You cannot take, chemical engineer and making a data scientist and vice versa. But if they understand each other and they understand the context and they understand the challenges, you will be amazed of the innovation that they bring then to the table. Hello. My name is Omri. I'm a general partner at NFX Bio. And today, we're doing something special. We want to send out the bat signal.
We want to call the tech entrepreneurs and show them that they can start a tech biocompany and change the world. So with me will be Yogeb Debbie, founder and CEO of Manabio, He was my co founder, a Gillum Copilot, the company we read together, a tech guy starting in Intel, now doing his second tech bio company, and he can explain all about the transition between traditional tech and bio. So let's jump right in. So you give Debbie, great to have you here.
People don't know, but we've known each other for many years now. You've been my cofounder, the chief operating officer. So being together in the trenches, more than five and a half years that we got it done. And what people don't know about you and, you know, I'd be happy if you start with your background is that you started in tech. You didn't know anything about bio, and you made the jump. And now we see a lot of people, a lot of tech Pete.
They made their fortune in tech They want to have the impact of bio coming back to bio. The kind of joke is how do you make a small fortune in bio? It starts with a big tech Morgan. So maybe we'll start with that. Like, can you tell us more about your background? How did you get to this point? Yeah. Sure. So, you know, thanks for having me Pete. Always a pleasure to talk with you, Omry.
So my background is, as I already said, a period of science, as I said, and I actually got jetting a water Intel corporate So I started as a software engineer, then became team manager, program manager, really working on real tech, wireless devices, you know, And after, about almost 7 years at Intel, we Pete. And you told us about this crazy idea of, you know, DNA, like synthetic biology and synthetic DNA.
And everybody is going to synthesize DNA and edit James, and we have to have software to edit genes And it sounded like, you know, science fiction. At the beginning, we Pete talking back in 2010, which was really early days for this. I mean, it was even before crystal was discovered nobody knew what it was. So I remember coming to your lab at Stanford when you did your postdoc.
And we saw that, you know, the in luxurious lab at Stanford old and you're working with actual pen and paper and, you know, we'll, like, software engineers. This, like, sounds so bad. Like, this is how you do science. This is how you Pete, how you make drugs. This is crazy. So I think that was the first step into this huge world of biology and starting to understand the differences.
Yeah. So you join me in this crazy journey and the pipetting like monkeys in the lab to making a IDE or a card tool for allergies. That was our company. So then he moved from you know, being a manager in detail to being a chief operating officer in a software company for biology. So how was that transition? So we started general compiled on this idea of, you know, people who are going to edit James and the needs of tools.
And what we did is a audacious vision of let's create you know, dot Pete for DNA. So that was the idea. And I remember a few occasions where starting with this episode that, Stanford when we saw that, you may walk with Pete and paper, then when we started creating the actual software general compiler, and we showed it to users, and we were in this mind oh, everybody's gonna use it for sure. And then we presented it to lab scientists on the bench. They didn't even have computers.
So that was crazy. And then the people that had computers, for me, it was an amazing opportunity to use our software skills to really change people life on the Beller. Because when we show them some simple features, we showed for us, it was simple application Flint interface application. And for them, it was they showed us actual booklet, physical booklets with tables and charts and backgrounds, which they used to use on daily basis.
And when we show them, like, interactive application on our software, it was, like, showing, calculator to a caveman. You know, it was like mind blowing for them.
So for us, it was crazy to see that even though, you know, I didn't have any scientific background, I honestly think I'm not smart enough to be a scientist at PhD. It was great to know that, using engineering mindset and software skills, you can actually make an impact, you know, on these people and then later on, of, obviously, on, like, impacts people, impact humanity on that. So that was, great.
Like, on the team aspect, I can say that one of the challenges that we got really early on was that we as software engineers and, you know, all the tech people, you're used to get some kind of product requirements, right, from the product Pete. And they say, you know, this is how it should look like. This is the problem we're tackling. Just, you know, just go and do it. And then you want to figure out how to do it. What's the best way to do it? There is never a question of can it be done?
I mean, in software, like, yeah, everything can be done in just a matter of how long will it take? Who are the people to do it? What's the most efficient thing and what are the priorities. In biology, there is the initial way. Can it be done? We didn't ask ourselves this when we came to Omri and we asked him, you know, should the software behave like this or like that? I mean, what's the what really the product requirements? What should the flow be?
And always like, well, in biology, sometimes it works like that. Sometimes it works like that. I don't really know. Nobody knows. So it was like, okay. How can we, you know, implement and develop any software application here, which we don't know the underlying requirements. So sometimes it will Morgan. Sometimes there will be bugs.
