Episode 23: Accelerating Healthcare with Data Insights
Bradley Bostic
Healthcare Technology Investor, Founder, CEO, & Board Leader | Host of Boombostic Health Podcast
“Do you have the right consents in place? Do patients know that their data could be potentially used for secondary research, for drug development or for outcomes research. These are very important secondary uses of, in particular, genetic data.” – Bridget Wegner, Director of Partnerships at Clarivate
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Episode Spotlight:
We sit down with Bridget Wegner, Director of Partnerships at Clarivate, to explore how diagnostic data is reshaping the healthcare landscape. From her early days in laboratory medicine to driving innovation in genomics for rare disease research, Bridget shares how data can transform patient care and accelerate drug development.
💡 What You’ll Learn:
This episode challenges the status quo, asking: Why is healthcare still siloed when the technology exists to connect the dots? How can we ensure every patient benefits from the insights hidden in their data?
00:00 From Forensic Dreams to Healthcare Innovations
Bradley (00:13) Hello, everybody. Thanks for joining us here for episode 23 of Boombostic Health. I'm happy to be joined by Bridget Wegner, who's coming down to be in the studio from Milwaukee. Bridget has a background in laboratory medicine that's extremely extensive, going back to neogenomics and then a stint at Tempus, and now as director of partnerships with Clarivate. And the topic really is all about the opportunity that exists to accelerate healthcare by better leveraging data.
Thanks so much for being here, Bridget. So I gave the quick thumbnail about who you are, but maybe just tell your story. How did you end up in healthcare? Why was that your focus and calling and how has your career evolved and what are you doing now?
Bridget (01:01) Yes, thank you for having me. Great question. So I think my interest in healthcare actually started in college. I had no clue what I wanted to do. I took Intro to Clinical Laboratory Science and I was determined to be a Forensic Scientist. So laboratory was always appealing.
Bradley (01:29) Forensic scientist? Was that because you wanted to help?
Bridget (01:32) Yes, I was obsessed with crime shows. I wanted to be the person in the dark room doing like all the DNA analysis and trying to find the criminals. ⁓ Unfortunately, Yeah, yeah, but no, the intro to clinical laboratory science was really interesting. So I wanted to be a forensic scientist, look at the pay grade through the stage and it wasn't the greatest, but then realized you could make an impact behind the scenes too.
Bradley (01:42) How many crimes have you solved so far?
Bridget (02:02) None. That's a different episode. Working in laboratory medicine. I actually got my degree in medical technology, medical laboratory scientist by background, spent a few years working in a variety of different healthcare settings from small rural clinics where I had to write all the results on paper ⁓ to larger healthcare organizations and reference laboratories.
Then I wanted to take my career to the next level and I've always been intrigued by data and using data to answer questions. So I actually ended up getting my master's in medical informatics as well too. And then ever since I've had that degree, I've kind of focused my career mostly on data and analytics, but specific to diagnostics because I do love the laboratory. I have a passion for it. There's so much information floating around within the lab that is used to make very critical decisions in healthcare.
02:54 The Power of Data in Healthcare
I akin most medical laboratory scientists to like true data analysts. The amount of information that they see on a given shift is just incredible. And the ability to have that pattern recognition just makes them ripe to be amazing analysts.
Bradley (03:10) So to put a fine point on that, there's all of this information that gets generated about an individual as they traverse their health journey. Whether you're sick or healthy or somewhere in between, laboratory information is constantly being generated. talked about this before, even the moment you're born, you're in a civilized, modern healthcare environment. Yeah, and the it generates all this data and then that follows you all the way through until your final moments on this earth.
I always talk about this in the context of my role as CEO of hc1, which our passion is about how you can unlock insights from the laboratory information, not just as a point in time data point, like you're sick, it's an acute issue. Let's run a test and see how to medicate you or treat you in some other way but rather how do we identify those signals that can be predictive and preventative? How can we help you get better faster? And then ultimately, if you fail conventional therapy in a healthcare setting, how do we help make it seamless where you can navigate into some kind of research that might help you and ultimately can serve to the better of everyone in healthcare who needs these advanced therapies?
So that's how you're, so you started with being out in some country hospital, manually writing down what the results were that came out of the machine. Yep. And then somehow evolved to where now you're looking at this more advanced picture.
