Breaking Down Silos with Ian Crone: Regulatory Data, IDMP, and AI Readiness in Life Sciences

Narrator: On this podcast you'll find interviews with high performing successful individuals in life sciences on a weekly basis. We cover their proven methods, principles, strategies and mindsets to implement new technologies that scale to meet the needs of people in our world.

Don: Welcome to this episode of Watch Science Success. For those of you who don't know me, my name is Don and I'm a digital marketer in life sciences. And so today my guest is Ian Krohn. Ian is the VP of uh, Regulatory and Strategy and Growth at Aris Global. And so with that, welcome Ian. It's great to have you on the Life Science Success podcast.

Ian Krohn: Thank you Don. It's my pleasure to be here.

Don: Yeah, thanks a lot. Would you mind just taking us back a little bit in your history? We were talking just before you got started recording here. Um, I'd love to hear a little bit more about your journey, what it is that brought you to life sciences and what is it that drew you

Ian Krohn: to this field that's really interesting. So I was thinking about this one and when I look back at uh, my history, I started in life science industry and I always throw back to the idea of I'm driven by science and what actually happened on the laboratory bench. When I think back, I started at Unilever as a lab technician and I worked my way up and I saw everything from development of um, a raw material compound right the way through to synthesis of a product. And I saw the way that that always happened in chemistry and had always been at the heart of what I was doing. And then I slowly progressed within the industry and I have very lucky to say that I've worked everywhere from compound to clinical trial. I worked for uh, large amount of big companies with data and silos of data. On the regulatory side, I was privileged to be one of the founder members of a company called Samrin that we developed a room solution. We brought the first UDI solution to the market with partnership with Vesenius Kabi. Um, and I, I really am passionate about learning and I've listened to a lot of my peers like Fritz Stop, Rebco Munich, Andrew Marwood, a friend of mine, and I adopted this knowledge all along and I absorbed it like a sponge. And I feel that um, it's really useful to learn from the experience that you have and the peers that you work with.

Don: Yeah, absolutely. And um, I mean our history, our history. I mean that's one of the advantages I feel like as well. But you know, through um, our history, not only do we build relationships, we also build that core knowledge right and um, it's just really important as it continues on.

Ian Krohn: Totally agree. And if you think about, even with my journey, the way it happened, you know, when I talked to you about the UDI situation, my very first stages, working with Vesenius, with companies like people like doctor, Dr. McHale, uh, uh, who was head of regulatory at Vesenius at that time, UDI was something that was, you know, a dream about. And we were building a system ahead of udi. And um, that really came about because of the challenges of breast implants and all the regulations around there. And now we see the latest challenges about IDMP and where that's been evolving. So I think that having a science solid route from Unilever has really helped me understand that not just in that industry, but in lots of industry, there's bottlenecks. Um, and what I've been really surprised to see is how that knowledge from those days has come back to the, to where we are now. Because if you look now in Unilever and Procter and Gamble and other companies, they're hiring regulatory people because they realize they are, you know, bound to the same regulations. So I see that all this knowledge is coming through and helping me.

Don: Yeah, I think it's funny because one of my last podcasts was, ah, with a quality person. And they were saying, you know, look, I mean, we constantly, um, are pressured one way or the other. And um, I feel like these things are investments in a company like you may not fully understand. And it might not be as obvious whenever you do it, but I mean, you think about some of your, whether it's the RIM or UDI or IDMP experience. Right. I mean, some of these things have evolved over time and you know, they didn't start out necessarily where they are.

