For all its amazing capabilities, technology is still a tool in need of humans to make it work. In medical affairs, advanced technology like artificial intelligence isn’t meant to replace people – and in fact, it cannot. What is the future of technology for medical affairs?
At the Reuters Pharma event in Nice, France, Within3 CEO Lance Hill discussed how technology is enabling medical affairs teams to work more effectively and become organizational leaders by using technology – specifically, four core technologies that are changing the way teams reveal insights when faced with an ever-growing mountain of data from multiple sources.
“I’m very passionate about the fusion of people and technology, and how technology allows people to do things better and more effectively.” – Lance Hill, CEO, Within3
Listen to the talk, view the slides, or scroll down to read the transcript.
Event transcript: Technologies to help unlock the power of insights and gain strategic ground
I’d like to introduce to the stage Lance Hill, who’s the CEO of Within3, who are global sponsors of the event, too. So make sure to introduce yourself at some point and go and say hello at their stand. Nice to meet you, Lance.
Lance Hill, Within3
Nice to meet you. All right, wonderful. Well, I’m thrilled to be here. Hopefully, everyone had a nice lunch and is settling in a little bit and hopefully not falling asleep yet. I’ll try to keep you entertained for the next few minutes as best I can. So my name is Lance Hill. I’m the CEO of Within3. And in my heart, what I am is a technologist. I’m very, very passionate about the fusion of people and technology and how technology can allow people to do things better and more effectively. And so today, what I’m going to talk about is insights management and the role of medical affairs as a leader in this space. And then some of the technologies that over the last couple of years have come onto the marketplace to help medical affairs organizations operate at a level of operational excellence that was just not possible years in the past.
So let’s jump in. So there’s the old adage that he who has the voice of the customer is king in a business. In life sciences, medical affairs is uniquely positioned to have the voice of the customer more than any other organization. The amount of interaction that we can have with HCPs and other stakeholders and disease community within a disease community, the depth of the conversations that we can have very, very different than R&D, very, very different than commercial. And so, really a primary value that medical affairs brings to any organization is bringing real-world insights, and real-world science back into the organization to either influence drug development, influence commercial strategy, or both. And when you think about where the sources of these insights that come from field force, medical information, virtual advisory board, medical congresses, there is a whole host of different venues, data, et cetera that is coming in that really needs to come together to have any sort of structured medical strategy, let alone be able to share that within other parts of the organization.
And all that information, all that data can be very, very difficult to gather, to harness effectively, to make sense of. And all of that is what I call the insight gap, this gap between all the sources of data that are coming into a medical affairs organization and the ability to make sense of it and disseminate it. And so with Reuters, last year we did a survey and asked medical affairs executives what are some of their largest problems regarding gathering insights, bringing them in, disseminating them, and forming strategy. And one of the ones that bubbled to the top was this one. Almost half said that being able to share insights across the organization from medical affairs was a challenge for them for a variety of reasons. And I’m sure many folks in the audience have experienced some of those challenges and reasons themselves.
And so that got me thinking a little bit about that 42% – coincidentally, about 40% of drugs that launch do not meet their targets. That’s probably a correlation, not necessarily a causal factor, but an interesting corollary. And so it got me thinking about 42%. If 42% of the time, we’re having challenges, sharing insights across the organization, what are some of the things that could be happening? So we could be in a scenario where we think our strategy is in good shape, our scientific narrative is out into the field and things are moving well. But in reality, we could have a situation where we didn’t see that there’s danger ahead because we couldn’t manage, gather, manage and disseminate those insights very, very quickly. Or maybe we’re in a situation where we’re talking to the same experts over and over again, and they’re telling us everything is great.
We love what you’re doing, we think everything you’re doing is correct. And in the background, there is a whole lot of noise in the marketplace, competing scientific narratives unmet needs that are, we’re not gathering because we’re not able to reach a wide enough net and bring that information back. Or people are sharing things with us that were unexpected, but we didn’t really have a way to capture that and disseminate that. Or maybe we have our strategy and we think we are really in good shape and we’re executing well. But you zoom out a little bit and maybe the pandemic, some people can relate to this may or may not have been me on more than one occasion during the pandemic, but maybe our execution is not as strong as we thought it was. And so this lack of visibility and this lack of sharing can really impact how effective a medical affairs organization can be. And again, one of the primary values of a medical affairs organization is the ability to really bring that voice of the customer, that voice, that real-world voice, real-world evidence, and science to the rest of the organization.
