Dustin Raney:

Yeah, we’re super excited to have you today. Why don’t you give us a snapshot of your background in the healthcare industry and how you came to your role at Acxiom?

Sonny Dalal:

Yeah, no, appreciate this. Thanks so much, Dustin. So I’ve pretty much spent my whole career in the life sciences space more broadly speaking, started off my career working with larger organizations and data analytics, IT tech services. And then more recently, in less maybe 10 years or so, it has been more with emerging venture backed organizations, really focused on data and analytics as well, and looking at different ways of how do you help pharma and then other life sciences firms engage with their physicians and patients more effectively. So I’ve pretty much spent could say over 20 years, gosh, I’m sort of dating myself there, but all within one industry. So I’ve really kind of got a good sense of the overall needs across the spectrum from developing a drug asset all the way through clinical development and through commercialization. And what brought me really here to Acxiom is that it’s really fascinating to see, and I think you touched on it, the evolution of data and analytics in the industry has really evolved quite a bit.

The types of data that’s available, the use of that data, how can you leverage that to be more effective in engaging with your physicians, engaging with patients, helping get right treatments to the right audience faster and really improve outcomes. And when I talked to folks exploring some ideas in the marketplace and saw what Acxiom’s developed and their sort of route from the data side, but the identity, the analytics and the activation piece, it just really feels really interesting layer to be involved in. Very unique, very differentiated and sort of its approach to address some of these problems in the industry.

Kyle Hollaway:

Yeah. Well, sunny, great to have you on board and certainly thanks for joining us today. And I know this whole area of life sciences and healthcare and such is certainly a hot topic. There’s a lot happening in this space, but also I think there’s probably a lot of questions that our listeners and even myself have because we’re talking about a highly regulated industry, one where there’s all kinds of concerns around like HIPPA, certainly patient information, information concerns around privacy in particular of how that data is shared, sensitive information about consumers. So just give me some insight into that. From your experience in the industry, how’s that being manifested within life science startups, even how they’re handling all that privacy consideration, but certainly as you kind of macro go out to more of the industry large players, whether it’s an insurer provider or an actual life science kind of company.

Sonny Dalal:

Yeah, no, it’s a great point, and I think that’s extremely critical. First to point within this industry, and I think in any regulated industry, but healthcare being one of the more regulated industries that’s out there and from a compliance and privacy standpoint, patient protection and rights. And so that’s absolutely critical. And I think having, that’s the first sort of foundational need to make sure that that infrastructure is there to ensure that there is a way to protect the patient information, patient records, being able to do that in a compliant manner. And there’s variety of different technologies that are out there. There’s a company called Data Von that does tokenization that people are familiar with, that they’ve grown quite a bit in the healthcare life sciences space. There’s other compliance companies that ensure certification when you’re combining different data sources together to ensure that you are integrating it correctly, but there’s no risk of re-identification and being able to make sure that that’s safe and protected.

So that’s extremely critical. Now, having said that, and once you are able to create, and I think what Acxiom has done is brilliant, and the ability to really create an environment that’s safe, it’s compliant, it’s secured, but then once you have that foundation and it’s protected, you need to be able to start answering very difficult, interesting questions to solve healthcare’s challenges. And one big area that we see in healthcare is the ability when you’re having, either you’re launching a new product in the marketplace or you’re in a competitive marketplace. One of the key challenges is having this ecosystem between physicians and patients and identifying them both, whether it’s internally within your systems or externally outside of your systems, but it’s being able to then how do you find them, engage with them, reach them effectively, get them on the right treatment faster. So yes, you need to have that sort of infrastructure of safety and compliance and privacy, but then you need to be able to then take action once you have that infrastructure in place and enable some of these issues that exist in the marketplace. Happy to dive into some of those use cases, but that’s critical. Critical first step.

Dustin Raney:

Do you feel like the industry is doing enough to, I guess, talk about the benefits of us sharing our data for our own health? And maybe at a macro level, it feels like we talk about HIPPA, like Kyle said, it’s like all these regulations and stuff around data, and it’s kind of gotten a bad rap. You have the bad actors out there that are hacking and things, but I mean really, do we talk enough about why our data is so important and how at scale we could all help each other get better? I don’t know.

