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What is the Insights gap and why should you care?
Historically, insight gathering in life science has been a fragmented process, when it should be viewed as a single endeavor. In this discussion sponsored by Within3, learn how to eliminate the insight gaps that occur due to disparate data sets, changing stakeholders, siloed information systems, and evolving scientific narratives throughout the product development lifecycle – and how Medical Affairs teams can achieve clarity, improve business function, and reduce risk with a holistic, technology-enabled approach.
Garth Sundem 0:00
Welcome to this episode of the Medical Affairs Professional Society podcast series: “Elevate”. I’m your host Garth Sundem, communications director at MAPs. And today, Lance Hill, CEO of Within3 is speaking with Mike Abbadessa, Executive Director of Medical Affairs at Within3, about how to eliminate the insights gaps that occur due to disparate data sets, changing stakeholders, siloed information systems, and evolving scientific narratives throughout the product development lifecycle. This episode is made possible by Within3 whose insights management platform helps life science companies identify the right people, actively engage them and get answers that inform strategic decisions. So, Lance will be asking the questions today, Lance, I will let you introduce yourself and then take it away.
Lance Hill 0:57
Thanks very much. So yes, I’m Lance Hill. I’m the CEO of Within3 very happy to be here with my colleague, Mike Abbadessa has spent a long and storied career within Medical Affairs at varying companies. And today, we’re going to be talking about insights management, which is a pretty cool topic, actually, we think about insights gathering within the context of Medical Affairs. It really is such a critical issue that pervades so much what Medical Affairs does. And you know what occurs to me when you think about insights gathering and other industries, it probably seems a lot more straightforward. If I’m developing, you know, a new version of a phone and I want to just pull a bunch of potential cell phone users into a focus group anytime I want. Hire any consultants I want, get to them anytime I need to. It’s pretty straightforward. Not so much though, in life sciences. So, Mike, maybe we can start off even a little bit about who you are, but then maybe talk about why insights are so critical to life sciences, generally, that Medical Affairs specifically.
Mike Abbadessa 2:01
Thanks, Lance. Yeah, no, I think it’s a great intro. I’m glad to be here. This is going to be fun. As you know, I grew up in pharma as an MSL, worked through the ranks MSL director, and then finally landed in a home office position, looking at really looking at data and how to use data to effectively make decisions and what I learned back in that day when I was an MSL, is that, you know, insights were considered, you know, the information exchanged during that KOL engagement. And it really was the value proposition for MSLs at that time, but as I progressed, in my career across Medical Affairs, and with other companies, you know, broaden my scope there, I now see this is really a more global process. It’s really one that follows the path of the development of the medication, you know, the pipeline asset or the even the device if you’re talking to a device company. And it really is the insights really inform and validate those strategies, and really build on that scientific narrative that evolves over that lifecycle of the product. And then, it’s just really as a more global process now. And as I step back, and look at it more holistically. And so, when you look at that process, really the one of the key components of that, of course, is the external stakeholders, ticker, these are KOLs, depending on where you are in your life cycle, that can be hcps, depending on where you are in the clinical piece. But really, those are the folks you’re relying on to advise you on that scientific and medical strategy. For your life science assets. It’s really, you know, things such as molecules, drug products, etc., even diagnostics, right. And those help create those strategies, as I mentioned, and the story for that asset. And it can be anywhere in that lifecycle. So, for example, early stage preclinical, you’re talking about a mechanism of action, and perhaps identifying the target for a specific disease community, or patient population, whether it’s a rare disease or a chronic disease, but you have something novel and now you’re starting off need advice. So you engage those, those key opinion leaders, they may be bad scientists at that time, and not necessarily clinicians. They then you go into a pre-launch prep and start to get into clinical data and the clinical development process and the data from that clinical, those clinical tests and those clinical studies, you know, what are those implications for that unmet medical need, or safety and efficacy, competitor analysis, or even a go no go decision and you’re talking about phase two to phase