Simon Sonntag, Virtonomy- Accelerating Medical Device Development & Clinical Trials | LSI Europe '22

Transcription

Simon Sonntag  0:05  

Thanks a lot. Thanks a lot for introduction. And good afternoon, everyone, it's a great pleasure to introduce you to Virtonomy in how we accelerate medical device development using virtual patient events. There are many medical device developers here. And we've learned all day, that the biggest challenge for them and they all share the same challenge in there, that is immense cost to bring these devices to market what can exceed $100 million, and also can take over 10 years, what is a lot in this whole process. Still, at the same time, many of these medical device developers fail in the process, and only less than 20% make it to the regulatory approval. And it's not getting easier this new regulations like MDR, but also coming from the FDA. This is even increasing the demand and the challenges there. The conventional process to bring a device to the market to testers on one hand, invitro tests, benchtop testing. On the other hand, invivo testing, like it was animals in human trials, in the last year is a fourth pillar has emerged, the so called in silico, testing in silico, because everything here is coming from the computer with computer simulations and computer testing. And this is now accepted by FDA but also globally, regulators and the FDA is even predicting that within the next years, over 40% of the regulatory process will come from virtual patients and simulations. And this is how it looks like. So the conventional process goes from the concept of a bench testing, prototyping, bench testing animal testing, cadaver studies, I wonder after many years of his high costs, for the first time the device is tested in human being when you fail here, you have to go back to the content. Because our approach, it's possible to test the device early on even before prototyping, using these virtual patients and simulations, and then also to substitute eventually replace experimental testing and animal testing. And to refine, expand the clinical trials. Imagine that you're testing your device, not just with 50 patients, but with hundreds or 1000s of virtual patients. By that we can significantly reduce costs time especially also risk to fail in the process to ensure the quality and also then the safety of the device, even before the clinical trials and then also after that. And we can also close the disparity gap of underrepresented populations, like for example, women, children, rather DCS and ethnic groups that are still underrepresented in r&d and clinical trials. Our solution is called V patients and it's an end to end solution very combined digital patient twins with artificial intelligence, multi physics simulation, and also predictive analytics. Here we can include as in silico technology in total product lifecycle of the medical device development and beyond. And then by that safe animals and humans by using our digital twins that are based on 1000s of humans and animal patients. Here we have greater the huge diversity in the so relating to the cardiovascular domain relating to the pathology, we are addressing heart failure patients, but also all kinds of heart valve diseases like mitral valve disease triggers, but valve disease, also different ethnic groups, data is coming from Europe and also North America and Asia, different age groups like we have patriotic data, but also adults and genetic and genetic data and different animals. So we have also in our database animals like sheep calf and pigs that you can use them to test your device in there to find the right animal type, but also transition from the animal to the human being. And first stage and our base aspects of the license, you can then test and virtual implant your device and the target population that is based on on this database. And the second part you can perform as this statistical population analysis to for example, look for inclusion exclusion criteria, eligibility criteria, risk case assessment, to then verify how does your population look like for example, also cluster male female patients and analyze this. Further on you can then also test the device tissue blood interaction by performing simulations, mechanical simulations, fluid dynamics simulations, but also electric physics simulations, and eventually create a report that can then be submitted as so called in silico evidence to regulatory bodies It is then used for assessment of safety and performance on this and this is how it looks like. So the first stage you can then select your patient for example, here are some 79 kilogram patient male, and then you can assess this three dimensional limb so you can see the anatomy and this you can also then make specific parts transparent to investigate, for example, the lung or heart parts in this here a cannula was placed in so you can find the proper position offers the proper angle of that it's an outflow cannula. You're gonna investigate this also from different angles and in the patient. As you can see here, once Have them found the proper location of this you can then have the setup of the simulation so in very easy to use environment to find the material properties of the of the device, but also surroundings of the tissue of calcification, grades, boundary conditions like the fluid, velocity rates, the outflow and so on, then start the simulation on the server that is run in the cloud. And once it's ready to get the results and can directly investigate and hear the results in a web browser and use and easy to use environment and other applications that we have are coming from total artificial hearts or ventricle assist device we can also identify then the virtual implantation of these patients in heart failure patients will also address artificial hearts, artificial heart valves, for example here as you can see the crimping of the stand and implantation and vessel wall and then also the blood interaction with the vessel leaf lens to investigate hemodynamic effects like thrombus formation hemolysis and so on the rest of it here also different design parameters and also see then the safety of the device. Others are also electric physics simulation for example, here is a two chamber heart model for investigating and pacemakers or house the dynamics of the heart movement on the device and vice versa to see here also durability issues. We have AWS integrator complete virtual reality environment you can use to analyze this in detail in a stereoscopic environment. Also to share this together with clinicians and have chosen a collaborative environment and work together in this virtual reality setting. You're also currently expanding from the cardiovascular domain to PDX domain domesticate then also artificial joints or spinal and other aspects relating to this. The feedback of the good the VA got proof that the outcome of this has significant benefit for the customers on the one hand, to speed up the process reduce the resources on the whole setups and whole aspects but also to give input is not possible as conventional approaches for was key for them to advance forward to reach the next milestone. And by that also to reduce the risk to fail in the process and data from our software. Varady accepted by the FDA in Europe but also in Japan in the submission process. You get also more and more visibility we are now recognized as one of the leaders in the stitches for the patient to win frontier, for example, had featured in the Boston Consulting Group article about BCG, about digital twins, then also mentioned by Raquel next to Siemens Healthineers, and also recently by Forbes, in an article about digital twins, but we're not stopping there. During the seed phase we have achieved our software, release the software and have now 10 paying customers on our platform. Our first focus was the cardiovascular domain. Now we are advancing to the orthopedics domain beyond the to the dental and neurosurgery domain. On the other hand, we are also expanding to clinical applications to use this for clinical decision support. And also then for post market surveillance once the device is on the market. Already, that's our first product we are addressing a huge market of 4.4 billion was the r&d in the non animal alternatives and in silico trials was the clinical trial domain and the clinical education, then, we are adding a market of 2.5 billion and more than 5 billion in the clinical decision domain. Last year, we raised our seed round was 1.75 million was for venture capital companies. And we're currently in the process of raising or 5 million series A to scale up the market expand to different domains and by that become market leader in the in silico clinical trials domain. All this is only possible as a top team where we're combining long lasting experience in the medical device industry and the sales process but also that deployment simulation data and AI and we are also supported by advisor from the business side and from the clinical side. Thank you very much