5 Essential Marketing Moves that Drive Early Medical Intervention

Hello, and thank you for attending today's webinar, Five Essential Marketing Moves That Drive Early Intervention, presented by OptimizeRx and Fierce Pharma. I'm Andrea, and I'll be your moderator for today. Before we begin, just a few quick housekeeping items. To learn more about our speakers, please visit the speaker bio window. If you accidentally close a window, you can reopen it by clicking its name in the top navigation bar. Additional resources can be found in the handouts window. This webinar is being recorded and will be available on demand within twenty four hours. And finally, we'll host a Q and A session at the end of the webinar. Feel free to submit your questions at any time using the submit questions window. And now I have the pleasure of introducing our speakers. Joining us today is Michael Paladino, SVP of Client Strategy at OptimizeRx and Maria Cipicchio, SVP of Strategic Market Intelligence at OptimizeRx. All right. We're ready to start. Michael, over to you. Great. Thank you for the introduction, Andrea, and thank you, everybody, for joining us today. We can go to the next slide. We got a little intro of Maria and I. We work at OptimizeRx. We have spent the past twenty some years in the life science industry. Maria has an in-depth background in marketing and bringing drugs to market. I worked as a clinician for a number of years in hospital practice. I then went to medical affairs within the pharmaceutical industry before coming here. And today we're going to talk about five strategies. And the nice part of these five strategies are many of us on this call have access to this information. It's finding the right audience. It's having the data, the intelligence, the timeliness of education, and then finally, measurement. So we can go to the next slide where we talk about the why. Okay? So here is the why. This is what I consider, yeah, no kidding, Mike, part of the presentation. Why do we do what we do? Why do we want to intervene early? And then the majority of this talk will be Marie and I kind of going back and forth around these topics of data and intelligence and timeliness of marketing. Next slide, please. So because I'm a clinical science nerd, or a research nerd, I feel the need to present some of the information of why early intervention matters for patients. And cancer in this therapeutic space inevitably affects so many people. Maybe some of us on the call, maybe our family members. So I wanted to look at a recent publication, or a robust publication. So here's just some information from the British Medical Journal, and it is a meta analysis of clinical trials. So it's not one clinical trial. It's thirty plus clinical trials. The cohort is over one million patients, spanning seven types of cancers. We probably are familiar with this. Again, may have been impacted with this in our lives or our families' lives bladder, breast, colon, rectum, lung, cervix, head and neck. What these investigators wanted to look at is if there was a delay in treatment or diagnosis, what type of impact did that have on the population? And if we show now the results from this study, you'll see here that a four week delay led to roughly a ten percent increased risk of death. This is profound. This is one month time frame in delay. And for those of us who have experienced this, or family members that have experienced this, it's not hard to have a one month delay, right? And I'm giving an example of cancer here, but this delay can happen in many therapeutic spaces, right? Cardiovascular, metabolic. Maybe the mortality risk is not as high. But this is just a great snapshot of saying even a one month delay could have a significant impact on mortality. And this impact in this particular trial is across surgery, systemic medical therapy, and radiotherapy. So this is why it matters. This is why we want to intervene early and help patients get on therapy early. Next slide, please. Not only does it matter for patients, it matters for providers, too. And this is a really nice snapshot of a quote from Doctor. Nicholson. She's an OBGYN, and she works at the Preventative Task Force here in the United States. And that particular group is tasked with prevention of adverse events, improving care by preventative medicine. And I really like what she says here, because it's October and it's Breast Cancer Awareness Month, but I think these numbers are pretty profound. And what she says is, by starting to screen all women at age forty, we can save nearly twenty percent more lives from breast cancer overall. This new approach has even greater potential benefit for Black women who are much more likely to die from breast cancer. And what Doctor. Nicholson is referring to is, about a year ago, there was a change in guidance by this task force to shift the age from fifty to forty for breast cancer screening to align with other oncology organizations. And you can see by that shift in screening how many more women we can improve their lives, and particularly in this black population who has a higher risk of mortality from breast cancer. So it matters. It matters for patients. We want to help providers be aware of the potential of early screening and diagnosis, so that the burden on the health care system and the outcome of their patients is improved. So that will kind of conclude the why we do what we do part of my presentation. Next