three, and then finally get to launch and really setting the stage now for what’s that real world evidence on insights, as the product now is in the real world, beyond clinical trials can validate some data, maybe the data is different. The perceptions are different now with those hcps. Maybe there’s educational needs. So those are the types of insights we’re looking for that really informed pharma, they’re crucial and then you finally get to the mature product and You know, it’s now looking at size of teams, which what’s the competitive analysis? What? Where are you from a payer perspective? Are there other new data needs do you need to do more research? And so that that’s really where you start to expand. Now, this happens across the spectrum of functions, whether it’s R&D Medical Affairs and commercial and for Medical Affairs, specifically, it’s really the adboards the field-based activities, you know, the MSL interactions, things are happening at medical congresses. And as I mentioned, those payer AQR interactions and formulary decisions. And really, it’s really through this, what we call scientific exchange, right, everybody on this listing is probably familiar with scientific exchange. But just a reminder, how unique that is to Medical Affairs, how that exchange of medical information in a very unbiased and objective manner yields important insights on how best to treat patients and how to bring those new medical devices to the market. So, I’ll just pause there, that’s kind of my, my view.
Lance Hill 6:01
Yeah, so thanks. I guess, following on that, though, the technologies that are involved. So you mentioned field medical, you mentioned advisory board, varying ways that insights come into the enterprise, into a Medical Affairs organization to make some of the decisions that you were mentioning, the technologies historically that are used there haven’t really changed, you know, 20 years ago, it was how can we get in the room with these audiences, whether it’s in a group setting, or at a medical Congress, or in a one on one setting in a physician’s office? And maybe fast forward to today? It’s kind of sort of the same thing, the pandemic has common and virtual types of engagement are more prevalent, certainly than they were five or 10 years ago. But the status quo through that entire process of Who should I talk to being able to understand what, you know, what, how to engage them to gain insights, and then what I do with it, you know, talk a little bit about what the status quo is, how the industry historically has done that.
Mike Abbadessa 7:04
Yeah, that’s a, it’s a great topic, and it’s one that’s near and dear to my heart, as you know, I’m, you’re talking about innovation, right? You’re talking about how do we innovate. And, you know, we’re talking about a process and it’s, and it’s painstaking, the way it’s has been done, I think there’s a lot of hope on the way it should be done. But typically, you know, as I mentioned earlier, you’re talking about these multiple different processes within Medical Affairs. So, these are this is, you know, within that, that, that function, there’s sub functions and processes on medical congresses, adboards interactions, one on one, like you mentioned, and each one of those, that data goes typically into separate systems, separate documents. It’s, it’s pretty much siloed, across even the Medical Affairs organization. So that’s the difficulty. And it’s very manual, so that they may have a CRM function, something that’s it’s document interactions, but you’re not documenting that in anything from an ad board, for example, and that you’re not putting too much information from a medical Congress. And yet, there’s some valuable insights happening depending on where you are. So that evolution has been somewhat slow, there’s been some incremental changes, but most of it has been in really the, you know, improving the process and how they manage that. But, you know, typically, what you see is that you’re using maybe a platform or a system, or maybe you’re using an agency. But these things don’t typically talk to each other. And that’s pretty much the norm. And this goes on for just about every process, and then they start to multiply that by the number of thought, therapeutic areas and disease states and products, right? In a larger organization. It gets complicated really fast. And it’s really hard to decipher those insights. And there’s a lot of time and energy put into doing all this manual work. For a lot of the science folks. Maybe talk about
Lance Hill 9:10
that a little bit more, Michael, if you could. So, you know, insights gathering is not something where you can say, every time you do this, it costs us $5. And if we can do it a different way, they’ll cost us $4, and set the heart ROI. And we should just shift to this other way of doing things. There’s a lot of implications to an organization on gathering insights very well, or not gathering them while they’re gathering them in a way that that takes a long time or maybe even too long. And we talk a bit about your experiences in that regard.
