התמלול המלא של Real Brain Technology is Powering Up Drug Discovery and Going Global

globally, um more than um um cancer and and more than uh cardiovascular uh diseases. 00:06:41.600 --> 00:06:55.600 Over the last um uh 30 years or so, um more than 96 percent of drugs uh fail in clinical trials uh when it comes to neurodegenerative diseases and neuroscience therapeutics. 00:06:55.600 --> 00:07:03.759 And uh more than 70 percent of this failure, um, it really goes back to the early drug discovery. 00:07:03.759 --> 00:07:26.720 Uh the literature but also practical experience points to the fact that when researchers are using not the right models to discover and to validate the targets, that leads to um an incorrect decision of the assets that they can um then continue the drug development pathway. 00:07:26.720 --> 00:07:39.199 So if someone makes a mistake at the early stages of drug discovery or it's not the right asset, this mistake can then um progress and can lead to significant failures down the track. 00:07:39.199 --> 00:07:45.279 So, what we're trying to do with our technology is to um uh develop new insights. 00:07:45.279 --> 00:07:55.439 So we have a technology that comes much closer to the human um physiology and uh how a disease may develop in a in a human setup. 00:07:55.439 --> 00:08:08.000 So we are able to apply this technology at the earlier stages of drug development and basically identify the the acids, but hopefully also later in clinical trials. 00:08:08.000 --> 00:08:31.759 So we have these micro tissues live in a uh in a 96-well plane, it has multiple wells, so you can imagine one uh just for the sake of this discussion, I will call them mini-brains, one mini-brain in every well where um uh they grow inside a specific um uh formulation of media to provide nutrients. 00:08:31.759 --> 00:08:40.480 And in this well, we are also um adding the uh the therapeutic compounds, the experimental treatments. 00:08:40.480 --> 00:09:02.159 And these treatments they have an effect on how these micro tissues are growing, how the cells and the neurons are changing, and then we can um evaluate uh what is the effect of this treatment when it comes to the neural networking, to what is their effect on neurotransmission and several other parameters. 00:09:02.159 --> 00:09:08.399 So, with one tool, our mini-brains, we can develop an abundance of data. 00:09:08.399 --> 00:09:17.039 We can what is the effect of the drug in the human neurons, any combination of um of brain cells. 00:09:17.360 --> 00:09:19.519 And what are you calling this technology? 00:09:19.759 --> 00:09:22.879 It's it's actually the real brain technology that we call it. 00:09:23.200 --> 00:09:29.039 So, how many of these you know, mini real brains can you manufacture, you know, in a day? 00:09:29.039 --> 00:09:31.759 Like, are we talking thousands? 00:09:32.080 --> 00:09:51.519 So, what we call now uh mini-brain, many people can also relate to um human brain organoids, uh, that it's it's a form of organotypic culture, again, in a 3D format, that they're trying to again replicate the uh the brain as an as an organ. 00:09:51.519 --> 00:10:07.360 And this technology has been uh has been used for hundreds of labs around the world uh for a for more than a decade, but there are some significant limitations with uh technologies like that in an academic setup. 00:10:07.360 --> 00:10:10.799 And one of these limitations is the scalability. 00:10:10.799 --> 00:10:22.480 Um, there are several limitations in creating such organotypic cultures at scale, that has been a limiting factor for their adoption as well. 00:10:22.480 --> 00:10:43.279 When you have um an adoption from the whole pharmaceutical industry, you need to make sure that uh your, I call it a product, this this technology, it is very important to be consistent but also scalable to ensure that the the data that coming out of this technology are the same. 00:10:43.279 --> 00:10:54.879 No matter where you are in the world, no matter who is doing the assay, it needs to have this type of um standards when it comes to reproducibility and scalability. 00:10:54.879 --> 00:11:05.519 And this is exactly where um what are the uh the barriers that we are uh let's say breaking with our technology. 