Digital Transformation & AI for Humans
Welcome to 'Digital Transformation & AI for Humans' with Emi.
In this podcast, we delve into how technology intersects with leadership, innovation, and most importantly, the human spirit.
Each episode features visionary leaders from different countries who understand that at the heart of success is the human touch—nurturing a winning mindset, fostering emotional intelligence, soft skills, and building resilient teams.
Subscribe and stay tuned for more episodes.
Visit https://digitaltransformation4humans.com/ for more information.
Digital Transformation & AI for Humans
Groundbreaking AI & Digital Twins in Biotech & Precision Medicine: The Journey from Vision to Implementation
In this episode, we dive deep into one of the most transformative areas of modern healthcare - AI-driven digital twins in biotech and precision medicine.
This groundbreaking approach is reshaping how we understand and treat diseases by creating virtual replicas of patients and diseases, allowing for more accurate and personalized medical treatments. Johan Juhlin from Stockholm, Sweden, the CEO of Mavatar, a company leading the way in this space on the global arena, is sharing his experience and insights.
Mavatar was founded in 2018, building on over 20 years of research in precision medicine from the Benson Lab, where foundational research laid the groundwork for the current technology. Over time, this research was refined and expanded, and unique methods to standardize and integrate diverse data sources were developed, setting Mavatar at the forefront of AI-driven precision medicine.
Mavatar’s innovations are revolutionizing the healthcare system and the world we are living in.
This interview covers following topics:
✔ Mavatar’s Vision and Evolution
✔ Development of Scalable Digital Twin Technology
✔ Technical and Practical Integration of Digital Twins
✔ Differentiation of Digital Twins in Medicine
✔ Handling Large and Complex Data Sets
✔ Ensuring Simulation Reliability
✔ Applications in Disease Treatment
✔ Future Advancements and Vision
Stay tuned for a deep dive into how AI is paving the way for a longer life and a healthier future!
Subscribe and join us for this thought-provoking exploration that promises to open up new perspectives on transformation, innovation, tech and leadership.
Find out more about Mavatar: https://www.mavatar.se/
About the host, Emi Olausson Fourounjieva
With over 20 years in IT, digital transformation, business growth & leadership, Emi specializes in turning challenges into opportunities for business expansion and personal well-being.
Her contributions have shaped success stories across the corporations and individuals, from driving digital growth, managing resources and leading teams in big companies to empowering leaders to unlock their inner power and succeed in this era of transformation.
📚 Get your AI Leadership Compass: Unlocking Business Growth & Innovation 🧭 The Definitive Guide for Leaders & Business Owners to Adapt & Thrive in the Age of AI & Digital Transformation: https://www.amazon.com/dp/B0DNBJ92RP
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Hello and welcome to Digital Transformation for Humans with your host, amy. In this podcast, we delve into how technology intersects with leadership, innovation and, most importantly, the human spirit. Each episode features visionary leaders who understand that at the heart of success is the human touch nurturing a winning mindset, fostering emotional intelligence and building resilient teams. In today's episode, we dive deep into one of the most transformative areas of modern healthcare AI-driven digital twins in biotech and precision medicine. This groundbreaking approach is reshaping how we understand and treat diseases, by creating virtual replicas of patients and diseases, allowing for more accurate and personalized medical treatments. Johan Juhlin from Stockholm, sweden, the CEO of MovaTower, a company leading the way in this space on the global arena, is here with us to share his experience and insights. Hello, johan, so great to have you here today.
Speaker 2:Thank you, emi. I'm really happy to be here with you today, so, and thanks for having me.
