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Arundhati Parmar
Moderator

vp & editorial director
@medcitynews

David Benshoof Klein

Co-Founder & Interim CEO
@clicktherapeutics

gabriel vargas, md, phd

executive medical director
@amgen

david kim

CEO
@digitx partners

Arundhati Parmar:
So I’m not sure if we can entertain you the way that video did but we’ll sure try. So thank you for coming this morning. I want to just start with Gabriel Vargas here, since he’s the big dog in terms of pharma and biotech.

You know we hear the phrase, “Beyond the pill,” a lot and I think in your case it’s, “Beyond the molecule.” So how much of that is coming from a genuine recognition of the power of digital health and digital therapeutics, and how much of that is paying lip service to the latest fad?

Gabriel Vargas:
So at Amgen I think we’re relatively new to the digital health space. I was asked about two years ago to start up an initiative in the clinical trial space to bring digital applications, digital approaches into our clinical trial development. So for the development of drugs, phase one, phase two, phase three. There’s been a lot of interest in Amgen and across biotech and pharma of how to integrate digital health approaches.

I think there’s a recognition that this is the way of the future. That there’s no way around not using digital health approaches. I think it’s more than lip service. I think the challenge currently is, how do you go about doing that? How do you integrate these approaches into our clinical trial development?

I think from our perspective we strongly believe in this idea of beyond the molecule. The thought being that in the future, and the future being not that far into the future, the next five to ten years, it’ll be pretty standard to be selling drugs with digital health applications. I think there are three major components from my perspective. There are going to be components that are gonna be helpful for the patient managing their disease, these are what we called disease management apps, or these are apps that will be sold along with the molecule to manage your disease.

You can imagine with a disease like migraine, which is one of our interests at Amgen, is you can have an app that keeps track of your migraine headaches, tells you how you’re doing with the molecule. It can have graphics built into it so you can share with your physician and see ho you’re doing with the process. So those are kind of disease management apps and I think part of that is also patient support networks where you can participate in communities. Novartis has done this, for example, in Hodge [inaudible 00:02:44] which they’ve actually funded a community support system.

The other general area is compliance. If you think about compliance, you might think about compliance for serious illnesses in general is pretty good but in actuality, compliance is quite poor, 30-40% of people don’t take medications as directed. So if you’re not taking your medication of course then it’s not going to be efficacious. So there will be compliance related digital health techniques and approaches being used. These can be something like Ai Cure, which is a company that uses artificial intelligence to look at whether you swallow your pill or not. Proteus which has a tracking device built into the pills, or something as simple as a text reminder that sends you a text reminder every day that says, “Please take your pill.”

The last category, which I think is going to be the most challenging for our industry is synergistic approach. And by that I mean, is, you can imagine developing a drug which has a digital health component associated with it, which actually is synergistic with the drug so that you get better efficacy out of the drug by having a digital health component. For example, many of you might be aware of the work of Sophia Vinogradov has done in schizophrenia and cognition. Schizophrenia using cognitive remediation, using basically computer software to improve cognition.

The thought is that you could combine a pill for cognitive remediation in schizophrenia along with a digital health approach and have it a synergistic process whereby each one by itself doesn’t do as well as the two combined. I think in general it’s not lip service, it’s where we’re going, and the challenge is really understanding how we’re going to get there.

Arundhati Parmar:
So we have two Davids on the panel now, I almost with somebody had a name like mine but, we’ll go with Dave in the middle and David over on the end over there. Starting with you Dave, it’s really interesting that you’re trying to develop validated digital therapeutics. I wanted to go back and quote something that the American Medical Association CEO said last June that ruffled a few feathers but I kind of feel like they needed to be ruffled. He talked about, “From ineffective electronic health records to an explosion of direct to consumer digital health products to apps of mixed quality, it’s the digital snake oil of the 21st Century.”

Fascinating comment. People in digital health privately told me that he’s absolutely right. I wanted to ask you about this idea that docs are a little bit flummoxed about the lack of data of some of these digital health products. So, how important is validation? How important is data and where do you stand on that?

David Klein:
Sure. That’s a good question. Since then the AMA has taken somewhat of an about face. We are, as a company, a bit different. In 2012 we founded the company with a group of neuro psychiatrists and we’re really ex-biotech investors and operators and, in fact, coined the term digital therapeutics in 2012, and really applied a very biotech like model to the development of apps. We felt digital therapeutics would be basically outcomes based mobile software.

