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Adapting Medical Affairs Engagement For a Disrupted Market

WBNR 0709 - Adapting MA Engagement in a Disrupted Market

 

About This Webinar:

Telemedicine and other factors have upended the ways in which Medical Affairs teams typically operate. Join Dr. Aswin Chandrakantan, Komodo's Chief Medical Officer, to learn ways you can thrive while facing challenges with:

  • The ongoing ripple effects of COVID-19 that need to be incorporated into strategic planning
  • New models for delivering value to HCPs
  • Long-term outlooks for the future of Medical Affairs

Webinar Transcript:

00:00 Neil Patel: Thank you everyone, for joining today's webinar, Adapting Medical Affairs Engagement for a Disrupted Market. We're super excited today to have our Chief Medical Officer and Senior Vice President of Corporate Development, Aswin Chandrakantan, on the phone. A little bit about Aswin. He, prior to Komodo Health was a senior leader in Google's Global Strategy and Operations, responsible for the implementation and support for Google's 240 plus ad products, sustaining 110 billion in revenue.

00:33 NP: He brings really in-depth healthcare experience and analytics experience from his roles as an engagement manager at McKinsey, while also a founding member of McKinsey's Healthcare analytics service in support of leading biopharmaceutical companies, payer reform in over a dozen states, opportunities working with revenue cycle management at top integrated delivery networks, and leading other strategic initiatives like Polio Eradication for Nigeria. He earned his MD from the university UMDNJ, now Rutgers Medical School, and a Bachelor of Science from the College of New Jersey. It's my pleasure to introduce to you Aswin and hand over the call to him for this webinar. Thank you so much.

01:19 Aswin Chandrakantan: Excited to chat today with everybody a little bit around what we're going to do in the disrupted post-COVID world. First, I wanted to talk through how medical engagement has been working, and some of the big paradigm shifts that we've seen in the industry. Some of them are very near term, and they center around COVID, some are longer term and require a more strategic response. And a lot of those pieces are underpinned by they taking a patient-centric approach to engaging providers and institutions, pivoting teams in order to support and adopt and embrace virtual engagement. And then the last piece is around segmentation of ACP so that you can drive the right message and scientific education to providers in order to drive better understanding and adoption of standards of care in the market in your therapy areas. And then lastly, we'll conclude with a Q and A session, about 15 minutes or so.

02:28 AC: So Komodo's mission is focused on reducing the burden of disease. We think about ourselves as a software analytics company. We have built the largest patient Healthcare Map in the U.S. And so what I mean by that is that we traced the journey of 320 million patients, the providers and institutions with AC care, the therapies and interventions that are used to treat those conditions, and the outcomes that result from that.

02:57 AC: And so what's very unique about the approach that we've taken is that we focus on working directly with payers and providers to get a lot of that patient-centric data, and we're really focused on cohort specificity, which means that we want to see every single encounter that a patient has through their journey in the healthcare system, and in a world of narrowing label indications in life sciences, the value of being able to get to that specific cohort that you and your teams are looking to study and you're looking to engage providers around that cohort is incredibly important.

03:42 AC: Talking a little bit about the company itself, we're a 250 member team, sitting across San Francisco as well as New York. We serve 20 of the 20 largest life sciences companies, over 55 biotech companies, and a couple of dozen med tech and diagnostic companies. We have thousands of users on our software applications every single day, and while we bring out-of-the-box software to drive immediate impact for your teams, we also have a deep partner partnership across the entire healthcare ecosystem so that we can build that resolution, specificity, and actionability for some of your most pressing problems.

04:28 AC: A little bit more around our Healthcare Map™. So I've talked about the 320 million patients. We capture about three to six times more encounter data for each patient due to our payer complete approach, and so that gives us unparalleled resolution into where patients are on their journey, and all the sort of specificity around where they are in terms of their disease characterization, as well as all of the touch points through the healthcare system. We think about our Healthcare Map™ as being linkable. Where we're able to bring in different data assets and key to systems, even on the client side as well as the broader ecosystem, and really help bring that canonical view and representation that we can both build better insights around and also build software and algorithms, machine learning, around.

