Nicole Baker

Embark on a captivating journey with Nicole Baker, the pioneering CEO of Biologit, as she shares her remarkable transition from academia to the forefront of pharmacovigilance on Truliant Talks. Nicole's narrative is not just about her personal evolution but also serves as an illuminating guide through the labyrinth of safety regulations and drug monitoring. Her candid conversation is a deep dive into the importance of patient safety, the impact of regulatory shifts, and the ever-present need for industry adaptability. We examine the significance of professional networks and the influence of major events like Brexit, providing an insightful look at how these factors have reshaped the European pharmacovigilance landscape.

As technology becomes increasingly intertwined with pharmacovigilance, Nicole lays out her experiences in harnessing AI to revolutionize the field. She reflects on the challenges of setting up a department during Brexit and the subsequent founding of a consultancy aimed at developing accessible AI models for the industry. We unravel the intricacies behind AI and automation, discussing their roles in improving the efficiency and accuracy of adverse event detection. The synergy between pharmacovigilance professionals and technology is spotlighted, as we explore the cautious optimism surrounding AI's potential and the journey from skepticism to acceptance within the industry.

Finally, we turn our attention to the future, speculating on how integration within pharmacovigilance could transform safety data analysis and application. We discuss the necessity of a broader perspective in adverse event reporting, touching upon the current inefficiencies and the potential for systems that ensure data accuracy and consistency. With Nicole's valuable insights, we conclude with aspirations for these advancements to materialize over the next five years, revolutionizing how we understand and manage drug safety. Tune into Truliant Talks for an episode that promises to broaden your horizons on the pivotal role of pharmacovigilance in healthcare.

Transcript

Speaker 1 0:16

Welcome to another episode of Innovation and the Future of Pharmacovigilance, a podcast series brought to you by Truliant Talks. I'm your host, indy Aluwalia, and I'm delighted to navigate the dynamic world of pharmacovigilance and risk management with you. A quick disclaimer first the opinions expressed in this episode are solely those of the individual guests and do not necessarily reflect the official views of Truliant Consulting or their own company. We're all about fostering insightful conversations here at Truliant Talks and we want you to know that any product, vendor or service mentioned does not imply an endorsement. If you're seeking professional advice for specific situations, we encourage you to go to our experts. Please remember this podcast content is meant for informational and educational purposes only. Content is meant for informational and educational purposes only Now. Today, we are very lucky and I'm so excited that we have Nicole Baker, who is CEO of Biologic, as our guest speaker. Nicole, thank you for joining us.

Speaker 2 1:20

Thank you, thanks for having me.

Speaker 1 1:24

Nicole, we have to ask the traditional question, the one question that intrigues all of our listeners, which is how did you get into PV?

Speaker 2 1:34

I think that's a good question. I don't know if anybody who has been in the industry for more than 20 years has entered into the PV world by choice. Really, I think most of us have done it by accident because pharmacovigilance was not, you know, like a very well-known discipline within biological sciences and so on. So I will tell you my story and it might be very long, but you can stop me at any time and ask me to move or to speak faster. So I got into PV by chance and I come from so I'm an immunologist, I did a PhD and then postdoc and so on. So I was in academia academia for many, many years and I was working on translational medicine and I'm kind of moving from animal to pre-clinical and translational medicine, going into humans and we did look at the safety safety of everything that involved what we were doing but it wasn't really called pharmacovigilance was safety and efficacy. That's what we called it.

Speaker 2 2:45

As we went along and when at one point I had postdoc'd for six years and the money was running out, I decided I said well, I need to find a job, a real job, and move away from academia, which was very painful because I loved my job and I loved being in academia and the whole creative side that goes into academia, that you can create your own experiments and you're free to do whatever you need and want. So I started looking for a job and I got a job in the HPRA as a safety and efficacy assessor. So, moving from a not so regulated environment into a highly regulated environment, that's where I started learning. You know what was the regulations and how to do things properly, and I was there for a while and that's where I've learned on how to read law, for example, and all of those documents that go with it. So it was a very good learning curve, I think, in my opinion, for my own development and also.