Ian Krohn: No. Uh, and they are evolving, you know, massively. They're evolving. And companies, some companies in my opinion, are still very much in a siloed approach and an attitude of we don't need to do it. But if you take idmp, one of the biggest challenges and for the benefit of everyone, what is idmp? It's the identification of medicinal products. Really. It's one of the biggest changes in the industry. Essentially what it is is a universal language for medicines to ensure regulatories in Europe or the US are looking exactly the same substance of data. And I felt that it's a bit of a deja vu when you look at 2017 was the deadline when we all should have been complying to idmp. And it's now that it's really real and ah, companies are going right. Well we do need to react to IDMP and you know, today what's different EMA sport rollout. And it's that phased approach. And what I say to companies is it wasn't about running a marathon. It's about you know, sitting down and thinking, well I can't run this marathon, I'm running a marathon and I need partners, I need to pass that baton to other people along the way. And it's really the companies that have really thought about the quality of their data have been the ones that are going to be successful and any of these projects that are going on AI I know, we'll touch that later. It's always about the foundation of the quality of the data that makes it successful or not.

Don: Yeah, I mean for anybody that doesn't know yearning right. I, I mean one of the things in researching for this podcast that I, I benefited from was the fact that you, you write pretty prolifically, prolifically about you know, the things that are impacting the regulatory space. So um, it made it made my job easier. But also like anybody that's interested in these topics, I would encourage them to go back and look that you look at your LinkedIn page and just trace through a couple of articles that you, that you've written. But I want to bring you back a little bit in terms of um, one of the specific things that you just mentioned a second ago was this regulatory deja vu.

Speaker D: Right.

Don: And uh, an IDMP deadline. So um, as you sort of look at um, things, you know, what is it that the industry, you know, really needs to do different now in this phase rollout.

Ian Krohn: That's really an interesting question. I think the challenge is that companies need to sit down and think about what is the, what is, what are they trying to achieve really. And um, okay, IDMP M is just one part of, goes back to having that structured data. It goes back to really thinking about master data management. And if you get that right, it's going to improve the efficiencies in the organization. One of the big challenges around um, the regulatory role, you know, I've talked quite extensively about how a regulatory role is changing in an organization. You know, it's massively changing that they are really now a gatekeeper and have an even more point of content in within an organization. And one of the big things you talk about references to the papers I write, I write those papers because I feel that there's a lot of younger people that coming into the industry are regulatory that are lost. They might have A degree. And, you know, a huge amount of work goes in to get degrees in regulatory. And I'm a massive fan of the Topper organization. But it's really understanding, okay, how do I translate that into real things that are tangible, that are, uh, challenges in the industry, and then how are we going to overcome them? And a big one was the single source of truth. Right. You go back to a day when I was a really good colleague of mine, Olaf Shupka, and we sat down and we talked about it and we said, you know, what is the holy grail? The holy grail to us was that you would enter data once into a system and you could use it multiple times across the whole of the system. So it was real quality data entry, but also driving efficiencies and the quality of the organization. And there's so. And um, compliance really. And when we look at it, we think about it. Have we really got a single source of truth in an organization? And I pose that question and, um, just stop and think about it. And what I think is we truly haven't. We've still got single source of truth, but in silos. And I think it's a challenge that the industry is still having to think about. And we need to think about that single fabric of understanding the data and how we actually make use of that across the whole of the enterprise of an organization. And I still think there's work to be done on that.

Don: Yeah, yeah. I mean, in terms of, you know, how the, how the industry applies a single source of truth as well, um, you know, one of the things that you wrote about was that you treat the, that the industry treated it as, you know, a massive data migration project and it didn't work. So why did that approach fail? And then what did it teach the industry?

Speaker D: You think?

Ian Krohn: Well, I think the thing or thing is that most companies think when they're, uh, doing these migrations of data that a big bang approach is the way to do it. Right. Let's just do a big bang approach. And truly, that isn't the way to do it. What you have to do is to, as I call it, do it as an incubator project, do a phase zero approach. So take a selection of your data across the range, look at it, map it to whatever system that you're moving from and how you're going to do it, and then think about how and, um, what resources you need on your side to make it work, whether that be project manager, program manager, whatever on your side, but also the vendors that you're working with that, they're going to need migration leads, tech leads and all the other things. And you do it in a phased approach with this phase zero. You also assess the quality of the infrastructure that you have to make it work because too many times people don't think of this. And then you run the project based on doing that phase zero. So you can actually then get a realistic timeline of how long um, the project's going to take, what the risks are, how you mitigating the project. And then also you have to start thinking a bit more about you've gone to your board and you've gone, I need this budget to do this project. You don't want on day one when you start the project going, actually we're overrunning so you have to keep control of it. And I think in one of my articles I said it's like you don't want to run away train. So it's that really thinking carefully about who you want, who are you going to have in your team, who are you partnering with and then thinking about, okay, we do this in a phased approach and then we scale it from a phase and that from my experience of working with several large blue chip companies on very um, complex projects, that that's the way to be success and then you can all celebrate together.