Speaker 1:Thank you. Mavatar was founded in 2018, building on over 20 years of research in precision medicine from the Benson Lab, where foundational research laid the groundwork for the current technology. Over time, this research was refined and expanded, and unique methods to standardize and integrate diverse data sources were developed, setting Mavatar at the forefront of AI-driven precision medicine. So, whether you are a tech enthusiast, a healthcare professional or someone fascinated by the future of medicine and AI, this episode is for you. Let's start the conversation and transform not just our technologies but our ways of thinking and leading. And if you are interested in connecting or collaborating, please find more information in the description, subscribe and stay tuned for more episodes. Subscribe and stay tuned for more episodes. Johan, to start with, could you please share a few words about your journey, about your background and about everything? What might be relevant to my question, my personal question what brought you to such an exciting area, biicine? It is so interesting. It is the future for humans, so please share a little bit more about your path.
Speaker 2:Yes, first of all, I'm willing to agree. I think this is the future and I think it's exciting. And you know, when I'm talking to my kids, they say, dad, you work a lot. And I say, well, I don't really work, because it's also my hobby. I feel that I'm free all the time because I think it's so exciting and even now, if I've been working with it for more than five years, I still think it's very, very exciting. So my background is that I'm a graduated engineer.
Speaker 2:I started working my first year in a nuclear plant doing mathematic calculations. It was exciting, I had a big interest in it, but I was too social to stay there. So after a few years, I decided to leave into the medtech industry and had different roles there and senior roles, and in 2011, 2012, I founded my first company, which was cancer diagnostic company, and then after that, I started another company and when Nikkel Benson was calling me in 2018, 2019, I didn't have a company anymore and it was a perfect fit. I thought this was so interesting that I decided to join with Mikael and Mikael basically had an idea. He had started his company and he had an idea of what to do in the company, but it was definitely not a product. It was a research product at the time.
Speaker 1:So yeah, sounds amazing and about those burning souls driving the progress, I can understand you and relate to it so much. When you love what you are doing, you don't feel the time. You don't feel the time, you don't feel the pressure or the workload. You are just there to develop, to expand, to see the next steps and that magic which comes from your efforts Sounds amazing. Can you walk us through Molotov's journey from the initial vision of AI in precision medicine to its current implementation? I saw that along the way you've got significant research support and just recently closed the funding round of impressive 25 million Swedish crowns, which is around 0.5 million euro.
Speaker 2:Yeah, so lots of the funding comes from the research that Mikael did. Mikael he is a clinician and was also starting researching became a professor. He started in gottenberg, moved to lynn köping and today he's based in karolinska, and during that year he had or still having a big research group, and so it was both lots of money coming into that research and lots of knowledge coming in, and that's a very important aspect. So when we started the company, we had a really, really good base and after that we realized't we did work for free in the beginning, but we also realized that it's impossible to work for free if you're about to develop something, especially in this area. So we had to take in money over the time and also building the organization.
Speaker 2:We we started with taking some people from Nikel's research group to building the competence and making sure that we didn't lose competence in the company, and after that we'd be adding on people with the specific competences that we needed, people with the specific competencies that we needed. Most of the people they have a medical background or a biomedical background with data science. One important aspect is actually that most of the people in the team are coming from the medical side, and because I don't think that you can build a company like this if you're coming from the other side, from the data side, so that's very important, and today we are 17 employees. Our plan is that we will double the force, so we'll be more than 30 people this time next year, and all of the people that we have brought in are smarter than me, so that's also something that's really good.
Speaker 1:Sounds amazing and actually I've been thinking while listening to you that Sweden is a very good place for this type of company, because there is so many talents in the area of scientific research, in the area of data development and AI. So everything you might need is actually very concentrated in this small country and you have access to the best in the world, to the best talents, to the best vision, and it opens up many doors yeah, we are.
Speaker 2:We are lucky in a way that we live in sweden, which have a system that support research, and they are both from the government but also from several institutions. You can have funding if you have interesting projects, and we shouldn't forget that there are also quite many family offices that support the research and the development that would like to lift Swedish companies and bring them out in the world, and we have support from some of these persons or companies or institutions, so that's really really good. And then also we have a healthcare system that's enable us to collaborate with the healthcare, so we can do trials with the healthcare systems and we can collaborate with clinicians or doctors. So that's very important.
