Garth Sundem   00:00

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 we’re speaking about data and network analytics to identify the right experts, with our own experts from Within3, namely Lance Hill CEO, and Sam Veeck, Vice President of Product Marketing. 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 first of all, thank you both for being here today. And, Lance, it’s always good to chat with you. So, I was wondering if you could get us started by telling us what you mean, by the right experts? Who are these people were looking for?

Lance Hill   00:59

Yeah, that’s a great way to start, actually. Hi, Garth, nice to talk with you again. I think, historically, because of access to data, or lack thereof, the right experts typically tended to be kind of a top down view of who publishes the most in PubMed, who’s attached to which clinical trials, maybe a little bit of who do we know who speaks at different congresses or conferences. And so the right person was really, who is the loudest, scientifically is usually what it has meant historically. And really, if you think about what you’re doing within Medical Affairs in different parts of, you know, everything from development all the way through product launch, and beyond, the right person might be very, very different. The right person for specific set of questions might looking at treaters and prescribers. The right person in another context, could be refers the right person in another context could be people with amazing market access experience. And so, the right person really shouldn’t be contextual, to what you’re trying to learn, or who or what outcome you’re trying to achieve, versus kind of a generic, here’s a database of people, some algorithm and a back this kind of ranked everybody usually based on scientific loudness. And in here you go, you know, go talk to these sorts of books.

Garth Sundem   02:28

Well, so Sam, I always think about identifying the right experts as a as a Field Medical thing where you’re looking for HCPs. So, you can have your MSL HCP scientific exchange, but it sounds like we’re expanding the definition. So you are, are we still talking only in the context of Field Medical? Or are we even expanding our vision of these experts beyond that?

Sam Veeck   02:52

Yeah, that’s a great question, Garth. And, honestly, it is an expansion, and it probably has been, but we, in the context of looking at the right people today, it’s starting really at the beginning. So, if you’re talking about clinical trials, for example, are you working with the right investigators? Are you identifying the right patient populations and, you know, placing your clinical trials in the right location, all the way through then to Medical Affairs? And then through commercial? And are you talking to the right HCPs to truly target and have the greatest impact within your drug or disease state of therapeutic area. And so, it really spans the entire product development lifecycle, depending what you’re trying to achieve, and come to your goals of where you are and who you need to be talking to. But there’s also, you know, expansion into specific areas as well, like geographically, are you talking to the right people if you’re trying to expand into global territories, for example. And so, it spans really the different individuals within life sciences, but also across the globe, in terms of talking to the right people and making sure you’re really targeting who’s going to help impact the things that you that matter the most to you.

Lance Hill   04:10

And you benefit beyond this, just to jump in, to think beyond, you know, beyond Field Medical specifically, right? So, you have in today’s world, a much more complex landscape of who Medical Affairs interacts with and kind of who within medical and refers is doing that interaction. So, you have things like steering committees and advisory boards. A lot of times Medical Affairs is involved in different ways in different sort of speaking or educational sorts of materials, you might be working with different HCPs or other experts on developing educational aids and understanding and assessing patient cases. You might be working with outside books in the publications or authoring domain, and have different thought processes there. So, while Field Medical has sort of the Who’s my call list, who should I be talking to on a kind of a daily basis or quarterly basis with a view, usually more of disseminating science to a degree. Also, in today’s world pulling information back, if you step back and look at all of medical strategy point of view, there are a lot of touch points. And the traditional way, as we mentioned, of who’s the loudest, scientifically, really isn’t a match in many, many cases.

Garth Sundem   05:23

That’s really good point. You know, it’s funny, I can almost have imagined in the title of this podcast, how to identify the right scientific experts. But you know, I’m glad that that’s not in the title, because we’re going way past that. So okay, it used to be the people who are loudest scientifically you go to PubMed, and I don’t know, you get number of citations. And Doctor, I don’t know what, but um, so if that’s not all we’re listening to, what else are we listening to?