Speaker 2 3:50

The pace of work within regulatory is slightly different from the pace of work that you have in the industry. So it kind of allows me to have the time to think and read and associate and have a clear mind when you're doing assessments. And also because I came from academia and I was a scientist, I was given the opportunity to do a lot of scientific work, which is what I really like doing, and I was working on immunological drugs and also vaccines and so on. So I went into an area that I knew very well. I knew the concepts of it and then doing assessments was kind of second nature. But then I had to take into consideration the legal requirements for developing new drugs.

Speaker 2 4:35

So from the HPRA I moved into pharma and most pharmacovigilance professionals they would move into case processing and kind of gradually kind of progress into their career. But with me it was slightly different because I came from the regulatory and I was an academic. So I went directly into as a safety scientist and as a safety scientist I was given a whole portfolio of immunological drugs and drugs for oncology and immunology. So I was very happy, I was in my element looking at those. But I didn't really know much about pharmacovigilance because within the HBRA we had the pharmacovigilance department but it was separate and the assessments that I did was kind of risk management. So there is where you kind of open up into risk management and signal detection and so on. So I had access to all of those documents but I wasn't the one actually writing those documents. I was the one reviewing those documents. So I went from reviewing those documents to writing them.

Speaker 2 5:42

So as a, as a pharmacovigilance scientist, I was given, you know, the the chance to one learn and it was in just before 2012 when the new regulation came on on board.

Speaker 2 5:54

So I was kind of on the on the the changing of having a process going into new processes, and I had a great opportunity to learn all the new processes, the new legislation and training was a huge part of the onboarding within the company that I joined, because it was also new and also the company was kind of new and progressing into Europe because it wasn't a European company and then it became a European company. So it was a great environment to develop and learn because it was a group of people that came together that was very keen to understand and learn the new regulation and to be really good at it and to do the right thing by the legal requirements. So we spend obviously some time learning and kind of putting our heads together to do our best. But it was a very, very interesting time and relevant time, I think, for everybody in the pharmacovigilance industry and relevant time, I think, for everybody in the pharmacovigilance industry.

Speaker 1 7:07

So, as we remember sorry, do you remember at that time how, how you felt about the new gvp guidance coming in?

Speaker 2 7:16

um, it was overwhelming, I think, when I was in the regulatory authority in the hbra, the new, the change that was coming in, was to have braille, uh, into the packaging and things like that and that was a big project. And then when I went into pharma for vigilance and it was like, oh, the new module, so it was like one small change in the regulatory authorities. They were like, oh, it's so much work. And then going into pharma and we had to kind of basically adapt and change and write new SOPs and learn how to work in the right way as well, because I think pharmacovigilance was a very reactive department where we received cases and we processed cases into signal detection, risk management and so on. But there was an excitement in the air, especially from the scientists, because the scientists they were thinking now I can finally do something. That is exciting, because case processing on itself is not exactly exciting. It is interesting, obviously you're reading case reports and things like that. But the main kind of where you can see the big responses is when you put all of this data together and you make sense of this data together and you can start doing predictions on what is relevant and what is not so much relevant and from what is relevant, how can I do assessments on this information, how really relevant it is, and also start working with more data. And I developed a passion for data and also scientific information and kind of going into doing those assessments and trying to find technology to help us to do it better, because it is very much. It's a very manual process. When I started we didn't have any processes in place and we did line listing, reviews and then trying to kind of putting groupings into place to be able to analyze the data. So pharmacovigilance, from where I came from at the start of it to now, and what we have, what has been developed in the past 20 not 20 years, but in the past, you know, 10 years or so, even more than that has been amazing to see the progress because most of the work was very manual and then companies had supportive systems. But the systems you know there was a a kind of um how good our systems are and can we rely on systems, how much of the systems that we have do we need, do we rely or trust, and how much you know qc do we have to do to make sure that it's giving us the right responses. So it was an interesting progress and a path that we had to take.