Speaker 1:That is super important. Without that access, it would be close to impossible to move it forward. What are the critical milestones or breakthroughs that allowed your vision to take shape? Could you mention that roadmap to your success?
Speaker 2:Yeah Well, so, first of all, I think that you always have critical milestones or road bumps that you need to to force, and they basically coming on daily basis, and you just have to select which one you should work with, because that's how it is to have a company like this. I would say that the first milestone for us was to prove that our technology worked, and then we were talking about proving it digital or with theories. Another milestone was to build a platform where we could test our medical avatars on and make sure that they actually were able to implement. Then, of course, we had the regulatory process. We had the trials in the healthcare, we had the funding part, building trust around the company, making sure that both investors and partners that we're collaborating with were willing to work with us, and all that.
Speaker 2:I mean all these things. They belong together. To be able to get money, for example, you need to prove that you can deliver something, and to be able to deliver something, you need to have the right competence and so on. So it's always challenges, but fun challenges.
Speaker 1:Exactly when you love it. It becomes just more fun Because you know you would be bored if it wouldn't be challenging, right?
Speaker 2:You're absolutely right.
Speaker 1:I know that. Speaking about challenges, now what were the biggest challenges in developing digital twins and integrating them into practical application?
Speaker 2:The evidence. I would say so building the twins was coming from. The idea was coming from the research, but building a digital twins it includes several moments or things that need to play together. For example, one important thing when you build a digital twin is that you need to collect data, and everyone knows that if you have crap in, it will be crap out, and we need to secure that. We had a way that was only taking in qualified data and the data that is available for building this twin. We had a way that was only taking in qualified data and the data that is available for building this twin.
Speaker 2:It can be our own data or we can use public data. If we use the public data, it's tons of data available and it's increased every day, but if we use our own data, it's very costly. Then we have to produce it ourselves and it costs millions of Swedish crowns or millions of euro actually, and so first of all, we had to choose which way to go, and we decided to go with the public data and we started looking in the public domain and realized that there are different protocols, there are different methods. How can we make this comparable, this data? And we developed a method of technology to do that. So that was one challenging part, I would say.
Speaker 2:And then, of course, building the algorithm. We were a bit too enthusiastic in the beginning and thought that it's probably enough with a few algorithms. But the disease consists of so many things that happens in a disease that we have to be lots of algorithms. That, for example, describing the genes interactions, how the cell interact with each other yeah, so many parts were included in that. And what else them putting all together.
Speaker 1:The level of complexity is absolutely incredible and the price of error is also too high. So you are operating in a very sensitive area and it is not obvious, but it is so great to hear how you are surmounting those challenges and putting one more block along your journey into the building of Prospera Future, not only for your company and your business but for the humanity actually. So that is amazing. Let's talk a little bit about digital twins. So how do they differ from other industries in precision medicine, for example, construction or engineering? Because you know, I have had these conversations on this podcast and actually for our listeners and viewers, if you are interested in learning more about digital twins in other areas, I had these conversations with guests from Dubai, from Abu Dhabi, and you can find those conversations in the other episodes. But here we want to hear more from Johan about the precision medicine and all those differences and commonalities. Probably as well. Are there any insights or technologies borrowed from other industries that have been adapted for use in biomedical digital twins?
Speaker 2:Excellent question. I'm going to tell a little secret. We stole the concept from the industry. It was already a proven concept that's been used in the industry for many, many years that you build a digital copy, for example, of a city and then you can foresee how the infrastructure works and so on. So that's the concept of a digital twin. So what we're doing is that we're taking a medical avatar and a higher resolution model of the human and we're using the digital twin concept on that human by testing drugs. So that's how it goes together.
Speaker 2:And, having said that, already today you can improve treatment by looking at a large amount of data of how patients are treated and you can select a treatment that would be better for the patient. But that is not personalized medicine, because then you're looking at a group of patients. You don't consider what kind of patient you're working with. You don't consider if it's a male or female, or black or white, or the metabolism or other aspects. So what we're doing is that we're building this high resolution of each patient and we can then do the digital twin concept on that. But the fact is that we stole the concept or borrowed it.