05:28 AC: The last piece that I'll highlight is that all of this is done in a de-identified, certified schema, and that's incredibly important in a world where privacy, as well as reducing disease burden, need to be balanced effectively, and so all of our software is certified de-identified and meets the most rigorous compliance standards. Talking a little bit now about medical engagement, this is actually one of the most interesting topics I think facing the life sciences industry in the past two to three years, where there's been a paradigm shift in terms of challenges around accessibility, the role of commercial versus medical affairs teams, the...

06:23 AC: There's often times a very, there's a very entrenched view around using pure bibliometrics, on the medical affairs side, and we're seeing a lot of adoption around a patient-centric approach, so that's the first trend that I'm gonna talk through in detail today. The second topic I want to talk about is that in the post-COVID world, we have to think about, what are options to engage providers that are now inaccessible in face-to-face interactions, and how do you drive that education around a particular mechanism of action or a particular standard of care. And so talking about some of the analysis and some of the market trends that we've seen, third is thinking a little bit more around segmentation when it comes to education and how that drives a differentiated and engagement opportunities for some of our teams. And last we'll close out on talking about A, starting in this world in which it's just about, these are the providers that I saw, moving to a world in which you can actually understand the providers and institutions where your teams are engaging and understand the disease burden or the patient impact of that, and some of the tools and software that we built in order to support that.

07:51 AC: So we're gonna go through each one of these topics layer by layer, and so to speak, and I unpeel the onion as they would say in Shrek. And so exciting topics for us to think through. And I think a lot of these issues having surveyed a number of chief medical officers and CEOs of our both SMD as well as top 20 clients, the biggest questions on everybody's mind are, "What are we gonna to do to our field forward personnel now that they're grounded respectively?" The second piece is, "Can we actually understand which providers and which institutions are engaging in telehealth or telemedicine-friendly behaviors versus not?" The third being, "How do we continue to support patient needs and what are some of the disease trends that we're seeing in light of COVID and the shift towards telemedicine?" And then the last piece being, "What is the longer term impact on medical affairs resourcing and engagement?" First topic, so the bibliometric approach, which we generally think about, I think about it as, I call it the gray beards of the industry, they're at every single conference or congress, they're the 50 to 100 people that everybody knows, and traditionally, medical affairs has emphasized those particular leaders...

09:29 AC: In that you need to, they need to understand your mechanism of action, you need to have some sort of engagement with them to be able to drive broader education around your program and your initiatives. And what we were finding now in 2020 and over our work over the last half a decade is that you can complement that with a patient-centric approach that includes the bibliometrics but now focuses on disease burden and a comprehensive profiling of the provider, not just looking at this very unilateral bibliometrics around providers, but then also understanding care practices, referral patterns between providers, and then really being able to understand what message is relevant to that specific provider. So there's actually four different pieces that in Komodo we think about when we think about a patient-centric approach. And so I've already started to highlight that clinical signals first and foremost, have largely been under-sampled or misunderstood or not used effectively in the medical affairs community, and I think at Komodo we've built a number of software applications to address that, and that's why we have 20 out of 20 life sciences companies partnering with us and almost about 70 other biotechs and med device companies working with us.

11:03 AC: And a lot of that is centered around the clinical signals. So being able to understand how many... What is the relative volume of patients that a particular provider is seeing. What is their connectedness to other providers? And are those paid providers sending them or are they... Sending them patients or are these providers largely sending patients to other providers? Are you the super specialist among specialists out in the community? And then the last piece is, what is the volume of patients flowing across all of these nodes? And so a lot of this is incredibly complex graph analytics, but then when you really boil it down, we're able to digest it into a single score that allows you to understand where providers are seeing, which providers are seeing most amount of patients and which providers have the highest level of connectedness, so you can make informed choices around the disease burden and the relative care... Standards of care adoption by a particular provider across the entire US. And so we're talking about tens or hundreds of thousands of providers depending on your specific therapeutic area, and not just focused on the top hundred.

12:23 AC: From a scientific signals perspective, this is where the industry has traditionally focused, and so we think that's incredibly important, right? Are you scientifically active, are you publishing papers? Are you engaging in clinical trials? That can and should be a significant... You should be able to have a significant understanding of that across the industry, and so it's not just about the top 50 or the top 100, you need to understand that for an entire market. So in a world in which you have particular providers that are new and up and coming, and they have just recently graduated, but they have a lot of scientific activity against them, you need to be able to pick up on those cues so that you can identify those emerging leaders. Network signals. I've talked about this in the context of graph analytics, and I think what's really important here is that it's not just about, "Oh X, this provider sees the highest percentile of patients."