We had a focus on validation from the beginning and really that we would validate ourselves just like one would validate a biotech compound. In fact, we just published this morning on one of our smoking cessation trials. I think what you’re seeing … There’s so much innovation in the space and there’s so much technology can actually do to actually reshape healthcare, that you’re seeing brilliant software engineers and new technologies that are directly applicable to software. The phone figures out a cool way to tell your heart rate or figure out your mood, and that innovation might be coming from maybe not healthcare folks.

They might be coming from two brilliant engineers from MIT that aren’t necessarily thinking that now we need to run a randomized control trial and really prove that this works. I think what you’re seeing here is an industry that’s getting to be more akin to your traditional large molecule or small molecule pharma model where people don’t really accept products unless there’s some clinical validation.

So I do see a narrowing of the field into a place where I believe that it really belongs. Products shouldn’t make claims around them until they have some type of clinical validation. I think that’s increasingly moving in the right directions.

Arundhati Parmar:
David, you said that you began your career in medical devices and pharma medical devices. The RCT as Orin mentioned, is sort of the Holy Grail. Is there a way that we need to rethink clinical validation and randomized clinical trials when we’re dealing with such a new modality of treatment as a digital health product?

David Klein:
Sure. And that’s a great question.

Arundhati Parmar:
That was David.

David Klein:
I’m sorry, and I had a great answer.

David Kim:
David, Dave …

Arundhati Parmar:
We’ll let you chime in Dave.

David Kim:
Thank you for that question. What we’re seeing in the digital health space is there are a lot of digital technologies out there. A lot of different solutions that people are building, a lot of different apps. So as an investor, sometimes it’s really hard to figure out what is noise versus what are really quality companies that we want to be really interested in. It’s now coming to, what Gabriel and Dave is saying, is that we have to start to look at the data that is coming out. We have to start to look at the validation.

We have to see are they actually really supporting the claims that they are making. I think that in a way it’s interesting that you have these early adopters who are willing to take the word for it and try it but if you’re going to really get the broad adoption, you’re really going to need to go through with these validation trials. Clearly, the best way to do it is do a randomized clinical trial if you can.

However there are a lot of different ways you can actually get a lot of data without it. One of the nice things about not needing to go to these academic centers to do clinical trials is that with the availability of technology and the broad adoptions that you have already with the iPhone and other mobile technologies is that you can get real world data, real world information from everyday activities of individuals that could actually start to give you the mass amount of data. With the advent of data analytics it could start to capture the real intelligent side of that data.

So, although I would love for every technology to go through a randomized clinical trials, I think there’s gonna be a time where the information you get from everyday use, but in a way that it’s just, you’ve got large volumes of it and the ability to extract really quality data out of that. It’s gonna be probably accepted. I know with the 21st Century cures act, that there’s starting to get inroads with the regulatory agency that they’re willing to accept information like that.

Arundhati Parmar:
Dave.

David Klein:
Thank you. We anticipated that might happen and did everything we could to avoid it but, it still happened. I’ll just augment what David said there which I think is right on. The FDA seems to be really clearing a pathway for software as a medical device. We’re pursuing that pathway for our major depressive disorder product and it’s one that really will require very robust RCTs. We actually, and I think it’s probably necessary for people who want to go into registration studies, and ultimately have physicians prescribe your technology and get reimbursement, you have to start thinking about that active control group right from the beginning.

As you’re developing your product, and as we develop our products, we’re really contemplating and in some senses actually designing and architecting what the active control group would be. I think right from the beginning, and that’s one of the challenges in the space, what are the control groups and this space? I think building and contemplating and architecting an active control as you’re developing your product, especially if you’re pursuing a rigorous FDA approved pathways is a really good idea.

Arundhati Parmar:
So Gabriel, let’s talk about that data for a second. When you’re looking to work with entrepreneurs at an early stage, and I’m sure there are innovators here in the audience, what level of data are you looking for? What will satisfy you?

Gabriel Vargas:
I think that’s a good question. I think that’s one of the challenges. As these are early days, many of these entrepreneurs don’t have a lot of data that’s available. From my perspective, what you have to look at with the technology is, does it fit as to what you’re trying to do? Is there interested areas for those medications and would they work well hand in hand? So we have, for example, a lot of heart failure programs that we’re developing and we’d like to have activity tracking as part of that.