Don: The nice thing for any company too, I would think is having this data alignment's gotta be powerful.

Ian Krohn: Yeah, it massively is. And um, it's alignment for a lot of reasons because you can use the data between the whole organization. If you have these master data projects, uh, in the background, you know, there's a lot of challenges in the industry and you might have decided on a RIM platform, whoever that may be, and you may then start doing RFIs and RFPs to look at mainly the RFI first stage to look at what else the company is doing, the competitors to look the system you have at present. And if you own that master data management system, it's very easy to move your data from one system to another once you've cleaned up your data. But you know, I could name one client that I'm um, a, ah, big blue chip company. And I remember I was sitting with C level and I was saying to them, you know, okay, you've decided on this vendor, you know, and they said, yeah, we have, uh, is it the right vendor? We don't know. But what we do know is it's a good way for us to structure and start cleaning up our data. And if we have a master data management project in the background, then you can do all the things I just talked about. So I think that's really important.

Don: Yeah, absolutely. And like you said, I mean we'll get back around to like AI and some of the tools as well, um, in some of the later questions. But I mean I really think it's a good time to do a lot of this stuff as well because of some of the enablement. But uh, yeah, um, so you describe what you call the telephone game problem or interpretive drift, um, where data loses its m meaning as it moves from clinical trial protocol to submission dossier. Um, could you give our listeners a real world example of how this plays out and why it's so dangerous?

Ian Krohn: Yeah. So I saw firsthand, ah, from moving from that lab bench to manufacturing in early in my career in pharma, a clinical um, team might define a dossier as from, as simple as a tablet. When it moves to a regulatory team for a submission, it gets translated to a film coated tablet. By the time it hits a supply chain or pharmacovigilance, the, the content's entirely different, it's in a different advised thing and we talk about adverse events accounts and then the safety system might not connect to the dots back again. So the original clinical profile is changing and um, that's really a drift that creates blind spots and slows down safety signaling and fundamentally risk to the patient and safety. So it's that that I've seen happening.

Speaker D: Really.

Don: Yeah. And then you've also um, contrasted uh, the science approach with what you call pragmatism over pedigree for a regulatory affairs leader reading, you know, any, and feeling any of that pressure, what's the core message you want them to hear?

Ian Krohn: Um, that's a really interesting question. So I think the core thing goes down to if you, if you sit across the table with executives or IT and projects, uh, you've got to think about it and you've all got to think on the same page. You've got to get alignment and you have to get alignment within the organization of realizing what, what all the stakeholders are looking for. And then how do you get a solution that fits what they're asking for and realize that you might not get everything all at once. And then this goes back to the huge challenge in the industry, as in take the RIM market. Do you go for a vendor that says I can offer you a rim, uh, event, a solution that basically will have regulatory pharmacovigilance, everything from publishing of ECTD all in one huge solution that really is there or do you look at it and go, do we go a best of breed approach and do we go for a company that has the architecture with the RIM and the data? But maybe the medical device is a separate solution and uh, maybe publishing is another solution, but it's all linked together with API and architecture. That's the debate that you have to have in an organization. And is there a right answer or is there a wrong answer? Um, there isn't really. It depends on the organization. But all I can say is when I go back to my time being a consultant at Sigma Aldridge, I remember sitting around the table with people like Bill Burns, the ex CEO of Roche, and probably people like uh, the CEO of GSK at the time. They would say to me that they look for companies to take more companies under their umbrella and provide a total solution. But the other thing is not many pharma companies go with one vendor across the whole of their system because it's too risky. So I think that if you do the thing that I'm saying and consider the best of breed approach, I think that is a way to be successful. But it goes back to that. You have to align with your stakeholders, you really have to sit around with them, um, and sit around and understand the challenges you're all trying to face. You're not going to solve every problem and really think carefully how do you move forward as a team.