Sonny Dalal:

Yeah, so I think that’s absolutely, I think data for data’s sake is not necessarily as relevant, but then what do you do with the data? And historically, there’s been claims data that’s been widely adopted and accepted to understand diagnoses and procedures and tests that are being performed by physicians on patients, and being able to collect that insight around a patient and have a unified view around that patient. And what types of medications are they on? Are they responding to those medications, are they adhering to those meds? Are you able to find those patients that are undiagnosed or misdiagnosed patients and where are they and who’s treating them? And all of these types of questions can be done, but there’s different data sources can answer different types of questions. Claims has its value and some limitations, and there’s E-M-R-E-H-R data that has value and potentially some limitations depending on what the use cases are.

And then there’s an area that’s really been relatively untapped, I would say in healthcare is of social determinants of health, consumer level insights, behavior, insights. They contribute significantly on outcomes and benefits of these treatments and decision-making both at the patient level and at the HCPA at the physician level as well and making those types of decisions. So having that ecosystem of these disparate data sources or we brought them a lot of these sources together here at Acxiom. I think that’s pretty interesting and unique in a sense. And I think that’s really where the industry is going is saying that there’s no one answer in any one data source. It’s what problems are we trying to solve? Are we trying to discover, I try to find undiagnosed or misdiagnosed patients? Are we trying to reach physicians who are potentially early adopters for a new treatment that’s coming into the marketplace? I think digital and data level engagement is been around for some time. I think healthcare is a little bit slower to adopt compared to some of the other industries in insurance or financial services and consumer markets. But it’s starting to grow quite rapidly just due to some changes within the industry too, and dynamics in the industry as well.

Kyle Hollaway:

Yeah, I mean in some ways it’s such a double-edged sword because you’ve got individual privacy and concerns around that for people. I mean, our health is obviously a very private and intimate piece. We tend to not share a lot and want to manage our own health piece, but there’s such a global and certainly community-wide aspect to health that you can see health trends. There’s certain, whether it’s socioeconomic or even just geographic impacts that again, you can start to identify things. And it’s one thing to be like, I think Kyle’s in the market for an EV. It’s another thing to say, I think Kyle could be at risk for cancer. I mean talking about a huge different value proposition here to Kyle even. And then also to the broader ecosystem of, like I said, the providers, the physicians, insurance companies, all that kind of stuff come into play. So I think it’s just a really interesting dynamic that is in a way unique, I guess in financial services you kind of have, because people take their financial holdings very privately and where that is, but health is, there is in some cases kind of a life or death component to this. And so being able to effectively pull that data together, obviously with an attempt at being as accurate as possible. So that’s where kind of identity comes into play. This is not a spray and pray kind of conversation. This is, you really want to be accurate about it, but do so with such a regard towards privacy, has really created an interesting dynamic within the marketplace. Now, you said you’ve come obviously from the industry as a whole, but in some kind of the startup space and ai, IPM ai. So there’s a whole another component to it of feeding all that information into some artificial intelligence. And I’m sure there’s some people that hair on fire when they think about that, but how have you seen that play out? How have you seen data, the aspect of really tying it together effectively and then feeding it into an AI solution set?

Sonny Dalal:

Yeah, yeah, that’s interesting. It’s a great question. And I think the term AI, as we all, it’s been used in very loosely oftentimes in terms of what is truly ai. And I think everyone has maybe their own definition from their own company. There are a lot of smart data scientists that I work with, and one of the smarter ones will say something to me, and I’ll believe it because he’s the guru or she’s the guru of AI within our organization. But it does evolve. There was a period of time lookalike modeling was considered, is this AI just doing a lookalike model? But is that considered a way of predicting events before they occur? And so what we would think about from our perspective coming to here and what I’ve seen in recent past is you hit on something really interesting is being able to see someone who’s diagnosed with a disease before they have the disease or potentially have a condition and identifying that.