One of the challenges in activity tracking is, as I’m sure many of you are aware, if you look at consumer grade activity trackers there’s a lot of differences in the precision of the activity tracking that you have. The question is how much imprecision can you get away with? So we’ve taken the approach of simply incorporating devices into our trials early on and saying we don’t think there’s enough validation out there, we’re just gonna look at it ourselves and are gonna incorporate these devices into our clinical trials and get the data out of it.

We did a small clinical trial late last year which was really a test of a couple of things. One was that we really wanted to understand data flow, how we get data off these devices, because that’s not that easy to do. Because you have to get data off the devices and put it into our own clinical database and that’s not as straightforward as you might imagine. We wanted to test the idea of using wearable devices in the clinical trial setting. So we used CRO that specializes in phase one and we chose healthy subjects because what we wanted to test was really data gathering more than anything else.

So we used Garmin VivoFit for a variety of reasons. One of them being that it has a one year battery life. To us that was very convenient. When you think of going into larger clinical trials we don’t want people having to recharge the device every day like you have to do with Apple Watch or something like that. So these are the things that are also pragmatic issues that come into play.

We ran a two week trial. 30 healthy subjects. They were outfitted with a Garmin VivoFit 24/7 and we added to that a medical grade device that also did the same thing. So it was a comparison between consumer grade electronic and medical grade device. Two weeks, 30 subjects, we got nine billion data points off that trial. Nine billion data points. And that kind of blew our data sciences capability right off the bat.

In comparison we ran a 30,000 patient cardiology study which just finished and that had 40 million data points.

Arundhati Parmar:
Mm-hmm (affirmative)

Gabriel Vargas:
So this is just an amazing amount of data and that we have to adjust for and try to figure out how to use it. But to answer your question, I think that what we’re looking at is incorporating these devices into our clinical trials early on and get a sense of what kind of data we can get out of it and how easy it is to work with them.

Arundhati Parmar:
So David, you don’t have the luxury that Gabriel has in terms of plug and play into their own clinical trials and yet you have to make decisions on which technology you want to invest in. What is your go to method of looking at these technologies?

David Kim:
You’re right, we don’t have the luxury of spending money on what we’d call high level risk, in this case, clinical trial risk. Depending on how big of an investor you are, you’re willing to take certain number of risks, that’s something you can manage, but you’re unwilling to take bigger risks. For example, I would not take quote unquote phase two or phase three trial risk. But I may take certain risks to get me to certain validation points or milestones in the company that makes me feel comfortable to do early stage investing.

Typically what I will do is, for example, a lot of digital health companies, fortunately, do not require a lot of capital to get to where they want to go. They’re using a lot of off the shelf technologies that they’re putting together for their own application, so often, there’s very little technology risk that you’re taking. Another one is you have pretty good founders who understand domain space really well. That’s one of the things I look for is if there’s a particular pain point, I hope that you’ve lived through them pain point so that you understand exactly what you’re trying to solve. Domain expertise is one thing that I also look for.

Then, often on the early stages of the companies are funded by other means. Sometimes you have founders who are so passionate about that space they will do what’s called bootstrapping. They’d spend their own money to get it to a certain point that there’s enough validation and that’s really interesting for me to see. That they’re so passionate about it that they’ll be champions and source their own capital. If I see that, as an early stage investor, those are checking off some of the risks that I would see. Then I would be coming in with a financial risk to take them to the next level of validation. Typically it’s not that ultimate randomized clinical trials but it is to a level that is, “Do we have enough to start working with a bigger strategic partners, or would they be willing to do the proof of concept?”

If some of the companies that we’ve seen have done that early proof of concept with some strategic partners and they have some positive data, then definitely they’re very attractive as an investment. But if I could go back to the overall use of data, one of the nice things about the new technologies that are coming out is even though you may have nine billion data points, actually, that’s raw data. There are other technologies out there that are doing incredible data analytics that will allow you to, again, parse out that nine billion data points to something that is really more manageable. Whether it is actually trends, then you use the trends more than anything else instead of the raw data points. Where it’s the learnings from that data and there are a number of data analytics companies that are focused just on doing things like that.

Arundhati Parmar:
Okay. Dave, you’re developing a product for major depressive disorder. Can you talk about how you approached the validation for that and how you’re trying to go to market with it?

