The language of life with Nora Khaldi, founder & CEO of Nuritas

Nora Khaldi is a mathematician with a Ph.D. in Molecular Evolution and Bioinformatics, and her years of research have focused primarily on protein evolution and comparative genomics.

Throughout her career, Nora’s ambition has been to disrupt the status quo in areas that have been void of technology by introducing new ways of thinking, big data, and new algorithms.

In 2014, she founded Nuritas, a Dublin-based biotech company that counts U2’s Bono and The Edge among its investors. Nuritas has combined life science, nature and artificial intelligence to develop its unique Magnifier Discovery platform and to identify, unlock, clinically test and patent peptides, turning them into powerful and precise ingredients that elevate natural efficacy and make our everyday products healthier, safer, greener and more efficacious.

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Music by keldez

Transcript

SPEAKER_01 0:00

Thanks for joining us on From Lab to Launch today. I'm Meg from Qualio, and it's my pleasure to be your host and introduce you to the movers and shakers of modern life sciences. If you haven't already, please subscribe, and we'd love it if you could give us a review on Apple or Spotify. Today we're talking to Nora Keldy, the founder and CEO of Irish biotech company Naritas. Nora is a mathematician with a PhD in molecular evolution and bioinformatics, and her years of research have focused primarily on protein evolution and comparative genomics. Throughout her career, Nora's ambition has been to disrupt these status quo in the areas that have been void of technology by introducing new ways of thinking, big data, and new algorithms. In 2014, she founded NURITOS, a Dublin-based biotech company that counts U2's bono and the edge among its investors. NERITOS has combined life sciences, nature, and artificial intelligence to develop its unique magnifier discovery platform to identify, unlock, clinically test, and patent peptides, turning them into powerful and precise ingredients that elevate natural efficacy and make our everyday products healthier, safer, greener, and more efficacious. Nora, thank you so much for taking the time to join our podcast today.

SPEAKER_00 1:23

Thanks, Meg. Lovely, lovely joining as well.

SPEAKER_01 1:27

So, Nora, you founded a company in 2014, and that was no small feat. That usually requires a strong vision and urge to make a difference. What led you to set up NORITAS back in 2014?

SPEAKER_00 1:39

Yeah, so it's an interesting story, Meg. So I worked, um, so I'm like you said, I'm a mathematician computer scientist, and I worked in drug discovery for a while and um using mainly algorithms to find better ways of identifying new drugs. But then I came into the area of nutrition uh after my PhD, and I realized it was a really interesting area uh where there was a lot of trends coming together. One trend was clearly humans were moving towards healthier options. They wanted healthier, they wanted more natural, they wanted things that worked for them. Um we had also these large FMCG companies wanting to differentiate their product, but really couldn't because a lot of the ingredients that are used in everyday products that we consume, whether it's a food, a beverage, a supplement, or even a cream, they're all the same. So there are 100-year-old ingredients that have been, you know, invented a long time ago, 100 years, and reformulated and repackaged, etc. So a lot of the differentiation today is really impossible. It's all about branding and marketing. And a lot of the ingredients are not don't work for what the consumers are looking for today. The trends of today are very different from 100 years ago. A lot of the ingredients were discovered at that time mainly for taste and cost. So better tastes, cost reduction, health wasn't even part of the equation. So when I came into the area, there was clarity in terms of there's a huge epidemic in the world. You know, people are getting um uh larger, so there's an epidemic of diabetes, cardiovascular issue, immune dysregulation caused by a lot of these ingredients that we're consuming every day. Um, and it's because of that, because they're old, um, because they've not been developed for health. And my first question coming into the field was why can't they make new ingredients? If ingredients is a limiting factor of big differentiation and also addressing the consumer needs that we're clearly moving towards healthier, more natural, more efficacious for them. And it's because it's expensive. So it's super expensive to create new ingredients. It takes decades and it costs hundreds of millions, and basically companies cannot recoup the costs. So ingredient discovery in our space is actually close to impossible. Um, so when I first came in, I'm like, okay, how can we make it possible? And coming from my own background, which is math and computer science, I realized that the issue was data. Um, that the reason why it was taking so long and costing so much is that the testing, the way they were testing for ingredient discovery, was uh tedious and random. And you know, if you take any plant or any source material, natural sources, you're talking about trillions of different molecules. So, how can you test and how can you know which one does what, etc.? And AI was the way forward. So coming into it, it was like, how can we create a technology that could help us identify faster molecules in nature and associate them to a health benefit in from various sources that were mainly food sources uh or plants that consumers have that we've been exposed to in the past. And how can we connect them to a health benefit and take them to market and make ingredients that not only are cost effective and um cost-effective and and and um uh stable in formulation, et cetera, but also have a health benefit? So our goal as a company is really about improving the health benefits of a lot of different products, improving the differentiation and creating ingredients that are better than what exists with an ultimate vision of improving the lives of billions of people.