slide. All right. Thanks, Mike, for all the great context on why early intervention is so important. Now we can dive into how marketers can support those health outcomes that early intervention can drive. We've probably got a lot of folks on the line right now thinking, hey, yeah, Mike, this is why I'm passionate about the work I do. But sometimes it's really hard, particularly for marketers, to see that tangible connection to how marketing is really making an impact. And for us, it starts by looking at best practices in a different light. Like, where can those best practices be adapted for early intervention? And what are the marketing outcomes that drive those better health outcomes that we're so anxious to get to? So a lot of this stems to thinking about different ways to think about right person, right time, right place to deliver that outreach that makes a connection. So today, we're going to talk a lot about audience segmentation and targeting so you can find relevant people at the earliest possible times. We'll talk about practical ways to coordinate targeting between HCP and DTC audiences in ways that drive earlier conversions. We'll also look at how to incorporate health data to inform channel placement decisions across the board and then leveraging some brand specific KPIs to optimize your marketing activity as you go through the journey. So Mike, why don't we start with the opportunities that marketers have to reach their relevant patient populations at the earliest possible point? And let's advance the slide. Great. So this is the section of finding the right audience. But before we find the right audience, I want to talk about this patient journey, or the diagnosis gauntlet, in the next slide. And just a real quick side note, I'm glad Maria mentioned, like a lot of us in the marketing space and media space often forget of the end individual for the banner message, for the commercial, whatever it may be. And I will say that I'm super passionate about using clinical medical education and bridging the gap here with immediate people and outcomes. So that's really kind of why we're here today. How can we improve outcomes? And before we actually find an audience that we want to help, we've got to understand the journey, right? And there's a lot of imagery on this slide. And that's why I call it the diagnosis gauntlet, because it is a very confusing journey quite often for patients, and at sometimes even for HCPs. Why I like to share this example, because this is actually a personal journey. My mother, her name is Eileen, she was recently diagnosed with a form of lymphoma, okay? And as you see along her journey, you see PCP visits, you see clinical testing, you see more testing, you see specialty visits, and then you see the potential of a diagnosis, okay? So this snake diagram, from my mother's experience, was roughly a year to get to her diagnosis of lymphoma, all right? And why we're here today is to talk about, well, we can identify people kind of at the end of this snake journey, right? But we want to help people like Eileen, and maybe your mother or father or cousin or child, to help identify these folks earlier in the snake journey. So we'll move to the next slide as an example of how audiences have historically been built, right, and how can we improve them. So historically, what happens is, and it's the colored part of this snake diagram now, we'll look at claims data. And we'll say, Show me the prescription, or show me the diagnosis. And that's okay. But that is at the end of this long journey, right? So for instance, if that was a strategy to help identify folks like my mother, well, that would have been a year later. But what we're trying to do here today, and what we're trying to leverage with all of our knowledge on this call is, how can we take that one year diagnosis, and how can we shrink it? How can we find the patient and educate either the patient or the HCP within months, right? So this is a snapshot of maybe what's historically been done that's colored here, medicine and diagnosis. Let's move to the next slide of where we want to be. So how do we build now an early audience? An example would be, again, kind of going back to my mother's journey, is we can understand at her first PCP visit that she had a number of CBCs run and INR tests run. One of the INR tests, which is a bleeding time but my mother's not on a blood thinner. Her bleeding time was elevated, right? And this was at an initial PCP office visit because she had bruising. We can identify that lab order. They couldn't figure out what it was. A few weeks later she has another INR performed at a PCP office. Okay? It's still elevated. These are signals early in the journey that something may be happening. As she went along her snake journey, she goes to a hematologist. They order a white blood cell count, and they order a morphology. We can see this by claims like CPT codes. She also has a bone biopsy. Again, another procedural code that helps diagnose lymphoma. And so I share with you these examples, because these are all claims data and information early in a patient journey that may be diagnosed with lymphoma or some other disease state, that inform us that this population exists, and where they exist, and the HTPs potentially treating them. So that is a way that we could potentially build and identify an early audience. Now I'm sharing the example of my mother and lymphoma. This