And there is that, unlike the consumer market here in healthcare, it’s a little scary. It could be a little bit unnerving to say, oh, you may have something and you don’t even know that yet. But what about the value of that? And I’ll give an example, whether it’s an oncology or even in rare diseases, right? Rare diseases, for example, I spent some time in that specific area, and it’s in a growing area for, we work with large disease areas, historically, diabetes and cardiovascular, but rare diseases is impacting smaller patient populations. And it’s hard to find, hard to diagnose these patients. Sometimes patients live with these disease for years before they get diagnosed and they deal with many different types of specialists, whether before they get diagnosed, they’re bouncing around the health system. You go see this doctor, a neurologist, and then you go see this cardiologist and they can’t figure out what you have.

And so now you have data and analytics. And so if you can use data like claims data for example, that we had in the past is that we could train a model of a sudden population of patients that are known that have been diagnosed with the condition, looking at all the treatments and procedures and tests and things like that. You can say, Hey, here’s a known population. Now let’s look at the known population and study that amongst a larger population of 300 million patients that we have within the claims universe over long periods of time, large data. And now we can start to say, oh, what other patients that are out there, here within the US population that have similar trends, similar patterns, and that’s really the crux of lookalike modeling. But essentially we could start to look at that and score those, right? And then what we did is what we would use that information and say, let’s score and say here’s a 99% match.

That patient could have the condition or 98% or 97 or 80% match or something. And so we provide those level of insights saying that to some level of confidence. We are not a hundred percent sure this patient has this disease and we don’t know who the patient is to, let me just take this back. So we’re not talking about specific patients, we’re talking about patient tokens. Again, all compliant, HIPPA, credentialed de-identified, but patient 1, 2, 3, 4, 5. We’ll just say, we know that this patient may have at an 80% chance or some likeliness of having this condition. What we can then do, what pharma companies can then do is take that insight and see who the physician is that’s caring for that patient within a period of time and enable them to go reach that doctor and the pharmaceutical sales rep, for example, to call on a physician and be able to engage with them and say, Hey, you may have a patient and data shows that you may have a patient that you may have seen within a period of time that has these types of characteristics. They may want to get tested. Don’t know exactly how that conversation goes, but that’s precisely it. So try to see if there’s a way to reduce the diagnostic journey, essentially get patients onto treatment, the right treatment faster, getting to the right physician faster with the right message, things like that. This data analytics and activation just really accelerates that and optimizes that whole process. And AI is a way to just make it a little bit more efficient.

Dustin Raney:

I know that me personally, if I had some kind of a rare disease or something or my children or something like that, it’s like I’m going to the far ends of the earth to try to figure out how to get the best treatment and if there’s things I don’t know about if enabling this data at scale is going to help inform me as a consumer that trumps, it’s like, of course I don’t want people knowing personal information about me, but man, do I want to know what those latest and greatest things that are happening that I can at least research? Right? Absolutely. At least understand.

Sonny Dalal:

Yeah, and you’ll see that there are treatments that are out there, clinical trials that are out there getting patients into a trial faster or to a treatment faster. It could be curative with gene therapy and cell therapy, some of these therapies that are out there if you diagnose them earlier before the disease progresses, just imagine there’s the benefits to the patient and their families, but also to the healthcare industry and the cost of not having to have this patient live with this disease and going in and out of the hospital and just improvement of healthcare overall and the cost of healthcare. There’s tremendous benefits across the board. Yeah, absolutely.

Dustin Raney:

So on the other side of that is my personal journey, healthcare, it’s always just seemed kind of burdensome, right? It’s like there’s so many factions in the whole chain, the healthcare chain and even going to the doctor’s office and then I might go to another specialist if you have asthma or something like that, and I keep having to enter my same information over and over again. It’s like at what point does the healthcare industry enable or allow identity to be handed over to a person to carry with them digitally? I think you’re starting to see some of those things as well, and that really is what’s going to drive maybe the holistic journey. What are your thoughts there?