SPEAKER_01 5:38

That's a lofty goal and a huge mission. What kind of strategic partnerships or collaborations have been crucial to your strategy and your growth with new neuros?

SPEAKER_00 5:50

Yeah, so obviously when you're building a new technology and it's not been proven, okay. At the very beginning, you're building something that conceptually, if it works, it was going to be massive, but you didn't have proof points at the beginning when you're like, theoretically, it should work. AI should be able to understand human biology and connect certain molecules in nature. We're focused on peptides with certain aspects of human health. Um, but it wasn't proven. So the first phase is all about proving the tech. And you need so first, the first initial investors that you get is very important. So that's the first partnership in terms of like not commercial but investor partnerships, where you're taking investors that are patient that understands that it takes a while to build the tech and prove it. Uh, so that was the first phase. It was like, can AI understand human biology and identify molecules that clinically are valid? So when you prove them clinically, they can um uh improve the biology and um and certain aspects of human health. So that took quite a few years to actually get it to a point where we were the first AI company to have proven an AI model within human multiple times, uh, into regulatory, into scaling, so scaling the product and onto the market. And now it's in like um the six continents now in various products globally, some of the ingredients we've developed through AI. Um, and so the first one was all about identifying the right investor partners. The second phase was obviously you can't just wait to create ingredients to start making some revenue. You really need to start proving the platform through through partnerships with different um large CPGs, large uh customers. And some of the very large ones, we had like large collaborations with the likes of BASF, Nestlé, Mars, and it's all in the public domain, Givaudon, etc. And those allowed us to co-develop ingredients with them. So, for example, BSF, uh largest chemical company in the world, we co-developed an anti-inflammatory for them that's today used in multiple products for anti-dandruff in shampoos and cosmetics, because they're they're big in that space. Um, so that's one example. For example, again, it's it's one that's based on AI. And it starts creating revenue, but also creates another way of um proving the platform and augmenting the capabilities of the platform. So that was the second phase. And the third phase, which we're we're now scaling significantly, is obviously the whole point of all this was to be able to create our own ingredients and take them to market. So prove the tech, um, take take the ingredients all the way from concepts. Like, for example, PeptiStrong is a good example of one that we went after muscle health, and we wanted to improve strength, mobility, um, energy production through muscle, skeletal muscle. And we created PeptiStrong, we proved it three times in three different um uh double-blind placebo clinicals, published it, scaled it, went through regulatory and took it to market. We did the same with a sleep ingredient uh that binds to aurexin, reduces cortisol. And that those are the cycles, and now we're in the phase of scaling commercially those ingredients globally. So now they're in various products, uh, like I said, in in six continents. And now it's all about you know improving the lives of billions of people, which means having our ingredients in as many products globally, um, in food and beverage, vitamin and supplement, and medical food as well. So those are, and and though, and that partnership there, it's more about the right customers that we put our ingredients through, uh, the right distributors sometimes, um, etc. So at different phases uh we're different, uh we needed different partners.

SPEAKER_01 9:52

And your customers are coming to you for ingredients. What else might customers be coming to Naritas for?