00:11:05.519 --> 00:11:21.600 Um because of the technology that we have been using uh with with the scaffold, we have the ability to really create thousands of these uh structures, of these human relevant structures every day. 00:11:21.600 --> 00:11:35.360 Um, so it it was a very um a very long RD process that we had at the SARA therapeutics to make this technology um compatible with automation. 00:11:35.360 --> 00:12:05.440 So we use robotic automation that can really uh create more than hundreds of these uh micro tissues in every two to three minutes, and we can generate thousands of these every day if necessary, and that allows us to really develop a technology that can be adopted at a global scale for the pharmaceutical industry, and this is what um we want what we aspire to do as the cellar therapeutics. 00:12:05.440 --> 00:12:37.759 We're trying to develop a technology that sets the gold standards when it comes to testing in neuroscience therapeutics, um, because another um benefit that we can provide with our technology, if it is um uh predictive but also scalable, we can uh set the benchmarks of different therapeutics and understand how new um uh experimental drugs perform against historical drugs that they have been in the market or not. 00:12:37.759 --> 00:12:43.840 And that can be very valuable uh for the neuroscience uh uh field in general. 00:12:44.159 --> 00:12:47.679 Where do the stem cells come from, the neural stem cells? 00:12:48.080 --> 00:12:56.000 Yeah, they are coming from um either uh healthy donors or uh donors that they have a disease. 00:12:56.000 --> 00:13:04.480 Uh Tessara is not the responsible company to retrieve these cells, although we we can if we want to. 00:13:04.480 --> 00:13:36.320 There are some specific specialized companies that we are

working with that um they do this as a job to have all the um ethics and the processes approved from the FDA or the uh regulatory framework of every jurisdiction to collect um uh cells either from uh from the skin or from blood, that then they can turn into neural stem cells, and then we we use these neural stem cells to uh yeah generate our micro tissue. 00:13:36.320 --> 00:14:17.600 And that uh allows us to um to go one step closer to the actual human clinical trials because what we're also um trying to do is to um collect um um cells from patients that have um different forms of Alzheimer's disease, I i and this is a very simple term I'm using um from different genetic backgrounds and different and sexes to try and replicate what the clinical trial is uh uh in a normal clinical trial setup with patients, but in the lab. 00:14:17.600 --> 00:14:41.919 So by collecting cells from individuals with different genetic backgrounds, we can somehow mimic this clinical trial in this, as we said, the clinical trial in this concept, where we create these uh mini-brains um from uh neurons that they're coming from individuals that they have different forms of Alzheimer's disease. 00:14:42.159 --> 00:14:45.679 And are you working with any drug discovery companies in Australia? 00:14:46.000 --> 00:14:54.559 We're working with um companies that develop neurological assets in Australia and also in the United States mostly. 00:14:54.559 --> 00:15:05.600 Um, so yes, there are um um uh listed companies and unlisted companies uh that uh are using our technology to de-risk their drug development pathway. 00:15:05.600 --> 00:15:22.080 Uh because it's not only the de-risking by collecting human relevant insight, but also trying to limit the use of animal models when they are not necessary in order to inform your uh readouts, can help companies accelerate their drug development path. 00:15:22.080 --> 00:15:35.440 So a relatively simple study can take two to three years when using animal models when it comes to breeding the animals, to get the information from the animal models and all the processes involved, and it's very expensive. 00:15:35.440 --> 00:15:42.720 And what it takes two years to complete in animal models, we can do with our technology in a couple of months. 00:15:42.720 --> 00:15:44.960 So, and at a fraction of the cost. 00:15:44.960 --> 00:15:53.519 So companies are using us already to de-risk and accelerate their drug development pathway. 00:15:53.840 --> 00:16:02.080 So tell us about the US market and obviously with customers in the US, what's been the response, uh, interest there in your technology? 