Bridget (04:48) Exactly. What is the secondary use case of all this diagnostic information that's floating around now? To specifically use to, your point, looking at patient journeys in an aggregate study, looking into drug development and biomarker discovery, and then outcomes research as well too. So the laboratory plays a part in every single one of those phases.
Bradley (05:11) So fast forward to Clarivate. Introduce what that is.
Bridget (05:15) So Clarivate is an information services provider. We have three different segments within our business that span academia and government, intellectual property, and then life sciences and healthcare, which is the vertical that I sit in. And then within that life sciences and healthcare space, we have our real world data application, which is the team that I'm a part of. So we're actually a very small startup segment within real world data that is specifically focused on genomics for rare disease research.
06:09 Navigating the Lab and Pharma Landscape
So very niche, very targeted, but having been in the diagnostic data industry for a few years now, I see you need surgical precision on some of these use cases because there is so much laboratory and diagnostic data out there. How do you distill it down to some meaningful insights, right? So we wanna be very strategic about the use cases, very strategic about the partnerships that we have on both the laboratory side and on the pharma side as well too. So I think that's where my background comes into play too, being on the diagnostic side, but then also venturing into this real world data space, how can we marry the two and get, make the most progress for patient care using diagnostic data.
Bradley (06:28) So said another way, a pharma company, which is the primary customer, when you talk about life sciences, these are folks that are developing new medications. Those pharma companies don't have internal time, nor necessarily even expertise to take a spreadsheet full of data that comes out of a lab and get down to the level of detail that's really going to provide value to them.
So, what you're doing is focusing on how to find those needles in a haystack for them. Exactly. I've actually had an experience with the alternative to that. And I would agree with your approach. It's an absolute tire fire when you just go dump a whole bunch of data on a pharma company. and there are unfortunately a lot of folks that do that kind of thing. I think they kind of create a negative perspective on the entire idea of how you can unlock insights from this in a way that improves healthcare. Instead are in this, how do we just dump data on healthcare and it doesn't help anybody.
Bridget (07:43) Yeah, 100%. And we've even heard the term low quality data coming from large reference laboratories that are very credible in the field who provide very timely and relevant diagnostic information for providers to make treatment decisions, but to hear on the other side that it's low quality. Is it low quality or is it not? The expertise isn't there to understand and digest and pick out the relevant data points.
Bradley (08:10) So you hear from a life sciences partner, hey, we got this data from these, this laboratory, but it was low quality and really translating that it probably means they just didn't have the ability to discern it in a way that was actionable.
Bridget (08:27) Yeah, well, and then you have larger organizations that may have satellite laboratories too. They each set up their own reference ranges. So you're already not comparing apples to apples on the same test, even though it's coming from the same quote unquote laboratory too.
08:54 Patient Data Privacy and Ethical Considerations
So you have to have somebody who understands the nuances of not just the testing itself, but also the landscape of diagnostics as a business too and how one site may operate under the same name but produce kind of values at the same time. But you have to look at it in context with the reference ranges that are established for each of those sites too. So there's a lot of that nuance that comes with the expertise of being in the laboratory setting too that you need to have to understand what it is you're looking at.
Bradley (09:16) Because there are different instruments that are set up in different ways and generate. Interesting. So, the hot button issue around all this tends to get into patient data privacy and data rights and so on. It's a bit of a sensitive topic, but I think it's an important one to just be really open about. Because I think in many respects it's misunderstood.
Bridget (09:20) For methodologies, right, exactly.
Bradley (09:46) How information can be used to improve healthcare and it can be conflated with, people are selling data. And there have been some big stories that really did not reflect well upon strategies. I mean, a recent one that's been hot in the news is 23andMe, who has filed bankruptcy. And I think they made some missteps in terms of violating the trust of the patients that were using the service that didn't really understand it.
I think what I'm hearing and seeing in what you do is it's the opposite of that where, Hey, we're very direct and specific about how we can bring information to life sciences that will either provide access to a given therapy to somebody in need or potentially even accelerate or help inform the development of new drugs.
Bridget (10:36) Yes, exactly. Very important point to the informed consent piece is one of the first things we look at with our data partners is, do you have the right consents in place? Do patients know that their data could be potentially used for secondary research? Exactly to your point for drug development, for outcomes research, right? These are very important secondary uses of, in particular, genetic data too.
