The Evolution of Clinical Trials Through Wearable Devices with Wessam Sonbol

Uncover how the seamless fusion of wearables with patient data is revolutionizing clinical trials in our latest conversation with Wessam Sonbol, the Founder and CEO of Delve Health. We navigate the transformation from cumbersome paper reporting to the sophisticated use of Patient Reported Outcomes and the continuous insights wearable technology offers. As we dissect the benefits and hurdles of this evolving data landscape, you’ll get an insider perspective on the intricacies of managing vast health metrics and setting benchmarks for impactful analysis. Plus, Wessam shares his knowledge on the reliability and strategic employment of wearables in clinical research, offering a glimpse into how these devices are altering the way we approach health monitoring.

In our discussion, the concept of 'wearables as a service' emerges, a trailblazing model crafted by Delve Health to elevate the clinical study experience for both patients and researchers. Wessam delves into the rigorous process of selecting wearables that align with trial goals, sharing how gadgets like Fitbits undergo efficacy evaluation. Be prepared to discover how innovations like automated compliance and concierge teams are mitigating study site burdens and boosting data quality. We also tackle the broader spectrum of challenges and advancements in clinical research, contrasting the swift advancements in wearable tech with the methodical progress of drug trials.

Join us to envision a future that prioritizes patient-centric care, reduced tool burden, and heightened automation, and don't miss Wessam's call to action for ongoing dialogue that aims to reshape the patient experience in the health and life sciences arena.

Guest:
Wessam Sonbol 

________
Reach out to Sam Parnell and Ivanna Rosendal

Join the conversation on our LinkedIn page

Transcript

Speaker 1: 0:21

Welcome to Transformation in Trials. This is a podcast exploring all things transformational in clinical trials. Nothing is off limits on the show and we will have guests from the whole spectrum of the clinical trials community, and we're your hosts, ivana and Sam. Welcome to another episode of Transformation in Trials Today. In the studio with me I have Wessam Spal, who is the Founder and CEO of Delph Health. Hello.

Speaker 2: 0:47

Rana, good to meet you here.

Speaker 1: 0:49

Nice to have you Today. We're going to talk about patient wearables for digital health and clinical trials and just to get us started, can you tell us more about? Typically in a clinical trial, how would we collect data in the good old days? Typically in a?

Speaker 2: 1:04

clinical trial. How would we collect data in the good old days? You know, the good old days is I'm a patient, I go to the doctor's office, the doctor asked me a few questions. I give them my question whether they're accurate or not, and that's about it. You know, it's actually an interesting story, actually an interesting story. We ran into this in the past with an Alzheimer's study where a patient was in pain. Patient got to the doctor's office and the patient actually had their caregiver with them. When the doctor asked them, how was your pain? On a scale of 0 to 10? The patient was like I'm at a better seven and the caregiver was like I think you would have probably more than that because, based on you know what we felt in the past, right, so, so anyway, so that's that's how we've collected in the past. You know we can only get the data when the patient comes into the office or somehow by, you know, third, high end recording of the data.

Speaker 1: 2:11

So and then wearables come in, but also just the patient reported outcomes, which were kind of the step before wearables, and how has that evolved?

Speaker 2: 2:23

this space, yeah, I think between wearables and how has that evolved this piece? Yeah, uh, I think between wearables and patient report outcomes, but we should probably talk about patient report outcomes first. This industry is really slow to adopt in general, right. I mean, even till today, 15 of studies are still conducted on paper, right, not even in even in EDC system paper. So, as we fast forward to today with PROs, I think we still have ways for PROs. We've gotten so much better today than we were 10 years ago, especially now that we have mobile phones. So in the past, even from our PRO data, it used to be a sheet of paper, right. You give someone a paper and your diary collect them, they come into the parking lot, they fill them out before they come into the doctor's office right, and it's getting better today, where we have, like, mobile apps, we have text messages, we have artificial intelligence that can automate phone calls right. So I think we're getting better. But as technology evolves, I think we're going to get even better as we get into PROs and wearables.