Speaker 2 10:14

So the first few years moving into pharmacovigilance from academia and then regulatory authority was a learning curve and trying to use the skills that I have of project management and so on into a new industry, into a new department and at the time you know, we were working with clinical development and regulatory affairs, medical affairs. But it was still a big gap and then it was like all of it was very much like oh, this is a pharmacovigilance problem or this is a regulatory affairs problem. Kind of take it away from my plate, because my plate is very full. But we tried as much as possible to work in very close collaboration with other departments to make our lives easier, but also for us within pharmacovigilance to have a good understanding of what happens in pharma in general. That is not just you know, patients take the drug and then they have an adverse event and they send us a report, but much more on what is the, the whole um, integration of pharmacovigilance with all of the other departments.

Speaker 2 11:19

So where do we? Where do we come in? Who can? Can we help? And more like we are a support but also fully integrated with all of the departments of a pharma company, that we don't work in silo and we really understand a lot of the other processes that happens within a company. And I think that was also important because if you come into pharmacovigilance and you sit on a table doing case processing all day and you have no idea what happens in supply chain in medical affairs clinical development that can be, I think quite, quite um, I don't know, you don't really have a full picture of of why you're doing this job yeah yeah and yeah.

Speaker 2 12:08

So that was my, my initial experience. And then I moved on to um, cro, uh, and cro was a different. It was similar to pharma but then it was slightly different. So you kind of seen from the other side on how to provide services to to pharma companies and how much visibility you have to the everyday. So you kind of lose that visibility of what else happens within the pharma company, because with services you're providing a services at a point in time.

Speaker 2 12:41

But because it was a qppv I managed to have oversight over the other activities. So moving from being a PV pharmacovigilance scientist into QPPV was very positive because that kind that gave me the opportunity to keep in touch with a wider network within the pharma company and that I didn't lose that ability to have contact with other departments, because the QPPV then would have a lot of contact with lots of other departments within a pharma company. So I think I was very lucky in the way that my that I progressed my career, that it gave me the opportunity opportunity to see how things actually happen and to support companies throughout their development, from clinical development through application of new licenses to the FDA, ema and so on and then into post-marketing. So it's a very sometimes you only see a point in time, but being able to go from clinical development all the way to post-marketing, it is a lesson.

Speaker 1 13:51

That is a very valuable lesson, I think, for a pharmacovigilance professional, that you're not just looking at things into one perspective, but you can see what the whole process is yeah, no, that's a, that's a really good point and so far, I think we're uh well, maybe about halfway through your career and, and it's just fascinating, you know your regulatory uh, academia, bahama, cro, qppv.

Navigating Pharmacovigilance Industry Transitions

Speaker 2 14:24

You've literally, you've literally touched it all yes, I had to say yes, but I've never. Yeah, but what I never did was case process like like fully enter a case from beginning to end to do you know the very basic of pharmacovigilance. I missed that part which sometimes. I have done lots of reviews of cases, but I haven't ever entered a case from beginning to end, so I skipped the most crucial part of paracovigilance, I think. At the same time, I have a very good understanding of the whole process and how it integrates with the community, with hospitals, with the regulatory authority and so on, with the community, with hospitals, with the regulatory authority and so on. So it's, I think it's slightly different from how most people have progressed within pharmacovigilance, like the traditional way yeah, yeah, and then you know yeah, sorry.

Speaker 1 15:23

No, I was just going to say I think. I think it's actually it's quite, it's quite interesting talking about non-traditional way of getting into pv because, quite frankly, drug uh well, data entry, uh sort of roles in pv, are they really around or are they really as prevalent as they were before? And where is the entry point for PV? Now I think you've shown a good example of you know an entry point that doesn't necessarily mean that you come in through data entry or you know being a drug safety associate or something I think it's, and it shows that, even though you may not have done that uh foundationary start, it doesn't mean that your knowledge on pv is at any point, um, uh, different to someone who had started out there yeah, yeah, I think so, and I think what is important in pharmacovigilance and in any other area is the curiosity and the wanting to stay up to date and the wanting to learn more and to really understand what you're doing.