So 23andMe...does have the consents in place, but because it's to consumers, is it just like when you download an app and you start scrolling through all the terms and conditions, you don't really look at them. In a health care setting, when you're looking at informed consent, you actually have somebody there kind of explaining it to you. So the patient is very well aware of what exactly is being done and then how that information is going to be used.
It's important for us as a company to understand what consents our partners have in place, like from a legal perspective and a compliance perspective are able to do data sharing because we have seen instances where the compliance or the informed consent forms, they don't really meet the mark. You can change the language and then anything moving forward you can, or you can go back and get informed consent from patients who have already been tested. But that's a little bit more work up front too.
11:54 Real-World Applications of Genomic Data
Bradley (11:54) Okay, so are there any specific examples or stories that you can share about how what Clarivate is doing has helped to improve life sciences?
Bridget (12:05) ⁓ that's like the bread of our business. We ⁓ do a lot of research for pharma that covers the entire span of the drug development life cycle. So we were speaking earlier, we have two teams within Clarivate that kind of span the entire continuum. So we have our discovery and translational research team. They're based out of Barcelona, bioinformatics heavy. They do a lot on the drug development and biomarker discovery end.
And then we also have our data insights and analytics team based in the states too. They're more on the commercial readiness arm of it, so market access, provider targeting, and then the middle part, know, clinical trials, clinical recruitment. We also assist with that as well too.
Bradley (12:52) Do you get to go to Barcelona?
Bridget (12:53) I wish. Trying to come up with a business case to make a trip out there. Yes, I would love to go sometime. Fantastic team out there. Very smart. I think I saw it was about 300 combined years of bioinformatics expertise. So I mean, it's a really powerful team out there.
Bradley (13:10) Okay, so as you navigate the startup inside of Clarivate that's bringing in more of the diagnostic genomic information, what kind of feedback are you getting in the market? ⁓
Bridget (13:24) It's across the spectrum. Seriously, we have some partners who are already actively doing these type of research projects directly with pharma. And there are very applicable use cases where it makes sense for labs to partner directly with pharma companies. ⁓ Sponsored testing programs is one. Clinical trial enrollment is another. So if you're a genetic testing company and you have a positive result on a patient and there is actively a clinical trial for patients who have that positive biomarker, the lab can actually do direct outreach because they're a covered entity. They can see the PHI. Everything that we do at Clarivate is de-identified.
We don't see PHI. We don't want to see PHI. We specialize in aggregate studies, longitudinal studies, and that's really where the partnership value comes into play, right? So you can take that diagnostic information and then we can do that longitudinal analysis outside of diagnostics, right?
So specifically in the case of rare disease, let's give us an example. If we partner with a genetic testing laboratory, that is the diagnostic data point, we can take that information, create a cohort of patients de-identified, and then look at the diagnostic pathway leading up to the actual confirmed diagnosis. And are there misdiagnosis pathways that are more common than others?
15:11 The Future of Rare Disease Research
And is that a trigger point for an intervention? Like, in the case of our pharma partners, is that an opportunity for the reps to go talk to the provider and say, hey, you may be caring for a patient that is expressing XYZ symptoms or procedures have been ⁓ done.
And we see this commonly as a misdiagnosis pathway. Have you considered testing for XYZ disease?So it makes the conversations very timely and relevant and can actually shorten that diagnostic pathway.
Bradley (15:16) And this is for certain specialists that would be seeing the kinds of patients that would have a given condition?
Bridget Correct.
Bradley Is there an example of one that would be related to a genomic test result that you could share just for our audience to understand?
Bridget (15:29) ⁓ so I don't want to get too specific because I don't.
Bradley (15:33) I'm not asking you to buy, that's why I was sort of, there anything, just to, just to kind of, ⁓ even just categorically, like what's the kind of disease that now you're really using genomics to test and diagnose versus the more traditional clinical lab tests or clinical pathology.
Bridget (15:49) Right. So one that we can think of in particular Duchenne muscular dystrophy or some of the muscular dystrophies, they do have genetic variants that are diagnostic. So we can work with laboratories that do maybe neurodegenerative diagnostic panels and anything that comes up positive that could be a data point within a longitudinal study.
