thanks to both Andy and Chris for sharing their expertise with us. You can find out more about both their work in the show notes.
We'll be back next time with an episode looking into epilepsy, and the new treatments which are changing the way we think about the disease. We'll see you there.