00:16:02.080 --> 00:16:07.440 And how often do you have to go to the States to meet with your customers and potential customers? 00:16:07.759 --> 00:16:22.399 Uh, we're a relatively new company, so we we started uh operations in 2020, but I think um we had a very good trajectory since it took us from concept to revenue about four years. 00:16:22.399 --> 00:16:26.240 So we started generating revenue in um 2024. 00:16:26.240 --> 00:16:31.840 So we're still a new company when it comes to commercialization and we're still expanding. 00:16:31.840 --> 00:16:35.120 We have a small number of customers, important ones. 00:16:35.120 --> 00:17:01.759 And we have seen a significant change in in the demand of our technology um after the FDA modernization act, where they um uh passed uh uh a law that they ended a blanket rule that um no company, no sponsor could start clinical trials without having animal models. 00:17:01.759 --> 00:17:03.679 So that was a mandate. 00:17:03.679 --> 00:17:17.039 This mandate doesn't exist anymore, which means companies can initiate clinical trials, testing uh a therapeutic um candidate in humans even without using animal models. 00:17:17.039 --> 00:17:33.759 And um after this uh this change in the in the legislation, there are several other changes that have happened, and the FDA has uh responded into these changes um um quickly, I would say. 00:17:33.759 --> 00:17:46.480 And very recently, uh just uh in April this year, um they developed a specific roadmap for phasing out the use of animal models in in general. 00:17:46.480 --> 00:17:54.640 So, what FDA is trying to do is in a few years' time, the use of animal models would be an exception rather than the rule. 00:17:54.640 --> 00:18:07.680 Uh, because new technologies like ours, they're more human-relevant, more predictive, and they can assess many of information that we get from animal models uh faster and more reliably and cheaper as well. 00:18:07.680 --> 00:18:15.519 So we're trying as a company to create stronger awareness uh of what we do in the US. 00:18:15.519 --> 00:18:24.880 As I mentioned, we are a small company, and unfortunately, Sara and many, many other companies are um well underfunded. 00:18:24.880 --> 00:18:27.200 Um, well underfunded. 00:18:27.200 --> 00:18:39.920 So we are trying to leverage um bigger partners um and run as lean operations as possible here in Australia in order to raise awareness of our products. 00:18:39.920 --> 00:18:49.680 So, as part of these um uh of these strategies are recent agreement and collaboration with uh nSphero , which is a Swiss-based company. 00:18:49.680 --> 00:19:03.039 Yeah, um and InSphero is is is a remarkable company and uh with a remarkable CEO, I consider them as the architects of human relevant in vitro cultures. 00:19:03.039 --> 00:19:22.000 Uh they they started with um uh liver, human micro tissues, and then they uh developed um uh cancer models uh and and and other models as well that really um help the risk development programs, uh like Tesara, uh, for example. 00:19:22.000 --> 00:19:31.920 And uh InSfiro is is the largest uh company with specialization in scalable um 3D human relevant in vitro technology. 00:19:31.920 --> 00:19:44.480 So working with a company like InSfiro um helps us to um to have a bigger footprint than what we have because we work as

partners and we have technologies that can complement each other. 00:19:44.799 --> 00:19:48.799 Well, congratulations on that distribution agreement with InSfiro. 00:19:48.799 --> 00:19:50.720 That is major news for you. 00:19:50.720 --> 00:19:52.559 And watch this space, I think. 00:19:52.559 --> 00:20:05.440 Um another um interesting announcement that from late last year was that you were part of a Cooperative Research Centers projects grant with Silo and the University of Sydney. 00:20:05.440 --> 00:20:09.440 That's a major project that you you're part of or leading. 00:20:09.839 --> 00:20:17.039 It is indeed something uh very very close to my heart because again, we are creating new new science there. 00:20:17.039 --> 00:20:26.960 It's um something that, in my knowledge, hasn't been done before uh using organotypic cultures to uh to get into this space. 00:20:26.960 --> 00:21:03.920 And to be more specific, what um the grant that we managed to get together with Silo and the University of Sydney is to develop um a framework of um and a pipeline where we uh uh Tesara is screening a list of compounds um originally sourced from xylo that they have uh that they have developed through their proprietary technologies, and then develop um new models of um drug abuse and specifically methamphetamine abuse. 