Bradley (16:10) And are there situations where there might be a diagnosis that the provider doesn't even know about what therapy is out there that can help the patient?
Bridget (16:20) Yep, that's another offering for Clarivate as well too, is provider targeting for specific therapies too.
Bradley (16:26) Rare diseases or nuanced where it's not just sort of the standard run of the mill. Hey, you get diagnosed for diabetes, for example. That's a pretty well-known pathway. Emerging diagnostics that are really pushing the envelope toward being much more precise.
Bridget (16:46) Exactly. Yeah. And we just see our pharma partners as another part of patient care too. So because, especially in gene therapies and biomarker therapies, companion diagnostics, it's evolving so rapidly too, that it benefits our physician partners to have pharma come and educate them on products that are out on the market, especially if they're caring for patients that would be the best candidates for these therapies too, when you're talking about very specific gene variations, right, and if the therapy is very relevant for that.
Bradley (17:20) So as in healthcare, as in any other industry, if there's no margin, there's no mission. There has to be some way to make money. Clearly in the pharma world, there's an opportunity to make, to produce more income in growth. If you have a drug that comes to market sooner, it's developed faster. Or the more that you're finding those folks who need certain drugs, you talked about the more the market access.
Bridget (17:27) Exactly.
17:50 Building Strategic Partnerships in Healthcare
Bradley (17:50) If you look at it from a data partnership perspective, how does this all fit together when you're partnering with a lab? Are they, ⁓ you know, what, what, what's in it for them? Well, I work in the lab space at hc1, you know, and, ⁓ we work a lot with labs to optimize growth operations, clinical impact. And there's this bubbling conversation about.
How should we be aligning in a way that is relevant to pharma? And I would also, before you answer that, put a really fine point on, ⁓ there's absolutely a critical need to be connecting the dots between the provider and the life sciences world. The fact that it's been so siloed has been an incredible impediment to progress. And my mom was an example of that. She died of colon cancer.
And by the time she was failing conventional therapy, there was no connection that was methodical at all to any sort of trial. was like whatever trial somebody might be aware of, you could maybe call them. And she ended up getting into a trial and it did not help. But it was not the kind of, when you consider that there is no more important industry than healthcare, how is it that we optimize the experience in e-commerce where if you order a new set of dish ware on Amazon, they treat it like it's life or death that they delivered to you on time.
But you go through a healthcare experience that may be life or death and you're treated like a number and there is not a connection. So my personal viewpoint is we need more of what you're doing at Clarivate and we need more of what we're doing at hc1. We need more of this ability to take all of this raw, massive volumes of data and transform it into the insight that can advance healthcare. So as you look at it, how would a lab or even a potential partner like hc1 think about the partnership with Clarivate and how that unlocks some kind of economic driver as well?
Bridget (20:02) Exactly. Yeah. So we're trying to be very strategic on who we partner with initially. So again, we're in the startup phase and we have an early adopter pharma partner who has a very specific indication that they're focused on, which makes us able to target very specific labs to initially partner with too. It's like, okay, we have the indication we're focused on. You do the testing to diagnose it. Let's come together and see what type of insights we can generate with.
20:59 The Role of Labs in Patient Care
Clarivate’s combined real-world data assets and the laboratory's genetic or other diagnostic information as well too. So we want to be able to show immediate value to our pharma partners and the type of insights we can gather when we look at claims, when we look at prescription data, and then when we look at diagnostics as a component of that too. Because we don't, and you asked earlier what are, what's some of the feedback been so far, a lot of these labs have already been approached by other either pharma companies or other data aggregators and said, basically, just give us everything.
We'll normalize it. We'll standardize it. And then we'll commercialize it. And then nothing ever happens because you have essentially analysis paralysis. You have way too much data. Like where do you even start with? So we're taking the approach of kind of a push and pull at the same time. So with our pharma partners and then also strategically picking out who would be an ideal diagnostic partner to help us start forming these use cases and these analytics and these insights so that we can show value initially and then start branching out from there too.
Bradley (21:39) So you're starting with a pharma need specifically. We need to find people or have people diagnosed with this specific condition. And then will you go into a lab and help them set up to even do a test that maybe they're not already doing? Or is it always the case that the lab's already doing the test?