13:26 AC: But it's also being able to characterize those relationships, understanding is this the internal... Is this the hematologist, oncologist that all the internal medicine doctors in Northeast Nebraska are sending their patients to, recognizing that the academic centers that are largely well known, but now as you want to drive education and adoption of standards of care in the community setting, how do you understand how these patients are moving, how do you understand the characterization of an entire care team, so who's the nurse practitioner for a particular provider that you might want to engage. And all of that is built into our network signals module. Lastly around industry signals, and this is actually incredibly important. We've cleaned, linked and parsed all of the Sunshine Act data, and so we can actually see since 2014, all the contractual engagement that our providers had across research, speaking and consulting in order to then understand, "Well, what is the level of engagement? What is the level of education? What is the level of financial obligations that a particular provider might have to say the competing therapies in the market?"

14:49 AC: And so you need to... If you're looking for fresh voices, well then you could immediately understand well is this person speaking and consulting for five other competing therapies, if they are that you might want to look at someone else. And so we believe that this patient-centric approach around clinical signals and network signals combined with a lot of the scientific and industry activity creates a holistic view around how to approach a provider and get that provider to understand from a patient disease burden perspective, how can they help drive the best standard of care for that patient? So we did a really interesting analysis here, and what we wanted to look at was, using Sunshine Act data, how well does the contractual engagement with the industry using Sunshine Act Data, actually mirror patient level disease burden? So what you would expect is, if you have a lot of patients in a particular county, or in a particular geography or a particular con catchment area that there's gonna be a completely linear curve associated with, "Okay, more patients, and more disease burden, and more pharmaceutical contractual engagement with providers."

16:14 AC: And what we actually found was quite startling, so we looked at the State of Florida and we looked at diabetes specifically, and we can do this for any disease area, but this was... The data was largely based on publicly available data sources, so it could be easily replicated, and so we wanted there to be robust scientific inquiry around our findings. And what we actually found here on this scatter plot is that, A when you look at the left, that is the dollar spend over the amount of cost that pharmaceutical companies are spending and versus the amount of cost or disease burden associated with that. And so on the bottom is the patient burden, by the number of patients, and on the left is essentially, how much is the industry spending. And so what you find here, the things on the lower left, on the upper right, are exactly in the right place. So places like Miami ton of patients that have severe complications of diabetes and a lot of investment by pharmaceutical companies. And on the lower left, low disease burden are largely in say farming communities and in Central Florida and low investment by life sciences companies in terms of their medical and scientific contractual engagements.

17:53 AC: The lower right was actually the most concerning. Because these are counties in Florida where there's a lot of patients that have severe disease, and there's extreme morbidity and mortality associated with them, but there's little to no contractual engagement with any of the providers there. And so these are the patients that are missing out on the opportunity to join clinical trials, these are the patients that are missing out on the opportunity of the newly launched therapies and modalities in order to... For those providers to know whether or not it's the right fit for their patient in terms of the standard of care. So places like Hillsboro are largely overlooked by the industry, and that for us poses a very spiritual problem, and also for us is a pronouncement that through the use of software and analytics, we can get to a better norm as an industry about where we invest in terms of scientific education in order to drive the maximum impact against disease burden.

19:07 AC: Second. So let's talk about COVID-19 very specifically. There has been a traditional face-to-face interaction model with key opinion leaders, and this has been in place for several decades, but the COVID-19 pandemic now has reduced the number of physical interactions, and we can actually see all of this through our Healthcare Map™. And so let me take you through a few examples. So some of our work was picked up by Reuters and the New York Times, CNBC, the Washington Post and Star and essentially it found that in diabetes hemoglobin A1C testing... Testing has dropped by two-thirds since March 19th, which is kind of the sentinel milestone of a lot of the shutdown orders and aggressive interventions by the government.

20:09 AC: And even in the context of cancer testing like leukemia and multiple myeloma, where you need to carefully monitor the progress of the disease, bio-marker testing as well as monitoring panels were down by a quarter. And so what that's telling us is A, that there's... Patients are getting disease, patients are getting sicker. And so it's not that patients are not getting diseases, that they're not getting colorectal cancer, for example, it's just we're not testing for them. And so these patients who are not getting the hemoglobin A1C testing or who, they are at severe risk for progression and complications and comorbidities, and acute deterioration, but we as a healthcare system, are not, we don't have the traditional ways to understand whether or not they're actually getting the care standards they need, and as a consequence, there's likely deleterious events for this entire... For the patient population across the US at large.