Yeah. Yeah. So it's been quite a ride, right, you know, and a learning experience, right, you know, five and a half years in the trenches building software for bioengineals seeing the price of a synthesizing DNA going down along the way, being in all the scene by a Beller conferences.
It's been quite a ride, and then we were lucky enough to get acquired by twist bar sciences a company making DNA where I became the head of COVID for Twist and you, aid in Israel and led the twist Israel, the entire group. Right? Yeah. So that was quite an adventure and the whole, yeah, the acquisitions. I mean, it was great because we felt and, you know, you know, and we we talked about it a lot.
We felt that we're, I joining this huge revolution and finally when we joined forces with, with another company that actually complements us. So that was great. And think that one of the, interesting things that happens also after the acquisition and for sure, even before Indian Copilot was that, you know, managing people that, come from these 2 different boards. So on one hand, you have the, obviously, software engineers, the writing code that was the competence of the team.
But on the other end, you had a lab scientist. So, Omry, yourself, but then other people as well, they have a room in the team from giving requirements, talking with users, marketing, customer support, QA, you know, we we hide a bulge. And I think that mitigating this gap between these two worlds was something, you know, you need to really give education to the 2 worlds of how to speak with each other and how to accommodate the challenges, you know, of each other. Don't worry. You came one day.
I thought it was 2 years before the acquisition. You came back and you say, you know, this is this new thing called CRISPR gonna change humanity. It's a gin genome editing, and it's gonna be a Nobel Prize one day. And nobody knew even how to spell Christopher. It was like, what this, like, weird, you know, kind of working on the trenches of the coding, you know, debugging to the middle of the night, and Beller come this, CEO scientist say, Hey, this crisper, this is gonna change everything.
And, after a few years, it was there, like, it was out there. And I remember that you know, when trying to explain people, so when I became the general manager of Swiss Israel, part of my mission was to also some kind of, give, you know, pictures and talks about the new generation of genetic engineering. We call it genetic engineering 2.0 or synthetic biology. And when explaining that to tech people and that because, you know, migrate on this tech.
So it was easy for me to think as a tech person, you know, biology is really different. Why is it different? It's because that software essentially is made by human, right, and, you know, we created software. So we will we understand it as complex as application can be and as complex as challenging and challenging tasks that you as a computer program will Pete.
Eventually, you know, we understand software, and we build the locations and complex things on top of the and biology or DNA, it's like the code of life and, you know, nobody created it. I mean, god created it of evolution, that is not documentation. And now we're trying to design it. And now I'm explaining Pete, I'm talking to the tech people.
Imagine that you have a softer the Flint software code, which there is no like, usually there is program counter runs from 0, like, down and there is 1, And, in biology, it's not that. You have first, you have multiple program counter, and then they're not starting at Flint 0. They started whatever. I mean, you can think about it as randomly. Not random, but we don't understand. So, you know, it depends on environmental parameters like temperature and stuff like that.
So really, truly understand. And then it doesn't go from 0 to, you know, down, it goes both the election. So 5 to 3, 8, 3 to 5. Right? So, you know, imagine how you can design on top of that. And then, can you hack things like that? So this is crazy. And then come crisper and crisper aims to change code in run time, like, while it's running in the living person. So that's so crazy. It's a real science fiction, and now I'm so happy it's coming to reality. Yeah. It's so funny.
You know, people, you know, I remember talking to my partners about mom with Biosciences before we decided to invest in them, and they told me, like, I don't know many things, but I know that this is going to win the price. And indeed, Jennifer, both of the co founder of Mabu's actually won the Nobel Prize a few years afterwards, but that was the easiest call ever. Yeah. And Balaji is a spaghetti code that, Pete no documentation. We didn't invent it.
It's the most complicated, most advanced technology on earth. That's biology. But the impact so humongous. Like, the ability to feed people to kill people to provide for humanity and the environment is just amazing using this technology. So so you've been entwised at its peak more than $10,000,000,000 company, and then you join Monday and help them IPO and become a really big company. And now you decide, you know, forget that.
I want to go back to biology, and you start a company called MannaBio that, I'm very grateful to be able to invest, close the loop, and be in the ball great. Now it's your time to suffer as a CEO. That's great. Hopefully, the next $10,000,000,000 plus company. So can you tell us what made you go back to biology? And then if you can explain what mana is doing? Yeah. Of course. After this journey, you know, I talked one day with, Roy Nevo, my long time business partner, which, you know, very well.