00:21:03.920 --> 00:21:32.319 So we are entering um the stage of like mental health um sector, uh, so to develop an in vitro model to assess um addiction and to assess how um new uh new therapeutic candidates can uh can prevent addiction or can be used to help people with addiction when it comes to uh uh yeah illegal drugs like methamphetamine. 00:21:32.319 --> 00:21:45.440 So we are bringing together expertise um like our technology that, as I mentioned, we develop a a whole new kind of of a disease model for this program. 00:21:45.440 --> 00:22:18.480 Uh the knowledge of um the and the expertise of silo developing some novel neuroplastogens, and I will explain later what that is, and also the expertise of the University of Um of Sydney, that they have developed some animal models as well to test the the reactions and the behavioral components that of course we cannot test with with our technology, and that can be used as uh let's say a uh a validation of our findings. 00:22:18.480 --> 00:22:32.720 So, what we are trying to do in these um uh in this ground is to identify therapeutic components that can change the neural networking of the human brain. 00:22:32.720 --> 00:22:54.960 So we want to increase neural plasticity in the human brain and create new connections because the research so far suggests that by by doing that, you are um helping a specific set of individuals to be um uh to accept new new new treatments and new learnings as well. 00:22:54.960 --> 00:23:18.960 So um, together with um specific programs uh designed to help people with addiction and with administration of such uh therapeutic compounds, um, we really believe that we can make

a significant difference in the life of this um of these people and change their uh addiction profile. 00:23:18.960 --> 00:23:26.960 And I have to say, I'm not expert in that field, so I apologize in advance if I say something um inappropriate there. 00:23:26.960 --> 00:23:54.000 Um, but the good thing about the Sarah is that um um we have already developed some really, really good and promising results that we've never seen before, which indicates that we can really see this effect of addiction um that we know from humans when we expose our technology to uh to to drugs like methamphetamine, which is amazing. 00:23:54.079 --> 00:24:01.920 It it's so you can see it's sort of in the test tube, you can see this interaction of addiction or the cells, you know, that we have to do it. 00:24:02.240 --> 00:24:15.920 So we can see we can already see um elements of what now it happens in the in the human networking, how the neurons are dhammased and they decrease their ability to communicate with other neurons. 00:24:16.160 --> 00:24:16.559 Really? 00:24:16.799 --> 00:24:25.599 Um, and yeah, it is something that hasn't been seen before, in in my knowledge, and we're really, really excited about this framework. 00:24:25.599 --> 00:24:40.319 And as part of the CRCP program, and I guess that's important for our industry, is that after the program we could use this this pipeline, this framework that we develop for for all the other companies as well. 00:24:40.319 --> 00:25:04.799 So it is really a technology that hopefully can elevate the the translation of Australian research and technologies to to help this program um and the problem which could be expanded to to it could be expanded to opioid crisis and and other issues when it comes to um uh uh to to problems in relation to addiction. 00:25:05.119 --> 00:25:06.720 Yes, and incredible. 00:25:06.720 --> 00:25:17.680 And you know, as we know, the the issue of drug addiction from everything from fentanyl to methamphetamine is totally changing communities around the world. 00:25:17.680 --> 00:25:21.200 Can you just explain what are neuroplastigens? 00:25:22.079 --> 00:25:26.319 Yeah, it um the neuroplastigens is is exactly what I mentioned before. 00:25:26.319 --> 00:25:44.400 There are specific classes of compounds that their main uh job would be to change the the neural networking, to promote the plasticity inside the brain, to to create new connections between neurons that they are functional as well. 00:25:44.400 --> 00:25:55.200 And uh together with this, there are several changes in the human brain because that allows uh the brain to learn faster, better. 00:25:55.200 --> 00:26:12.480 In some cases, it can help change the uh neuroinflammatory profile as well by using therapeutic candidates that can uh again help the addict brain to perform better in combination with other behavioral treatments. 00:26:12.480 --> 00:26:40.000 And again, I'm not expert into all the treatments when it comes to addiction, but