Lance Hill   05:56

So, they’re so and that’s kind of where one of the, there’s two big innovations, I guess, technologically that have happened. And there’s a number of companies, including ours, that are really investing in these two innovations. So, one is expanding and widening that dataset of the places you can go to understand who matters when. And then second is applying network analytics on top of what would be otherwise a list of people to understand who actually interacts with who on what topics, what frequency, in what ways. So that’ll let you understand a different set of things as well, you put those two things together, and you have something really, really powerful our internal data has shown that if you only are doing kind of KOL ranking via traditional methods, depending on your therapeutic area, it does differ by therapeutic area, somewhere between 20 and 60% of the people that would come up and traditional ranking are usually not the best people for various types of engagements, there is, there is a pretty wide difference in some therapeutic areas. So, on the data side, what that really is, is not just the scientific piece, which still matters, but also integrating into that single view disambiguated, you know, Dr. Lance Hill is the same as Dr. L Hill, is the same as Dr. L H, or just, you know, whatever the different ways that you might be identified in different places, but also integrating social, digital opinion leaders, digital conversations, so much of science, as an example is happening socially, but also so much is people talking about difficulties in access, treatment, etc. So automatically integrating everything happening in the social realm into that single view of the person, treatment data, real world data, which, you know, really historically was more a little bit the purview of commercial to help them kind of understand, you know, what pills are moving and what regions and that sort of thing. From a medical point of view, there’s now a lot of information available, that is correctly set up for medical with kind of the regulations that apply there to help you understand referral patterns, patient journey, misdiagnoses, comorbidities, things that help you identify where your science is falling down, or things they help you identify a different set of stakeholders who are involved on the treatment side, that may be really important for you to be interacting with. And then finally, transparency. You know, over 30 countries publish some sort of transparency database that says, you know, Dr. Lance, working with my competitors or not, and really understanding the competitive landscape, and even the messaging analytics landscape, frankly, what scientific voice are my competitors, putting out there? You know, all of that data can come down and touch back to people. And that I think a lot of companies, certainly Within3, have done a lot to bring that data together very, very simply. And it makes it really you’re, you’re almost operating with one quarter of the necessary information if you’re only working off the kind of who’s loudest, scientifically.

Garth Sundem   09:01

Okay, well, let’s dig in, Sam. So, we moved a little bit there from individuals to networks. So why is it important to know how all these people relate? What is the power of a network in comparison with just the power of KOL ranking individuals?

Sam Veeck   09:19

Yeah, that’s really where the power comes in. Because if you think about a typical disease community, there could be 1000s of people in that disease community that have some sort of work when we talk about volume of work, so they’ve published something or they’re treaters, or somehow they have an impact in that community. But when you look at all of the data, there could be hundreds of 1000s of different connection points between those 1000s of people. And so, the network mapping is essential to be able to take those hundreds of 1000s of connections and data points and make sense of it in a scalable manner. And so, what it really does is it maps all of the different ways in which people are connected to each other across those For, you know, categories of data, so not only is an individual potentially publishing or working with someone else, but they also surely connected to another individual who has a connection to someone who would be a great impact to the work that you’re doing. And so, it starts to kind of uncover this network of individuals and insights that you could otherwise you would never have, if it was just a plain, you know, it’s just one level of connection, and you’re seeing that, you know, Sam Veeck, works with Lance Hill, that’s fine. But is there a next layer of connection that is really going to drive this valuable impact for the work that you’re doing? And so it’s taking all of those connections, and there’s a lot of algorithms and it’s been honed, you know, really over decades to be able to validate that these connections and the strength of connection can really impact the work and decisions that you’re making by talking to the right people that you can glean from the impact of that social network analytics.

Lance Hill   10:59

And historically, there, Garth, the, the way a lot of kind of, quote unquote networks, or network Analytics was done in the market is to say, okay, so I published something Garth, your co-author, or connected. So let me look at the PubMed data and try to figure out who’s offering with who, yep. And from that, you kind of say, oh, that’s, that’s the network. But that’s only one way that people work together. It’s who’s in the same, the same centers, who’s, who’s seeing the same sorts of patients who’s working on the same sorts of treatment guidelines, there’s a whole variety of them, there’s over 12 different ways, just you can easily look at different types of connections between HCPs, for instance. And so the trick is to have technologies that can bring all those different ways to gather and weigh them appropriately. So that you’re getting a more holistic view, the example I would give is imagine, you know, logging into Facebook. And instead of being able to say, who’s connected with who you kind of get a directory, and it would say, oh, Garth, is Garth is a nine and Sam’s a six and like you have a ranking of somehow social activity, but you don’t have any sort of, there’s Garth, no, Sam Veeck, I’m not quite sure. They just both happen to post a lot on Facebook. And that’s kind of the difference between maybe we’re the technology in the industry was two or three years ago, to where it is today, where those more sophisticated network that are applications that we’ve been used for the last decade, on the social media platforms, the algorithms behind them is what I’m talking about. Not obviously, the, you know that here’s a picture of my dog park, but the actual algorithms, those are being applied to life science, now into this to this issue. And that’s really, again, really surfacing up a much finer tooth comb on who matters in a specific context, because you now have context in that map. It’s not just a generic map based on who publishes with who.