Speaker 1:Oh, interesting, and considering that you just mentioned those cities and digital twins of the cities, my first conversations were exactly applied to the construction area mostly. So if somebody wants to learn more, it's just to listen and develop that number of insights and dive deeper into what we're talking about. But it is so interesting and it is amazing to hear how different verticals, different types of businesses, are helping each other and supporting each other on this revolutionizing way of introducing actually a new way of leading our reality and the new type of future I was thinking about something else that is important to mention.
Speaker 2:I mean, the reason why we can do these digital twins today is actually the implementation of new technologies, and we don't have to invent them all ourselves, but they all together bring something that we can use, and I mean the digital twin concept is something. But also, if we look to the healthcare, they implemented, maybe 15, 10 years back, the single cell RNN sequencing and that meant that you suddenly can study how cells and gene interact with each other, and that's an important component for us. Before, we were only looking at bulk material and we didn't get the full picture of what was actually happening in the cells. And that, together with AI, big data analysis from computers, it helps us. But it's all these technologies together that help us build this new technology the digital twin or avatar technology that's really impressive.
Speaker 1:So to highlight this fact to everybody who is not working de facto with biomedical industry but still developing those technologies, it might happen that exactly your efforts brought something into the biomedicine and helped out Johan and MovaTAR to develop those amazing breakthroughs. That's really interesting to hear. Tell me more. How do you manage the quality and volume of data necessary to effectively develop MovaTARs and disease models? So molotovs medical avatars.
Speaker 2:Yes, so that is one very, very important aspect of it. The data in is very important. If you have good data in, it will be a good result. But, of course, also what question you're asking? The algorithm we have and we realized that very early that we need to qualify the data that we're working with. So we have several steps how to qualify the data.
Speaker 2:We're working with public data and there's lots of data and this data is so much data that we will never be able to take care of it or handle this data. So that's the amount we're talking about of it or handle this data. So that's the amount we're talking about, and we can look at specific diseases and we can analyze which data that we would like to work with. But the challenge with the data is that there are so many different protocols, so many different technologies and so on and so on. That is not comparable as such technologies and so on and so on. That is not comparable as such. Therefore, it's very important that we have people with the right background that can interpret and say what the data is and also make it comparable, and sometimes we find big data sets including thousands or hundreds of patients that we would like to look at, but it's so different from what the other data looks like, and then we use our methods to narrow down to make sure that this data would become comparable. Did I answer your question?
Speaker 1:Yes, you did. Thank you so much, but it led me to another question how are you ensuring that digital twin simulations are reliable enough to make life-saving decisions?
Speaker 2:Yes, okay, we can do that in different ways, but one simple way of doing that is that, for example, if we build a disease model, let's say a lymphoma disease, and we know that there are various drugs to treat lymphoma, then if we test, if we shoot all known drugs on this disease all lymphoma drugs should end up in this lymphoma disease then we know that we're doing something right. So that's the first check box, to check that. But then we can also see that if we're adding patients to this disease in different patient groups that have been treated with certain drugs, we can see that the treatment that they got actually falls down and will respond in the same way that it was treated for the patient. So that's the next step of validating the disease models. And finally, we have to do it in the healthcare system, and today we have set up collaborations with healthcare centers all over Sweden which are working with us to do this, and this is building the evidence around the platform, or the twins, or Mavatars.
Speaker 1:Exactly the Mavatars. The future of humanity? Yes, amazing. And now you already mentioned the future of humanity, yes, amazing. And now you already mentioned just one example of that disease, the lymphoma. But what kind of diseases can be treated overall with these incredible solutions? Maybe cancer you already mentioned neurological diseases, alzheimer, allergies of different types, maybe infertility? Can you provide a few examples of a successful implementation of Mavatar in patient care and the real outcomes?