And we said, you know, it all was, by the way, it was also at Mandel's combat time, and and we said, you know, forget that we have to start a new company. We have 2 requirements. 1, it has to be something impactful and preferably in the life science business. And the other one is it has to be something with software because we have the same software.
And so we tasked ourselves with finding this next challenge, and it was obvious that we'll gonna need, another co founder, another scientific co founder, because we need someone from the science background. And so we went on for a few months of ideation talking to Pete. Right? We we didn't think we're gonna bring the next idea So we talked with many people, PhD professors, and these people in the academia investors and entrepreneurs.
And eventually after a few months, think you actually introduced us to 2 professors from the Technion, which is the kind of the MIT of Israel. And one of them, Avish Schroeder is a chemical engineer and expert in drug delivery in all technology. And the other one is Kara Binsky. She's a machine learning and AI Pete.
And both of them worked at that time at part of the academia on the idea of leveraging learning and AI in order to predict lipids and lipid nanoparticle formulations for drug delivery of, gene therapy of nucleic acid based therapeutics. And we met together, and the first we fell in love with the Pete, so Adi and Kira. And then we also fell in love with the idea and understood this this.
For me, it's very exciting because the opportunity that we have here is that, you know, for the past decade, I mean, people working on this crystal and Beller biology, and it's clear now. Well, I I said before that people didn't know how to spell crystal. Now it's almost a household name, CRISPRNA, Morgan with the COVID vaccine and everything. So everybody knows that the next modality of therapeutic and vaccine is going to be based on the click, I'll see the therapeutics.
So whether it is crystal RNA, DNA, different types of RNA, right? But then apparently, the button like there is delivered because it used to be the case for other drugs that delivery was kind of not a must or you could use something generic. But now with nucleic acid therapeutics, you have to have something which is tailor, tailored to the payload, tailored to the, target organ that you need to reach So you have to have delivery.
I like to think about it as if you're on an astronaut, want to fix the space station. Let's say the astronaut is like the crisper. So you cannot just walk to the space, you need a space shuttle with oxygen, seed Beller, pass the atmosphere, lens safely, etcetera. So this business of building space shuttles, it really needed on one hand, on the other hand, it's really hard. And when talking with illegally companies, they say, you know, it's really hard. As I said before, biology is not known.
The law the underlying logic is not really known, not understood well enough. So it's really hard to come up with the new designs of new space chat, especially if you want to overcome great challenges. Like targeting different organs in the body are with different types of payload, etcetera.
So the literally companies, which they're all, you know, really smart scientists, super stunt Pete, But they're all doing what they call real science, which is trying to rational these to make it with rational design, which is really hard because we don't know the underlying logic. So what we do and our hypothesis is let's leverage on the other end. We have currently almost on the shelf machine learning, AI, talented people that know how to develop these algorithms. So let's use that.
Apply that on data or relevant data, either generate data take existing data and then come up with a platform to predict new delivery vehicles. So new lipids, lipid nanoparticle formulations, and then we'll be able to actually the liver is nucleic acid based therapeutics to different organs and cell types in the body. So that's the idea. We were really lucky to have you, as part of FX and leading all seed round about a year ago.
And together with Lambdael, which, by the way, Lambert also sits on this intersection of software and life science. So we'll really fortunate to have you guys invested in on Pete round. And today, you know, we're 1 year, like, just celebrated on anniversary. We have many achievements along the way, but I think, you know, this, kind of tech bio spirit is really, really part of the company right now. So just to clarify the delivery problem, right?
You know, when people think about drugs, they think about going to the pharmacy, getting a Pete, topping it in their mouth, some water, and that's it. That's a delivery. Just get into your gut and spread to the to the body and it just works. But then new modalities of drugs like protein antibodies, and you cannot eat them because they get degraded in your stomach. You need to, you know, get them through an IV. And then the new modalities of nucleic acids If you try to eat them, then degrade.
If you try to put them through an IV, the body will react negatively to them because naked DNA and RNA usually means viruses are attacking us, you know, you don't just have, like, random DNA and Alan in in our bloodstream. So you have to cover them with something. You have to create a shuttle that will direct them to the right cell to affect that cell type.
And that's the huge problem of delivery that you are trying to solve with a combination with a real tech bio platform company that has a combination of AI and machine learning, but also actually physically chemically as exercise for smaller cues and testing them on living things to see if it works. And then closing the loop and learning from that and, you know, creating new delivery options for patients.