Speaker 2 16:39

Otherwise, you can get into situations where you might have gone too far to be able to kind of step back and fix the problem. And I think pharmacovigilance, you really need to have had experience in situations where you've learned from somebody else on how to deal with it and you have experienced different situations where you know what the best strategy is and even when you know that sometimes, if you're dealing with a different company or a different regulatory person, it might was the solution you had might not work with the other, because as much as we would like to have everything harmonized, things are not completely harmonized within the industry and companies do things differently and regulatory authorities also do things differently. So I think you also need a level of. You need to be pragmatic, but also have used your common sense in a way. I think you also need a level of. You need to be pragmatic but also have used your common sense in a way to get up with the legal requirements, but you also need to use a little bit of common sense on how to do this and know where to look for things, because the information is available. There is a lot of information out there, so you need to and you you might not be able to retain all of this information in your brain, but you also need to be able to say, look, I'm going to look for where to find this information.

Speaker 2 18:20

And another thing that I think it's very important here is the network of pharmacovigilance professionals.

Speaker 2 18:27

We are very a close community and everybody. I find it that people do want to help each other. So if you have a question, if you have a doubt about anything, you can try to find a solution within your company, but you can also try to find a solution within your network and the network that you've been building along the years, and I think that is very, very, very valuable. You know, the experience, the hands on ability to solve problems is very important within Pharmacovigilance, is very important within pharmacovigilance, and I think we have a very close community where we really want to help each other, because, at the end of the day, we are just a part of the system that is looking after patient safety and the patient is at the end. You know we really want the patient to be the first person that we are looking at and trying to promote that patient safety at any. You know that has to come first and I think the community does see that as really the most important thing.

Speaker 1 19:46

Yeah, I think sometimes, and we'll get to, uh, your current state, um, uh is your career, but I think certainly there are some vendors out there that may not necessarily be able to put the patient first, um, and they don't think like that, and I, and I think it's very important to remember, at the end of the day, that is the most important thing, that is the crucial thing. In fact, if we fail that, we failed our jobs and we failed people that we may or may not know. So you were at CRO and then back into pharma, I believe.