in my in my understanding, and what we want to achieve is, as I mentioned, these therapeutic compounds to be in addition to um specific behavioral training and and and um guidance that these people will get from other services, not just by the uh the use of uh therapeutic compounds. 00:26:40.319 --> 00:26:43.119 And how long is this CRC project for? 00:26:43.119 --> 00:26:44.240 Is it a couple of years? 00:26:44.640 --> 00:26:45.200 For three years. 00:26:45.200 --> 00:26:46.559 It is for three years, yeah. 00:26:46.880 --> 00:26:47.839 Absolutely fascinating. 00:26:47.839 --> 00:26:53.920 Looking into the science of addiction at a test tube level, at that neuron level, must be mind-blowing. 00:26:54.240 --> 00:27:04.079 It is, it is, and and soon we we plan to to launch uh ready-to-use uh platforms or plates for mini-brains. 00:27:04.079 --> 00:27:16.079 What that means is that so far all the work and revenue we have generated is by providing in-house drug screening services to uh to companies. 00:27:16.079 --> 00:27:31.119 But now we're developing uh a program or a product that we can um distribute this type of plates, 96 well plates or 34 well plates, with the mini-brains inside that they're leaving. 00:27:31.119 --> 00:27:44.079 And and companies can will go in the near future in our website or through our distributors to order these mini-brains so they can have them in their lab and do a variety of testing. 00:27:44.079 --> 00:28:12.240 And we really help that this will um uh we think that this will help the translation of research in Australia but also um globally and uh help neuroscience innovators everywhere to progress their program because if we want to have um a transformational change into uh the development of therapeutics for neurodegenerative diseases, we need to solve this problem collectively. 00:28:12.240 --> 00:28:29.519 So we can use all the brain power in the world uh available, and many smart people in the US, in Europe, in Australia uh to use the best tools and find problems and therapies for neurodegenerative diseases. 00:28:29.519 --> 00:28:38.720 So we we want to create this enabling platform to raise the the standards and the successes of clinical trials. 00:28:39.119 --> 00:28:41.200 How do you transport this material? 00:28:41.200 --> 00:28:43.279 Um, does it have to be refrigerated? 00:28:43.279 --> 00:28:49.200 How long is the lifespan of these mini brains in this sort of manufacturing device? 00:28:49.920 --> 00:29:10.640 We are at the last stages of RD, and I cannot reveal all the information, but uh most likely we will not need uh uh cold chain solutions to transport these micro tissues, which makes it very simple for us and inexpensive as well for for the customers of our uh technology. 00:29:10.640 --> 00:29:30.559 And once the customers um receive our micro tissues, they can stay in their labs for months and months to do to studies chronic exposure uh uh studies and assess the uh uh yeah how effective their um

experimental drugs are. 00:29:30.559 --> 00:29:55.440 Uh but also what we are very excited about, and I'm again I'm going even further in the future, what's what we want to do, having the ability to create such uh so many micro tissues and literally have millions of data points, is we want to use um, and I'm I'm using the term vaguely because there are many different systems that can be used. 00:29:55.440 --> 00:30:16.079 Uh, we want to use artificial intelligence AI to Combine an abundance of data from safety, toxicity, electrophysiology, and others to create a very strong predictive model that it's going to work together with our mini-brains. 