SPEAKER_00 9:59

Uh so they're coming to us to to um uh for various. So so ones is you know, if they're already working in the protein space. So you know protein trend is massive today. Um, but you can only put so much protein in a product. There's a limit to how much you can put in. PeptiStrong allows them to optimize that protein. So your body uh has um allows so PeptiStrong allows your body to double the effect of the protein. As an example, it doubles the effect, doubles the effect of strength, of energy, you get double the energy, double the strength, double the power, etc., double the recovery. So it's a differentiator that allows these companies not to just play on the grams of protein, but the quality of that protein and how your body actually processes it. Um individuals wanting to create more energy, so they want to go after the energy market and they want to go after more stable energy, and they want to uh go after consumers that improve consumers that are fatigued or feel fatigued during the day. All those are different areas of application of Peptich Shawn, one of our ingredients. There's also a different area which is sleep, where we developed a sleep ingredient where, for example, they would uh melatonin is the largest um sleep aid today uh in the space of consumer, but it has a lot of effects that consumers don't like as well. And what we've done is a plant-based non-hormonal replacement of Pepti, uh Pepti sleep, it's called. Um, and it's a really interesting peptide. And again, this is we've just launched it a few months ago. It's in various products today already, which is great, and it's growing um significantly. And and so forth. We have one in and one in um glucose management, um, one in bone density, et cetera. So we we have a pipeline of ingredients in development at different stages. Some of them have made it to market, some of them are earlier. So we partner with different customers, customers that want to launch in the areas we're in already, or see something in the pipeline that they want to already partner with early. So when it's ready, they'll put it into their products. Or sometimes it's about a new ingredient, like say with Givaudon, for example, we are co-developing um um sweet modulators and or flavor modulators in general, uh, how to modulate flavor in a healthy way. Uh, and that's some of the work we're doing with Givaudin, as an example. So it can be finished ingredients uh or ones in the pipeline that aren't finished yet, and they want to get access to those before, or co-developing something completely from scratch uh for very large markets and very large consumer needs.

SPEAKER_01 12:43

Exciting. And looking ahead, how do you see the peptide and nutritional landscape evolving over, say, the next two to three years?

SPEAKER_00 12:50

It's interesting, Meg, because when I first started Neuritas, those two areas, which is peptide and AI, were not known. Like in 2014, like AI for people meant artificial insemination. Literally, that I got that multiple times when I was presenting. It was like AI, does that mean artificial? So artificial insemination was more known than AI at that time. And um, so we were first to kind of bring those technologies to the to the this area. And then peptides was the same. Peptide is in the realm of pharma usually, and it's like, okay, what's a peptide? And it was um the reason neuratas and I chose peptides at the beginning was that I put a simple matrix at the very onset of neuratas to understand, okay, what are the areas uh what are the type of molecules that we should go after if we're going to use AI and transform the ingredient space completely. Um, and I put a matrix, and obviously you go through like large molecules, like proteins, you go through uh small molecules, et cetera. Peptides was the one that came in always high in terms of um uh in terms of the matrix I put in, in terms of regulatory friendliness, because it is a nutrient like a protein, in terms of production level, cost effectiveness of production, safety, et cetera, et cetera, access. So peptides was the reason, but at that time very few people knew peptides. What's interesting today is the trend has appeared over the past maybe two years and it's just growing like crazy. Obviously, GLP1 has played a role there, uh, all the GLP1 agonists, but ultimately peptides are really interesting molecules because they are the language of life, um, they are the messengers of the human body, major signaling molecule that tell the body what to do all the time. So you really can modulate and optimize your health through peptides. And this is why um, this is why we went after peptides. It's I do believe, and the trends show it, that peptides are the next uh big uh area. And and it's interesting because there's no limit to the number of peptides. It's not like small molecules with a small space. Peptides is the largest space known to humankind in terms of numbers, because there's no limit with what you can do with peptides. Um, so I do believe that peptides are the next big uh health-promoting ingredients uh that are going to really take over and and be functional ingredients in every product we consume.

SPEAKER_01 15:25

Amazing. Like just sounds like we've just started to scratch the surface of what we can do with peptides.