Developing Technology for Pharmacovigilance

Speaker 2 20:28

Then I went back into pharma and it was just at Brexit time and Brexit for I'm based in Ireland, so Brexit was a noisy period and I was a QPPV and there was a lot of discussions and most of the QPPVs were based in the UK and it was for me it was very sad to see because they were very, very experienced QPPVs and they had contributed enormously to the, the pharmacovigilance community, and then suddenly they had to either like, move countries or become a UK QPPV and then the changes there was was quite and it was a very long period. That didn't you know, like when we were like, oh, next year, next month, and then at the end was a very long process to come to an end where the Brexit really happened and the changes happened. And so it was a bit strange during that period of time where we relied so much on QPPBs based in the UK and suddenly that was no longer Europe and also, like, the EMA was based in the UK and we are in Ireland and Ireland is such a small country and we relied so much on the MHRA and on joint like everything was done in a jointly way. So we worked very closely with our colleagues in the UK and to create, you know it was Europe. And then suddenly they were moving away from Europe. So it was a strange period of time. But what happened was Ireland was the country where a lot of people thought that all the QPPVs would kind of move to and in reality it wasn't really like they moved to lots of other countries in Europe like the Netherlands and so on. So the work, you know it was a very busy time. The work, you know it was a very busy time and I was supporting to set up a pharmacovigilance department for one company that was moving away from the UK because of Brexit and then they were setting up in Ireland. So I did all the supporting activities and set them up and so on and all the pharmacovigilance activities that have to go with it. And at one point I thought and at that point I was already becoming very interested in technology and how to develop new technology and what are the new technologies. Because as a head of pharmacovigilance one of my roles was budget. So how can I bring down the cost and how can I work better? How can I have my team to have supporting technologies to let them do their work better, to give them more time to do assessments and so on. So all of this was kind of playing in my head and I didn't really have a lot of access to all of this data and technology and, being kind of a medium-sized company, it was difficult to get access to it. So I decided I said I'm going to leave and I'm going to set up consultancy and set up and see if I can kind of move on to a more technology type of role where I can start developing technology and let's see what happens. So then I left my job and I started looking at the kind of startup world and I had no idea because I was, you know, I came from academia, which was very it's a large industry. It's a lot of people involved and you're well looked after and everything is not everything's done for you. You have to do your experiments, but you are in a community, a very wide community of people. Then pharma CRO as well. I worked in very large CROs. So there was all the support and everything. Give you support to go to kind of starting a company and thinking you know how and what can I develop and do I have the credibility to do something like that? Because I'm a pharmacovigilance professional, I'm not an AI, you know. And then AI started kind of everything. Everybody was doing automation and AI, which are two different things. Everybody was doing automation and AI, which are two different things. So I met Bruno and Bruno was writing at the time he was writing a thesis on natural language processing and how to find words within text. And I was like, actually we could use this for pharmacovigilance, especially for the literature monitoring, because that's exactly what we need to do when we're reading articles, looking for safety information, we are looking at patterns and we're looking at words, and we're reading hundreds and thousands of articles to find events. And I started talking to Bruno and Bruno said to me well, if you pay me a salary, I join you. I have no money to pay him a salary. So we then applied for a commercialization fund within Trinity College Dublin and we decided that the best option was to incubate our idea and develop our idea within the university and within a center for artificial intelligence, because then we would have access to very good talents to help us to develop the most, you know, the best system in class. So, and the other thing, I wanted to develop something that would be of use of use not only for one pharma company, but the whole industry. And my thinking was, if I develop it directly with one company, they will have, you know, the ownership of that product and it will not be used across. And then the other consideration that I took was if you, if you were looking at how small and medium-sized companies have access to systems and technology, they really don't have access to it. So I wanted to create a product that even the smallest company would have access and would be able to use it out of the box. So my whole idea and concept was I need to develop technology that is out of the box, that even if it's one person, if it's one consultant, one person will be able to use it, and if it is a very large company, they will also be able to use. So I didn't want to exclude smaller companies with no access to systems and technology within the company. So that's what happened. And I also wanted to create AI models that would be able to work for any drug. So it wasn't specific for one drug, so I wasn't creating a portfolio of products for one pharma company, but I wanted it to work across from, I don't know, paracetamol to vitamin A, that it would work for any product. So that's what we did. So Bruno came on board. So that's what we did. So Bruno came on board. We started in Trinity on the first day that Ireland went into the first lockdown. So I got my and I was actually very happy to go back to academia. So I was really, really excited that I was going to go back to my previous life and to a previous university that I had worked. So I was like I'm so happy, I'm going back to academia and it will be great and we will have, you know, that kind of lifestyle again where we are going to be among scientists and we can have lots of really interesting discussions and we're going to learn a lot and we're going to be having the time of our lives. And COVID started and so we we were like fully remote. So we all went home and we set up everything in a remote way that we could work together without having to stop the the project. And the project was never delayed because of that. We just learned to work from home and remotely and there was no delays. No, didn't really affect us and in a way, it really worked for us, because one in pharmacovigilance became evident why do we need pharmacovigilance and that wasn't evident before, like people knew what pharmacovigilance people couldn't even say it was spell pharmacovigilance. It was like pharmacovigilance like people wouldn't even be able to spell that. And it became evident what what we were doing and why we want to do it and how patients were at the epicenter of what we were doing and also companies were probably less busy going to conferences and having meetings. Outside that, a lot of people accept my invite to have a chat and talk about developmental technology. So I'm really thankful to everybody that at some point in time accepted my LinkedIn invite or my invite to have a chat, because all I really wanted to know what the industry was looking for, what do they want? What would they love to see built? And from there our ideas started flowing and we started building technology, but based on comments and based on the need and based on my own experience as well, on what I was seeing. And then from Bruno, from his experience in developing technology for other industries so he worked in fintech, for example, and his job before joining Biologet he was working in insurance, so he was already working with large volumes of data and how to make sense of that data. So kind of all came together. We probably were the right people to make this project work and the right people at the right time, and everything else that happened. So, yeah, so this was three years ago, four years ago actually, because the first year we were in Trinity incubating and then we spun out on the company. This month, the month of April, is the anniversary three-year anniversary of the company and two-year anniversary of the product.