is across all disease states, right? This is with cardiovascular disease. These are neurologic conditions, all right? There might be particular imaging tests, CT and MRI scans for Alzheimer's disease, to find patients early in the journey. Next slide, please. Mike, what would you say to those agency folks on the line that have a hard time identifying some of those early medical intervention points? Yeah. So that's a good segue or a good conversation point. A lot of people we work with, and maybe people in this room, we partner with agency and media people. And we also partner with direct marketers. Maybe they have different needs, right? Agencies quite often, because they have such an expertise in the media world, they may not have a complete understanding of patient or HCP journey of all of those things I just rattled off, right? Lab tests, codes, maybe my mother was on rituximab, one of these medications, the infusion for lymphoma. Folks like us in this space who can offer clinical and also marketing experience, we can help build that journey based off of data we have, and also the experience we have in this space. So that's quite often how we can assist and help agency folks that really have expertise in media, but maybe not so much in these clinical journeys. And what about pharma marketers who maybe don't have that robust journey to work with? Mean, agency partners are leaning, I think, a bit on the pharma partners too. Is there anything different for the direct marketers that you would say? Yeah, yeah, and I came from that space. Although I was in medical affairs, my counterparts were marketers. What I found was, they had a very strong knowledge, because they live and breathe this, every day, maybe one disease state or one brand. So they often had the overall knowledge of this type of journey and maybe where they wanted to intervene. But they didn't always have the bandwidth to dive into this level. The claims data, the imaging that would the CPT imaging, the CPT lab orders, a J code for administering an infusion, right? That's where folks like us come in. So we're completely partnering and supporting with the marketing folks. But I never want to take away what they do for a living, because they certainly live and breathe their brand that they support. We're just kind of there for that next level of knowledge. All right. Good. Let's go on and talk a little bit more about I'm big on take home points. All right? All right, that sounds Yeah, the take home point of me rambling here is, we can use data and knowledge to find patients earlier in the journey. And when we do that, the likelihood of a better outcome will ensue. That's my take home message from kind of phase one of the conversation. Okay. Let's dive into a little bit more of that data and how we can use the patient, as you described as sort of the North Star, to create a shared data infrastructure for the entire marketing ecosystem. Let's go to the next slide, please. So we know patients really, even though they are the North Star, are only half the picture in any life sciences marketing scenario. So for those indications where early intervention is key, the HCP landscape can almost be more complex than the patient landscape because you're looking at a lot of different kinds of profiles and a lot of usually a lot of, as you mentioned in your journey, different steps of specialists and PCPs. And every other day, we're really seeing companies in our industry releasing information about the benefits of audience alignment, patients to HCPs, but not a lot of practical direction on how marketers can actually achieve that or measure it. And when you boil it down, you really have to, as a marketer, align two very disparate audiences the channels that they're consuming media on and then also the timing of the outreach to support that care conversation that you're really trying to drive with your marketing. And there's so much data involved in those decisions that it's impossible to get there without a single data infrastructure tailored for your brand's marketing use cases. And also AI, that's not what this is about. But AI helps a ton when you have that much data that you have to sort through and make decisions based off of. But as I mentioned, the shared data infrastructure really starts with that patient. In the case of early intervention, that patient definition is more likely to be a medically specific consumer profile, the way Mike described it, because you may not have a diagnosis to work off of at this point, right? And so you're using medical and clinical data as markers. So the goal is to connect every marketing decision that's made back to the need of the patient. And one detailed patient definition can provide everything you need to build a deterministic ecosystem for your marketing. Next slide, please. So for us to talk about this in a tangible way, I built out a hypothetical use case around early intervention for Alzheimer's disease so that we have kind of a practical example. This is not a case study. We don't have any affiliation with these brands. I just Alzheimer's is a really good early intervention case because there are currently two disease modifying therapies that can be used prior to diagnosis and at the earliest possible onset of symptoms. Those two treatments are Kisumla by Lilly and Leukembi by Biogen ISA. Now, according to public sources, about three percent to five percent of the mild