Speaker 2: 3:35

We look at wearables as part of the PROs, right. However, I think from a last presentation I did, there was only about maybe 15,000 studies that have really used wearables, so I think we're still a ways away from using a ton of wearables in our studies. But as we look at wearables, you know, the patient goes into the doctor's office, they go home and we've got no clue what happens to that patient, right? So there are pros and cons when it comes to wearables. The pros is we learn a lot more from patients than we ever have. Right, we learn more about their habits, their movements, their heart rate, their sleep, their stress.

Speaker 2: 4:19

There's so much information that we can get from these patients. But then there's also the problem of we've got so much data we don't really know what to do with it. But then also we've got the problems of people come in and making some unrealistic expectations of, like I want to get you know heartbeats per second, you know. And we're like well, if I give you a heartbeat per like two minutes, there's still a ton of data that you don't know what to do with it, you know. So I think people are still not sure what do we do and how do we look at wearables. But then there are also oh, go ahead, I'm sorry, you're going to say something.

Speaker 1: 5:01

Yeah, well, I was just thinking. So, yes, there are a lot of wearables. They collect different things. We don't know what to do with it. One of the questions that I get most often is do the wearables measure anything that can be used for clinical purposes? Is any of it actually valid?

Speaker 2: 5:17

I think it can be valid based on what are we looking after, right? So there's only maybe like a handful of studies where these wearables were the primary endpoint, right. In most other scenarios the wearables are either observational or secondary, as we're trying to figure out what's really happening. One of the biggest problems we see often is somebody will come in and say, hey, we're giving these patients treatments, we want to give them a watch to, you know, see their activity after their treatment, right. And we're like, well, you've got a bigger problem. You don't even know what your baseline is. You don't even know what that patient was moving before the treatment or not, to figure out whether this wearable is really going to help you in the study or not, you know. But we've also seen kind of the positive effect where some studies we've seen where we've given patients like an Apple Watch or whatever and there seems like, hey, these patients were not mobile at all before the study and now, guess what, they're actually more mobile. And we've seen other stuff. We're saying like, hey, these patients have in the past recorded that they're going to the doctor X number of times and now their doctor visits have reduced dramatically, you know. So there are benefits to the wearables, whether in a clinical trial or outside of the clinical setting.

Speaker 2: 6:43

I think it'd be amazing to learn more as we put wearables on these patients for a longer period of time. So that way, do we know, like what is their quality of life beyond? You know, weeks and months, you know what does it really look like from a patient perspective and as you look at like like value-based care is going to be huge, right when it comes to these wearables. Can you, you know, imagine you can utilize a wearable device so that we can measure heart rate, breathing, whatever, like a ton of wearables that we can talk about and you know we consider, well, as you're going to commercialization, what is it really going to look like and is it going to make you, you know, give you better evidence for, you know, value based care?

Speaker 2: 7:34

So I'm a believer. I mean, even when you look at some cancer studies, I believe there is a need now to collect more of heart rate based on some drugs, etc. So how are we going to do that? Are we going to ask the patient to go to the doctor every now and then, or can we use some sort of an FDA clear device with some of these patients at home that can have at least like a good 90 accuracy and we can transmit this data in like near real time, you know I kind of want to go back to the to the patient reported outcomes, because the purpose of those was to understand more the patient, not just as a kind of an object where there's some stimuli and response and stuff we can measure, but also what is their experience with the disease.

Speaker 1: 8:31

And it sounds like that from wearables we can learn way more about the experience of being a patient than we could just by like measuring stuff on the patient, and that seems to me that it creates a new kind of data that we may not even know what to do with. Exactly like you were saying about movement earlier, suddenly we see more movement, but did we measure things like that before? Or is this a new type of information that we're getting for treatment?