AI vs Automation in Pharmacovigilance

Speaker 2 30:45

Wow so that's where we are and there was a lot of progress no-transcript that did exactly what we did in pharmacovigilance, but if you do it now, you will find a couple of companies that are doing similar work to what we are doing. So but what we were earlier on in the curve because we kind of picked it up earlier and really wanted to progress in building something that would be useful and would be adopted as well. So that is where we are now and there is adoption, there is a good understanding of what we do and we will keep doing it. And listening.

Speaker 2 31:55

I think listening is one thing that I didn't I just less so when I was working in pharma, because, as a QPPV, you listen but you also want to give your opinion, more so than when you were a ceo or when you were developing technology. When you're developing technology, your listening ability has to be amplified because you really need to listen to what people want and your own ego and your own I want this or I want this. This way, you kind of have to put it to the side and you really need to see the bigger picture and how you can support and help companies to do what they need to do.

Speaker 1 32:42

Basically, I think you are absolutely bang on there. Thank you for everything that you've just gone through. There was a couple of things that I really want to, which I don't know if they were just accidental sort of, but the one that I always bang on about and it was a small bit that you said was AI versus automation and that they're not the same. And I have seen, still to this day. Still to this day, I see vendors promote AI when it is very clearly not AI. Ai may be a piece, it may be, I don't know, a couple of percentage points, but the majority of the software is not AI. So, from your point of view, what is the difference between AI and automation?

Speaker 2 33:38

I think there's a big difference and there's a big difference in the development and the governance of the software that you have to do. So automation could be steps, and it could be going from step A to B and you're automating and you have processes. It's more about process and that you are automating the process and you're making the process work more smoothly. But ai involves a lot more any type of ai. When I talk about ai, I'm talking about machine learning, I'm talking about nlp, I'm talking about large language models and I'm putting them all into kind of an AI big bucket. But when you're thinking about, in our case, large language models, they weren't really the flavor of the month when we started four years ago or even five years ago, thinking about it and what we wanted to do was to have a real life. And you're talking about pharmacovigilance, which is a highly regulated environment. So we couldn't. What we created and what we wanted to create was a safe model, and it's very important to say it's a safe AI model because it has to be reproducible. We need to be able to have confidence in those models that we are not missing any important information.

Speaker 2 34:58

So we paid a lot of attention from the very beginning to create specific models for pharmacovigilance, using artificial intelligence as the enabler of us doing that and developing the models. And we also went through what is the best process to do that and we had to learn what what would work and what wouldn't. And what we learned is that the best model works when you have pharmacovigilance professionals working with you being part of that team. If they're not part of that team, that is never going to work.

Speaker 2 35:35

Because if you think about it, the models that we have it's like me, it's, it's, it's a, it's a clone of me reading articles and finding adverse events on those articles or the person you know like. It is not only me, obviously, but it's. It's following a process of how a human would do that. So our models are combination of machine learning and lp and so on. We haven't, we have some large language models, but they are not on the finding adverse events, but they're more towards um summarizations and things like that. That doesn't need to be as precise and we put the kind of the first steps within pharmacovigilance. It has to be an exact science because we cannot miss adverse events. We need to be able to um have the confidence that is doing the right thing every time. It's like the confidence of a part of a pharmacovigilance team that is doing case processing that they're doing the right thing every time, that they're not making mistakes.

Speaker 1 36:39

And how would you so? Let's be honest, there is a lot of. I think there's two sides to this in PV. There's the natural tendency of PV to be very conservative and say, oh my God, there is this new technology and we don't know what to do. We don't know where to start. But then there is a flip side of over-eagerness from some people to implement a technology simply because they know that and again, you pointed it before the potential to reduce costs and that seems to be a big thing. And so you have these two competing factors in pv at the moment, where you have these extremely conservative. It's almost like politics, except for for technology. There's two extremes. There's a right we got we have to have the best technology in pv. And then there is the hold up. Wait a, a minute, what are we doing and how do you balance that as a vendor?