Don: The other analogy, and I'm, I constantly tell, you know, people, look, I mean, whenever you look at me, I'm an old guy, right? And I mean I certainly have lived through a lot of different technological advances in my lifetime and it's amazing to me all the new things that continue to come in our space. But back to the best of breed versus you know, do I want the combination? Right? I mean, and you know, there's, there's a, I think whenever you get a really good Swiss army knife, it's great to have a really good Swiss army knife because it has all the things built into wine. But the one thing I liken back for a lot of people is if you can remember the days whenever VHS and DVD were built into your television, a, uh, big tube television, normally one of the three would die first. And you had to decide like, am I going to get rid of the thing? Am I going to try and do something still with the thing or not. And to me it's the same thing in terms of technology today. It's like, hey look, you could buy the combo version and it might work well for you for a While, however, like what if one of those things starts to not work as well? What do you do then? Um, you know, becomes a key decision for the organization as well.

Ian Krohn: It's a massive decision. And I think personally from what I see in the industry, I think times are changing. I think if I look at the number one publishing tool in the market, it's probably Lorenz is the biggest publishing tool. If I look at the number one medical device solution, I'd probably say it's company Ramses. You have to look at the expertise of what you're trying to achieve and one cap does not fit all. You've got to look at your organization, the spend, the savings and all the other pieces to really think about what it is. And I talk about in one of the articles, we're all on um, a digitalization transformation journey. But the vendors need to align with the actual customers to see where they're at on the journey and how do we all work together on that journey. It's really important.

Don: This is my last question in terms of like background questions and then we'll kind of move on to Aeris Global in the next section. But just really interested in hearing how do you balance the need for long term data strategy with the reality that the compliance clock is ticking today?

Ian Krohn: Uh, really interesting question. Um, the compliance clock is ticking. Why is the compliance clock ticking? Because the way that we develop drugs has changed. Right. And the way we develop drugs, the biggest challenge change in the industry I would say was Covid. Right. Typically a drug used to take 10 years to develop. So you did have that time to redefine and all those other things. Whereas now you haven't got that time. Typically now they're wanting drugs to market in 10 months. Is that the right way? No, but I can't say right at the end of the day that's what's happening. But what is actually meaning is more and more important is your data structure going to be cruden up the scrutinized to the hills and you have to make sure that you're adopting these things. And you know, I know at some point we're going to talk about AI, but that's a huge shift in the industry. Every single company I can name has got an AI strategy. But what those AI strategies give are all going to be different in different organizations. Right? The way from a HR company using it through to manufacturing using it, everybody's looking at different things different way in a lens. But my major thing I would say is that because of this drug development push, you've got to drive more efficiencies within the organization. You have to think very strategically about the partners that you want to work with and, um, where they're going in this digitalization journey. And you have to also think about the staff that you have in your organization, not to reduce your staff like a lot of people seem to think. That's not the way I feel. I feel it's about thinking about the core competencies of the people that you have in the organization and seeing that they have the right skill sets to help you grow as you're doing to be, number one, compliance and number two, getting your drug to market quicker, to obviously make revenue. And that's what my view on that one.

Don: Yeah, I mean, I would say I'm very aligned with you even on, like, the marketing side. Because, look, I mean, we can take any message that you want to put out there with AI. And I can create a ton of AI sloth. I can create stuff that doesn't resonate with people, stuff that doesn't answer core questions. And you kind of think about it's even more risky in your face because, like, you know, you think about the fact that, you know, now we could take that AI swap and if there are people or humans watching it and going, hey, this isn't exactly right. There's something else that needs to be said or added or removed.

Speaker D: Yeah.

