Speaker: The BioWorld Insider Podcast.
Lynn Yoffee: This is the BioWorld Insider podcast. I’m Lynn Yoffee, BioWorld’s publisher. Our guest today is Doron Aspitz, the CEO of Verix. The company recently released a state of the industry report for 2023 that details how pharmaceutical executives are handling the brave new world of artificial intelligence. Verix surveyed directors, vice presidents, and C -level executives in sales, marketing, and brand management roles at pharmas in the US that have more than $100 million in annual revenue. The survey concentrated on the challenges presented by AI in executing a commercial strategy and business considerations for implementing AI tools. Welcome, Doron.
Doron Aspitz: Thank you for having me.
Lynn Yoffee: Doron is here today to discuss the report with Lee Landenberger, a BioWorld staff writer and the BioWorld Insider host. Over to you, Lee.
Lee Landenberger: Thanks, Lynn and Doron. Thank you so much for joining us. It’s a worldwide podcast today. Doron’s in Tel Aviv. I’m in Atlanta and we have a production studio in London, so it’s nice to have everybody connected.
First off, Doron, I really found the survey that you conducted of pharma execs and companies compelling. So if you would, tell us a little bit about your company, Verix, and then also why there was a need to conduct this survey.
Doron Aspitz: So if I start with the company itself, Verix has always been intrigued by the idea of how do you connect strategy to execution, especially in the commercial space, and how do you use data and advanced analytic solutions to really harvest insights and guide execution in a more optimized manner and continue to do that in an eloquent manner.
And so we started our journey in the pharmaceutical commercial operation a few years back and slowly started to realize the need, the disruption that’s been taking place in the industry. And as a result of that, started to build a solution called Tovana, which helps pharmaceutical commercial companies execute better, optimize their execution and target their business opportunities in a much more profound manner that allow better interactions with the HCPs as well as provide patients with the right set of therapeutics.
Lee Landenberger: And then the survey, I guess you want to know what companies need because this is a new, AI is a new thing for them. And they’re just now and really incorporating it steadily. So I’d like to know why you felt the need to conduct the survey.
Doron Aspitz: So if you think for a second, the pharmaceutical industries have gone a fairly dramatic shift over the past few years, moving from general purpose medicine to adopting more precision medicine and precision therapeutics. And that shift essentially is a profound shift.
It’s taking over the entire industry. It’s already more than 50% of the top 100 brands in North America are precision medicine oriented brands. They achieved obviously benefiting tremendously patients, but at the same time it disrupted the way commercial executes their go to market strategy and their understanding of the market ecosystem competition, where are the business opportunities, how to address problems, and many, many different aspects of the go-to-market strategy and execution. And as a result of that, we were intrigued by how the change is taking place in the way they execute and what kind of tools needs to support that execution in a better way, how to address the plethora of data that’s been formed every day and how does that bring the change into the organization? How do they adopt the change, et cetera?
And so that was when we were as executive team wrestling with those questions, we sort of thought it might be a good idea to put together a survey, a more professional survey, go to the market and solicit some feedback from people that really are having those sorts of problems on a day-by-day basis.
Lee Landenberger: Well, let’s dive into some of the data that you harvested. So in one of the key takeaways of the survey results, you found that 74 % of executives that you surveyed cited a lack of automation as a major challenge for getting timely insights. Can you give me some insight on what those challenges were and what kind of problems that they present to companies?
Doron Aspitz: Absolutely. If you think about it, the industry grew up with many different consulting companies that provide services to the commercial operation in various capacities and various business use cases. And as I indicated earlier, that change actually necessitated a different approach to solving problems and enhancing the use cases with different data sets and different analytic methodologies, all of which are more complicated to do manually, or even use episodic tools or ad hoc approach to answering a business question. And that started to create this plethora of one-time type solution or episodic approach to solving problems or what I call one-and-done. You run an AI ML model, you predict what’s gonna be the right target. And then the next time you do that is probably nine months later.