Sonny Dalal:

A hundred percent. I think one of the things that we often talk about and I’ve often talked about is patient-centric marketing, patient-centric targeting. That’s been a term that’s out there, but true centricity and being able to connect that patient to the right physician and getting them on the right treatment. The only way we can get true patient centricity and patient engagement is through identity management. I think that’s really, you can use a lot of different third party data that’s out there. We talked about claims data and EMR data, other data sources that are available, lab data that’s out there, that’s great if we can tie these data sources together internally and externally and create this unified view of this patient that’s true patient centric targeting or engaging. And if you can have you be able to study them, be able to analyze them, be able to engage with them, it’s tremendous what the potential is.

And honestly, when I first came on board and I heard learning about first party graphs and identity graphs, it was all very, very new to me because we don’t use that terminology in the life sciences space, but all of this is needed and just talking about it in different ways, I think it’s just a little bit of maybe a language barrier, but we just need to adjust that a little bit. But I think it’s absolutely, people are starting to think about it, digital marketing and digital targeting and how do you reach the right audience faster is absolutely critical. And yeah, this is absolutely needed. And I think I’m hoping more and more companies, we are starting to see this more with the larger pharma companies who have maybe bigger budgets and ability to kind of pivot and a little bit of both, but they are willing to adopt and take some more risks. But now we’re seeing it across the board, even the early stage pharma companies and biotech companies are seeing the value of this.

Kyle Hollaway:

I think certainly the collaborative environment of the cloud coupled with the ability to effectively manage some identity through tokenization and such. But really as you said, I mean it kind of goes all the way to individual touch points with the consumer. So at the physician being able to capture the right data and understand being able to connect that both internally within that physician office to all the other activities going, but then be able to effectively get that tokenized or shared in a manner that’s privacy compliant but is highly effective and accurate, such that then when you start moving over to the provider or certainly if the patient’s even managing their own data and dealing with that way effectively, bringing that together and doing so with the degree of accuracy that you would anticipate is critical in your engagement with the industry players. What’s the general stance on cloud clean rooms and such? What are you hearing from

Sonny Dalal:

Yeah, I mean, as I’m seeing some of the use cases starting to see the cloud and clean rooms, it’s been there, it’s been being utilized. Now oftentimes, to be perfectly honest, I’m working more with the business users, if you will, like the brand teams largely, or the digital and analytics. I see that here, probably that would require a little bit more involvement from the IT and data management team, so understand sort of the value of that. But one interesting use case I would think of is during mergers and acquisitions, I think there’s a lot of m and a happening in the industry right now. Patents are expiring within the pharma space right now. You have with that expiration, more generics coming out. So now how do you replace that? The revenue shortfall, there’s going to be a lot of revenue. So it’s all going to be through acquisitions or licensing deals, licensing new assets, new drugs for larger companies, buying up smaller companies, larger ones who have large commercial operations.

The small ones are more development organization that developing a drug through phase one or phase three clinical study. And then potentially if they have positive data, they’ll get acquired, whether it’s a Lilly or Pfizer or BMS or Merck or GSK, they’ll ultimately, so with that said, clean rooms could be an environment for them to share data and insights between an acquiring firm, a firm to be acquired and being able to share doing the due diligence. That’s just one thing that just came to mind as I’m kind of exploring how that could be leveraged in the marketplace and allowing companies to do some due diligence to see if this is a good fit from a product market perspective to make those types of decisions. It’s one factor. I’m sure there’s many factors evaluating acquisition, but sharing that level of insight would be pretty valuable.

Kyle Hollaway:

Yeah, that’s great. That’s a great angle on that. That is tangential to the actual health data itself in the sense of creating, like I said, the drug or looking for trends, but then also in the m and a side. That’s interesting. When you’re looking at the industry, a lot of, certainly in financial services or other industries, we see a lot of companies building out their own data science and analytic teams really going that data first mentality and really being data driven. What do you see from probably mainly more on the provider side or other pharmaceutical type folks on that?