Speaker 2: 8:58

Yeah, I think we're definitely getting more data. We're getting better data, new measures that we haven't tapped into previously, right. But also, like, when you look at like outcomes and measures, there's there's something as simple as like just the quality of life questionnaires. Right, it's out there, but I'd love to know, like how many? What is the percentage of studies that you really use? Quality of life questionnaires, right? A lot of times we ask that question. It's like don't you want to measure that patient's quality of life? And they're like Nope, we've got a specific goal. We only want to measure are they going to the bathroom or not? Right, well, that's cool, but what about the patient? What about the patient experience? If I'm a patient in a study, I want to be involved as part of that study. I want to be involved from the perspective of. I want to see that they care about me and I'm not just another data point, you know.

Speaker 1: 10:01

But in my experience it's because those are two different use cases. The qualities are useful for health technology outcomes, for reimbursement purposes, whereas the clinical folks they're squarely focused on getting the drug approved and submitting to health authorities, and those two groups have not really aligned on the same data that we collect from the same patients yeah, but patient experience it shouldn't matter from a you know.

Speaker 2: 10:28

I mean, we're in an industry that's caring, right. We're supposed to be here to save lives. So if we're here to save lives, why are we not here to really kind of learn about that patient experience and make sure that you know I'm saving your life, but I'm also interested to make sure that I want your experience to be better. I mean, some of these drugs, I mean I put my family through clinical trials. I've been part of a clinical trials and the experience is like a hit or miss, honestly, you know. So, yeah, there's a lot there.

Speaker 1: 11:05

There's a lot there. There's a lot there. Have you experienced any wearables that have a clear clinical purpose and use?

Speaker 2: 11:12

yeah, oh, that's a good one. You know, the one thing that I always tell about wearables is every wearable is good at one thing, but is not good at everything, right, so we'll talk about, let's say, the Cardia or Apple Watch or Withings, like each one of them is, like, really solid about one thing. And you know, the other pieces are, like, you know, okay. Like, for example, if I was to take the Apple watch, right, apple watches there's a ton of studies out there that talk about, you know, they've got what an 86% accuracy from you know, collecting heart rate. However, what about step count? How accurate is it? If I was to take an Apple, apple and a garmin? Well, garmin is going to be a lot closer to realistic step count versus an apple, just because that's where they stand right with the gps tracking etc.

Speaker 2: 12:10

So, each one of those devices, we look at them as like it's really good at one thing. So we always tell people if you're running a study, you want to use a wearable, what is the end outcome? What is the problem that you're trying to solve? Because everything stems from a specific problem that you're solving for or that you're looking to solve for we can help you identify. Well, here's a good wearable that will get you, I don't know, 80% accuracy, 90% accuracy, right, depending, of course, once again, on the actual outcome. I think it would help a lot better to kind of figure out what are we measuring and how do we want to measure it.

Speaker 1: 12:47

And how do you learn about these different wearables and figure out what is it that they are good at?

Speaker 2: 12:54

This Look at my watch right, like I've got like a whole lot more on my desk. Right, like I'm in testing mode 24-7,. Right, I'm like I'm the craziest guy around, but there's always there's gold standards, right, gold standards from figuring out, you know, the device, figuring out, the data measuring. So we use when we measure something and we test something, we test using different devices so that way we figure out which ones are really more accurate, which ones are not right. And we'll do some crazy things, as in like I'm taking x number of steps, take an x number of movements, to kind of like, for example, I was actually, um, I've been testing fitbits like crazy, right, because I'm trying to figure out what are they really good at, right, and, and you know, like I'll use like the step counter, the sleep, and I could be like working out in my spot, in just kind of standing up and down and guess what the step count on the fitbits is going to keep moving if If I'm wearing an Apple and a Fitbit and a Samsung, for example.

Speaker 2: 14:01

Apple and Samsung have done a much better job because, guess what, if I'm going up and down, my step count hasn't moved because I haven't moved, you know, versus Fitbit, it's moving every movement I make, you know. So we do things like that to kind of figure out what really works, what really doesn't work, um, but and and what really meets their, their real needs.

Speaker 1: 14:25

Uh, uh, for, for some of these devices, and this is this leads me to ask you about what you mentioned in our pre-call, this concept of wearables as a service can. Can you tell us more about that?