Don: So I, I mean, I, I agree with you. I think we're going to be in this period of time where the companies that go, hey, look, I'm eliminating these jobs because, uh, AI is now replaced those jobs. They're going to be coming back later and going, well, wait a minute. I probably shouldn't have p the trigger so quick. And you know, unfortunately, my business is suffering because people are seeing this. And I just, I, I like to like it as AI slop. It's just, you know, AI's really good at doing things and doing things fast. It's not necessarily always good at doing things, uh, in the best way. And so that's where humans still have to come back and check.

Ian Krohn: I think it's so, so important. I think it's like you can't take the human out the loop of where AI is going. AI really is important, but so is a human. Because we need to have that interaction, we need to have that decision making and checking to make sure in confidence more and more things will happen. Because AI is only as good as the data that you build it on the foundation. And that goes back to, as I said, the master Data and the learning of the AI really. But you know, it's something we have to embrace and we should embrace, but we embrace it in the right way.

Don: Yeah, absolutely. So let's talk a little bit about Aerith Global and uh, what you guys are doing. Specifically you described Sporify as an intelligent agile bridge rather than a rip and replace solution. So how does that work in practice? Um, and where are you seeing this fit in the industry?

Ian Krohn: Okay, that's a really interesting question. So let's just take a step back and think. Okay, I left recently, um, a company that was number one in the industry for data migrations. That took me to some really difficult conversations, um, with companies and also some really challenging projects. You know, and I built some really great contacts and um, friends working with on some really challenging projects. But I decided that I wanted to leave, um, that business and I wanted to go back into a vendor in the RIM type space. So I evaluated all the plays, uh, I looked at them and thought about where they were and I landed in now, um, Ares Global. And why exactly did I land in Ares Global? Because I joined Ares Global to drive this regulatory strategy and growth because I passionately believe that the industry is looking for a new solution. And um, when I say a new solution, let me try and explain a little bit more. Well, their technology aligns perfectly with my philosophy. Instead of forcing companies into this traumatic high risk data migration, Spotify connects to the existing RIM system, whether that be VIVA or what. And it's a non invasive overlay. So while it scans the existing data, identifies the gaps against the EMA spore, and then it will give you suggestions and corrections, which means you can do the right things at the right time. And um, what it also will do will help you with your IT ecosystem. So we can actually put Spotify into somebody who's a VIVA client and works perfectly well in that way. If you were purchasing the new Ares Global, um, lightsphere products, it's built into it from day one. So it's very important. And now obviously because of all these regulations of EMAs and spore, it's real that you have to be IDMP compliant. And that's, you know, a really powerful tool that we have in there, uh, along with other capabilities in AI that we can talk to as well.

Don: So let's talk a little bit as well about the Cross Domain Intelligence or xdi, uh, which you call the data cortex. That's a vivid metaphor for me as well. And um, you know, how does, how does XDI let a safety Team and a regulatory team keep each other others own language while still achieving IDMP compliance underneath.

Ian Krohn: That's interesting. So the human cortex processes information from different senses and turns it into a single understanding. A safety team thinks to say medra, a regulatory team thinks in idmp if you force them to speak the exact same language this will destroy the domain expertise. XCI sits between them as a real time translation engine that they both keep the specific workflows and terminology but the business achieves the total underlying effect. So where I see XDI is, and um, this is my personal vision is we talked about the single source of truth. If you had XCI over all your system you would have a single source of truth because you'd be able to drill down to all the information. And XCI is something that is evolving. Okay. So what we're doing at the moment is we're doing it in a very staged and staggered approach. You know we were the first to launch agentic AI and capabilities like that very successfully against in the pharmacovigilance side and in the regulatory. So XDI is really launching into straight away the pharmacovigilance and um, we're then going to move it towards the regulatory space too where we see the need is really important. So it's a stage approach, it's very much controlled approach and it's very much going to see the clients sitting around the table and saying where are your problems? And then how could this solution potentially help you going forward? So it's very consultative and it's very much that we're working with select companies to really get on board in this journey of this exciting thing of XVN

Don: makes a lot of sense. So I've also heard you say as well that you can't have smart AI with DOM data, uh, with everybody racing towards generative AI and autonomous agents and life sciences. How does getting your IDMP foundation right become the competitor's advantage rather than just a compliant checkbox?