Sonny Dalal:

Yeah, yeah. I think it’s a trend that’s picking up. In fact, I would joke oftentimes in my recent past is that who do you find yourself competing with sometimes? And I would say sometimes I’m competing with my client because we could do a lot of the work and we’re trying to outsource, having them outsource it to us to do some of the analytics and insights and deliver those insights. And I’m starting to see a lot of my clients who I’ve worked with for several years will ultimately after three, four years of working with them saying, Hey Sonny, we’re going to start building up our data science team and our analytics organization and we’re going to purchase data ourselves and we’re going to do this. And it was kind of wrapping my head around, it’s like, why do you want to do it all yourself? But it started to make a little bit of sense in the industry.

I think there’s this need to have more control. There’s a need to do things a little bit faster, a little bit different than market. As we were talking about. It continues to remain competitive. There’s going to be a lot of competing products in the marketplace. How do you respond faster? So I think companies are building out their data science team, data engineering, data investments. And so that is growing. And I feel there’s some interesting, where I see Acxiom can play in that is to really support and be able to enable a lot of that, having this intelligence hub, allowing them to kind of create and build audiences themselves and activate it, having that more control, perhaps reducing cost of the spend that they have, working with some of the agencies and being more efficient and faster to do some of those digital activation campaigns more rapidly. So while it’s happening, it’s almost like instead of fighting why it’s happening, say, let’s embrace that change. We understand now that this is going to happen. How can we enable you, whether it’s the platform, whether it’s the activation side, whether it’s working with the data that you’ve already purchased, maybe there’s some way we can complement and enhance that data, but then leverage that and help build better models for you or allow you to build your models and activated. So I think flexibility is going to be key in this marketplace on both sides.

Dustin Raney:

Yeah, that’s great. At Acxiom, we get to work with vendors across all different aspects of healthcare from the insurance companies to the pharma companies. And a lot of times, Sonny, the pharma companies, the audiences they’re trying to build and model off of aren’t necessarily B2C your business to consumer patient models. It’s more like healthcare providers because the pharma companies are selling into doctors and who are ultimately going to be the ones. So it’s almost kind of like that wholesale model,

Sonny Dalal:

But

Dustin Raney:

Finding healthcare provider leveraging all that data becomes super interesting, right? Because for instance, if we took a use case, what if doctors are people, they’re consumers that carry phones around and maybe I go to a pharma site, AstraZeneca, whatever, and I’m Dustin Rainey, but I’m also a doctor.

Sonny Dalal:

So

Dustin Raney:

If there’s technology that can bring those things together to personalize an experience, knowing I’m a doctor and knowing that, hey, I have maybe some new drug that you need to understand even before the healthcare or the pharma rep comes into your office, do you see a lot more potential on the side of marketing to healthcare providers? B2B? Almost

Sonny Dalal:

A hundred percent. And I think you hit this. I think there’s this tremendous amount of growth around precision and personalization. And that’s not just at the patient level, it is definitely at the HCP at the physician level as well. So to be able to engage with the physicians with the right message at the right time, whether it’s a branded campaign, the drug’s already on the market or an unbranded campaign that the drug is still in phase two, phase three development. They’re still recruiting patients and they’re waiting for data, but they want to start to get the message out. And I think to be able to find those physicians wherever they are digitally, they might be on ES ESP N or on CNN at night. Doctors are people too, just like you said, I think I heard some term of going from wearing a white coat to blue jeans, I think or something like.

And I think that programmatic targeting non, we call it nonpersonal, but what I mean by non-personal in that sense is that historically pharmaceutical companies, sales reps would engage with their physicians at their physician’s offices or go to the hospitals and whatnot. Getting access was relatively easy, even pre covid or even years prior to that, you could have a sales rep. Nowadays it’s more and more challenging. Getting access to physicians is extremely difficult. Getting the right message to them is becoming more difficult from a physical rep perspective. So this non-personal engagement strategy is digital strategy, digital engagement. It’s absolutely critical. It’s getting to the physician wherever they are whenever they are, whether they’re at a conference and you’re getting a message to their mobile phone and say, come to boot 3 0 5, we’ve got this product. That could be whatever. You can do it to that personal level based on where they are, what sites they’re on, they’re on ESPN in the evening because physicians are consuming information constantly and they don’t have the time during the eight to five hour sometimes to meet and learn about the new medications. And so that’s absolutely critical, personalization, getting to the right position at the right time. But I think you mentioned another interesting point is being able to be more targeted. So we have targeting exercises where in pharma used to do with their target lists, but they’re slowly evolving to that target list to more on a dynamic targeting in the digital world. And I think that’s going to become more and more prevalent. I think physicians want to consume insights information that way too. And we’re seeing the results. We’re seeing results, good results, positive results.