cognitive impairment and dementia populations may be eligible for these treatments, and yet less than one percent of those patients are actually taking them. And there's lots of reasons for this. A lot of them are centered around access and availability. But there's a big reason for it that marketing is really a perfect solution for, which is lack of testing. These drugs require biomarker testing before they are able to be prescribed. And so that's something that we can obviously see in the data. So there's several medical flags that can be used to build that initial medically driven consumer profile. Those would be cognitive screening tests, standards of care for MCI and dementia, and then recent changes in physician visit schedules, either lapsing or more frequent visits to PCPs. A lot of companies, when they're thinking about targeting, will use tokenized data seeds, like a one patient profile, and then add noise for scale if they're going out to find those patients in an omnichannel fashion. But when we do it, we have a bit of an extra layer of privacy built in, which also happens to work really nicely for Alzheimer's disease, which is we actually map the prevalence of that profile geographically. And we target against that instead of targeting against the actual health data. And this way, we can pinpoint hotspots and prioritize outreach to the surrounding neighborhoods. And it's nice for Alzheimer's in particular and other early intervention cases because there's a better chance of capturing caregivers as well as patients. So there's a bit of an echo effect built right into that. And this same concept actually helps us to identify receive the outreach. So we have our medical markers. And for these Alzheimer's individuals, an extended care team will be at play, right? So you need some way to prioritize the HCPs, particularly early in the journey. And if you're using this shared data infrastructure, you can use that patient profile and the same medical markers to identify the HCPs, for example, who are conducting more screenings or who have the highest volume of patients who fit that profile. And this also gives you a way to think about your audience when AQ doesn't help much because AQ is obviously a very diagnosis based metric. When you are using the patient profile to drive and prioritize the HCPs, you can actually see how much of your doctor and patient population actually overlap. And so it gives you a little bit of an early indicator of some connection there. So now that we've got the consumers and the HCPs taken care of, you can layer in the channel and content preferences. You can use the same medically driven profile and conduct analytics with combined consumer and clinical data to look at the preferences of your actual population, which is in contrast, Mike, you were mentioning best practices today. Again, today, typically what people are doing is looking at survey data of the Alzheimer's population, for example, to make these types of decisions. And they're going out and they're refreshing that data. But you can actually take a look at the actual consumption habits of your population and use that to make some more informed decisions. So in this way, the clinical markers of potential brand candidates actually become the backbone of your marketing ecosystem, and you can shepherd their journey with your marketing. Mike, do you want to talk more about consumer preferences and Yeah. The There's my segue. So we can go to the next slide. Now is kind of the part of the conversation. We can find audiences, we can find the audiences with data, both from a DTC or a patient perspective, as well as an HCP perspective. Now we need to find out where is best to talk to them, right? Marketing budgets are finite, right? You want to spend the money wisely in the right places. So after what we just kind of discussed with you, it's now the time to say, all right, what information do we have to be efficient and very precise with where we want to target education? So we can go to the next slide. This next slide is some nice imagery, but it's actually founded in data. And when I was building the patient profile for someone with marginal zone lymphoma, particularly females over the age of seventy, we were very specific with that patient profile. We then said, with that specific patient profile, not just anybody diagnosed with Marginal Zone Lymphoma, but somebody seventy and older, female, because my mother was the case example, with this diagnosis, and with some rituximab therapy, what type of information consumer data could we get back so we can understand in which channels to educate people like Eileen? Okay, what channels do they favor? And this exercise was kind of interesting. This exercise was done blinded from me, although I know that my mother's habits very well, obviously. And they're fairly aligned. My mom spends a lot of time on Facebook. That's kind of her one social media source. She doesn't watch a ton of TV. When she does, she watches the news and crime documentaries, right? And so when I was kind of doing the clinical presentation and build on my mother's profile and getting that claims data, we had our consumer team building this out. And I said, Wow, okay, if we wanted to do a media campaign on folks like Eileen, well, seems pretty dead on, right? It's not going to be perfect, but it's very directional on what somebody that fits my mother's threshold really meets, and