Mike Abbadessa 9:44
Yeah, it’s been, like I mentioned, really, it’s been an evolution. So, things are moving but it’s slow. So, when you and when you think about the flow of data to information, you think about where that data comes down from the field or an ad board or a congress That flow is really slow, it’s slow within the team, and then it’s slow to get it back to headquarters or to share that within the larger organization. In typical report is a monthly report on insights from a field based medical team, for example. And that, that, that information that delay, so you’re talking about the cost to me or the delay, and the time it takes to get that information so that that news becomes old news A month later, typically, what happens is you will augment some of these systems with email. And that’s used as kind of as a relay system to add another and it adds another layer of data and delays even more. And then when you think of the volume, email, some of that stuff gets lost. So, it’s, you know, I talked to my counterparts in Medical Affairs all the time. And this is what they’re challenged with is like, they’re using Google Sheets, they’re using different documents, they may be using PowerPoints to put things together. And it’s just not a crisp way to do that. And then when you think about the cost of personnel time, you know, recently you mentioned ROI, it was, I was just talking to a top 10 pharma company, Medical Affairs executive. And he mentioned actually that they did a time and motion study, and they looked at just the reporting aspect this this month report. And what do you think the, how many hours a month, you think it takes them to do that one report glance, just, just take a wild guess
Lance Hill 11:26
I would have no idea. Okay, don’t even hazard a guess.
Mike Abbadessa 11:30
So, he’s, he said 185 hours a month. And when I did the calculation, being a former manager, that equates to a little over 150 annually, of just that one segment of, of that process. And so that’s, you know, that that was actually very interesting to hear, because then we always kind of, you know, look at a swag or a number try to estimate that they’ve actually did the study because and they were looking at how to how to alleviate that pain. And then when you look at another, one other aspect, I think that’s, that’s an interesting one is when so let’s just say you’re selecting your top advisors for an ad board. And, you know, you only think about this until after the fact and that this is where I’m coming from, as far as you know, this retrospective look, but if you’re 50%, or even just 25% off on selecting those the right who you think are the right people to be at the red board, that has huge implications, on the advice you’re gonna receive or don’t receive, and pasta resulted in other ad board, incorrect projections, you know, maybe a misinformed decision, etc. So, I think, you know, there, the ramifications are real, and they’re, they’re costly.
Lance Hill 12:46
Yeah, absolutely. I think when you look at it from that point of view, even ignoring the business impact of the insight process, not delivering you the correct insights, or delivering your menu in a timely enough fashion or an integrated fashion for your making decision. It sounds like the manual process and cost of dealing with this fragmented kind of way of doing it is, is very high. And when you think about it, I think historically, because this process was so fragmented, it’s broken down into kind of some departments almost. So there seems to be a lot of companies, some part of the organization that’s in charge of determining kind of the who, who is the set of folks that folks should engage with? And, you know, under what circumstances and maybe where in the world, it seems like there’s another set and part of the organization that is involved with the actually engaging these folks finding them, contracting them, engaging them or, or gaining access to them, whatever the case might be. There’s a compliance component throughout all of this, that I think slows things down, or at least makes things not as streamlined as other industries that maybe aren’t so compliance LED. And then you just spent quite a bit of time talking about the workload and trying to understand what quickly becomes a mountain of data and turn that into something usable. When you zoom out and look at the process, why do you think it’s typically siloed? This way, within organizations in terms of a headset?