David Klein:
Sure. So we have a product, really it’s a cognitive emotion control training exercise and it’s essentially dosed three times a week over the course of six weeks for about 10 or 15 minutes and really we’re seeing, in now two randomized control trials against an active control group, which consisted of really working memory. So it’s a very very strong active control group. We’re seeing over 40% decrease in symptoms of MDD on overage against a control group which is really around 15%. So much more of a separation there than you’d even see in a drug study where placebo, you know, sugar pills, have extremely high effect.

Really, it’s, I would say, a golden age for this era and for digital therapeutics. You’re seeing a pathway really seemingly open up to get these approved and DiNovo classifications as class 2 medical devices for the treatment of certain diseases. So you’re talking about actual labeling on these software programs. And we’re seizing that moment, if you will, and pursuing that pathway after two randomized controlled trials, we’re now in the process of designing a registration study and we’ll have a pre-submission meeting with the FDA in the next few months to propose and get feedback on that registration trial.

Really, taking a somewhat … It’s interesting because the actual pathway is a medical device pathway, but the end product looks more like a drug, in terms, it’s prescribed and drives outcomes. So you’re seeing a really kind of regulatory friendly environment for these products and frankly that’s what seems to be needed to get widespread reimbursement and we strongly feel that these products belong in the doctor’s office and should be prescribed, whether it’s alongside a traditional pharmacotherapy or, in fact, in lieu of one. We see a lot of opportunity in depression and insomnia to actually have software prescribed as first line treatments instead of pharmacotherapy.

Arundhati Parmar:
Next question is for whoever is bravest on the panel. And for Gabriel he wants to bad mouth his competitors.

Gabriel Vargas:
Haha.

Arundhati Parmar:
Are there some pharma companies that are more cutting edge in terms of adoption of digital health than others?

Gabriel Vargas:
Yes. I’ve been to a lot of digital health conferences, as you might imagine, in the last couple of years. I think there’s an almost bell shaped curve, if you will, of people getting into digital health. I think my company is somewhere in the middle. We’re not at the front but we’re not too far behind either. I think there are other companies that are a little bit further ahead. I think Novartis is a good example. I think they’ve done quite a bit of work, for example, with cardiology in which … Entresto, they’re looking at digital health component to it.

At the end of the day I think everybody realizes that this is the way to go and I think if you look at all companies they will look and say, “Yes, this is the way to go. We’re not quite sure how to get there.”

There’s this concept of being a fast follower. The concept is you let other people do the work, then you figure out what works, and you follow as quickly as possible. The upside of that is you’ve taken some of the risk out of the question because you’re following what has worked. The challenge of course is you’re behind the competition. They’re already incorporating these devices into their molecules and going beyond the molecule. And so you tend to be, you are behind them. And I think that’s a competitive issue, because I do think all molecules will be, at one point, packaged with some digital health apparatus, because that will be what will be expected.

If you look at how many billions of smart phones are around the world, and the fact that the younger you are, the more likely you are to use the smart phone, so there will be a generation in their 20s and 30s and 40s that grew up using smart phones and they expect everything to be done with that. So adding a smart phone app to your medication is going to be just standard. So I think that’s the way we have to go, it depends on your strategy of how to get there.

Arundhati Parmar:
So when, not if, in terms of adoption?

Gabriel Vargas:
Yes.

Arundhati Parmar:
So for the less brave on the panel, when you look at pharma and how they’re adopting, what do they have to do beyond hiring someone as Head of Digital Health?

David Kim:
I’m gonna give a plug for [inaudible 00:24:22] because they’re the funder of the investment vehicle that I’m managing. I think that I can make this a generalized comment to all of pharma. Perhaps a little less for biotech, but definitely for pharma. Is that I think by nature, the players in this space are very conservative. They’re gonna need more than just glitz and information to say, “Hey, we’re gonna really do this.”

I think it literally has to go with almost the culture of the company themselves. Definitely it starts from high. If the leadership hasn’t bought into it yet, it’s not gonna filter down to the individual business units. The leadership has to really state that we are going to integrate digital health as an important part of our strategy and move forward with it. And then have more of a comprehensive type of strategy because you can’t have mishmash of different things that are trying to do different things. Many of the big pharma are multinational, global, with a lot of different units, and I think the important part is everyone is on the same page to do that. After that it’s about understanding what digital health is.