But as you know, optimizing execution, improving execution is about a methodical approach to solving problem on a continuous ongoing basis and that necessitated basically automation. The data is too vast, the problems are too complicated addressing one particular action may sometimes require five to 10 different predictive models to arrive at what I call dynamic targets or better forecast or targeting. So that meant that you can no longer do that in an episodic manner, but rather a more holistic approach, automated such that you can reap off the rewards of doing that.
And it essentially, if you keep doing it manually, your insights, inside generation production flow is much slower, it’s much less accurate, it’s more prone to error and consequently decreases the quality of engagement with HCPs and patients and it decreases the agility and you’re really missing the mark on what technology can bring to the table. That’s not to mention that it’s hard to assemble already unavailable data assets in an integrated fashion. It’s really…all of those problems really stand in the way of optimized execution and accelerating brand growth. And that’s what we’ve seen through the research where people really manifested those type of problems.
Lee Landenberger: I see in the responses that 82% of the executives that you surveyed said that they do not have the proper tools for redeploying AI models across their brand portfolio. And that hinders their ability to implement AI-driven analytics at scale. Could you expand on that a little bit for us?
Doron Aspitz: Absolutely. I think every one of us used Excel at some fashion or, and as you know, Excel is the most interesting tool or I’d call it sophisticated tool, but it lacks context, it lacks understanding of your particular set of questions. And the same issue comes with AI ML tools. In fact, there are many, many tools.
AWS is fraught with those environments and services and tools and whatnots, many others. But the thing is they’re mostly horizontal tools. They lack the understanding of pharmaceutical commercial execution. They lack the understanding of a brand. All those contextual concepts that needs to come to bear when you solve a business question needs to be built into those solutions.
So essentially you have a couple of approaches. You can do, build them every time you have a business question, you can build them from scratch, or you can take platforms like Tovana that we’ve generated, introduce that platform or set of tools that you stitch together, this profound deep knowledge of and understanding of what is pharmaceutical, how they operate, what are the problems, what are the questions, who are the various personas that play a role in that complex go-to-market strategy. And once you’ve done that, you now can automate and start to run and harvest insights and provide guidance to the various operating units, the marketing, the sales, the managed market, the MSS, all of those. And so that need is what stands in the way. It’s not the question of the tools or …
The tools are the tools, you just need to kind of educate them and bring them up to where they can provide a much more automated quality solution. And that’s what we’ve done with Tovana.
Lee Landenberger: So a large majority of the executives that you surveyed said that they believe their organization’s revenues would be significantly increased if they had stronger insights. Can you tell us a little more about those results?
Doron Aspitz: Well, it’s interesting. I mean, I’ll give you a few examples of what they mean by that. When we step into an account for working together collaboratively to understand their ecosystem, their brand, execution, their competition, et cetera, we find just a simple example. We find oftentimes, almost about 40% of the targets are inaccurate targets. They’re not tiered correctly. Some of them are even not relevant. And especially in a precision medicine, that is the case.
The fact that potentially a size of a clinic is large, but your brand treats specific mutation of an oncology disease sometimes render that particular clinic mood because they don’t have such patients or they have a low mix of such patients. And so that understanding of the internal execution on the ACP side and the patient population, et cetera, necessitate different type of approach.
And so if you think about it, if you start addressing the wrong areas, you spend a lot of energy on the wrong directions, or primarily the wrong directions, and you spend a lot of marketing dollars on being ineffective, then you start to lose opportunities, and you’re not really optimizing execution. And so what I’m pointing out is that you have tremendous amount of data, you have the tools available.
And so being able to actually harness all of that into production environment would give you the benefit. And if you don’t do that, then you’re missing the opportunities. The point being is that accurate predictive insights lead to a better targeting, which leads to a better message, which leads to a better HCP engagement. The HCP found the information you provided more pertinent.
And then as a result of that, you now have an optimized sales and marketing execution, which then leads to growth.
And if you miss all that, obviously you’ve missed the mark.