21:20 AC: What we also found is that there's actually... There's two messages on this slide, first is that there's been a massive surge in the percentage of clinical encounters that are being done remotely, that are digital through telemedicine. That's point number one. Number two, is that there is actually a really high variability across geographies and institutions in terms of the percent adoption of those digital medicine and telemedicine initiatives. And so we took a few sample, the geographies across different risk pools, and here you can basically see in the smaller bar next to every single large bar is the percentage of telemedicine visits pre-COVID, versus those of post-COVID. And so, what's startling here is that in pre-COVID times there's, there was only 5% of healthcare providers in America that had any routine telemedicine presence, post-COVID that surged to over a third of them. So that's excellent and that's actually the trend that 6X increase is important in order to keep patients connected to their care, and our belief is that virtual engagement is likely to grow as right now, the trade-off between in-person treatment is somewhat fluid, and we believe that this trend is here and it's here to stay.

23:03 AC: One of the other pieces that is somewhat for me sad personally, is we also looked at the number of lab procedures that were being ordered pre and post-COVID, these are from, all the way from chronic diseases on the right, like hypercholesterolemia and diabetes, all the way to acute conditions and oncological conditions that have high mortality rates and high... They're aggressive in terms of progression, like breast cancer and ovarian cancer. And across the board, we basically see a slash of anywhere from 40 to 90%, 90% in the more chronic disease area and about 40 to 50% in the oncology area. And that for us is... That's a warning sign for us as an industry, and a couple of takeaways there for us is that A, there's gonna be a massive impact in terms of delayed care, or in terms of our healthcare system. B, when COVID-19 begins to resolve over the course of many more months or maybe even over the course of years, there's gonna be a certain amount of disease and care that's been backed up in the system, and there's gonna be a massive spike in care. And so all of that is observable and knowable today and that's where getting in front of it, through the use of software, being able to characterize which doctor's doing telemedicine versus not.

24:47 AC: If they're not doing testing for your particular disease, then we already know that those patients are not getting the right standard of care. So then being able to even be the advocate on behalf of the patient to say, "Hey look, we... Forget about which therapeutic modality you're gonna use as an intervention, if you're not doing testing, there's gonna be a gap between effective prevalence and prevalence, and that's only gonna grow over time." And that for us should be alarming as an industry and also as an industry that's focused on patient well-being, these trends can lead to catastrophic outcomes. So I actually wanted to take a moment to take us a little bit through the software itself. So this is a view into aperture, this is focused on breast cancer, pre-COVID there are about 4500 providers that were telemedicine users, and we've included that on the tag, and as you can see on the left.

25:55 AC: And post-COVID, that number has basically 5X to 17,000 providers, and this is all real-time cleaning, linking, parsing, tagging the providers and their behaviors, so that your teams can make informed choices about how to reach providers to know which providers are still providing care, and also help them understand care standards and also examine some of their specific... Provider-specific behaviors to make sure that their patients understand what care they should be receiving and which therapeutic modalities are available for the most vulnerable populations. And so this is a very quick demonstration not only of the increase but then the pull-through to a specific therapeutic area and we can do this for any therapeutic area on the planet and the value that it brings you and your medical affairs teams.

26:51 AC: We're running a little short on time so I'm actually going to just skip through the last two sections not because they are not important but just out of the respect for everyone's time. Right now using data, there's an opportunity to segment and profile providers in a way that we never could before and so I would say that the industry has lagged because of a lot of blunt outreach efforts that are largely based purely on scientific means. With a one-size-fits-all approach and now we actually see through the use of analytics and software that you can profile and understand providers even from afar without even talking to them through software and technology that you have that piercing insight into their practice to help understand what conversations you should be having with them digitally or through any email or non-personal initiatives that you might choose to launch.