Speaker 2:One important thing is that, first of all, we have not launched the platform in the healthcare system. If you ask me that I would like to have a twin, we could provide you a digital twin for you, but we don't do that because this is very important, because we don't want to go outside of the healthcare system, because in the healthcare it's always a lot of trust, and so we will stay in the healthcare system, even if we get requests in between. If we can help people and the full-scale lounge will be in the healthcare system, yes, but we can. Basically now, when we're lounging, we're working with four cancer diseases lymphoma, melanoma, lung and breast cancer.
Speaker 2:Cancer diseases lymphoma, melanoma, lung and breast cancer. If you look to, if you Google how many diseases with belonging drugs you have, you will get the results from FDA that there are approximately 13,500 diseases that are treated with medication. So that is basically the market that we can work with, so we can create disease models for all these diseases. However, we will most likely stay with the most common diseases and now starting with cancer, and I mean the effect we see when we're now testing these models is huge. It has huge impact, having in mind that approximately 50% of the patients don't respond to treatment. It means that one out of two patients has a delayed treatment or maybe will not be treated at all because the consequences are so bad in some diseases.
Speaker 1:It is a very difficult question and you know probably many of those who are listening to us right now they can relate to their own friends and family members and their life would go and develop completely differently if they would get the support, the right support at the right moment and if your breakthrough technologies would be already in place at that moment.
Speaker 1:But they are still not there, but coming soon and it is a really big hope and a great great news for everybody who knows there are so many of us who can guess that if somebody in the family had that type of problem, that it might hit back. And I have also people in my network of friends and colleagues who mentioned several times you know what I know that I might get this problem because it is transferable, you know, from generation to generation, and I'm in the risk group. So it means a lot for all of them who are just thinking about it and obviously, even so much more for those who will need that type of treatment yes, yeah, it's um, yeah, it's a very, very strong technology and the tool that we are about to launch.
Speaker 2:it will have a huge impact. And I'm also thinking about there are so many elder people today that have a cocktail of medications and they are not in control of what they're really getting and sometimes it turns out that this cocktail are having a direct negative impact on them and might be toxic. And all that kind of question or all that kind of situation we can avoid with this technology. So, there are many areas that can be improved.
Speaker 1:It is absolutely amazing and so promising. We could keep talking about this, and this is one of those few cases on this podcast when the topic is really strictly connected to the emotions as well, because it is about our life, our health, those we love, those we care about and our future. So it is a very special edition about technologies, but so closely connected to who we are and how we are. And just to wrap up this amazing conversation, what future advancements do you envision for avatars? How do you see human health and life quality changing in the next five to ten years from now?
Speaker 2:I do think that in the short term, we will see lots of changes. From easy solutions Like, for example, there are AI buddies or friends that will help lonely people, I think that's a fantastic solution. It's maybe not the most advanced solution, but it's a fantastic solution for all the lonely people. I also see that AI will release time for monotone tasks, for example, for example, but that's also great and it would probably open up our eyes in the near future how we can get the support from technology. But in the long run, I think that the algorithm that we have today they are not strong enough, but they will be developed over time and with that we will see opportunities that we couldn't imagine how big they are.
Speaker 1:So true. It gives a lot of hope and such a bright perspective. So thank you so much, johan, for being here today, sharing everything with us and opening up for this amazing perspective for the humanity. It is really giving hope and promises a higher quality of life and more enjoyable life, longer life. Thank you so much for working with all of that and creating that future together with your colleagues and applying your vision to the reality.
Speaker 2:Thank you very much. It was a pleasure to be here.
Speaker 1:Thank you for joining us on Digital Transformation for Humans. I am Amy and it was enriching to share this time with you. Remember, the core of any transformation lies in our human nature how we think, feel and connect with others. It is about enhancing our emotional intelligence, embracing a winning mindset and leading with empathy and insight. Subscribe and stay tuned for more episodes where we uncover the latest trends in digital business and explore the human side of technology and leadership. Until next time, keep nurturing your mind, fostering your connections and leading with heart.