SPEAKER_00 15:32

Oh, absolutely. And then also, you know, the limiting factor at the times was, you know, when I first started NeuroTas, like anyone that understood a bit about peptides were like, but peptides are not bioavailable. You know, they're not orally available. If you eat them, they just break down. You're like, well, it depends. And and the reason why people thought that, or the literature thought that, and scientists thought that, was that there was only a small number of peptides that were known and studied. And those were not prone to be orally available. And as a consequence, it was like, well, if those are not already available, all peptides are not already available. But peptides, like I said, it's the largest space known to humankind. There's a lot of different peptides. And the goal through AI is to identify the ones that are efficacious and also available and work in clinical, so work in humans. So they they reach the the pathway, uh the target they need to reach, they they um exercise their efficacy, and then they're um they're broken up into amino acids.

SPEAKER_01 16:37

Amazing. Nora, can you share a pivotal moment in your company's development where you had to make a tough decision? And what was your outcome? Was it the decision to go with peptides?

SPEAKER_00 16:49

Oh, there was there's so many of them. There's so many of them. I think I think the one there was this case study actually with Carvard on NeuroTas, and it came right after COVID. Um, and and I think COVID was an interesting period for many, many companies, and especially for like all companies. Uh, but for us, it was interesting because we were it was it was a moment of like reflection in terms of uh focus because ultimately when you have an AI platform and you're going after all health areas, it's super hard to focus. So the goal, so COVID really was both super hard, super tough, because it was like, you know, um super tough for everyone, for everything, finance, uh employees, uh, everything. But also it was a really good time because it allowed us to say, okay, we can't do all this. We really need to bring it down to two or three and to cut everything else. Market size, east to market, uh, biggest consumer trends that are coming along. And we saw the consumer trend of muscle health when people didn't see it because we knew all these um uh um molecules like GLP1 were going to hit the market. So there was gonna be a more of an awareness of muscle being an important organ before before actually that launch. So we knew those trends were coming and it was about focus, it was about repositioning. We had to cut a lot of the, like many companies, a lot of people. So we had to reduce our focus um and and every other area we had to cut off to conserve runway. And but one thing I maintained, which actually went against what uh the majority of individuals were telling me, including shareholders, was when was the investment in the tech itself in AI. AI, you constantly need to feed it for it to become better and better. And the feeding in our space is expensive. It's not like it's feeding off literature. Uh, you have to actually create the data yourself, biological data. And the ultimate um decision at that time was well, you know, you cut everything, you don't spend on that. Let's let's just spend on taking the ingredients we have to market. So clinical, regulatory, accelerating. The decision at that time was no, we we cannot we cannot stop feeding the AI tech because it becomes obsolete. We need to keep feeding it and we need to keep investing in it. And that was actually um uh uh all those decisions were super hard from people decision, uh moving from you know, cutting down to um to what what projects do we maintain, what projects do we stop, uh, to like, okay, we yes, we need to cut uh expenditure, but we still need to spend on the early tech, even though it doesn't monetize there and then. Um, so those are some of the the decisions that when you look back, they were the right decisions to make. I've made also other other decisions that were right, but those were completely the right decisions to make at that time.

SPEAKER_01 20:12

Yeah, I think a lot of folks did get distracted with COVID and go chase UA approvals and things. So to hear that you missed and invested in the long term is really amazing. I think that's been a probably the key to your success through that time and and going forward.

SPEAKER_00 20:29

You have to, yeah, yeah.

SPEAKER_01 20:31

Well, funding is always top of mind for our early stage and scaling life science companies. What lessons can you share with our leaders navigating funding strategy in today's market?