Sam Veeck   12:57

Yeah, and to me that it’s like precision targeting, right, so you can look at it and you might have your traditional list. But when you’re looking at it from the network Analytics view, you can say, for this specific question that I need to have answered today, or for the specific goal of what I’m trying to do, who are exactly the right people that I should be talking to, to have the greatest impact. Because you can be talking to someone and they can have impact, so but it doesn’t mean they’re going to have the most significant impact that you can truly have. So.

Lance Hill   13:25

If you were to zoom out for a second, just to kind of think about this way. So, imagine you’re, you know, you’re thinking about your medical strategy, and you’ve got your plan of who you should be interacting with, you know, ASCO is coming up, you’re in oncology, you’re kind of putting your plans together matters. And I imagine you’re using your normal, who do we know who we known for a long time. And imagine you’re 20% incorrect, one out of five of the people that you’re going to be talking to, aren’t really the right people. And imagine your competitor is only 5%. Incorrect. That’s a material difference in the effectiveness of your medical organization compared to a competitor. So, it really does. It’s not just theoretical, it really makes a huge difference in the efficacy and ultimately the business success of the activities and medicals involved with to have the latest and greatest and always updating view of who matters for specific context within their disease community.

Garth Sundem   14:22

And who matters. So, it’s not just somehow mapping all these connections and seeing that, you know, this person is connected to those three people and this person is connected to those four people. But you know, eventually the goal of Medical Affairs is not just to know the network but to influence the network. Can we, can we know who you know who to call first to actually affect? I don’t know what the opinion of the network or the or the knowledge of the network? Do we know how to affect the network?

Lance Hill   14:56

What you can see easily through a network lens, you can see, who are the people at the center of the network, who are the people at the edges of who are the people that are connected very, very broadly. And a network is, it’s more set up, it’s not like a big circle. And as people in the business people on the outside, it’s more complex than that. So, there might be someone who’s very much in the center of a network between the US and Japan. And that market, this is a position, for example, that is heavily involved there. And here, may not even be viewed as a top KOL in Japan. But if your goal is to look at kind of bridging a global divide is a very critical communicating between the two regions, as an example, Japan, the US or something like that. So you can actually see in the shape of the network, who are the people who are the connectors, and who are the people that really information follows through. And if you’re adding that into things like social listening, you’re also integrating with that real time if they’re, if they’re active on social, or they’re listening to other folks who are active on social what the opinions are to that for your question. So you can you can use this information to start building those views. And then, and then, you know, again, if you’re in, for example, the US you combine that with treatment data, you can also begin to see kind of who’s seeing which regions, or which centers are seeing certain types of patients that matter. And so, I can even understand, like, I need to have a lot of influence here, because this, this part of the region is really, really active in this particular disease state. So, there’s a lot of information you can find a about who would you need to know, to affect the most change? Which is question number one? And then if you know them, what do you what do you know about them that can help you have a really productive set of conversations with them to achieve, you know, have them understand your scientific narrative and begin to adapt? You know, they’re thinking perhaps, along the lines of the data and evidence that you’re presenting to them?

Garth Sundem   17:00

You know, you can say, oh, go ahead, Sam. Sorry.

Sam Veeck   17:02

No, Just one quick point to build off of that and allowed by the technology nowadays is because of the data and the network analytics applied on top of it, and being able to see the connections and, and everything that Lance was just talking about, you can quantify the reach that those individuals that you’re selecting really have within your, your disease community as well. So if you’re picking 15, people, you know, randomly off that list, you can see is it reaching, you know, 40% of the community or 60%, and how much through the first degree connections are those people are reaching, and it can help you get very targeted with these are the top 15 people to reach sometimes 80 90% of the community, just 15 people out of the 1000s of individuals, because of the way that they’re connected and the reach that they really have?