27:58 AC: So here, we see that we had a specific client that was focused on the renal cell carcinoma space, they had 122 providers on their lists. And these are the traditional, all focused on bibliometrics and what we found here is that we were able to take their static lists of providers that they thought were important and that basically add 10X the number of providers that had profiles that would benefit from education, that were seeing a ton of patients, that were scientifically active but that had been traditionally overlooked and so this was a piercing way in order to understand well, which provider should I be providing more clinically-oriented message around safety and efficacy versus which ones should I be focused in a little bit more of a scientific basis for engagement, which ones have taken money from industry versus not and how do those contractual engagements potentially influence their care patterns and so there's a lot of analytics that's built in here, the recognition being that the top 100 and the top 200 is not gonna cut it in this day and age.

29:23 AC: And just to exemplify that we had a medical director at an emerging biotech that they launched Aperture, they found 240 new emerging and clinical leaders within three months based on our deep profiling and segmentation and you can see in here we provided the clinical focus of that provider, all the care teams and the referral patterns and all of their work across the science as well as the industry and they were able to double the number of emerging leaders that they were engaged with to drive education around care standards. The last piece I'm gonna largely just gloss over and highlighting that A, we as a medical affairs industry have had very blunt instruments to measure our impact to the market.

30:25 AC: And it was largely focused once again on bibliometrics but now Komodo has launched impact reporting which actually ties the providers that you have touched or your teams have touched and tie it to the percentage of patients that have been reached at a State, County and National level and so it's incredibly important now because now you can tie back well, what percentage of the patient disease burden have I actually touched as a team just as opposed to, "Oh, I talked to 50 providers this month," and, "Well, was that a good proxy, is that bad? Is it just the people that you knew before or are they the providers that are actually out there seeing patients?" And so we believe that's knowable and it's actionable and so we've built instrumentation and software and features in Aperture that help you drive that level of insight and that level of measurement and instrumentation within your teams.

31:33 AC: So we're incredibly excited by the opportunities of this and the value this has unlocked for both patients as well as medical affairs teams. So key takeaways, first, rapidly reshaping environment, over the longer time horizon, we're seeing a lot of access restrictions and there's increased emphasis around medical affairs to focus on scientific education and align their efforts against disease burden. In the short-term, there's a question around who's working? Who's seeing patients, who's not? Who's digitally enabled? Who's testing their patients, who's not? And all of that's knowable through software and we've built software specific to that for medical affairs teams.

32:22 AC: And you can reach the right message to the right provider at the right time at the right setting of care through virtual channels, almost all of our providers in our Aperture software of millions of providers, we have email addresses that are [32:37] ____ certified and opted in. So you can reach those providers and provide them the scientific education they need. And the last piece that I would say is that with the right partners with out-of-the-box data, software capabilities you can help... You can get your medical affairs team performing at the next level and optimize your impact despite some of the market challenges we're seeing. So with that thank you so much for your time, I'm going to pause there for any questions and I'll turn it over to Neil to pose those to me.

33:15 NP: Right, thank you and if you could go to the next slide as well, Aswin, just to have that up one more, perfect, one more. Great. Again, for questions, there's a Q&A box at the bottom corner of the screen. We have lots of questions coming in, so feel free to continue to submit those. We'll try to get to as many as possible in the next five or 10 minutes here. Aswin, one of the first questions that's come in, which I think is very relevant to the sort of conversation we've had today around extending your KOL universe... Can you explain more on trends of how patients are moving and the need for more community rather than academic center KOLs? Could you expand on that a little more, please?

34:05 AC: Absolutely, so two pieces nested within that question. So first, I would argue that the era of KOLs is largely over, I know that's almost... And the reason I say that is that it's incredibly important to be able to educate providers that are seeing patients. And so those care decisions are being rendered not just at academic institutions, but out in the community, much as the questioner has already implied. And so, first of all, we're seeing a lot of heterogeneity across institutions, be them community or academic in the post-COVID world, and their relative adoption of telemedicine. The second piece is, is that when you think about communities, we oftentimes think about them as being relatively un-sophisticated or unwilling to take challenges or unwilling to adopt a new care standard. And what we've actually found is quite the opposite. We oftentimes find that large academic institutions can be just as entrenched or if not even more in terms of what's on formulary, what's not, and there's a lot of business and economic decisions that go into it. Versus in the community a provider is much more able to make fluid and discerning care choices around... And they just need to know what the standard of care is.