Bridget (22:03) We want to start with the ones that are already doing the test because we understand their clinical business comes first, right? Serving patients and serving their referring providers, that's their number one priority in the day. We don't want to take away from that. We want to meet them where they're at from either a technical perspective, regulatory perspective. We want to be consultative and partners if this is something they're interested in exploring.
So we have a whole team of data engineers, data scientists, and we can take raw data in its rawest form, but then we would just need the subject matter expertise of, this is exactly what we're looking for. Help us distill that. We may have some questions about what we're looking at, and then you can just provide the feedback. But we don't need you to create custom, unique reports, right? And if you do need that help, maybe that's...where another technology partner comes into play. So if you're already working with somebody like an hc1, a software solution company, that could be done in partnership with services you already have in place too.
Bradley (23:12) Okay, so what do you see as the vision for any new startup has a vision and a mission and do you have anything to share about what in five years from now or I don't know, you pick the time horizon, but what do you think, what does that picture look like after you've done the hard work to create this foundation and how does it benefit patients?
Bridget (23:35) Yeah, we want to create essentially a partnership model where it's funnels going in, but then opportunities going out as well too. So we want to be able to move the needle in rare disease research. And that comes with a partnership with pharma. It comes in partnership with data aggregators and insights, and then also bioinformatics and diagnostic testing companies too.
And there are, we talked about this a little bit earlier too, but there are components that you know, in the de-identified space, we can't do, but then is there a referral funnel back to our lab partners when it comes to clinical trial enrollment or sponsored testing programs where we can make the introduction or it can be an extension off of an aggregate study, right? We see a misdiagnosis pathway happening in one of our patient journey studies. Can we have pharma intervene at that point and say, hey, maybe you should consider doing testing for XYZ disease.
24:03 Vision for Data in Healthcare
And we know a partner laboratory that is doing that testing and we'll cover the costs for your patients for that. So it's essentially what a sponsored testing program is. So the vision is kind of becoming that knowledge broker or the middleman broker of these moving pieces that need to happen in rare disease research, right? And we're kind of like the central spoke for the wheel, right?
Bradley (24:54) How does the clinical research organization model, the CRO model, fit with what you're doing? ⁓
Bridget (25:01) Well, some laboratories actually do have their own CRO too. So they can do the diagnosing testing for it, but then they could also do the clinical trial enrollment. And then ⁓ we are also speaking with academic medical centers, integrated health networks too, that may have their own research arm too. So now if we're working with pharma and we're doing research in a very specific indication and they want to start doing clinical trials.
Now we have a pipeline back to our academic medical center partners for maybe PI oversight, right? And we can help with clinical trials, site selection, and enrollment just from an enablement perspective.
Bradley (25:39) And Clarivate's much broader than Lab. So in the specific area where you're focused with Lab and you're partnering with Life Sciences, are you bringing some of the other Clarivate data capabilities to bear as well?
Bridget (25:54) Right. That's where we see the value proposition is in the combined data assets. Because like I said, there are opportunities for diagnostic laboratories to go direct to pharma when it's a case where its two covered entities need to, or they need the PHI component or the outreach component. It absolutely makes sense to work directly with the laboratories for that. But then when you're doing some of these longitudinal studies, that's really where we want to focus our efforts on is the combined and the insights generated from the longitudinal studies. Everything is de-identified, correct.
Bradley (26:25) De-identify meaning that it's not as though you're identifying Bridget specifically. You're saying, people that fit into this cohort have these certain patterns. I can't remember the term you used for the care pathway, the diagnostic pathway.
Bridget (26:42) Yep. Or like a misdiagnosis pathway in the case of rare disease.
Bradley (26:45) I'm looking for , so, okay, so this is putting it like in human terms, the tragic situations you hear about where this person was having these really awful debilitating issues and nobody could figure out what it was. And so this is an opportunity to better identify those folks.
27:05 Closing Thoughts on Data and Patient Outcomes
Bridget (27:05) That's right, exactly.
Bradley (27:07) Okay. Well, that's really amazing work. It's incredible to hear how your career has gone from, you know, early days of wanting to solve crimes and all the way through to now solving for the next breakthrough medication and how to help patients. Right. It's pretty cool.
Bridget (27:27) Well, and really enabling laboratories as well, too. You know how squeezed they are on revenue always, right? They operate on razor thin margins all the time. And this is just, is this another revenue opportunity for the laboratory itself, too, right?