Dustin Raney:

I think it’s probably obvious that a lot of these pharma companies, especially some of the smaller ones, they don’t have a lot of first party data. One of their biggest challenges is they don’t have a lot of data to go do a lot of analytics on, so they need help. So it takes companies like Acxiom that can aggregate this data and do it in a privacy compliant way and then connect it back to healthcare provider type data in a privacy centric way. So you can make that, and obviously Kyle and I we’re identity wants

Sonny Dalal:

Like absolutely

Dustin Raney:

Thing I’ve learned a lot from, right? It’s the thing,

Sonny Dalal:

I think identity is the center of everything really. It really is. And the fact that we’re able to do, I think historically pharma companies realize that this is probably a need and it’s necessary. Now you have chief patient officers, which never existed. We have chief privacy officers that didn’t exist in the past. And I’ve learned that Acxiom was the first one to have a chief privacy officer in the industry. So that’s pretty cool.

So I think to your point, historically in the pharma life sciences space, there was a lot of fear on uncertainty, doubt of can we do this? Can we do it compliantly? So I think it kind of stayed at that level. There wasn’t anyone to give them a sense of confidence that it can be done compliantly with privacy state, being able to identify patients across disparate data sources internally and externally in a way.

And then not just patients, but physicians as well to then get them the right information and be much more effective. And I think now that we can do that, we have the technology, we have the identity, the data, the digital, and created that whole ecosystem. It’s very powerful. And I think pharma companies who are more advanced and more and more are by the minute are starting to see the value of it. And we’re seeing, we’re talking about commercial use cases right now, largely, I mean there’s use cases across the board, whether it’s clinical trial recruitment, which we didn’t touch too much on, but how do you accelerate the trial recruitment, getting patients in, recruited faster, finding sites and investigators, and there’s a lot of use cases that we don’t involve, but an early stage discovery as well. So it’s happening. Pharma companies becoming much more digitally focused, and I think we’re at the right time to really help support that and drive their growth.

Kyle Hollaway:

So obviously you mentioned previously the big players, the lilies, the GSKs and such, and then some of the m and a taking place with smaller entities. Let’s talk about that just a little bit in sense of competition within the market. And also I just keep thinking about things like Strava, wearables, wearable devices, which are capturing health related data on a consumer level, and then what kind of responsibility do they have with integrating into that ecosystem? Do we anticipate that there’s going to be more and more kind of avenues for health data coming into these ecosystems where there’s collaboration and learning, kind of what’s your take on that side of the market?

Sonny Dalal:

Yeah, I mean, I think being in this industry as long as I have, I think there’s always been silos of data sources as we talk. There’s been claims data, there’s been lab data that’s been out there, E-M-R-E-H-R now that a lot of them are being able to commercialize their data sources and being able to start to package it, cleanse it, make it usable, standardize it and whatnot. So absolutely, I think there is this sort of demand, this thirst of what can data do for us and how can we use whether it’s wearables, is a really exciting in another area, another level of, I think innovation and change. I think that it’s still emerging in terms of its, I haven’t personally speaking, not that saying that it hasn’t been happening, but I haven’t seen it much from a commercial use case. I’m starting to see it a little bit more in the clinical use case because there’s a lot of remote clinical trials or let’s say disparate clinical trials that are being done if patients can’t to a particular site, or maybe it allows the patients to be in a trial at home, they might be wearing a device that’s collecting data, and that data then is getting uploaded into the system and then getting to the physician who’s conducting the study and things like that.