where she would potentially consume education. Great, next slide. So then let's talk about the providers, right? So Maria talked about the synchronization. And it's not just the patient, it's the ACP too. So when we want to talk to HCPs, they're consumers as well. And here's a nice snapshot. We took a rather broad list of hemochs and hematologists. And we said within our network of OptimizeRx, where can we talk to these folks? Right? And again, if we wanted to build a media campaign that's all encompassing of both patient and ACP, and kind of really focused on early intervention, we have this mix of reach. We have a really strong programmatic and social media reach. And then we have a point of care or EHR reach of roughly fifty nine percent, sixty percent, a bit lower than programmatic or social. But nonetheless, we have reached within the point of care. So if we were helping marketers, or if we were marketers, we would have to determine based on the brand strategy or the disease strategy, where do we want to spend our money? Do we want to heavy up and programmatic only and educate it from a DTC perspective? Or should we level it? Should we layer in a point of care marketing strategy? Great. So Mike, on that point of care, particularly on this slide, you've got sixty percent reach programmatic and social look like they're kind of slam dunks. How important is EHR in early intervention when we kind of think about it as the last stop before medication? We're talking about. Yeah, that Okay. And I think that the foundation of this question is this has been asked before, right? So much of point of care in EHR is thought the prescription of the HCP. They're writing their prescription, right? And the whole idea of this conversation is, well, how can we help way before the prescription, right? Earlier diagnosis. And I think the question is a little deeper than that, because as a former clinical pharmacist, and I still talk to my friends in practice now, any of these areas of media are not the holy grail of consuming in-depth knowledge, right? They are particular locations to trigger more research or more knowledge. So what I mean by that is, if I'm in the EHR and I'm seeing a particular patient, my background is in cardiovascular, and they have history of cancer, and they have history of a clotting disorder, and I am flagged on guideline updates to particular clotting disorder treatment, I go, Okay, once I see this patient, they're okay, let me go to UpToDate. UpToDate is an amazing resource for diagnosis, imaging, lab, medication therapy information. That's where I go to my deep dive, okay? So I rambled a bit, but the moral of the story is, is there's an opportunity in point of care EHR, even if we're not talking prescription, to trigger something in a clinician's mind, that they should be aware of what's going on with that patient and investigate further somewhere else with depth of knowledge. And I'm going to share, and as we kind of move through our presentation, I do have a really nice case example that is focused within the EHR actually for early diagnosis. So the kind of proof is in the pudding with this particular case example. Thank you. From an Alzheimer's perspective, I'm thinking about the use case I was using. But it's kind of a biomarker test that's early in the journey. So when you were practicing, how would you learn about new diagnostics to qualify patients, or new standards of care? Where do you prefer to go for those? Yeah, those are that is a requirement for clinicians to keep up to date, whether it be from CME, continual education, or whether it be, again, sources like UpToDate. I was on earlier today, and within UpToDate, I searched most recent guideline updates within the last six months. So it's kind of upon the clinician to proactively go and continue to educate themselves. But I kind of come back to the point of like, an awareness play. Sometimes there is a very nice awareness trigger in EHR, or social media programmatic to say, Oh, there was a guideline update for how to treat clotting disorders in patients with colorectal cancer. Let me go to UpToDate to see that what that is. So these are not the holy grail to get the depth of education, but they are wonderful places to trigger a clinician to go further into that information. Great. Okay, thank you. And next slide. Yep, so we've talked quite a bit now about some straightforward ways to develop and align audiences and prioritize channels. I think the true Holy Grail, of course, is that next best action ecosystem that you're trying to build. Let's go to the next slide to start to look at what that looks like in a patient journey. So for early intervention in particular, you heard Mike talking about identifying those early medical inflection points. So again, revisited the Alzheimer's use case because the question that we're really trying to answer with our marketing is, how do you convince somebody to go to the doctor? How do you convince them to get tested for something that might not be on their radar yet? Or it's on their radar, but maybe it's not the most pressing thing. And the timing of the outreach for these types of scenarios are especially critical so that the messaging isn't just dismissed, but instead it becomes really a valuable part of the care dialogue. And as you know, the goal of every marketing strategy is conversion. But when we're talking about early intervention, it's particularly