Roger Assaker, MDSIM - Spine Simulation Software | LSI Europe '24

Roger Assaker 00:02
Okay, good morning, everyone. My name is Roger Assaker, and I'm here to tell you a little bit about the story of MDSIM, which is focusing on superior spine care with an AI-driven digital twin. So the founders got together a while ago; we started bonding and discussing the idea of medicine. I cannot tell how many years ago, but fast forward a couple of decades, we have Richard. Richard is a professor of neurosurgery specialized in spine. He has more than 15,000 surgeries behind him, and he's an innovator with 35 to 40 patents in medical devices, all focusing on spine. Danny, who is on the right, has a PhD in computer modeling and simulation, specialized in aerospace, and spent most of his career in automotive, with the last 10 years dedicated to quality and regulation. So he's taking care of quality and regulation within MDSIM. And as for myself, I'm an entrepreneur with a PhD in computer modeling and simulation as well; I've created companies, sold them, and ended up managing the company to which I sold, with several hundreds of millions in revenues. So, as I said, we started discussing this story a long time ago, and basically, two engineers and one doctor discussing, we said, why don't we take the technology, which is used on a daily basis in automotive and aerospace, and apply it to medical? And this is the story behind MDSIM.

So the things that we are trying to do are related to aging, scoliosis, osteoporosis, tumors—all of these will cause the spine to degenerate and deform. There's more than 2 million of these kinds of surgeries a year. The clinical solution for this is basically to fuse the spine. So to take a couple of vertebrae, you know, the vertebrae that are concerned, cut them, do osteotomies, put screws in them, and connect them through rods. The problem with this surgery is that it's complex. It can take hours—10 hours sometimes, and more. It is costly, and in the US, it costs more than $200,000 to do it. The problem is that it fails almost 40% of the time. So the surgeon needs to do the, you know, the patient has to go through revision surgery 1, 2, 3, 4, 5, 6 times. So the idea is, and why is this? Basically, it's because the solutions that are given to the surgeon today to plan his surgery and to optimize it, to know what the outcome will be, to have an idea about predicting the outcome of this surgery, are not offering enough value; they are not accurate enough, and they take a lot of time to be used and applied.

So this is why we, the three co-founders, decided to build a team. The team consists of PhDs and biomechanical engineers in AI and computer modeling and simulation, basically. And this team has come together. The concept is very simple: we take a patient, the patient will go into a CT, an MRI, an X-ray, and we build the digital twin of this patient. The digital twin is a real reproduction of the patient. It's a high-fidelity, patient-specific, biomechanical digital twin. This digital twin will help the surgeon to apply his surgical strategy beforehand and see what the outcome will be. For instance, in this case, is it better to fix L2 to L5 or L2 to S1? What will happen to the remaining spine, and what will happen to the devices that are implemented? The idea is to avoid mechanical failure and spine failure.

So this high-fidelity, biomechanical digital twin of the spine is nice; it's a nice technology, it's a nice concept, but it's typically used by engineers, and it takes hours and days to do it. So what we have done is we used it as a backbone to a portfolio of products which are first used to work on unhealthy individuals, who need to have check-ups at different points in time, and to basically prevent the problem of spine degeneration and deformities. If, in such a case, the patient will deform at some point in time and need spine fusion, we have developed a product to do geometrical alignment and to ensure mechanical balance to avoid mechanical failure. The solution is connected to the patient, so the patient can take care of his own health as well, and it can be used by engineers and medical device companies to design patient-specific implants. It can also be used in an immersive manner by medical students to learn about spine fusion surgery.

So why do we think that this will be a breakthrough? Because we designed it in such a way to be high fidelity; you know, this is the unmet need, basically. The surgeon—we have, you know, on top of the team, we have a medical board. We have like five KOLs who are working with us on designing the software, and we have a scientific board with five professors, all specialized in spine biomechanics. We defined the solution to be high fidelity. So it's patient-specific, it's biomechanical, it includes muscles, ligaments, and it gives you stresses and strains in the spine. It is smart, so it adapts. It proposes automatically some solutions that the surgeon can choose to use or not or to modify, but it will help him decide. It's easy to use, as I said; it will be immersive, and it's designed to be usable on a phone in 10 minutes of time, and efficient because it's applying AI all over the place to do everything as automatically as possible.

So why should we care? Because basically, first and most importantly, it will improve patient life while reducing the cost and the time for all people involved: the physician and also the hospital. So it's not rocket science. We are not reinventing the wheel. Actually, what we are doing is taking a technology that has been applied for more than 60 years, and I was managing the company that pioneered this technology at an industrial level, taking this technology and applying it to medicine.

And why now? Why now exactly? Because AI will allow this kind of complex technology, which was before done by engineers for engineers, to be applied by physicians in 10 minutes of time, without knowing the technology behind it. And now it's important because all the trends in healthcare are about prevention, reducing costs, personalization, precision medicine, digitalization—all these mega trends in the healthcare industry are addressed by this solution, and AI will make it usable in different ways.

So the market is huge. We are in the orthopedic market, which is more than $50 billion. But I don't want to get into all these big numbers. But if we sum up, if we go bottom-up, with all the 2 million surgeries that are done a year, and we charge for the software as it's used, we have an addressable market of $3 billion a year, with $570 million a year of serviceable market. So our plan is to reach 25,000 patients by the end of 2028, and our products are being developed right now. So everything is not yet ready, but we will be submitting the first product, you know, Spine Sim Align, to the FDA and CE in 2025 and starting to generate revenue in 2026. Then we will have another product coming to market in 2027-2028, which will generate additional revenue.

So our plan is to reach €500,000 of monthly recurring revenue by the end of 2028. So why are we here? We are here to raise €2 million, two to five million, but a minimum of €2 million. The objective is to take our first product to market, so to get it FDA certified and CE marked by mid-2025 and to take it to market in 2026. If you are interested, just let me know.