Mike Abbadessa 14:21
Yeah, that’s a great, that’s a good. That’s a good point. I mean, you hit on a really, you know, solid piece there. And it’s, it goes back to what I said earlier about this. Zooming out and looking at, you know, insights are really embedded in this drug development process from cradle to grave of that product, if you start thinking at the very beginning. And I always think about that scientific narrative piece. And that’s that piece is the scientific story that you’re building with that asset and it continues to build over time as that as that product evolves and navigates the regulatory process. So, you mentioned compliance. So, all along steps of the way You know, I don’t think there’s any other industry more heavily regulated than healthcare, maybe the airline industry, right? Instead of a way we’re always checking because we’re dealing with patients, right. So, it’s highly regulated. And I think that also makes it somewhat restrictive in some of this. And the way you deal with the data, it has to be confidential, it’s private, of course, and so you have to put it in systems. And so, depending on your favorite system, or the system at that time of lifecycle, that tends to help create silos as well. So that’s, that’s another piece. And the other thing you mentioned, I think I was talking about it, I said, global, but now think about global Medical Affairs, now you’re talking about across the globe, right across different countries and different regulatory pieces. So that adds another layer of complication. But when you start to look at it as a whole, its processes, these processes have insights coming out, in every aspect. And I think that’s the crucial piece. That’s why it’s so important. And those insights are paying are the capital that really pays the dividend on that strategic planning from the early, early stages preclinical to clinical and as I mentioned the launch. So when I look at some of the specifics, and you think about those early adboards, setting up the strategy, really, and identify what that medical need, how do you get that data out, it usually goes into some kind of document that goes into perhaps an agency and then that’s input is given to those folks, maybe the medical directors, within R&D, or the medical directors with Medical Affairs. Now, whether or not that’s all shared across the organization, it gets to the MSL is at the time of, you know, the pre-launch activities, it depends on the organization depends on, you know, how well they thought that that process does. But these are all the pitfalls of trying to gather these insights from this, this really global process across this, this medication, and no one’s really looking at it from the top down. It’s, it’s happening in in real time, across years, with multiple different stakeholders, and you think about folks that might turn over within Medical Affairs, and where did that information reside? early on versus later on? And is there a succession plan for that data, and how that how that transitions from one group to another. And then it finally comes down to the launch piece when you’re really talking about access to these medications. So now you’ve got a product that you think works really well, and it’s there is an unmet medical need to achieve? And now the difficulty comes is how do I, how does this drug? How do patients get access to it? How can physicians now use this drug, and so then, the final piece of that, of that journey is now getting in the hands of the prescribers and ultimately the patients. So, you can see there’s hurdles and pain, pain points all along the way. And the systems we have in place right now are really kind of fragmented, but they don’t, they don’t, they’re not cohesive.
Lance Hill 17:58
Absolutely. And so thinking about how to begin to address some of these challenges, and why now, why, why these challenges existed, but what’s changing now, that is allowing really a new way to do things, I think, some of the technology innovation that’s occurred, really, in the last two years, maybe four is really game changing with regard to this insights process, allowing us to potentially do things at a speed that’s been unheard of, and a level of accuracy, that’s been unheard of. And this is, and these technologies are going to be a little bit of the topics of our subsequent podcasts. But maybe at a high level, you could touch on three areas of innovation over the last, say, four years. One being, you know, the difference in helping identify and know who you should be connecting to, and closing that loop versus maybe the older days of looking at who’s published what on PubMed, and figuring out what you can do from there. You know, second is, especially with the pandemic, bringing that to light, what virtual engagement allows and, and maybe third, as a part of overall insight gathering strategy. And then third is the ability to post process and organize the sources, different signals, from all sorts of insights sources into a real time strategic view, to allow people to make decisions.