Ian Krohn: Interesting point. So AI is essentially an advanced pattern of recognition, right? Recognition engine, isn't it? If you feed it, it's fragmented. It's that telephone game data where I talked about, if we confidently think about it, because IDMP forces you to get into structure and uh, governs the product data doing the hard work of compliance and today builds that clean data foundation you're going to require for enterprise AI, uh, for now and tomorrow. So the organizations that treat IDMP as a strategic baseline will be those that will be autonomous agents and actually will generate work and efficiency.

Don: Yeah, makes Makes a lot of sense. It makes a lot of sense because, uh, I do feel like we're at a building block, right? I mean, the future, who knows what the future is still? I mean, there's a lot of stuff that still keeps getting thrown at all of us, I feel like on a daily or, you know, weekly basis.

Ian Krohn: So, yeah, if you think, if we go back and we think about what was the biggest change in all our, uh, lives? Well, obviously the Internet, right? Think how that's evolved. And now we've got this new thing of AI and you know, your children are using AI and everything else is going on. And then, you know, I think is such a powerful tool, but the tool needs to be used correctly. And, um, the other thing is a caveat where I think I wrote one of the articles on it, which is it's okay to fail. Right. Not every project is going to work. It's a learning curve thing. It goes back to my days of being a scientist on a bench. Not every experiment works, but the one that does work and is successful goes out to a product. And just think how they roll out globally around the world. It's the same with AI. We have to treat it very much as incubator projects, working very closely with industry and then working out where is the benefits to them, that is driving efficiencies within the organization, improving safety, improving compliance, or all those wonderful things we're all striving for. And that's where I think things are important to think about.

Don: Yeah, absolutely. Um, also in terms of your leadership, right. So I've seen that you've led people in Europe, people in apac. Um, what is your philosophy on leading technical teams through high stakes regulatory programs where the deadline pressure is so intense?

Ian Krohn: That's really, uh, an interesting question and a cool question. So I always, uh, believe passionately, if I go back to my days of starting out, I have some great mentors in Unilever. Ian Rob, who's a world expert in polymer chemistry. Another, um, guy was Stuart Carr, who was a zeolite expert. And then in my other days in the pharma world, I had people like Andrew Marr, as I said, personal friend, but also a great knowledge expert. And then people like John F. Mills, one of the founders of Covance. I had the pleasure of working with him. I think about this regularly and I do mentor people because I think it's a great thing to do. So I think an early person told me about mentoring. You manage systems, but your people are people. And when you're dealing with complex scientific instruments like RIM data migrations, it's easy to treat teams like algorithm, but people need context and they need safety, they need reassurance, they need focus, they need fostering and they need to have that understanding that you are truly there to listen to mental and to guide them in the knowledge that you learn. And as I said, I'm very lucky to say that I've had some m outstanding people who've given me that mentorship and I love doing it for the younger generation, whether that be someone who says, I've just come out of university and I've got a degree in regulatory. What do I do next? So I wrote series of articles to try and help them or to try and think about what's all this terminology of idmp. And I called it Alphabet soup. And that got quite a lot of interest in the industry because we all taught terminology. So I think that we have to realize that it's good to give something back. And I really do passionately believe in that.

Don: What's the greatest piece of leadership advice that you've ever gotten?

Ian Krohn: It's okay to fail and to realize that everybody has strengths and weaknesses. And if you have a team of people that you want to surround yourself with a team of people that are, uh, better than you in some areas, really that's a smart way of managing people, is having people who bring that knowledge base that you haven't got, but realize that it's a team basically that makes things successful.

Speaker D: Yeah.

Don: So I have just some rapid fire questions for you here at the end. What inspires you?