important to identify what I'll call, let's say, the conversion pipeline, which that is otherwise known as the customer journey or the patient journey, which we talk about all the time. But we have the data available to us now to identify multiple conversion points along that journey, right? And to do it in real time and to actually have it be influential in our marketing mix. So for this Alzheimer's journey, there are three big inflection points in the it's really pre Alzheimer's journey at this point. For the drugs that we're talking about, Kasumla and Leukembi. There's the specialist referral. There's the diagnosis. And there's the biomarker testing. And each of these points is identifiable using claims data. And each of them require essentially a conversion or a decision to get to the point of even considering therapy. This is a really similar story for all early intervention use cases. And as marketers, I'm always encouraging our teams to say, use these facts to advocate for budget or to look at your measurement of marketing outcomes in a different way because overall these milestones are going to help you identify if your marketing is working, if you're meeting these mini conversions along the way. They'll also help personalize your messaging in the context of what the doctor and the patient are facing, which is why it will help to drive conversion. Let's move on to the next slide because the best practice here, right, is really matching that CTA, the really clear CTA, to the audience. And typically, the CTAs that we're seeing in pharma ads are, go to the doctor and ask about x, right? But on this slide, can kind of see you can vary those CTAs quite a bit when you understand the journey that the patient is on. You can see those CTAs and marketing outcomes arranged along the funnel. And I'd encourage you to think about, though, what happens as the conversion happens Because in light of particularly what we were talking about earlier, the audience profile of each group actually changes as you move down the funnel, right? So for example, at the top of the funnel, your patient really needs to wonder if they need specialty care. And that PCP at the top of the funnel isn't going to be ordering biomarker testing, which is that prerequisite for the two drugs that we're looking at. So when we work with clients, we handle this by predicting those milestones and updating our audiences against those predicted milestones so that as the audience mix kind of changes in terms of where they are, so will their messaging and the channels that we're trying to reach them on if it's pertinent, right? So if you're not able to kind of dynamically optimize that audience for conversion, a step toward it is still getting more accurate around those brand specific segments with your audience data. Either way, you have to be using fresh data because you can't achieve the level of personalization we're looking for in early intervention with an NPI list or even a canned consumer audience that was developed six months or a year ago because the people have obviously turned over since then. And so there has to really be some kind of refresh cadence built in. Mike, do you want to maybe chat through that case study? And before we move on, I love this slide because we talk a lot we've talked a lot about the audience from a patient and ACP perspective. You walked us through this synergy. And I can't highlight enough, because I was a clinical pharmacist, I was a patient in part of my life. The messaging is quite different, right? In your example here is the patient might not even be aware this therapy exists. So the message is around awareness. The specialist knows it exists. The specialist might be concerned about access and coverage, right? So it's not only like, are we in the right channel, like I mentioned earlier, are we sending the right message? Because odds are, if you're a specialist for Alzheimer's, you're well aware of safety efficacy. But maybe you think this patient is not commercially insured, and they can't get drug if it's an infusion or an injectable. It's going to be extremely expensive. These are the type of messages that that clinician may need to have. So message varies as well, but just wanted to jump in there. We have a case example I can show you on the next slide. What is the right KPI? For the discussion today, a lot of what we're saying is early diagnosis, right? Much of our partnerships within the life science industry are quite often changing HCP behavior and quite often prescription. That is not necessarily the case today and the particular strategy we're trying to meet. So if we go to the next slide, I really like this particular example for a few reasons. I'm biased. I came from a medical affairs organization. This is a medical affairs program. So these particular folks wanted to bring HCP education on disease state, not necessarily brand. And this challenge, or this goal of this program was, we have this rare genetic pediatric growth disorder. Okay? We have a very small group of specialists within the United States that know how to treat this population. We don't really need to educate those one hundred specialists at those four systems. Right, they were a part of the clinical trial to get this drug approved. But what we need to do is we need to educate the general pediatricians on the signals and the phenotype of this particular pediatric population, so that we can