Mike Abbadessa 19:22
Now that’s, that’s very, that’s very insightful. No pun intended, but I think it’s a great point. It’s so for me, and you know, you know, this about Atlanta, it’s all about the process, you know, I got into the process. And so, what I’ve seen starting off, just, you know, we’ve talked a lot about, you know, the needs and everything. Well, what I’ve seen, you know, through my travels with some of the highest performing teams is one piece is they know the process so they understand that this is a process and they understand that there’s these barriers and they have an approach. They understand scientific change all the all these things pieces, and it’s not just they understand it, it’s all the teams are on board. So they, they educate everyone, they hold me accountable to understand the process, they’ve, they’ve mapped out the processes, so it’s consistent. So going back to your, your point about identification of K wells, you know, you know back in the day it was when I was an MSL, we would identify those kales, we go out there and do it, you know, feet on the street, we do all our sleuthing And to your point, we look up in PubMed and other tools, we had library tools to figure out how, from publication perspective and a clinical trial perspective who the top k wells are, or perhaps you’re handed a list from, from our R&D colleagues from P eyes, and then we go from there. But as the pressure became more and more, and there was more and more information, number one, and more and more launches, right, some teams were, were blossoming and teams were emerging. Now we looked for some technology. And so, we looked at KOL mapping tools. And again, a lot of that was focused on their publication status, and we’d get a list of the top prescribers, the top publishers, and it’d be a giant data dump. And then we’d have to sift through that to understand who they might be, you know, and it was another effort that was, you know, we had to go through now what we’re finding is there’s better ways to do that, you know, there’s a lot of technology advances from a social media perspective, just a lot of data out there, I would go Google Analytics, and you look at the work that’s been done with AI and, and some of the other technologies, advanced analytics. So, we can start to understand not just who these are, but who are they connected to, in, in a in perhaps in a disease community, right to see. And we can focus in laser with laser focus, look at who the community should be, and who the folks we should interact with, whether it’s at the early stage and ad board, you know, phase one, phase two, clinical research, and then really validate that as we go forward. So that’s really new. And that’s relatively not that common yet. It’s still emerging technology. pandemic, you know, to your point about the pandemic earlier, that really did a couple things. One is it proved from an MSL perspective, and my point that we could do scientific exchange, virtually there’s always this question. In fact, when I was in MSL, we were told not to do anything electronically, there was a lot of compliance risk, we were concerned about it and nobody was really pushing it on hold, some companies were, I think, but where I was, we weren’t doing that. So now here, fast forward years, and here we are for the last year and a half. Obviously, it was a dip at the beginning, but we had no choice. So, we were interacting, and platforms emerge that made it much more easier to do that. We hear about zoom fatigue. But there’s other ways to do that. So, you’re not doing this over, you’re doing this, you know more of an overtime perspective versus, you know, constantly being on a web call or webinar. But what we found was, I think that and although, you know, a lot of webinars on this, you’ll see coming out in the last, oh gosh, last six months, this idea of a hybrid and hybrid engagements, and that we’re not really going to go back to face to face. And the main rationale there is that the HCP is they like the fact that they don’t have to be on face-to-face meeting with everyone, every day, they can actually do this virtually. So, I think that evidence is starting to generate, and it gives flexibility and more of a customer centric piece. And then finally, it’s really when you look at everything being gathered to this global process. How are you going to now decipher and really distinguish between the signals and the noise of what’s a true insight. And what we’ve seen over the last couple years is we’re actually starting to call insights, things that are derived versus the actual information exchange, right? So now those are actually called single point observations or data point observations or observations versus the insights are really
Lance Hill 24:03
an amalgamation of all that data and then filtering using advanced technologies, Ai, for example, machine learning to pull out some of those key concepts, those themes. So we’re just starting to see that as it emerges. A lot of it is in pockets. We’re doing it in some areas we’re not doing in other areas, but really I think the need is obvious that we need to do this on a global basis across all these different processes within Medical Affairs.
Garth Sundem 24:29
All right, you two. This is Garth back. I have to thank you, Lance and Mike for this. It’s so interesting hearing about insights as a process you know, and such a changing process, you know, to identify you said virtually engage, and then post process these signals to figure out what is really an insight and what is just an observation. So, to learn more about how your organization can partner with Within3, visit Within3.com. MAPs members don’t forget to subscribe. And we hope you enjoyed this episode of the Medical Affairs Professional Society podcast series: “Elevate”
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