Speaker 2: 14:38

Yeah, it's something I'm really passionate and excited about, right. Like, if we look at it, every single one of these tools right here, right, they all have like sensors built in them. But what I struggle with is, if you want to use a device, there's only one app that you have to do. Well, what if you want to use three different devices? Then you've got to download three different apps of some sort. Then what? If I download the apps, how am I going to get the apps to, let's say, a scientist like yourself or somebody else that can correlate the data, right? So at DelveHelp, as part of our clinical study pal platform, which is an end-to-end platform that can collect data from patients, improve data, patient engagement, et cetera, we've developed the concept of wearables as a service, which basically means I can integrate multiple wearables into a specific study and onto a specific patient. I can assign one or more wearables for that patient, right? So the beauty here is we've kind of broken from the silos of you've got to download multiple apps, multiple tools to. I don't really need anything else other than you know, depending on the device, but, for example, if you're using a device that is cellular enabled, I'll find a way to get you an app that's downloaded directly onto the device, right? Or if it has to have some sort of an SDK because this is kind of what the device allows, then I'm going to only ask you to only download only one app for your entire study, right? So here we're collecting data from multiple sensors, but also the way that we collect data from sensors is going to differ. The way that we're going to manage compliance across different devices is going to differ Depending on the organization, depending on how we're getting the data. Some of the devices we're able to upload our own app that can truly collect the sensor data directly from these watches or whatever, and some of them we can't. Some of them we have to connect using like an SDK or API. But at the end of the day, we're going to get the data. We're going to get the data into a central hub where we can report on it. But then how do you manage compliance, right?

Speaker 2: 16:52

So when you think about compliance, one of the more common ones you hear about is sites get frustrated because if they're not getting data from these patients, they're on the hook to pick up the phone and call these patients and guess what. Sites are always like we don't want any more devices for these patients, right? So we've automated that within our system, where you can configure the system to. You know, I want to look for this every four hours, every eight hours, whatever that is, and, based on whether we're here or we're not here, we can send off automated messages, emails, et cetera to the patient, their caregiver, et cetera.

Speaker 2: 17:31

But then we also have our own concierge team that can pick up the phone, call the patients and figure out, like is there a support issue? Is it a problem with the device? Do we need to do something? So that way, we're truly reducing the burden off the site. We are providing the extra capabilities and services for these patients to make sure that we're able to improve the data outcomes and improve compliance from a patient's perspective, right? So, as we look at it, this is kind of our concept of wearables as a service, right? Figure out what wearable you want. We'll integrate all the different wearables, we'll help provide feedback on what we need to do, but also centralizing the sensor data into one repository versus multiple tools.

Speaker 1: 18:23

I like that you've reduced a lot of these wearables to their sensor piece and the data that you can actually get and actually made it workable for conducting clinical trials or health as such. But have you had any feedback from the creators of these wearables for how they feel about you actually stripping their offering down to the main components?

Speaker 2: 18:48

It depends on who we talk to, right, we talk to quite a few of them. Some of them are open to partnerships and, you know, enabling us to kind of be part in the middle, to kind of really help from a research perspective, enable better data collection. And some of them, honestly, they're like, hey, listen, we're comfortable with just kind of pushing out five, you know data every five minutes and this is, you get what you get, you know. So it depends. At the end of the day, it comes down to true collaboration. Are they really kind of here to help us advance research and advance patient lives, or they're just here to just kind of sell us a device and that's it?

Speaker 2: 19:34

So it varies and it depends. Actually, one of the more recent ones that we've been kind of testing is, I think I told you, like the circle. The circle ring, right, you know. But this is an example where they're like hey, we'll give you data every second, we'll give you data every five minutes, depending on what it really is, which really kind of helps us and allows us to help sponsors and pharma, medical device companies as well.

Speaker 1: 20:05

So now we've kind of talked about the more structured piece of clinical data. Could this also be used in healthcare more broadly?