Lee Landenberger: All right. The budget the company set for AI data and analytics are dramatically increasing, especially this year compared to previous years. Doron, can you tell me what that tells you about the future of this kind of a technology?
Doron Aspitz: As I said earlier, I think this is really fascinating because I see more and more companies every day looking to increase the efficiency and what’s encouraging about it is that merely the name precision medicine means that you want to be precise in the way you provide guidance and you want to be able to provide therapeutics to the right patients, and et cetera, et cetera. And that is really encouraging, meaning from sort of a spray and pray type methodology, the industry is moving into a more precise execution, into more precise providing HCPs and patients with more appropriate material and improving the overall patient health care if you think about it and that precision idea that was born way a few years back, starting now to shape up in a manner that allows HCPs and patients to be getting the right diagnosis and the right therapeutic in a much more strong manner and being supported by the pharmaceutical and that’s encouraging to me as far as the pace at which companies are providing that kind of support.
Lee Landenberger: Yeah. So, when you got all the survey results and you had a chance to look back on everything that you, that you got, were there any surprises for you that jumped out from the responses?
Doron Aspitz: It’s a good, very good question. I don’t know if I call it necessarily a surprise, but if you think about it, there are many markets that already are using AI and digital transformation, adoption is a natural step in the market evolution.
And so… and that usually transformation happens when a market really experiences significant disruption, which is what I was talking about, the move from general purpose medicine to more precision type medicine. And so that started to necessitate that transformation.
And what you start to see is this cross pollination between different markets either CPG, consumer packaged goods and retail and FinTech and et cetera, providing some more, I wouldn’t call it guidance, but providing technology, domain expertise and people. You see in the industry, people that are taking high level position that you wouldn’t think or they didn’t necessarily grow up in the pharmaceutical space. And that’s actually an interesting maneuver that is we see it every day of the week, right? I mean, take a look at some of the leaders of the organizations today coming from different industries. So you see that move to digital transformation, you see that move to this cross pollination, what I call it.
And then you see the AI tools and technology to drive that efficiency starting to come in into the marketplace in a more profound manner. And then that’s…I wouldn’t call it a surprise, but it’s actually great to witness and experience and understand the amount of excitement inside the commercial operation and eager to change.
Lee Landenberger: Yeah, terrific. Is there anything that we didn’t talk about that you’d like to mention?
Doron Aspitz: I think that the thing that was interesting to us to understand, and I don’t think we understood it initially, and it’s something that we’re working feverishly to adopt, is this thinking about, okay, we’re doing the transformation, AI tools, new data sets, new approaches, targeting, forecasting, all of that, but then can we as vendors help enable that technology to be integrated with all the ecosystem and be more immersed with existing working environments within the pharmaceutical. And I think that’s a need that came out from the survey. And we were somewhat very intrigued by that story.
And so as we started to learn more and more about it, it makes perfect sense where if you really want to change from within, you got to be integrated within the existing environments, the CRM, the different business use cases, the different tools that they’re using environments such that you make life more integrated and therefore allowing the flow of information and decision making much more streamlined.
Lee Landenberger: Great. Doron, thanks for your time and your insights. I appreciate it and I want to wish you the best of luck to you and the company.
Doron Aspitz: Thank you so much for having me, I really appreciate that.
Lee Landenberger: Oh, it’s our pleasure. Lynn, back to you.
Lynn Yoffee: This is such an interesting topic and AI is developing so rapidly. I think we should check back in with Doron in a year. Hopefully he’ll do the survey again to see just how much has changed and been updated in such a short period of time.
That’s our show for today. As always, BioWorld will continue to keep you informed of all the most important scientific, clinical, regulatory, and business updates. We’re a daily news service covering drug development. If you need to track the development of drugs, turn to bioworld.com. Follow us on X or email us at Newsdesk@bioworld.com to get in touch. Also, if you’re enjoying the podcast, don’t forget to subscribe. Thanks for joining us.
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