educate them within their EHR when they're seeing this population, to refer them to the specialist. And that is this is a hallmark case of early identification, early diagnosis. Let's get to the generalists so they can refer this particular patient to the specialists who can care for this patient. And when we measured this particular program, we looked at and you can pop up the slide in full we looked at referral rates, we looked at the referral to the pediatric endocrinologist, as well as genetic test referrals. So there are many points that we can look at to say, did this intervention improve the way that this population was managed? And I think from these outcomes we can say that, yes, this is a very nice standard of care of how we would go about educating referrers to get the patient to the specialist. Again, just one example. We measure all of our programs. Everything varies in terms of what folks are looking at based on their KPI. One size does not fit all. But this strategy has become very common in pharma. And the reason being, the manufacture of drugs has highly swayed to specialty pharma and niche disease states, right, that are quite often treated by specialists. So I think this is a nice example to highlight. And Marie, I'll pass it over to you. Yeah, and you can see exactly your marketing outcomes highlighted right here. And when we do these studies, Mike, we're looking at campaign exposed populations versus non, right? And so typically, when we take this and we transfer it to a results conversation in terms of script impact, we'll see those scripts pulling through now that we've seen truly the referral rates change and the right specialists that we're exposing and are involved at higher rates. Let's go to the next slide, please. So this really brings us to our summary of those five steps that marketers need to take to optimize their marketing for early intervention. And we've really talked through all of them today, building a medical driven profile using early consumer milestones or early clinical milestones to find your audience. Use that profile as a north star to build your whole marketing ecosystem, prioritizing clinical data over demographics based decisions, predicting and measuring marketing outcomes, and then taking those marketing outcomes and conversion pipeline as your leading indicators of success and using them to optimize your campaign throughout its lifecycle, not necessarily just engagement with marketing material, which is what marketers tend to have to rely on. So there's a lot of tangible and practical ways that you can adapt your marketing strategies for early intervention. And that takes us to the end. And I'll go ahead and move into Q and A now. Thank you so much. It is time for the Q and A portion of today's webinar. If you haven't submitted your questions yet, please do so now. All right, let's jump right into the questions. So for the first question, how do you get to know about the preferences of the audience at the macro level? The patient journey is different. What sort of data is important for marketers to know and to make the patient journey more accurate? Yeah I would kind of break this into two different parts, right? So if you are starting with the patient like what we were talking about, you're looking for the tests that help you kind of stage which part of the disease that you know you're trying to target and you know what may be essentially what we will be using as you know looking for in the claims data such as potential comorbidities or other medications that they might be on. And so those are sort of the markers, right, that we're using. And then from that perspective, you can take a look at combining the consumer behaviors of those specific profiles that you've built, right? And so you can use that essentially to look at the preferences of the audience, because you've identified the segments of your audience. And then when you integrate the consumer data and their habits, you'll be able to see their preferences. All right, another question. In some rare diseases, you'll have a disease diagnosis, but specific symptoms without the ICD-ten code, they don't kick in for a few years. Do you have any thoughts on how to address your objective? Yeah, so some of this for us, it goes a little bit back prediction and looking at what that profile is. So we use AI to predict when a patient may be approaching certain stages of their journey, And so from that perspective, you know, we're sort of using, you know, as a profile to project out, you know, when we might see a patient hit certain stages in their journey. All right another question. How does the fragmentation of the EHR systems in the U. S. Affect making all of this work? It seems like you end up having to work with multiple data systems which can result in higher costs. Yes. The fragmentation is a big factor that we're trying to get around here. Obviously the way that we get around it is by using the claims data to actually do the targeting instead of using the data inside the systems themselves, because that way you're kind of getting a look at the population, across the full population that you have versus what's just present in specific EHRs. And then of course, understanding the EHRs that the NPIs are actually working in has a big impact, of course, on where you're going to make media placements. All right, another question. What is the total reach across channels? I