Speaker 2: 20:14

Yeah, yeah, for sure. We see a bigger need for it in the digital health space. We've got't matter and within that digital health solution, we can track what's happening to that patient at home and provide suggestions, whether it's, you know, your sleep has not been good, you're too stressed, you know? Have you tried these vitamins? Have you tried these test kits? But also we're seeing hospitals that are looking to deploy more of these tools at home to provide better remote patient monitoring capabilities, so that way they can, you know, reduce hospital visits. They can improve patient care. So I think there's a ton of opportunities from a wearable perspective, when we look at wearables, there is just 2023 alone. Over 1.2 billion wearable devices have been sold and that number has gone up nearly 35% year over year. And it's global. It's not just US right, it's US and the Middle East and Europe, so it's everywhere.

Speaker 1: 21:40

Everybody is buying these wearables and putting them on. That's a very large number, amazing. Okay, one more thing I wanted to ask about the usage From a patient perspective as an individual. Does one also need to test all the wearables to understand what might make a difference, or are there some shortcuts that can be taken?

Speaker 2: 22:03

You know, when it comes to patients like, you and I are different. You and I are going to have different habits. You and I are going to wear our ring different and it's interesting because some patients, you know they'll put on like a Fitbit and they're like you know, this thing kind of irritates me, you know, I don't want to wear it anymore. And we have to be thoughtful, we have to listen to the patients and kind of figure out like it could be something as simple as like the wearable is just not for that patient, right? They're just not going to wear it, period. Let's just kind of retract it and give it to someone else that is going to use it.

Speaker 2: 22:44

We get a lot of questions about age, for example. Right, and I'll tell you, the most best compliance pieces are patients that are, you know, 55 years and older. You know they're a lot more compliant than younger patients because they want to be more involved in their health. So it really varies quite a bit. It depends quite a bit from patients. But we go back and it's actually one of the core pieces why we have developed a true patient engagement capability within the tool because we want to listen to the patients, we want to collect them, what's important to kind of figure out, where do we need to change, and catch issues as they become issues. It really becomes more of opportunities at one point right. Opportunities at one point, right. Um, our pushback a lot of times is really from uh, an irb, a protocol, a sponsor, they're like, nope, we don't want to go that far, we don't want to go there with the patient. So it it.

Speaker 1: 23:50

it varies that makes sense. I'm curious about your experience in this space in general, because I know that this is your third technology company in the health space. I would like to hear more about your perspectives on has it become easier to create something new and useful? What has the evolution looked like for your perspective?

Speaker 2: 24:17

You know, like, as I mentioned early on, this industry is very slow to adopt. It has become more difficult to develop new tools, yeah, but I think that there's a lot of, there's a lot of, there are a lot of opportunities, right. So, kind of, with AI and chat, gpt and and more wearables on the market and more apps on the market, I think it's going to get tougher. I think we're going to have access to a lot more data than we ever had access to before and as we think of, you know, like I don't know think of, like the neural networks, right, and how that all can grow, grow and, like good God, what can we do? You know, I think research is going to get better over all over time, but I think it'll take us. It'll take us quite a bit of time, right, we just we need to push with better opportunities and and and and honestly kind of empower those different opportunities to you know to to get there, different opportunities to you know to to get there.

Speaker 2: 25:43

Clinical research has been a fun place to be. I enjoy it more and more. I've talked to a lot of patients, and the patients that I've spoken to are one of the reasons why, like, I enjoy being here, truly, like wanting to. Can we truly push the needle? Can we truly do something different? But I'm opportunistic.

Speaker 1: 26:12

That makes sense. What do you think is the greatest challenge for adopting more wearables into both clinical trials but in the health space more generally?

Speaker 2: 26:26

uh, accuracy, um, it's the number one question we get, right. So accuracy, battery life, um usage, um usage, I think there are multiple challenges, but I think accuracy and battery life are probably the two most common ones that we see in the industry. I think we have to integrate more of these wearables, honestly, into more studies, so that way we can learn studies, so that way we can learn more, so that way we can implement better tools that can help us be a lot more accurate, right? But once again, I think, if we can define some of this upfront and a lot of times it's I don't know what, I don't know Right? So if I, if someone comes in and says, or if I'm trying to run a study and say like, hey, I want this data to be 90% accurate, is it realistic or not? I don't know. I'll be honest with you, right, because it's gonna depend on the patient population, it's gonna depend on the disease state, it's gonna depend on am I asking the patient to charge this wearable every 15 minutes? Right? It's going to differ dramatically.