Bradley (27:43) Yeah, absolutely. Well, with laboratories, what we see and the reason I started HC1 is that they are central to nearly all diagnostic decisions, yet they tend to be relegated to a second class level of focus and the impact of lab when it's leveraged as a strategic component of healthcare delivery and where the information is utilized in a more comprehensive way is truly profound on patients' outcomes and patients getting better faster, which saves a lot of money in the healthcare system. So all too often, whether it's diagnoses or its medications, the fixation is on what does it cost for a test to be run or what does it cost for a pill?
It doesn't really matter if you're not diagnosing people effectively or you're getting them on the wrong pills because in those cases, even if it's the cheapest pill, for example, you end up in the hospital at a minimum, it costs $7,500 for you to roll into the ER and get cared for and sent back out. And so I think this shift to value-based care that's happening runs directly through maximizing the way that lab information is utilized and then ultimately playing that out, the better you can get people treated sooner or even prevent disease.
That's really the future. So as I look at the future I want to be part of in healthcare, and I'm trying to create in healthcare, it's one where you know, without a doubt that the underlying apparatus that's there, that's interrogating all this information is doing that in a comprehensive way.
That is going to identify what that diagnosis is. As soon as you know that this specific test result diagnoses this specific ⁓ condition, and there's a therapy for that, shouldn't everybody benefit from that? Exactly. But we still are operating on this, ⁓ like back in the day when communications were having a string and you know, cups hooked together. And in your respects, healthcare still works that way, where it's just not quite sensing and responding in a way that is as quick and powerful as what the technology makes possible. So, well, I certainly commend you for the work that you're doing. Thank you. Clarivate and appreciate you being here on Boombostic Health. And look forward to finding ways that we can collaborate. Well, with that, we will transition to the verdict with Emily to talk more about the legal and regulatory considerations of leveraging this kind of information.
Bridget (30:15) Yes, thank you for having me.
The Verdict with Emily
I'm now here with Emily for the verdict and we are discussing the evolving landscape of collaborations between providers and pharma and specifically the conversation with Bridget Wegener, who's the director of partnerships for the emerging lab segment for the company that she's working with. we both, Emily and I do a lot of work in this space.
Emily, thanks for being here first of all, and would love to hear your perspective on how you're seeing these collaborative relationships between labs and pharma evolve over the past couple of years. And I certainly have my point of view as well, but would love to hear from you. And I think ultimately ⁓ how you see this as a possible pathway to improve healthcare for patients and also maybe even enhance economics for labs.
Emily (31:35) Yeah, that was a loaded question. So this is actually a timely discussion. I was actually reviewing one of these contracts this morning. Seeing about preparing to enter into one of these contracts and you and I have talked about this a little bit. Like monetizing data, right is determining who has the rights to data, but taking a step. I think there is this misconception out there and you and I talked about this recently. In fact, I'm speaking about this at the War College in a couple weeks.
That folks think that just their data alone is, ⁓ An ancillary revenue stream that's untapped. I think that's necessarily true. Like there's certainly value in data. There's a lot of labs out there who think that just their pure raw data alone, ⁓ is like this gold mine. And I'm not sure your perspective on that. know we, started to have that discussion, but, I certainly see that a lot amongst our pathology groups that we're talking talking to and the labs, but as we push this digital pathology discussion forward, one of the driving factors and ⁓ points, trust in that discussion is how can we take the digital data and convert it into something that drives revenue and is something that's attractive to pharma.
The one that we were looking at this morning that actually we as the health care at McDonnell Hopkins we were kicking it around was interesting because, which is not a patient facing provider, right? The lab had the obligation to collect all of the consents from the patient to transfer this data to this research entity. And so they were supposed to transfer it fully identifiable. Transfer to the research entity, the research entity would then de-identify the data rights with respect to what they could do with the data from there. And not really anything that was beneficial to the lab, which begs the question of why would you take on all this risk and all these reps and warranties if you are going to realize the value of all of that work sort of behind the scenes. The long-winded way of saying a lot of folks don't understand what they're doing when they're entering into these data sharing, pharma partnerships, but they just think that by doing so, they're going to get some sort of revenue stream.