35:48 AC: And so I think there's actually a lot of opportunity in order to educate the market around better care standard or specific at risk populations and what the right options for those patients could be. And so I would urge our audience to just think through, rather than thinking about the juxtaposition of KOL versus not, think about this off in the perspective of a patient. And so you can have somebody that's doing incredible research in the industry, but if they're not touching care decisions and they're not making care decisions for patients, then you need to make sure that you have a balanced view of the folks that are making care decisions versus not because academic adoption doesn't, and an understanding of care standards doesn't actually lead to the best outcomes for all patients across the US.

36:51 NP: Great, thank you. That's super insightful. Another question here on the line is, you spoke about the use of this data for HCP or KOL identification and engagement. Can you speak to other areas that you can leverage the sort of insights here in Aperture, other use cases potentially?

37:11 AC: Yeah, so great question. Let me just rattle off a few and they're not exhaustive. In the same way that I would say is like, what questions could you ask Google. I would almost imagine that as like, what questions could you ask Aperture. We've basically, for medical affairs teams built Aperture to be able to fit different levels of seniority across the entire life cycle. So some sample case, our use cases include clinical trial, site identification and investigator identification. The second piece is being able to understand everything from advisory boards to panels and being able to set those up correctly so that you have fresh voices in the market and you have emerging as well as existing leaders in them. The third is field force planning, so being able to understand where there might be a lot of disease burden, but you may have a mis-allocation of the number of people versus the disease burden in the provider population that needs to be educated.

38:23 AC: So you oftentimes find is that we tend to cluster field force purely around population centers, but when you actually look at the standards of care being implemented, you realize there's a delta, that there's actually some missing understanding in the market out in the communities, and just being able to recalibrate that. Being able to build your entire medical affairs strategy, which is what populations, what institutions, where are we seeing the biggest gaps, is it around the gap between testing or is it actually around education on specific treatment choices, or is it around the understanding of specific comorbidities and the relative application of our therapy or not. All of those use cases are bundled into Aperture. So it provides you both the landscape view of the industry, but also provides you the deep profile view of providers as well as institutions. And maybe I'll close off on that use case, which is increasingly medical affairs teams, not only have to think about individual providers, but have to focus also on education of entire accounts and thinking about, "Well, okay, this particular provider might be making choices that impacts the care flexibility and the care choices of all the providers in that particular system. And so, just being able to rationalize that, understand that, study it, and then make an informed choice about how to engage, is incredibly important.

40:00 NP: Thank you, that's a great answer. We're getting a lot of questions on... And so, I'm gonna try to bucket all of these together around our data sources or clinical data. Can you just remind the audience in terms of how Komodo sort of goes about sourcing this data, perhaps, and then tying it back to questions around measurement of disease burden, and so [40:24] ____.

40:24 AC: Great question. I love that we're becoming much more conversational, as an industry, about this. First, 320 million patients in the US, that is nearly census-level representation of the US. And clean representation across disease areas and geographies, our data is largely focused on encounter data. This is the encounter that a provider has with a patient, and there's artifacts from that, that are... There are largely claims that are essentially sent to a payer, and that provider needs to be reimbursed for their services. And so, it's highly scaled, it's highly normalized, and so we can actually take a lot of that, clean, link it, parse it, and build a lot of our referral maps. And so, this level of scale and representation can only be done on certain data sets.

41:24 AC: When we want to do specific studies or specific work that requires EMR data or lab data, we can certainly bring those in as well. But our core asset, and the core of Aperture, and the core of Pulse, and some of our other products, are all focused on this encounters data. And the differentiated approach for us is, we don't want to know a sample of the patient's journey, we want to know the canonical representation of all the patients in the US that have a specific disease, and their journey through the healthcare system. And so, we've created a much more aggressive bar for ourselves, as well as the industry, in order to study these populations, and so that life sciences companies and medical affairs teams can make informed choices about how to drive better care standards for those patients.

42:19 NP: Great, thank you. And I think on that note, we'll end today's conversation here. We'll try to get to all of these questions for the audience we haven't answered, via email, as follow-up. So, really thank the team today and everyone coming together, Aswin for this presentation. Again, follow us on komodohealth.com, follow our blog, our LinkedIn, our social handles. And we continue to add insights, and refresh our insights on our Healthcare Map™ and the software solutions, on a daily basis. And so, follow us and for future webinars. Thank you so much, and have a great rest of your day, and an excellent weekend.

43:04 AC: Thank you so much, everybody.

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