Pharma is an expert on getting a drug to an approved product and selling it. More and more they’re experts on marketing and selling the drugs and less about development, but that’s what they know and what they do really well. Now try and integrate a new type of technology and new type of mindset to how you develop and ultimately sell. It’s gonna take people to be more receptive and understand that, you know what, this is where things are going to go and we have to work actively to do it, instead of kind of being pulled along.

Arundhati Parmar:
Okay.

David Kim:
I think that it’s getting there but it’s not going quickly. I would say it’s actually more on the frontier side than it is in the middle of the road, but I’ve seen a number of other players who are saying that they would do it, but in reality, underneath, culturally they’re not there yet.

Arundhati Parmar:
Not there yet. Okay.

So we’ve talked a lot about data and validation. I want to talk a little bit about data sharing which seems to be the real block in terms of empowering researchers and patients to fully make use of the products that they’re using. So how do you look at data sharing? It seems like large companies, like Medtronic for instance, really believes in the value of data and they’re working with IBM Watson to do predictive analytics by using data collected from their insulin pumps, but they are not uploading that data onto the IBM Watson cloud. Which is sad for other people in diabetes. In behavioral health and what you’re doing every day, how important is the sharing of data?

Anyone?

David Kim:
I took a break from investing and spent four years at a healthcare software company in which we took large amounts of data and found, ultimately, a predictive analytics tools, but, part of that, we had to look through about 60 million clinical logs of EMR data. From there we’re finding inferences and models to predict future chronic disease events. I would say, especially in the era of digital health, that’s one of the key things that you have to know. One of my colleagues, he’s a data scientist, because for us to make an investment in the space, we really need to understand not only, do you have access to data, but how good is the data and what can you do with it and what can you learn from it?

Especially in pharma, they have so much data. I would ask the question, “What are you doing with your own data?” Not only getting access to new data, but what are you doing with your own data? And it’s not information coming out of new products but if you’ve done clinical trials, what are you doing with the clinical trial data and all of the learnings you got from it? Is it being shared within the actual company itself? And I bet you for most pharma the answer is no. I bet you it’s been pretty siloed and it hasn’t even been shared. And so, I think the mindset is there that people want to look at data and use data but I don’t think it’s there yet. And part of it has to do with, well we’ve always done it this way so why should we start to change? And again, changes are going to come but it has to be driven right now.

Right now there are a lot of different technologies that people can use to take new data and do something real interesting with it. And it’s available. Are you ready to actually use it?

Arundhati Parmar:
So Gabriel, how do you use data?

Gabriel Vargas:
I agree with David. I think we have a lot of data that we’ve captured from our own clinical trials which are actually siloed. A couple of years ago we were developing a new drug and we were getting an adverse event in our clinical trials. We were asking the question, “Is this something you’d expect to see in a certain percentage in a healthy population?” It might just be what you expect to see.

And we could not get access to the rest of the data we’d done, even though we’d run thousands because we didn’t have an easy way of accessing data. So, that’s within our own company, you can imagine the challenges of going outside the company. So it would be great to have a pre-competitive arena where you actually share a lot of this data from clinical trials, even if all you’re sharing is placebo, right? All of us run … Big chunks of our clinical trials are placebo and we could look at baseline data for placebo and how that changes. But the other thing, getting back to digital health is, you could imagine having a pre-competitive space as you could actually go through the validation process of a lot of these devices. Why does every company have to do that individually? Why couldn’t we just team up together and say, “We’d like to understand which is the best consumer grade activity tracker.”

Put Fitbit there or Garmin or whatever else you want to look at.

Arundhati Parmar:
Right.

Gabriel Vargas:
And you’ve got a consortium and you get the data out and you analyze it. Okay this is the best in these circumstances, this is reliable data, captures your heart rate, captures your steps, whatever.

The other component in data that I think is important for digital health is capturing new clinical end points. So we’re gonna be using digital health devices and you can imagine a huge case is activity tracking, again. I’m picking that because it’s pretty simple. You could use a consumer grade wearable and have as an exploratory endpoint, where at the end of the day you can use it with pairs and demonstrate that your drug has an effect on the activity level and pairs might be interested in that. But the Holy Grail, the way I see it, is to take digital health devices and develop new clinical endpoints which are more objective and can be adopted for pivotal trials where it’s non exploratory endpoint, it’s actually your primary endpoint.

Arundhati Parmar:
Okay.