00:30:16.079 --> 00:30:50.400 So we want to have the best input possible from a technology like our mini-brains and using the right um data science and artificial intelligence to combine all this data that we can get and uh really help companies and the industry to uh have a transformational growth when it comes to the development of uh therapeutic candidates that they really have an effect and uh potentially can help millions of people with um neurodegenerative diseases. 00:30:50.720 --> 00:30:53.119 And all manufactured in Parkville? 00:30:53.599 --> 00:30:54.799 Uh yes, that's right. 00:30:54.799 --> 00:30:58.480 We are based at Jumar since December 2023. 00:30:58.480 --> 00:31:02.960 Um, yeah, and we manufacture that um here in Parkville. 00:31:03.200 --> 00:31:04.799 It's a great story, Christos. 00:31:04.799 --> 00:31:11.359 And you worked early on in your product development through the CSIRO Kickstart program. 00:31:11.359 --> 00:31:19.440 So, what would you say about companies thinking about partnering or working with some of those types of incubator programs? 00:31:19.440 --> 00:31:21.119 How helpful was that? 00:31:21.759 --> 00:31:28.480 Well, I can uh I can only say that without the Kickstarter, perhaps we wouldn't be here today. 00:31:28.480 --> 00:32:12.160 Uh working with CSIRO and uh and the team there in the uh uh biomaterials team um and the biology team and the kickstart program was fundamental because the the company just started with with a with a concept and an idea that we shared with CSIRO, and they made this idea a reality, working together to develop our our biomaterials, composition of matter, and and anything else was was fundamental, and then to develop the the processes that these biomaterials can be um synthesized at scale. 00:32:12.160 --> 00:32:22.799 This is really uh fundamental to have consistent manufacturing at scale and CSIRO was uh yeah, critical for that, critical. 00:32:22.799 --> 00:32:28.799 And the Kickstarter program helped us to do that because we literally had no money. 00:32:28.799 --> 00:32:31.119 I was not working, I quit my job. 00:32:31.119 --> 00:32:34.799 Uh the job I had, I said, okay, this is it. 00:32:34.799 --> 00:32:38.799 I'm making the seller therapeutics, is going to happen or not. 00:32:38.799 --> 00:32:59.119 So we're very fortunate that we

found an investor that wrote us this um 50,000 check, let's say, in the beginning, and we used that directly for the CSIRO Kickstarter program to double that that money and yeah, uh create or materials. 00:32:59.119 --> 00:33:00.720 Yes, that's that's how it started. 00:33:01.039 --> 00:33:17.039 Very much an Australian-born innovation developed here and manufactured here, which is a fantastic story because you are a startup, and as you've said, it is very difficult to get funding, it's very difficult to get investment at that early stage. 00:33:17.039 --> 00:33:19.680 Just a fantastic result for you. 00:33:20.000 --> 00:33:26.640 I I think it is, and it's a good Australian story and technology that can really go global. 00:33:26.640 --> 00:33:37.519 We had minimal support from um government initiatives or state initiatives in order to do that, no matter how much we have been we have been trying. 00:33:37.519 --> 00:33:45.759 And our our one of our um goals as well is to be a financial contributor to the economy here in the ecosystem. 00:33:45.759 --> 00:33:52.640 And to be honest, this has not been recognized almost at all, or in at very, very minimal uh states. 00:33:52.640 --> 00:34:22.079 And um, yes, I would really like to see initiatives that they help um companies like the SARA because we are not the only ones, because um uh like the Tessara, many other innovators at Jumar in Victoria and everywhere in Australia can can really help um create new innovations that Australia can be proud of, and we can have a significant part of the common economy to be based in these type of innovations. 00:34:22.400 --> 00:34:28.559 Do you feel like investors in the US are are more likely to go for a new experimental type technology? 00:34:28.559 --> 00:34:32.079 They're just more of a first mover on that science. 00:34:32.079 --> 00:34:34.159 Are we a bit cautious in Australia? 00:34:34.559 --> 00:34:36.800 In my humble opinion, yes. 00:34:36.800 --> 00:34:38.400 Very, very cautious. 00:34:38.400 --> 00:34:41.519 We do not celebrate risk, I think. 00:34:41.519 --> 00:34:56.000 And I think we we can learn more from the um the US mentality that they they celebrate risk, they celebrate uh failure in some cases, um, because that is the mother of all innovations. 