Speaker 2 37:40

So I think it's all about timing. It's all about timing. So the first clients that we had, they were adopters. They were like really early adopters. They're very keen, they were very involved and they trusted us. So basically it wasn't trusting the technology, it was trusting me and Bruno as people that we were saying the truth but also obviously looking at the results. But also they were trusting us that what we were saying, what we were developing, was real. And, as they could see, it was real. The adoption just became easier and easier and easier, because then the trust was building up and they could see that the results were also good. And I think that is like when you look at the balance.

Speaker 2 38:30

And so for us, the very first few years, it was that battle of talking to people. And sometimes I would be talking to people and they would get up and put their hand up and say I don't believe you, you don't have a model that works. And I was like, yes, I do, I can prove, we have a patent, we have a product, we do have a model that works and can do what I'm saying Because at some point probably they were used to seeing PowerPoint presentations where people were promising the world of automation in lots of different forms and shapes, but when they saw us talking about our technology, some people would say this is not real, you don't have a, you don't have it. And I would go and say, get quite offended. Um, that somebody was saying to me that I didn't have a product that did what I was saying it was doing, and I would be quite defensive and but, at the same time, they have the right to do that. They have the right not to believe in what I'm saying until I can prove my point that or they can see that what I'm doing. So it was.

Speaker 2 39:32

You know, if you think about the last three years that we started, the difference we see is huge in terms of adoption and the difference in going from the status quo of I will keep doing what I'm doing, and that was one of the worries that I had when I started. I was like and then the platform also progressed in a way that we were putting new models into the platform to help companies, but my initial thought was to create only the AI piece that could be plugged in into the existing system, so they didn't have to do a huge change management of how they did the process, because pharmacovigilance is not just the adoption of the technology, but it's a change in the process. That is what costs money and you know your QA gets really panicky about it and that costs a lot of money to the company. And think about pharmacovigilance as well as being we always we don't have enough people to work, so for us to put in a new project on top of that and take people away from their day job, it's a problem, right, because you don't have that many people that you can take away from the daily job. Say, now you're going to start implementing new technology for the company. So that was the initial hurdle that we had. That well, we need to find early adopters and we need to find people that have time, because if they don't have time, if they're struggling with time, they will not be able to implement this, because our implementation doesn't take very long. But they need to say yes, I'm willing to take the time to do this. So now it's different, because we have done so many implementations and more companies know about us that the trust has evolved into. Other people have done it, but the early adopters, they were brave, they trusted us and they were very brave to implement a system that was new and new machine learning, new NLP, it was brand new. So, and now we are in a slightly different situation because the adoption now it's like every company should have it because they want to save time and they need to improve their processes.

Speaker 2 41:54

But it is becoming easier for us as a company to you know, for new companies to come to us and say, well, let me look at this, and they are looking at us with different eyes from how they looked at us three years ago. And I think chat APT as an example we don't, you know, we don't use chat APT but as an example that made them realize that AI is here. Ai is here for everybody. And that was the message that we wanted to convey four years ago, saying we want AI to be available to every company, independent of the size of the company. It's not only large companies that should avail of technology. Even the very small ones should avail of technology, like even the very small ones should avail of technology at a cost that is affordable. So I think that's what ChatGPT did, said well, you can use it like it's, it's available to you, and that's what we're doing.

Speaker 2 42:50

We say, if people ask me, when should I start? You know, within a company that is quite small and kind of growing and they say when should I start using AI? When should I think about it? Because a lot of very small companies are like I'm not going to think about that because I have so many other problems. And now I say to them now is the time. You can look at it now and you will be able to implement it now and it will save you so much time and it will automate. Going back to automation, it would automate some of the tasks that it's taking a long time for somebody, a human being, to be be doing. But we also say that we, we had a human in the loop, so the human is there. The human is part of the process.