Gabriel Vargas:
So instead of having, for example, the six minute walk test is a traditional, very well understood, regulatory endpoint for a lot of diseases. Parkinson’s disease, pulmonary diseases, in which you have a patient walk for six minutes and you time them and you observe them. You could imagine instead of having that really old fashioned assessment is, could you have an assessment at home where you have sensors and trackers that give you real world data of how the patient is doing at home, which at the end of the day is what we’re really interested in.

Arundhati Parmar:
Absolutely.

Gabriel Vargas:
And if you could actually get that data and developed at such a way in which the FDA is fine and comfortable in taking those data I think it would be a huge step forward.

Arundhati Parmar:
So we talked about pharma and biotech and whether they’re embracing with open arms or being a little more circumspect. How about physicians and providers? The thing that I hear a lot is, “Oh all this technology is great but it needs to fit into the clinical work flow.”

That, to them, is the gold standard, so to both the David’s, how do you bring about cultural change amid health systems and providers?

That’s a tough one.

David Klein:
Sure. That is a tough one. And I would say perseverance pays off, right? Really what our business model is really not a direct one. We’re not creating entirely new networks of providers and so on so forth. We’re partnering with payers and providers on one side, and on pharma on the other. So we’re really sliding into established distribution channels and companies who really have those relationships. Now I think just to go back to where this conversation started, clinically validating these technologies is critical. And really when you create a new digital therapeutic, which is essentially is new medicine, at all times you have to keep in mind that this is not something that can make the doctor’s life harder.

We were just talking about this earlier. It has to be something that is easy for the doctor to use and that is a simpler, more efficient, and quicker process. I think what you’re seeing in this is what I would liken to a revolution where just like there was a biotech and a large molecule revolution, and those gained acceptance and those got integrated with pharma and so on, I think that you’re seeing it here. I think that this pathway of software as a medical device and to get these products approved by the FDA and to have that stamp and to have that barrier to entry, if you will, and to get reimbursement, those are all steps in the right direction, and I think ultimately in the next year or two you’re going to see doctors prescribe software programs to patients and those patients are going to come back and say, “Wow that was really helpful,” and then that will spread more and more.

I think it’s going to be a bit organic, but I do believe we’re on the cusp of a massive revolution here in the space and these products are about to start competing with pharmaceuticals. So not just as marketing tools that help drive compliance, it can help drive outcomes but actually products that are prescribed in lieu of a pharmaceutical. So I think think you’re about to see major backing from pharma and from other types of groups like that, that will educate doctors. They have huge medical education divisions, so I think we’re really right on the cusp of a major revolution where doctors will be prescribing these software and that will grow really really fast.

Arundhati Parmar:
So on that super positive note, I wanted to open it up for Q & A. We have about nine minutes or so left, so anyone in the audience that would like to come up? I think we have some floating mics? Come on, don’t be shy.

Megan:
Hi, my name’s Megan, I’m here with Stride Health, we help people get access to health insurance. People will call us and say how can I use my insurance coverage to do x, y, and z? So to add on to your question about how to change the culture with clinicians, how do you see it changing the culture with patients being open to trying digital therapy? Thanks.

David Kim:
Let me tackle that one. And I may end up with my thoughts about how to change the ideas of clinicians. But, for patients, it’s largely about I think two things. One is ease of use. They want to do something that makes their lives easier. The other one is that it doesn’t cost them anything. When I look at investments and somebody tells me it’s going to be direct to consumer, I start to cringe because I find that that business model is really difficult. You either hit a home run or it’s gonna be really tough to generate revenues because consumers as a group, they don’t really spend as much as you think they do. Something that they really think that they need, they may do it, but overall, if you look at all the apps out there, they’re willing to pay a dollar, five dollars, maybe 10 dollars for an app, but on a continual basis if they see that they’re spending hundreds, they’re going start to feel … if it’s out of their own pockets.

So often I look at the business model and I look for those business models that are more B2B and that ultimately will be used by the consumers but is paid by another organization, like a business. So that makes a lot more sense.

In regards to the physicians, and again, I’m going to sound really cynical, but another thing I do is I follow the money. If the physicians are ultimately making money or it’s costing them less to do the right thing, then they’re more likely to adopt it. If you’re going to make them pay for something or make them spend extra time using it, the likelihood of adoption is pretty low. Even if they are philosophically champions of that particular therapy, them actually adopting it is fairly low. Unfortunately, that’s kind of how the whole system is run. You have to see how the alignment is. And a lot of it is fiscal alignment. If you’re gonna make life of a physician harder by saying now I’m gonna give you reams of data that you need to look at in my 15 minutes so that I could get the right answer from you, it’s gonna be really hard for them to buy that type of technology. You have to make the lives of the people who are actually going to use it much easier. And ultimately, for them, hopefully they can make more money doing it.