00:34:56.000 --> 00:35:10.320 And we can see how innovation now is the driving force of economy in in the US, from the services businesses, the software, artificial intelligence, and several other components. 00:35:10.320 --> 00:35:14.880 Innovation is what is driving economic growth, in my opinion. 00:35:14.880 --> 00:35:25.039 Um, and I think Australia really needs to think hard on that and create innovations with competitive advantages and uniqueness to do that. 00:35:25.039 --> 00:35:36.559 And we have seen also examples of Australian innovations that they have not been recognized in Australia, but they did get recognized in the US and now they're part of a of another economy. 00:35:36.559 --> 00:35:43.760 And although in newspapers and articles we we call them Australian innovations, they are not anymore. 00:35:44.079 --> 00:35:46.480 Well, they're born here, but then they leave. 00:35:46.480 --> 00:35:51.119 And they take you know the IP and the and the job opportunities as well. 00:35:51.360 --> 00:35:51.760 Exactly. 00:35:51.760 --> 00:35:52.079 Yeah. 00:35:52.320 --> 00:36:01.760 It's a really interesting problem, I think, that that the sector's facing in terms of employment for uh for scientists and for um biomedical engineers. 00:36:01.760 --> 00:36:05.840 Obviously, there's a huge opportunity there around this type of technology. 00:36:06.159 --> 00:36:06.719 Absolutely. 00:36:06.719 --> 00:36:12.159 There is a huge opportunity, and CSIRO also, again, uh it's a fantastic organization. 00:36:12.159 --> 00:36:20.639 Um, they created um a report a couple of years ago when it comes to the development of non-animal technologies. 00:36:20.639 --> 00:36:31.599 Uh, and we identified that the growth opportunity and the financial opportunity of Australia alone in these technologies alone can be more than 1.5 billion of growth. 00:36:31.599 --> 00:36:34.719 So we are talking a huge opportunity here. 00:36:34.719 --> 00:36:41.599 Um, new technologies, uh uh, new skills that they can be developed uh from companies like Tessara. 00:36:41.599 --> 00:36:43.760 Tessara is a is a tiny company. 00:36:43.760 --> 00:36:46.719 Uh it's it's about eight people that we have. 00:36:46.719 --> 00:36:52.719 Um we we need more people, but we also need more capital to employ more people. 00:36:52.719 --> 00:36:57.360 So we are trying to run a very lean operation and try to achieve as much as possible. 00:36:57.360 --> 00:37:29.440 But hopefully, um everything that we discussed, the changes in the regulatory framework, the new innovation that we develop with the ready-to-use plates and the artificial intelligence components can help us grow our business through revenues, but also becoming more attractive to uh domestic and US investors um to help us grow the business and um create more uh uh uh skilled uh experts that can help the Australia to grow as well. 00:37:29.679 --> 00:37:36.320 Well, it sounds like definitely the right time for your real brain technology and exciting times ahead. 00:37:36.320 --> 00:37:46.719 We'll be watching with interest, Christos, and we wish you and the team all the best at Tessara Therapeutics on developing this amazing technology. 00:37:47.039 --> 00:37:47.920 Thank you, Caroline. 00:37:47.920 --> 00:37:50.239 I'm very um grateful for this opportunity. 00:37:50.239 --> 00:37:59.920 MTP Connect has been doing also a fantastic work um managing development grants and opportunities that they provide to biotech companies. 00:37:59.920 --> 00:38:13.199 And I think it's a very strong contributor to creating opportunities for Australian biotechs to thrive and grow and again uh bounce above their weight and be become globally competitive. 00:38:13.199 --> 00:38:15.519 So thank you for everything you do as well. 00:38:15.840 --> 00:38:19.519 That was to Tessara Therapeutics CEO and managing director, Dr. 00:38:19.519 --> 00:38:24.719 Christos Papadimitriou, discussing their real-brain technology. 00:38:24.719 --> 00:38:31.280 You've been listening to the MTP Connect Podcast. 00:38:31.280 --> 00:38:36.480 This podcast is produced on the lands of the Wurundjeri people here in Nam, Melbourne. 00:38:36.480 --> 00:38:38.079 Thanks for listening to the show. 00:38:38.079 --> 00:38:42.000 If you love what you've heard, share our podcast and follow us to more. 00:38:42.000 --> 00:38:43.519 Until next time.