Speaker 2: 27:46

I mean, if I count kind of the different types of wearables, I mean we get wearables from like rings to watches, to like a chest strap and some of the chest straps, some of them are painful because guess what? Actually, I got to stick it onto my chest with some sort of a tape, right, and someone like that's a bit hairy, right, like I'm like when I pull this out, it's going to, it's going to be painful, right. So it's, it's going to differ. I think we just we have to be realistic with our expectations and, you know, think about it from an agile perspective. We're going to learn, we're going to implement what we learned and it's a process. You know, if you look at where EDC started in this space where we are today, it's been a lot of years.

Speaker 1: 28:39

So that's another question I have for you. We see this divergence between development times for drugs, which are still very long, and for wearables, which are relatively shorter, and they do get better and better in shorter cycles. Do you think that they will ever be able to convert somehow, that the two can find a mirror union, or will they just keep evolving at two different speeds?

Speaker 2: 29:14

I think there's going to be two different speeds. Right, because when you think about drugs and why it takes long for drugs, it's because of the different phases. Right, because when you think about like drugs and why it takes long for drugs is because of the different phases. The efficacy it's something that's going inside your body and when it's inside your body you don't really know what it's doing inside your body. Right, versus if it's a wearable, I'm using it, it's outside my mind. I can easily just kind of take it if it's causing me a rash and take it off and kind of move on. So I don't know that drug timelines are going to shorten a ton more. I'm hopeful that we can do more better, that we can run more studies as time goes on. Cheaper, right, involve more patients, but then patient recruitment is a problem.

Speaker 1: 30:03

So yeah, Wissam, could you tell us more about how you ended up in this space?

Speaker 2: 30:10

Yeah. So I graduated college and it was in the heart of the bubble and couldn't find a job and someone was working on something and he said, like hey, you want to join? I'm like sure, I don't really have anything else to do. So I joined a company and our first product failed. We pivoted and we developed a couple of other products and one of them was bought out by PPD back in 2004. And I just kind of stuck to it. I enjoyed kind of the entrepreneurial aspect. I've worked for other larger organizations like Optums and et cetera in the past, but healthcare and life sciences is where my passion is.

Speaker 1: 30:59

Well, I can definitely relate to that, and that's also a perfect segue to the question that we always ask our guests at the end of each episode. If we gave you the transformation trials magic wand, and now this magic wand has the ability to grant one wish that can fundamentally change the life sciences industry, what would you wish for?

Speaker 2: 31:20

Better patient experience. That's like the one thing that I kind of live on, honestly. Better patient experience, um, and reducing the number of tools that we're giving the patients uh, automation is huge, right. So how much of this can we truly automate so that way we can reduce the burden of the patient and the sites? And I think in these two there is just a ton of work that needs to happen still.

Speaker 1: 31:52

That's a good wish. Well, if our listeners want to learn more about you, ask you more questions or want to learn more about Delve Health, where can they find you?

Speaker 2: 32:03

Yeah, definitely, delvehealthcom. You can also find me on LinkedIn, kind of reach out. I do some videos on LinkedIn every now and then with you know. Here's what I learned today. Here's what is cool about this wearable or not you know about this, wearable or not you know.

Speaker 1: 32:24

So um always love sharing our experience in hope that it will help benefit everybody else in the industry. Well, I hope our guests do our listeners to reach out Um, and thank you so much for coming on the show. This was super interesting. Thank you so much Appreciate it on the show.

Speaker 2: 32:37

This was super interesting. Thank you so much.

Speaker 1: 32:43

Appreciate it. You're listening to Transformation in Trials. If you have a suggestion for a guest for our show, reach out to Sam Parnell or Ivana Rosendahl on LinkedIn. You can find more episodes on Apple Podcasts, spotify, google Podcasts or in any other player. Remember to subscribe and get the episodes hot off the editor.