Ian Krohn: What inspires me? M a tangible connection, really. So what do I mean by that? So knowing what I do is helping in some way to improve patients and um, get drugs to market faster and safer. Because why is that important to me? If anyone does follow me on LinkedIn, they'll see there was a turning point. And it was in fact, when I, um, left the company, my own father was diagnosed with cancer. And I was on a plane, just landed in, uh, Japan. I got a phone call from my wife and she basically said, your dad's just been to the doctors and he's being diagnosed with terminal cancer. And I was like, what? What? You know, And I basically got on a plane. I didn't even check into Japan, Nikita Airport. I got on a plane, I flew back, uh, had equity in a business, which was Samarind. I sold my equity outlet business and I'd convinced my management and um, partners to let me go. And I spent a year of seeing my dad to the end with cancer and when you do something like that. I actually got to know my father more than I've ever done in my whole life because he was very career focused, brilliant father. Um, but he inspired me, um, by the way he coped with cancer and how he coped with it and right to the end. So that is my thing that I think about that on a daily basis and I think about anything I can do to drive efficiencies and really think about how we can get drugs to market safer and faster. Um, I'm all in. I'm signing for that.

Don: Yeah. Well, first of all, sorry to hear about your father. Um, great to hear about the experience though, because obviously, you know, one, the closer we get to anybody's story, the better. And uh, thank you for, for sharing that. What concerns you,

Ian Krohn: the gap between AI marketing hype and the actual data readiness, that's what concerns me. So I worry that companies are, ah, deploying AI before they've done that, really thinking about cleaner cleaning up their data. Right. So that's why I say AI is one part of an organization. It's about though thinking about where you are in your digitalization journey. And you know, I've seen so many companies, mergers and acquisitions in some of the big generic companies I was involved in where they buy another portfolio and they're trying to merge into another company. And the ultimate game is obviously they want to get it out to market as quickly as possible and then they find that it's in a legacy data and it's not being set up properly and the challenges around that. But what I do see is there is big advantages now with the AI capability. And you know, my own personal view is data migrations will be totally different because of AI, because you won't need to do as many data migrations because the AI will do it automatically. So I think some of these migration companies, sadly, unless they evolve to these new ways of AI, will be, you know, turning into the dinosaurs like Documentum has.

Don: Yeah, it's funny that you say that because I had somebody give me something that was complete garbage a couple weeks ago. It was, uh, if you could think, if you could envision a spreadsheet, but essentially you, uh, had names in one columns and then in the next column they'd add email addresses. In the very next column without, without much explanation they had another set of names and then the next column had another set of email addresses and some of them had blanks all over the place. And I was like, I have no, I mean and essentially the question was, could you put this in the CRM and can you email, you know, the people that are on this list? And so I remember looking at it for a while. I was like, you know what? I'm going to just try putting it into AI and I'm going to see what comes back and see if we can't get, like, one aligned list with names and email addresses so we can do what the client asks. And, um, whenever I handed it back, they were like, how did you do that? And it was like, thank goodness I could do it, because I honestly, I couldn't even see M, you know, giving it to my administrator and saying, hey, look, can you sort this out for me? Because you would have been working on it for, I don't know, a month or two.

Ian Krohn: Yeah. And that's a prime example of where AI can massively help you. But you still needed that human in the loop, right? You still needed you to have the idea of using AI, asking IT questions to be able to do it. Right? That's the thing. So it's a mixture of both those things. I go to meetings and I take notes down. And, um, when I take the notes down at a meeting, I tend to do it the way my brain works. I take one word and I have a very good memory. I remember everything about things. And then what I do is I dictate it into a phone and go, right, the meeting was about this. We talked about this and this and this. I put the points down and then I get that information and I'll put it into a thing and say, right, use my notes here, make it into professional set of minutes, and it will really amazing. But you have to know the information that you put into it. It structures it, it practices typing and all the other pieces saves you so much time, right? It's not that I'm not taking the notes down in the meeting, it's just my brain is like, you know, I could tell you everything we talked about today. And, um, people are like, how can you do that? And I remember one of my companies, um, I was with, uh, I'll name it, it was Dirk Bode, my CEO of fme. And he said to me, ian, you've been in this meeting, it's very rude. You haven't actually taken any notes down. And I, again, I will share with you and be totally honest. As a child, I was on the verge of dyslexia. And it really, really worried me and concerned me. But then I found I had a gift. And my gift is I don't forget things and I remember everything. And Dirk said to me something. I said, okay, so you asked me this, this, this and this. And we went through it and he was astounded. I said, yeah, I have a weakness, but I have a strength. And I've made that strength really make overrule it. And he actually, you know, was quite impressed and surprised and shocked in one thing. And I think that's the key to being in where you embrace the tools that you have. We all have weaknesses and strengths and we, we do what we need to do to make ourselves, um, drive efficiencies in ourselves and in the jobs we do.