Yeah. Exactly. And I think the point you hit on this sectional integration between these, 2 type of expertise, I think that's the opportunity that we have here because if you look around most the companies, at least in the delivery space, as I said, they focus on real science, and it's really hard. And that's why they they told me, you know, we don't understand the logic. So it's, like, based on gut feeling or intuition. You know, that's the way people, do drugs. I mean, it's not scalable.
So they tell me, this is why it takes so much time and so much money to do it. And so how hypothesis is to really shrink the time it takes to find the, let's say, clinical candidate in, like, weeks instead of years. So that's our vision. And in order to do that, that's the only way I believe today to do that is the integration between these two worlds of real scientists.
We still need, you know, wet lab and everything, but on the other hand, Pete with tech mindset with tech skills that, by the way, ask naive questions. They they're not by us by whatever they lean on. They don't need to be unleavened of some biases on their, you know, history. And so it's really funny to see that you know, sometimes it's really simple to make huge steps.
You know, sometimes if you just make a simple script of generating, numerous candidates to test and then solve them in some way. We'll save few days of work for, So we see these on a daily basis where the software engineers come and sit actually in the lab. This is very important to, you know, integrate the people. So the software engineers, they come and in the lab, they see the mundane work.
And, you know, the number one thing that mostly puddles us, like tech people or software people is that if when you say, you know, manual work happens more than 1. Even one is bad, but if something mundane happens more than 1, it's like it hurts. You know, we cannot tolerate it. So immediately think about automation. You know, it's a human nature to be lazy. So tech people, they take laziness to the next level, which is Hey, we have to make automation.
And when I say automation, it's really simple. It's software automation. No robotics, you don't have to have it, always. So in software, it's really simple. So you automate things, you make scripts, and you make life much more simpler. So the scientists, they have now time, and they have their minds free to think about these problems and challenges. So when we combine these 2 worlds, we get, really, like, 1+1 equals, you know, 4. And plus.
So the main reason I want to talk to you today is because we go to academia and we see amazing IP. We see just its most incredible science that can really change the world and make huge impact in people's life. But the kind of culture we have in biology is not very important in the world, and Pete are missing the founder, the entrepreneur that can take it out of the lab and run with it.
And we see a lot of people that got trained in entrepreneurship in technology and they would like to do something with impact. And they would like to have the impact of bio, but, not sure that it can do it. So somebody who's doing it, you don't have biological background. You have software background, and it's now your 2nd tech bio company. Like, what translates well? What works? And where do you need help? Like, how can we make more people intake come and start companies in bio?
Yeah. So that's a very good point. So first, the gap between the two worlds is real. I mean, the risk gap I think that a result of, what we described before that, you know, software Pete, since the underlying technology is known and computer React really fast. So everything is really rapidly. I mean, you get feedback on the spot. So you can improve your software. You can get results. And once you change a bit in the software, you can own the same day. You can see results from the it's amazing.
I mean, think about if you could develop a drug and see the reaction of the market after like, it's my Flint, right? And in bio, it's not the case, obviously. Even leave it regulation aside. It's not the case because it's really Beller science. It's really health. But I think that in tech, what was developed in the past, you know, the the many years that the tech exists is this culture of first, you know, everything is possible.
And then a result from that is that many cultures evolved on the basis of not on, like, doing curiosity driven science, but on doing, like, R and D, which is just how you make things most efficient, the best user experience, the best value for money, you know, R and D etcetera. So you have a lot of good concepts which results in impactful work and prioritized work and focusable.
And I think when you take this into the scientific world, I mean, you cannot make a scientist you know, just give you and walk estimate. Like, it will be 2 days, and it will be 2 days because it doesn't power because everything is curiosity, but you can still push the Currier and you can ask questions, which will lead to better answers in terms of the management, the self management of the person, like how you manage yourself, how you wanna measure yourself, how you wanna spend resources.
So if we talk about tech, you know, Since everything is so rapid and fast, there is a huge competition, but you have great three worlds and you have many people working on that, and there is a lot of capital. So in many cultures, you know, the culture is kind of, spend money and don't waste time. Just let's save time and spend more money and get results faster. I feel sometimes in science, in bio, people are working from the, opposite way of let's save money and on the expense of time.
And so even though it is still like real science or not. You know why? The main reason is, you know, you do most of the science in academia. And academia, you don't have money and the workforce and PhDs are for free So they don't care. Yeah. And I think, correct me if I'm wrong, but I think that then in the bio, the culture evolves much because of the epidemic. I mean, many people that work in biocompanies, they grew up in the academia. It doesn't happen Flint tech.