SPEAKER_00 20:42

Funding is interesting. Um we've been we've always been able um to attract funding and the right and and the right type of funding for our company um and the right quantity as well. And we never went overboard. Um we we always raised more than what we needed, but didn't go crazy because ultimately you need to build up, you need to build enough uh and and and um and grow into your value as well. But I think the major things that I think are important from an investment perspective is have your story, right? So the what you're actually trying to changing our, you know, positioning science into something tangible that has both impact and commercial value is not easy. And you have to be really clear with that commercial value. You have to be ambitious in terms of like how big this could be if it worked. Uh, that is very clear and has to have huge impact. You have to have a good team as well around you. And I think people are super important in the uh In whatever rays. So team, the right positioning and the right, the right commercial positioning as well, not just the impact, but the commercial positioning. And then you have to show a growth trajectory. And I think this is more important today than it was, let's say, in 2021. Today, like we raised after. So we raised during that period where growth and real commercial traction is important. And I think that is that's key as well. So having commercial traction, whether it's like a bunch of, even if you don't have a product yet, but um a bunch of customers wanting that product when it's ready. Um I I remember during COVID, that's the other thing we did as well, which was super important. One of our clinicals stopped. So we couldn't actually sell our ingredient because the the clinic, the clinical, um, the CRO and university that was carrying out the clinical just closed down because of COVID. They couldn't carry on uh doing the clinical. That was a massive kick for us because it delayed the entire system. It delayed our ingredient from from uh launching literally a few months later. So what I did then is like, well, we can't get clinical data during COVID. So what we were going to do is get consumer data to start selling because the goal was to get to market. So we created a we're a B2B, we're an ingredient supplier, we're we're not uh D2C, but we created a D2C product. We branded it, we created a website D2C, we put it both on our website, Amazon, and then social media, and and I've I took some of the team and and and put them towards that and got external agencies to help us to prove that the uh, and this is for fundraising, to prove that there's a market for what we're developing. We didn't have a clinical, but still consumers were willing to pay quite a lot to access the ingredient, and we got consumers' reviews, et cetera, et cetera. So those kind of um commercial uh proof points, no matter how you get them, are super important. Um, so I that's what I would say to people raising investment.

SPEAKER_01 24:20

That's great advice. All right, very great advice. Now I have to ask Alex on our marketing team is a huge fan of you two and wanted me to ask you to get to meet Bono and the Edge personally when they became investors, and if so, what were they like?

SPEAKER_00 24:35

Oh, yes, so uh super nice. So they're you know, ultimately they've lasted all this, all these years because obviously they're great musicians, but they're also great business people and great minds. So um, and that's why they've lasted. They know their fortees, they know their weaknesses, they work well together, um, and and they really want to leave an impact in the world. So I I I was, you know uh incredible business people, both. And then I remember even with Edge, he's also a business person, but also um uh a science fan. So he's um he loves science. Um and he can explain experiments like like a scientist. So I think uh it was it was amazing, really good people. Amazing, and great supporters for the company as well.

SPEAKER_01 25:38

Amazing. Well, thank you for sharing, and that's amazing that they're so invested in the outcomes and the impacts that you're making with NERITOS. Um, no, I have to ask because I am our uh quality lead here at Qualeo. What systems or philosophies do you have in place at NERITOS to ensure scientific innovation doesn't come at the cost of quality or compliance?