Don: Absolutely. Thank you for sharing that. And last question. What Exciting.

Ian Krohn: Wow. Breaking down silos. I love going into companies. When a company says, we don't need that, we've got it covered. And then because I have the knowledge and experience from lots of other companies, I can turn that around and I can actually sit around and say to them, okay, you might have that covered, but have you thought about this? Have you really sat down and thought about, if you don't do this, what's the risk about this? Um, and companies are a bit shocked. But then when I make conversation points to them, they go, actually, you've got a good point. An example, one big blue chip company turned around and I got a phone call and I'll name the company from Beaver. We were doing a big migration. The project was off, absolutely off track. And we went into the meeting and they were like, well, the problem is the timeline. You said you were going to be able to do the project. It's now slipped because of quality of the staff that we had in the project and other issues on all parties. No fault of anybody. I sat down with some of the technical team and I went, okay, why don't we do this in parallel? And, um, people are like, what? Well, say we did the two streams in parallel. Could we do it? Yeah, we have to run two teams up, but that drives the efficiency. We could do that for a bit. And then we have a program manager, not a project manager over the whole lot. And if we do that, how would that work? You know what? We didn't just catch those three months up, we catch six months up. Clive was exceptionally happy. We did what we needed to do and it was thinking out that box. So I love the fact of challenges. I love the fact of using my knowledge that I've learned from experiences to help the industry. Say, you don't have to reinvent the wheel. That's the Message I would leave in we don't have to reinvent the wheel. There is so many things we can learn from other industries that we can take on board to the pharmaceutical industry. Point in question, look what's happening in the cosmetic industry.

Don: Yeah, yeah, exciting for sure. And um, definitely a way to approach this as well. So. Ian Krone, I wanted to thank you for being on the Life Science Success podcast. Thanks a lot for being here. Thank you. Thanks for sharing your story, um, as well as the personal story with you and your father. And lastly, I mean it was great to hear about all of your experience with Aeris Global and everything that you guys are doing as well. So thank you.

Ian Krohn: Exciting times ahead. Really exciting times ahead in the whole industry. I think it's this year is going to be the year of change in the industry and uh, next year will be the year of implementation. And I think regulatory is now seriously on the map within the industry and Aris Global with some of the things that they're doing. Watch the space. There's some really cutting edge things. You know, there's some amazing people that I'm working with in the team now and I think we're going to have some really good conversations. But anything I can do to help anyone in the industry, reach out to me by LinkedIn. I willingly will help and advise and

Don: absolutely everybody can come and check out your, check, uh, out your LinkedIn to, for you, uh, know, directly from me to you. I, I definitely enjoyed it in researching the podcast as well.

Ian Krohn: Thank you, thank you so much and keep going. Anything I can do, always reach out. Thank you, Dom, and look forward to speaking to you again.

Don: Thanks for.

Ian Krohn: Thank you.

Speaker D: Thank you for listening to Life Science Success. For complete details about this podcast, including show notes, how to get in touch with guests and more episodes, please visit www.lifesciencesuccess.com. if there's someone you'd like for us to invite to the show as a guest, please let me know by sending me a message at the podcast website. Please click subscribe on your favorite podcast app, share the podcast or tell a friend about it. And last but not least, rate the podcast.

Don: Thank you again.