So the modern medical affairs team is a wash in data points and interactions and regions and across the whole life cycle. And it makes it extraordinarily difficult to manage through all of that cycle. And so what happens typically is organizations historically have looked at each of the tactics along the way of insights management as its own little process. So an advisory board is its own kind of self-contained process. And field engagement is its own kind of self-contained process. And then pulling all those things together, let alone harmonizing those across an enterprise can be really, really difficult. And so teams actually using spreadsheets and manual reports and trying to pull things out of CRM systems that oftentimes weren’t built for medical in the first place. And a variety of other kinds of things that come into this process. And so it obviously makes it pretty difficult.
So what we need to get to is this ability to have a single process whereby all the information’s coming in, it’s being rationalized and harmonized and turned into actionable outputs that we can then use to adjust our strategy and form our counterparts. And then the cycle continues together over and over again. And that’s really what insights management is. It’s this overarching idea that insights management all the way through as a single process and what are some of the ways we can make that process more effective and gain a competitive advantage ultimately, and bring therapies to market faster, so patients have what they need when they need it. So what I wanted to do is talk a little bit about some of the technologies that are influencing the insights management space. So especially over the last couple of years and with the pandemic and not having a lot of events like this, it’s been hard to keep up a little bit with some of the innovation. Still, there’s a lot of R&D dollars in the technology industry really trying to help solve this problem.
How do we make medical affairs excel at identifying, gathering, and communicating insights? And so I want to talk about some of, at a high level, some of the technologies that as you talk to different companies you may hear about and they all have to do with insights management in one way or another. So I’m just going to talk about four. There are others that are also really important to understand. But the first one is I’m going to talk about is advances in the disease community, understanding who we should be talking to and what context to get the insights that we need. So historically, the way things work, most companies have a program where you’re identifying KOLs or external experts that you decide, here’s who we need to have relationships with, they’re going to give us the best advice. Or perhaps we think that they’re the ones who say, publish the most or speak the most, that congress is like this.
And so they’re the ones who are important. And so kind of the legacy way to do things is to take a bibliometric approach where you’d say, here’s all the physicians, let’s say within my disease community, within my disease area. And I’m going to look at things like the number of publications membership on committees, and I’m going to rank them one through 11. But really, when you think about it, there’s something called the Invisible College. And what that is, if you’re a physician, you’re in medical school, how you’re learning and how your opinions are changing is very top-down instructor to you. But after you go out and practice, that changes how information flows to you and how information that you have flows to other people really shows how a scientific narrative can influence a larger community. And so what’s happened over the last two or three years is really the application of network analytics.
And so, in this example, these were the top 11. Here’s a set of other people who didn’t make my top 11. And maybe for budget reasons, I can only interact with the top 11 right now within my program. But when I put them into a network, and the networks are always specific by context, what is it that I’m interested in understanding? Let’s say it’s how science moves across a network of HCPs. I begin to see who’s connected with who. And what I notice is that while not ranked high, some folks have very key positions in the network in how they influence. It might be that this person here is really a gateway. So I can see that my top five folks who publish the most are all maybe associated within the same kind of research circle, probably reinforcing each other’s ideas but not necessarily influencing the broader whole, where maybe this person is a gateway to a different region, maybe this person over here in the far right is very, very active online digitally.
And so really amplifying a lot of what’s happening and what their opinions is and has an outsize following relative to what they’re maybe publishing scientifically. Or maybe there’s a person who is a gateway to an underserved community that wouldn’t be obvious if you’re not applying the algorithms that work in network analytics. And these are a lot of the same algorithms that Facebook and LinkedIn and these consumer networking companies have pioneered for 15 years now really being applied around this idea of HCPs and influence in the invisible college. So network analytics is a term that you’ll probably hear a lot as you look at different companies playing in this space. Stakeholder engagement, the advances there is another really powerful technology. So if you look at the ways that we engage, whether it’s one on one or in groups, your choices are really real-time live like we’re doing right now, real-time virtual engagement, like my friend with the boxer shorts sitting in front of a zoom screen or an MS team screen.