Garth Sundem   17:50

Well, it sounds like you would need to go to these networks with strategy driven questions, you know, to your point, you know, maybe you can find a connector that would allow you to expand into the Japan market, but you would have the strategy driven goal to expand into the Japan market. So is the first step in expert identification. To decide from a strategy-based perspective. What questions you in what people you want to find in that network?

Lance Hill   18:24

Today, yes, for several years ago, it kind of didn’t matter. Because whatever question you had, your answer was, who publishes the most write it, but in today’s world, that’s kind of the power of it. And that’s the power of some of the technology platforms that different companies have invested in, is the ability to get very granular with those questions. So older, older technology would say, here’s a database of HCP profiles as an example, and we have 500,000 More profiles than the next vendor or whatever it was all about kind of the gathering, the profile was kind of at the center of it, what you’re talking about now, Garth, is really that the why you did it in the first place. So that when you have specific questions, like I want to understand in the context of treatment, guideline formation, you know, while I maybe can’t access those working on a treatment guidelines directly, I want to understand the world they’re living in more directly so I can get a sense of what matters there. Or on the flip side, I want to I want to be talking to sets I want to be talking to examples of positions that are most likely to refer patients that I care about or diagnose patients that I care about then than others and get their view of the world versus maybe the general population. Those specific sets of questions are just they become just as easy to answer. Then who speaks the most at ASCO coming back to that example? In today’s world, and that allows a kind of intellectually curious and smart medical team to really maneuver very, very well and very, very nimble in the market.

Garth Sundem   20:05

So, if I want to know X, Y, Z, or if I want to have XYZ type of influence, you can look into a network, not just from publications, but from all these data sources and know how to answer that question or have that influence. Like, that’s the goal. That’s the strategy draftable from Medical Affairs teams.

Lance Hill   20:29

Yeah, ultimately, ultimately, it is it’s two things. It’s the influence. And it’s also who has the right voice of the customer across to make the best decisions. And those are, it’s really bi-directional, right? So, there’s the field medical, get them get the message out there. But then there’s also the, let’s make sure as we’re forming our strategy, that we’re doing it in the right way. And I think this these sorts of technologies, all this data now that’s available, it’s integrated and built more for medical than just commercial, which is really critical. And then second, is the fact that you have these network analytics technologies that are becoming more robust every day. As you know, as technology companies invest in this space, you really can drive that and you move from having to worry about, where’s the data? Is it clean? Where did I get it? What does it all mean? I need a bunch of data analysts to figure this out. That takes too long, I’ll just default back to who I know, just something that is much more answer driven. And you can just focus on one of my business questions and get those answers versus one of my business questions. Let me call the analyst group and eight weeks from now, they’ll have run a bunch of you know, data warehousing analysis for me to come up with something.

Garth Sundem   21:43

So, Sam, it’s not just who we should be talking to, but who we should be listening to?

Sam Veeck   21:48

Yeah, exactly. And, you know, to the points we’ve been making, it’s the technology needs to be both contextualize as well as visualized. So, through all the context points and everything else, it visualizes not only the people you should be talking to, but listening to, and wherever those questions are. And wherever you are being able to get those answers from the context. That is really visualized through technology. So I think sometimes when we talk about these maps and social networks, like it feels so ambiguous and vague, but really, the answers can be gleaned through really good visualization platforms that can surface a map to the answer versus just lots and lots of data and the context behind it.

Garth Sundem   22:34

It’s like one of those 3D pictures, maybe what are they called, stereoscopic? Where you’ve got those two things, and you blur your eyes, and they come together, all this 3D thing. So, the technology allows us to look at these squiggly lines, and actually see a fully rendered 3D picture of the thing that you’re of the thing that you’re…

Lance Hill   22:53

And you’re exactly right. And in fact, you can actually see 3D renderings of the actual network. And many of the technologies they render them that way. So, you can actually, you know, look around and say, Who’s this over here? Who seems to be this person between these two large blocks in the network? It’s actually it’s, if you are a data geek, and you dig that it’s actually pretty interesting. But yeah, you’re exactly right. The technology is advanced so much and, and a lot of R&D is going into it. So, it’s not even where it is today is not where it’s gonna be triggers. Now, there’s a lot of companies really trying to make this a lot easier for medical organizations.

Garth Sundem   23:27

So, I dig it, and I’d like to see it. So, let’s leave it there for today. And we will all hopefully have the chance to look at some of these 3d renderings of complex networks. So, thanks, Lance, and Sam. 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”.