Bradley (34:03) Yeah, it's interesting. The evolution that I've seen is say within the last five years, it shifted from pharma wanting to have insight that is provided from lab data and thinking that buying lab data was going to help them to realizing and actually categorizing that kind of a data sale as ⁓ when the pharma folks would receive it, low quality data is how they would label it. And really it doesn't mean that the data didn't have value.
I think underscores the point you're making, which is the raw data, especially if it's just independently lab, it's really not very valuable. It's when it actually gets processed and refined, kind of like if you take black muck out of the ground and what you really need is jet fuel. The black muck isn't worth anything unless you have the actual refinery process that generates the jet fuel. And that's what we're seeing happen now really with this connection between providers and specifically labs and pharma.
And with what Bridget was sharing, their group is taking a very laser focused approach to understanding rare disease that relates to a genetic variant or genomic test output and partnering with the lab really more like a clinical research organization approach that the lab is taking to go identify and engage under the full consented process to get patients into trials or get them medications that they can benefit from. That's like on the completely other side of the spectrum from the historical approach. So it's evolving fast.
Emily (35:58) It is evolving fast and yeah what you're speaking about there is more like the CRO probably in conjunction with some sort of IRB where you have all of those appropriate authorizations until recently. What I didn't realize and sort of shame on me. Was that in tandem with getting the data from the labs. Pharma companies are also getting data from other types of providers, radiology, certain redacted medical records.
And so to your point about the raw lab data not being worth much, but if they get, you know, a million lab records from a particular demographic or location and they get a million radiology reports or something, they're not necessarily matching them up, but the data is linked, related and can track related data from population health trends or, risk to a particular demographic, which to me, I found that really interesting. A
I think the important thing when you're seeking to protect your data in those situations is making sure that the pharma company never actually takes it a step further to try and actually link and re-identify those two independent data sets. In fact, this came up, if you were on a call when we spoke to a medical ethicist who was talking about the availability of data just out in the public. And pharma companies have this limited data set from a lab or de-identified data set based on what's available in the public domain and using AI, is there a possibility to re-identify that data? And I think maybe in some cases, but certainly not always yet. But I think that's something to keep in mind as like the technological nature of all of this continues to evolve.
Bradley (37:44) Yeah, the common approach with linking those different data sets is using some type of a tokenization ⁓ process, which is just a way to say you're assigning some unique number or unique string to a given identifiable individual and following a consistent methodology to do that across multiple data sets. So you could connect somebody's grocery shopping with their medical record, for example, without actually identifying who the person is at that research, more like public health level. And that's, I think a good example just to be a bit more provocative than just common healthcare information. But to bring it home, I think the precision is getting a lot higher with respect to solving problems with these insights. And the lab plays a key role in that.
I think the idea that a lab can go sell their data and that's going to generate a lot of revenue. is very much akin to the jet fuel analogy. There's a lot of processing that it takes to make it valuable for pharma and make it valuable for patients. But I think the future is bright because there are a lot of innovators and a lot of caregivers and labs providers of all types working together to try to unlock this and what I think about is we are all on this journey with our health. And the more that there can be insight on all of the information comprehensively throughout that journey to help us prevent illness, help us get better faster if we do have a diagnosis, and ultimately help us participate in research in the event that that's needed or have access to some type of less known therapy if you have a rare disease.
That's really positive. And I have a very abundant mindset on all of this. I know that there is a potential downside. If you have bad actors, I do see over time, a lot of those bad actors that are more of the commodity oriented folks also getting kind of, ⁓ running their course, ⁓ and folks identify now, Hey, these players that really bring scientific expertise and bring some type of technology prowess and can help us bring a more comprehensive set of insights into pharma, into research to the benefit of patients. That's important for all of us to embrace. And let's just be vigilant about making sure that it's done in the right way.
Emily (40:17) Yeah, I think that's accurate.
Bradley (40:19) Awesome, Emily. Well, hey, thank you. It's always a lot of fun to ⁓ break down the conversations we're having here. Clearly, this whole data world is a ⁓ really super important topic, one that's going to be covered in depth as well at the upcoming Executive War College. So looking forward to being there and ⁓ continuing to uncover opportunities that can benefit patients. Thanks, everybody, for joining us for another episode of Boombostic Health. We'll look forward to seeing you next week.
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