And then an anytime engagement, asynchronous engagement. So this technology on the far right is one that a lot of organizations are adopting at a very, very rapid pace to supplement what they’re doing in the left two boxes. And asynchronous engagement is more like an online university style, which is really where that technology was pioneered, which is depending on the context of what you’re doing, you’re setting up an environment that’s maybe open all the time, maybe open for a couple of weeks. And that environment is built with the workflows that you need to execute a certain type, let’s say, of insight gathering or pubs development or et cetera. And so in these sorts of platforms, instead of saying we’re going to have a virtual advisory board and we’re going to invite 10 physicians into a room or into a meeting and we’re going to try to get through all our agenda in four hours and ask all the right follow-ups and then kind of deal with all the output in this scenario, instead there is an environment that’s open, the materials are there the physicians can come and interact with each other.
A really popular example of this style of communication is around excellence in medical congresses. So there’s a workshop tomorrow on that topic that will go deeper there, but how do you get the most out of a medical congress, and how do you use the sort technology to gather insights and also to connect people who can’t attend to those who can’t? So these sorts of asynchronous platforms open up a whole horizon of value add in terms of how we engage. So technology one was who we engaged. Technology two was an example of how we can engage differently. The third technology I want to talk about is insights trending and reporting. So AI is a buzzword. I was popping over to some of the other sessions, and everyone’s talked about ai, ai, ai. It’s a very, very popular buzzword. You can think of AI hopefully more simply like this.
So AI is the overarching term for building a smart machine that is capable of doing tasks that usually a human would think about underneath the overarching AI. Machine learning. Machine learning is the idea that you can have the computer automatically learn what’s right or wrong by looking at enough data. So it’s a subset of overall AI. And a subset of that is deep learning, which is can we teach a machine to think a human the ultimate – and never to replace a human, by the way – only to maybe make a human’s job a bit easier. So really, even the idea of AI that the term, you should almost think of it more as like intelligence augmentation or something than artificial intelligence because it doesn’t replace. So a style of deep learning is natural language processing. And natural language processing is very much like when you have sir on your apple phone or you’re talking into typing something into a search bar and it’s understanding what you’re trying to say.
It’s the idea of taking normal human topics and breaking them down into things that are easy to categorize and work with. And so in this particular case, in the insights world, a lot of the insights that come in are unstructured text. I met with Dr. A, and Dr. A said this, and I’ve recorded that and I’ve typed my notes, and here’s what they are. And if you think about a situation where you have that happening by the hundreds or thousands, it can be very, very difficult to organize that together. So what AI does the insight space it takes something like this and says, is this topic, is this positive? It’s well tolerated, that sounds good. Is it a negative sentiment? It’s scary, that’s not as good. These technologies now understand a full battery of life sciences terms. So broader than just kind of generic healthcare AI they’re very, very centric.
They know what an adverse event means, they know what sentiment means, they know what adherence means, and they know the terms that help us. And what it lets you do is immediately organize things in real-time as they’re coming in to help you say, Show me all the negative things that have been being are happening right now about my particular strategy or my particular concept. And the last one I’ll share is this insights management platform. Generally, these are sets of technologies that bring all these capabilities together to allow you kind of one platform to manage that insights management process end to end, which gives you a tremendous accelerating factor in really supporting the investments and training other things that you’ll be making with any good team. So in conclusion, while insights management may seem scary, here’s our shock shark fin again. And sometimes overwhelming. It turns out that maybe it’s not so scary after all.
And maybe we can go ahead and have a nice little journey in the pond and not be so scared about insights management. There is an e-book if you scan this QR code that will get you more information on some of the technologies that I shared today. Or you can, here’s my shameless plug, you can head to our booth and see a demo of any of these technologies and other ones I didn’t talk about within a direct platform. But I highly encourage everyone to really get educated on these concepts. This is where the industry is going and the organizations that are able to take advantage are really going to be able to move quickly. So with that, thank you very much.