think this one came in while Mike was talking about one of his case studies when we were modeling the audience. And for this one, it's pretty audience dependent, of course. Like, the NPI matching can be done across channels that's sort of connected to the same answer around the fragmentation of the ecosystem. Because whatever channel you're going to activate the media on, the NPI matching is becoming more and more prevalent, you can find the NPIs and where they are at the EHR in particular and across channels. And then of course it's also connected to connecting consumer data to that clinical data. That will help you understand where your consumers are consuming media across those channels. Another question, what role could AI have in claims data mining to ID patients and HCPs to target messaging? I think this one is actually really similar to the one I answered before. But for us, we are using AI to navigate lots of claims data of the whole US population. And so it obviously can speed up and make the data more recent. And then also we're predicting where there actually isn't data, but where a patient journey may end up going so that you're predicting where to place media before the patient is quote unquote there. And in that way you truly are targeting a consumer, right? Because they may not quite be there yet. Another question. You talked about identifying patients earlier in their journey using available claims data. How do you balance that level of targeting with privacy requirements and data use restrictions? Yeah, we get this one a lot. So first off, like everybody else that's working in this space, we're working with de identified claims data. So there's no identification. What makes what we're doing a little bit different here is we also aren't working even directly off of a token. We do use tokenized data. However, the health data itself isn't actually what we're using to target. We use neighborhoods, right? So we're mapping the prevalence of a profile to a geography and then weighting geographies based on the likelihood and prevalence of a profile or disease in that geography. So it's very privacy by design oriented, so that we don't have to rely on specific health data when we're actually getting to the targeting stage and activation stage. Another question for smaller brands with limited data science resources, what's the best entry point for implementing the kind of shared data infrastructure? I think for this one, I would say to start with a pilot, mostly because what you would need to do is build the case for doing this kind of across the full ecosystem. Because what you're really trying to do is build this personalized look. So maybe pick one segment or pick one channel where you have this approach and show the value of the more personalized and segmented approach there so that you can kind of spread it across either the rest of your brands or around the rest of your conversion points. Next question. How do you determine the right balance between upper funnel education like disease awareness and more conversation driven messaging in early stage campaigns? I would say for this one, like a true understanding of the conversion pipeline and the markers that show that it's working. So if you have your segments built around the funnel stages like we were talking about, you can get a feel for the volume that you're going to need in each stage to make that conversion. And so from that perspective, you will know where you're light, so you can know where to spend more of your resources to try to fill it up. Another question beyond oncology and neurology, which therapeutic areas do you think are most ready for early intervention marketing strategies? For this one, I think that it's more a question around brand specificity than it is around therapeutic areas because I think in every therapeutic area you've got brands that are working toward addressing symptoms early in the journey or maybe disease modifying very early in the journey. And so I think it has more to do again with the brand. The way that we approach this is also a very common approach, of course, in rare disease specifically, too, because the patients are much harder to find, particularly in such a large in the population. So yeah, this would be very brand specific. All right, another question. How often should audience definitions or data models be refreshed to maintain accuracy in early intervention campaigns? I love this one because it's as refreshed as possible, as real time as possible, is where you want to get to here, particularly in early intervention. We're looking for symptoms. We're looking for early markers and comorbidities and right when people are starting to take medications. And so that's going to be changing all the time. And so we want to try to refresh as much as we can to make sure we have recent data. We're doing it weekly right now when we are targeting HCPs and monthly on the consumer channels. All right, well, that's all the time we have for today. I'd like to thank our speakers for their thoughtful contributions. Thank you, Maria, for answering these questions. I'd like to thank our audience for joining us. If we were not able to answer your question, we will do our best to follow-up after today's webinar. As a reminder, a recording of this session will be available on demand within twenty four hours. Thank you for joining us and we look forward to seeing you next time. Thank you.