SPEAKER_00 26:01

It's very important. And um and I think one of the biggest learnings, Meg, at the when I was before, again, when I was a scientist and and um well before NeuroTAS, it was the realization that you can find something really incredibly good from an efficacy perspective. So you can find a molecule that does something incredible from a health perspective. But if that molecule is not producible, if you can't produce it, if it's not stable in formulation, if it makes the product taste really, really bad, this is in our space, if you know the cost is too expensive, et cetera. Uh, and if the quality isn't there, because ultimately all these companies have a standard of quality and safety, et cetera, that would kill the project, no matter how great your molecule is. So it's super important, and this is why AI is really interesting, because AI can look at all these at the same time. So we when we developed uh magnifier, magnifier doesn't just look at efficacy of a molecule, it also looks at like its stability in formulation, it looks at its heat stability, can it be baked? Um, it looks at uh its oral availability, it's its uh allergenicity, it's so different factors that make up its scalability. Can we scale it in a cost-effective way? So we don't advance with an ingredient into further costs in terms of biological in vitro testing, ex vivo, into human without knowing those factors first. And that's through AI. So we had to develop different AI systems that became expert in all those fields. And this is why, um, and and then in parallel, you also develop a team. As we as we started taking ingredients to market, we develop an excellent team from a supply manufacturing quality control, because ultimately there are no large companies that are going to work with you without them going through your system and making sure that the quality is at their standard. So that is absolutely important, Meg. And actually, um, and this is why science alone does not work. It works in a in a combination with other parts, uh, quality, uh, commercial viability, et cetera, et cetera, to make it viable. So, yeah, very, very important. And also innovation in general, because you want to maintain innovation in a company. So, for example, with those, we know that the industry we're in, which is food, beverage, VMS, vitamin supplement, medical food, does not exist on their own. You know, there's other industries around them that influence them. For example, technologies like wearables that allow now consumers to make better choices. So, very quickly today, consumers are gonna be able to know if a product works or not. Um, and that's gonna increase. That choice is allowing consumers to choose better and make better choices for themselves. Those technologies now are growing and growing, growing really fast, faster than our industry. And they're gonna allow consumers to differentiate between brands that are just, you know, talking versus brands that are really wanting to make a difference and have ingredients within that really work for the consumer. And this is why, for example, we started integrating wearable technology in our clinicals so that people can actually not only feel it, but they can actually measure it and see it on their wearable. So, with sleep, for example, we integrated with the rings and some of the watches where you see, for example, your REM augment, your deep sleep augment, your your heart rate variability and so forth. So you're you're look measuring different biomarkers on the go with an ingredient because that's where things are going. Um, so you want to maintain that innovation while you're also making sure the quality and all the other systems are working as well.

SPEAKER_01 30:04

Amazing. Amazing, Nora. Um, any parting lessons from your journey that you'd want to share with aspiring life science leaders?

SPEAKER_00 30:14

Um I think the biggest one is listen to the market and adaptability. I think adaptability is the biggest factor of any if I'm talking to founders especially, but I think anyone, it's kind of in any job, it's being able to listen, hear what the environment is saying. If you're an entrepreneur, you're hearing your market and you're adapting. I think adaptation is the largest and biggest skill set anyone can have for success, um, especially as an entrepreneur.

SPEAKER_01 30:51

I think that's great advice, adaptability, especially as technology is changing so much faster in our times these days.

SPEAKER_00 30:59

Yeah, yeah.

SPEAKER_01 31:00

All right, Nora. Well, my last question is more of a fun one. If we ran into you at a bookstore or at your local library, in what section would we find you, Nora?

SPEAKER_00 31:10

Oh, so I'm gonna talk maybe more about neurotask. I I please. Yeah, so it's like, okay, so people would think at that time, I remember when we first started speaking about neurotask to different customers, more science fiction, you know, it's like science fiction, is this real? You know, sounds really cool, but it sounds so sciencey and so science fiction. And is it real? And uh, but we're real, so it's in the real uh maybe autobiography or or redefining uh the history or or um how a new industry appeared in in the history of of um uh uh of a new innovation. Or so so that yeah, so you'd see you'd see as more in um autobiography or history rather than actually uh science fiction, which is which is interesting, I think. Um yeah.

SPEAKER_01 32:11

Well, I would definitely pick up that book. I've been fascinated by your journey and all the decisions and and pivots you've made during COVID to have the success you've had. I think you're a true pioneer, Nora.

SPEAKER_00 32:24

It's been a thanks a million, and it was lovely talking to you. Thanks a million.

SPEAKER_01 32:27

Where can our listeners go to find out more about you and connect and follow Neuritas's journey?

SPEAKER_00 32:34

So, first, obviously the website neurotast.com for sure. And then we are um also uh we have a lot of um uh social activity as well. So LinkedIn would be a good one, Instagram, but LinkedIn would be a really good one personally for me and for Neuritas as well.

SPEAKER_01 32:52

Lovely. Well, we will link those in the show notes. Nora, it has been a true pleasure.

SPEAKER_00 32:57

Thank you. Thanks.