Carolina Aguilar Presents INBRAIN Neuroelectronics at LSI USA '23

Transcription

Carolina Aguilar  0:04  

Hi everybody, we are INBRAIN. We are a health tech company using graphene to decode brain signals into breakthrough medical solutions, where 50 people with more than 35% of women were spinoff of the graphene flagship, which is a consortium that the European Union put with 1 billion euros to actually bring graphene to market. We raised significantly funds as to get to first inhuman this year. And now we are looking for a series be run off 55 million. We also managed to get a very big collaboration with Merck on bio electronics. So combining the neuro electronics potential with a bio electronics potential, we can get access to a 25 billion business opportunity. Now, this is what legacy technology of platinum and add on have been able to do. Decoding the size of a zebrafish that has you know, it's tiny, and it's only 100,000 neurons. Now the brain has nearly 100 billion neurons. And we need to understand it because one out of three people actually have a neural related disorder and 30% are refractory to medical treatment, building a big cost for our society. Every leap in humanity has to be linked to a key material from a stone age to silicon age. Today, we believe that be dimensionals materials like graphene are the next breakthrough for nanotechnology. Now graphene is a Nobel Prize winner material is the thinnest material known to man at an atom thick yet, it's 200 times stronger than steel, a very good conductor and very biocompatible. And as the Nobel Prize winner said, game, it's about the physics that it's able to deliver. Legacy therapies based on blockchain and video are just big limiting the adoption of neuro technology. They have also very poor resolution that need very precise implantation on very small nuclei of the brain, and therefore limits the outcomes that we can get these patients. And also usually they don't relate to the environment data of the patient, and therefore don't drive personalization. This is exactly what we can change. Graphene drives miniaturization to a cell cell like size, we can drive also very high resolution in a bidirectional way. So actually increasing the outcomes, increasing the adoption, but also bringing new biomarkers on environmental the patient and connecting with modern electronics to drive full personalization. We mean decoding the brain nuclei by nuclei like that, we will never make it. But neuro related disorders are relating to a secret on the brain that is pathological. This is just an example of the first indication we are doing Parkinson epilepsy and then speech more on the brain computer interface side, you can see how it will work, we will we are placing a cortical brain computer interface module on the motor cortex in this example, and then a subcortical module deeper in the brain. And we are looking at the synchronization of this network, in this case, the nigrostriatal pathway for Parkinson detecting pathological biomarkers and correcting them to increase the percentage of time in therapy of a particular patient, therefore increasing the outcomes or reducing the side effects. Same for the disease areas. This is exactly how our platform reflects the therapy. We have a cortical brain computer interface module that can have up to 1024 contacts just like Elon Musk, and so cortical module that has also quite high resolution all connected in a powerful intelligent decoding unit that also connect to the external biomarkers of the environment of the patient, driving that full personalization. I won't go into a Neriah, which is the one that we developed with Merck. But the mission is to connect the central and the peripheral nervous system because at the end, we have one nervous system. You see this is how it compares to legacy technology, legacy technology, some Platina Lydian has Milly metric sizing, reducing the potential on the outcomes detection. And also if you compare to the graphene technology, we can go submit a metric with a lot higher resolution 10 10,000 times smaller than the standard of care. So what we do is two main things because we can inject 200 times more charge injection at a very low impedance, we can reduce battery management and actually reduce the systems. So driving the militarization and the higher adult adoption, but also we can drive 10 times better signal resolution and therefore outcomes. These are just two examples on recording so reading and stimulating Writing. So on recording, you see that actually, we can read bands on the brain that metals cannot read. Therefore, it's like having a microscope that suddenly sees that bacteria. So we can create that antibiotic, we are seeing things that the others cannot see and therefore deliver therapies that the others can't. So that's what recording and stimulation we have compared to other polymers that are also coming into the market like the one from Mulaney. And we see that we have very much a very superior stability. So with a stimulation that material doesn't degrade like others. Now, the first application has high resolution, but the second technology that we are applying on the cortical brain computer interface goes to ultra high resolution. And there we can read every single frequency of the brain from 0.1 hz to kilohertz, were actually on the zero point where hertz on the low frequency bands, we have bands that actually are the ones that precede an epileptic seizure. So by looking at these bands with metals cannot see we can actually anticipate that epileptic seizure and stop it because stopping a seizure once has start is very difficult. But looking at minutes before that it starts, it's very easy to stop. Now on the graph below, you see the recording of the 1024, contacts life in an animal. And this has been published in Nature. We have blue and also the pathological estate control in a Parkinsonian model in rats, and now we are doing also in large animals. And we can read single unit activity LSPs. So we can also modulate the classical data. But we believe, and I'm sorry, I cannot show that data, that the closed loop and the treatment of these diseases is not only in single bands, but a combination of bands that actually relate to that sacred pathology. And all that requires a lot of signal processing. And that's why we are also coupling and developing a data hub with data applicants or clinical applications and research applications. With Series A we have achieved a lot. We have actually drive driven and FDA police app that has been proved to be very positive towards a commercial application in the US with a cortical brain mapping, acute cortical interface or interface. And we have also driven the subcortical to large animal trials. So the only two milestones that are pending to do is the efficacy studies on our animals of the subcortical interface and the first in human in cortical. And just recently we also received on the European Commission 17.5 million that will be part of the series be making that 55 million pause possible and actually having more than 50% of that. We have a very experienced team coming from powerhouses like Philips, Medtronic, Anwar but also material science. And then on the clinical side, we have also a very global clinical board. And recently we have also incorporated and we will announce soon, a vision board with a Nobel Prize graphene winner actually joining us another important people like David Eagleman, which is a very distinguished Stanford Neuroscience scientist. So we build credibility, but also be civility. We just want last month the Best Innovation Company in 2022 in Spain, we are looking for these partners for Series B and as I said, we have more than 50% if you feel this is of any interest, feel free to actually reach me after this presentation. Thank you, everybody.