So it is starting to get adopted more and more and more. And I think there’s definitely a thirst and an appetite for more data. I think though ultimately, and I think we said earlier in the conversation, is that it’s not just having more data or it’s how do you kind of leverage the value of different data sources, and is it better when it’s integrated potentially? If you tie social data with EMR data and claims data, how much of a better view can you get of that patient? Because every data provides claims, for example, gives you robustness, but may not give you as much depth. E-M-R-E-H-R data, for example, medical records gives you a lot of depth, but may not get you a lot of volume. And so depending on what the goals are, what the business case, business case for the patient or for the physicians will drive the demand for what types of data is going to be needed.

Dustin Raney:

That’s awesome. Well, sunny, unfortunately we are running low on time. I can’t believe it’s already been over 30 minutes wise. That was a quick one. This

Sonny Dalal:

Is great. This is great.

Dustin Raney:

Yeah, I mean there’s just so many exciting things happening in healthcare for sure. Absolutely. It’s just a

Sonny Dalal:

Great time. I’m really excited to see, yeah,

Dustin Raney:

To kind innovate in this area quick, we’ll give you a couple of lightning round questions and then we’ll wrap it up. So you mentioned patents are expiring. Do you see more pressure from the generics and stuff coming in?

Sonny Dalal:

I think so. I think there’ll be pressure from the generics that could drive pricing down a little bit more. I think there’s going to be, with patents expiring, they’re going to have to pricing pressures, but also revenue pressures too. So how are they going to, there’s going to be a shortfall of revenue for these large companies. So tremendous amount of more acquisitions as well will be a big part of that as well, from larger companies and smaller companies and trying to collaborate more effectively.

Dustin Raney:

Okay. Then we’ll make a shift too. So in the banking side, FinTech came in and disrupted the financial services industry. You see the same thing happening in healthcare with health tech. Do you think it’s going to really disrupt the market

Sonny Dalal:

On the tech side? You mean on the health tech side or,

Dustin Raney:

Yeah, just some of these tech companies that are more nimble. You feel like they’re going to come in in the same way as FinTech did

Sonny Dalal:

To disrupt. Yeah. Yeah, actually, I see what you’re saying. Yeah, no, I think so. I think anything else, size and small. So the reason why large pharma companies would require smaller biotech companies is their ability, the smaller one’s, ability to innovate. It’s very expensive to develop a drug. The clinical trial process is long, cumbersome and very expensive. The small companies can develop it faster, much more efficiently. The large company has a commercial arm and commercial operations to be able to bring it to market. Similarly, whether you take the FinTech to the Healthtech side, there’s a lot of innovation at the small. I’ve worked over the last several years, I’ve worked with some VCs in the industry and I talked to them about their portfolio firms. There’s some really cool companies out there that are able to get some capital and really make some innovation with us on the privacy side, compliance side, tech engagement, digital, there’s some really cool stuff. And maybe Acxiom could be the one to acquire some of that over time, too. Yeah.

Dustin Raney:

Alright. Last question. If you fed all the data about Sunny into ai, what are the three words that it would produce to describe

Kyle Hollaway:

Without violating HIPPA?

Sonny Dalal:

Without violating HIPPA? I would say I’m really passionate about the industry, really passionate about the industry, about patients, about healthcare, very ambitious for growth. And I think also really empathetic connector of people and ideas and really, really enjoy that and helping the industry and working, supporting the company as well as patients and physicians in the marketplace.

Kyle Hollaway:

Well, sunny, thank you. I really look forward to spending more time with you in the work life and just seeing you take off and really do great work here in the healthcare and life science industry. So excited about that and really thankful for you just coming on and sharing some of your insights. This is fascinating topic, and I know our listeners, I’m sure there’s a lot of nuggets that we’re able to take from that. And so to our listeners, thank you for joining us and we look forward to further conversations. You can find all of our podcasts at Acxiom.com/real talk and on your favorite podcast platform. So hope to see you out there and thanks again, sunny for joining us.

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