Speaker 1 43:37

Yeah, and the human in the loop is definitely a good way to keep reassurances for people who are worried about moving to AI. I know one example I always think of in my head is if you were teaching young indie how to do data entry again and compare that to, maybe, an AI bot. I think the AI bot may have done better than my initial few cases at least. So it's just a different way. But I find it interesting that you talk about small companies and the fact that they and I've talked about this previously in podcasts or had guests that talk about this which is the technology truly will completely change small companies. Bigger companies obviously they will get cost savings, but it will completely revolutionize smaller companies who are trying to do pv correctly, um, and be able to lower their costs because their costs are very low yeah, yeah, and you know if there's a message, yeah, they should start early looking at it at this, and you know adoption is.

Speaker 2 44:59

there's a message, yeah, they should start early looking at it at this, and you know, adoption is there. Other companies have already adopted it. So now it's kind of been the follow on trend, you know, like the early adopters, and now it's kind of going to everybody else that is adopting the technology. But from my point of view, I want to keep it affordable and available to all sizes of companies, not just the very large ones, but the large ones.

Discussing Integration in Pharmacovigilance

Speaker 1 45:23

we like them too yeah, from the largest to the smallest. It's fine. Um, nicole, it's been a absolutely fascinating conversation with you, but, um, we've come to pretty much the near the end of the podcast and there's a another question that I I always ask, and, uh, it's a very simple one, which is what's next for pb I think.

Speaker 2 45:51

Next, I think it's integration. So at the beginning I was saying that when I went into pharmacovigilance, I was happy to understand how pharmacovigilance works in terms of how it integrates with other departments, but it has to be much bigger than just within other departments within the company. But I think we need to understand how pharmacovigilance connects with healthcare professionals, hospitals, policies. It's a much bigger context on how we do what we do and how we can help, how we can improve the quality of how we provide information, education, and I think if the integration doesn't happen, we will still have this very silo collect data from here, rework that data and plug it in here and take this work from here and then do it again. There's lots of repetition when you think about it, like, think about data coming from a hospital or coming from a pharmacy or coming from a clinical trial, how that gets moved along and how broken that is, how many times people need to have to pick the data, work on the data and transfer the data again, and so on and so on. So I think in my view is we need to find ways to work together, but also the source of information needs to be easily transferable from one point to another, because it's a much bigger picture, much, much bigger picture than what we're looking at the spontaneous cases coming into the safety database that's a fraction of it. And now with digital health and wearables and the combination of product with medical device, with wearables, and then extension of all types of products, because we're talking about pharma here, but there is a lot of other products that could cause harm to, then they're not patients, but they're people. You know the amount of um, natural medicines and neurothuticals and cosmetics and and so on, like the.

Speaker 2 48:05

The scope of work here is so wide that and what we need to do is to really keep an eye on the bigger picture and also be open to technology, on how we can integrate systems. So we can. It's not that I want to remove people from the activities, but people should stay at the assessment piece. They shouldn't be collecting the copy and pasting data from one database into another one and copy and paste, because the way of doing that is so prone to error and inconsistent data. And then I even had a patient one day coming to me and saying you know, I find it really annoying that I give you my point of view, I give you a safety report and then, if I've asked you to read the safety report that you provided to the regulatory authority, it's completely different from what I initially provided because it changes the language. So a patient report.

Speaker 2 49:04

Once you put it in the safety database, the language will be changed so it reads very differently from how, and I know it has to be done that way, but I think it is important to be done that way. But I think it is important and in my point of view it's having data that is connected to the next point and to the next point and to the next point that we can, that we able to analyze that data do you think that is possible in the next five years?

Speaker 2 49:35

possibly, I don't know, in five years it is. But I think we, we, we need to think about systems, that we build them, like lego blocks, that they can be put together. You cannot build a product that is a black box and you just chuck things in and spit them out like it has to be a buildable. They have to be buildable systems fascinating I.

Speaker 1 49:59

I like the uh lego analogy. Um, last week, uh, we had, uh, we had the uh supermarket analogy and this week, yeah, the lego analogy. I think, I think, I think I'm picking up analogies as I go along. Nicole, it's been absolutely amazing speaking to you. Thank you very much much for joining us on the podcast.

Speaker 2 50:20

Thank you. Thanks so much. It's been a pleasure talking to you.