Arundhati Parmar:
It’s really important you mentioned that because we’ve not really talked about the issue of reimbursement of digital tech. And that’s the biggest 800 pound gorilla in the room. How do you approach payers to pay for these types of products? As you mentioned, if physicians are getting paid for it, they’re probably more open.

David Kim:
What’s really interesting is the payers are the best customers. Ultimately, they are at risk. Meaning that they have dollars at risk. If they could find a way to maintain the same level of care if not improve it but cost them less to deliver it, they’re very interested. You have to show them that you can do it, but they’re very interested. This is where I would say that a lot of these ideas that improve workflow that find errors in systems or anomalies. One of the areas that we’re interested in is how do you use big data to find these situations where there are anomalies that could potentially save the risk bearing entities money?

Or how do you create a situation where you provide better care so that in the long run they could actually do better? Especially, incentives are that if you have to meet certain quality measures and you help them to meet quality measures, because if you don’t do that you either get a penalty or you don’t get your bonus. And they’re very incentivized to actually do those behaviors that allow them to do better. But, again, being the cynical person, usually they’ll do it because it allows them to make more money or decrease cost.

Arundhati Parmar:
Okay got it. Any more views on the panel on that?

David Klein:
I’ll just add to that. I think with the innovation that you’re seeing in digital health, you’re seeing innovation in payment models. We’re going out with our smoking cessation solution in an outcomes based pricing model. So payers don’t pay unless people quit. So it’s a pay-per-quitter model. You’re seeing a shift from this PM per member, per month type model to an outcomes based model and I would encourage people to embrace that model, it makes sense for everyone. It makes sense for companies like ours, it makes sense for the payers, and it makes sense ultimately for the patient who are afforded and effective and efficient treatments.

Arundhati Parmar:
That’s the overall trend in health care anyway, the pay-per-performance whether you’re digital health, or a medical device, or pharma. Any other questions from the audience?

Lyla Taylor:
Hi there, my name’s Lyla Taylor and I’m here with Demy-Colton. My question is: often with mental health treatment therapy is paired with medication as part of the treatment. Do any of you see digital mental health being required as part of a treatment program? So it’s something that would be necessary as part of the program, not optional or secondary but something that’s a working pair.

David Klein:
I could talk to that for a second. I would say absolutely. I would keep in mind that a lot of these things are indicated already with big behavioral health. So look at whether it’s depression or smoking, look at smoking for example. Some things like Chantix, even nicotine replacement therapy, so the gum, the lozenge, the patch. These things are indicated with behavioral health management. They’re just not being utilized. So I would say that, yeah, I see these things as absolutely being required in that sense and I also see, and we have experience now that we’re getting, with insurers really putting these as kind of step up type therapies. Hey, why don’t you try this before you go on this medication for years. So I would say that not only in conjunction but you’re seeing formulers starting to look at this space as, “Hey, maybe we should add in as a step up.”

David Kim:
If I could add to that. In my former life I actually was a practicing internist. When you practice medicine there are certain things that you do because it’s well accepted in the community. But it takes a long time to get accepted in the community. It starts with good, clinical data to support why you would want to use this digital health therapy in conjunction with medication. So you need to prove that out. Then it usually goes through the society and then it gets populated. Now, this process of getting adopted will be accelerated if there are means such as controlling the formulary, or there’s, Kaiser, where you have the provider network and physicians actually working very closely together and they can change policies very quickly. When you communicate that policy, then it gets quickly changed within the Kaiser community.

Until, unless you have that acceleration, it will slowly get permeated throughout, but it all starts with the data. If you have data to say this is the way things have to be done, then it will start to be accepted.

Gabriel Vargas:
Yeah, I agree, to add to that. It basically follows the initial comment I made, which is, if you have [inaudible 00:44:28] in which you can combine your drug with your digital health application and show that that is actually superior, then that eventually, if you have enough data, will come out as the standard of care.

Arundhati Parmar:
I think we’re almost out of time so I want to thank the panel for an interesting discussion and hope you have learned more throughout the day today.