In fact, you finish your degree after the war, like, 3 years. Most people don't really do Pete or even masters. You don't really need that, you know, to be super effective and you know, get well compensated in the tech companies. So after 3 years in Akadin, which is totally just undergrad, right, You are out for industry, and you make all your career in industry. So you learn at the big companies, small companies start at but it's all business oriented.
And in science, you spend few good years in academia on research even before you work in a company. So this is kind of you know, so it makes your culture, the the DNA and the culture as in academia. So things like, you know, yeah, we know it takes time. You know, it's really hard even to evaluate people's performance because, you know, you're making experiment, and then you get the results after 6 months. In tech, after 6 months, you already filed him 6 times.
Like, it's a the Ohio, you know, great people in 6 months. So the turnaround time from idea to results is something which is meaningful. Anyway, it makes tech people to be thinking in in a process oriented, which is like structured, very process oriented, like, very structured, and they all also invented all these mechanisms because the problem with tech is not like the problem inside. Right? The problem in tech is how to do it most efficiently.
It's not like, as I said, not like whether it is possible. So we invented and tech Pete. They invented mechanisms of how to make sure that we work in a focused, most impactful way. So, you know, tools like everyone knows, right, agile development, you know, the sprints and daily stand ups and all of those tools that, make sure that the team works most efficiently, and the results come in the best way, etcetera. So when we at Mana, for example, apply that, you know, it's funny.
The beginning, it was funny. Like, the scientists, they didn't even understand it. Why do we need daily stent up? I mean, every day, it's James update. Right? We're still working on it. He doesn't talk. He doesn't talk. We're still working on it. But then, Roy, which, you know, is an amazing person.
Amazingly, they're amazing and he said, no. I mean, guys, you need to audit what's your plan for today, even though, and it is okay, you know, not to reach, I mean, yeah, you defined the goal and you didn't reach it because 1, 2, 3, still, you have to report it out. You have to say, what are you going to achieve today? Even though this task. I don't synthesize this molecule, whatever. Yeah. It's a 3 days walk, but breaking down in 2 days and define what you need to do today.
So task breakdown, Beller planning, you know, better focus. These are all concepts which, they were evolved and got matured in the tech, but they certainly have place in the bio in the scientific world as well. I mean, we see it every day. This is so important to what you're saying here because I think, again, we're trying to get more tech founders to come to bio and, you know, their reactions what do we know about bio?
And then my answer usually to them and to my partners when they want to evaluate the bio companies, 80% of the company is the same no matter what the company is doing. 8 James and marketing and management and support and all of that. And then if you're in a tech bio company and you understand the tech side, you know the tech side. You know the 10% of the tech side. And then you just need a very strong bio partner to compliment you, and you can be a CEO.
You can be a COO, you can be CTO of, of a tech bio company, even if you don't have a background in bio at least that's my experience. Does that fit well with your experience? Yeah. It's a good point. You know, it's kind of, you're hesitated in the beginning because you you're not, like, I feel that I will not be the one that comes with the scientific innovation, right? It will not come from it. This will come from the science, it's from scientists, and there is a gap.
I mean, obviously, you don't understand the material. Right? The way I think about it and and to mitigate it is first, you know, ask questions. Be humble. You know, don't assume that you know things. And I think in the beginning, you know, in the tech days, back in the days, it was like the senior people were kind of, they thought they were the smartest. It's not like that anymore. So for a long time already in, even in the tech, people are humbled.
They're not, like, the smartest people in the room. So I think that we'll use to not be the smartest people in the room. So you need the humbleness of, you know, even, like, sometimes it's even hard. So think about code review, okay, in the tech, like, when you develop software, but it's always the manager is doing code we understand, etcetera, and him, we cannot really encourage you for some difficult use for the scientists.
We can still ask questions and learn every day I think, you know, this is the most important thing is to get the right resources to learn. Now I don't mean learn them because you need to replace the scientists and these scientists yourself, but learn in order to understand the language so you can understand better when they describe you a problem or whatnot, how you can Beller help. And I think you're absolutely right on the getting the right partner, which has the scientific, you know, skill.
It could be a partner. It could be just know, Pete in the team that each one is an expert in his field. So what you really need to do is to find the people that can help you vet and screen the right people for the company because I could not hire, I mean, the lead chemist in our team. What do I understand with chemistry? You know, So we need to have the scientific cofounder for that to Pete and say, you know, this is the number one, person in Israel. So, okay. So, you know, no brainer.
Like, I just need to do some kind of an HR interview for him. That's it. Right? So I think that's a huge Beller. And it helps in the that world, you know, the the network is important. So Pete, it's important even more because the network will really help you bridging this gap of the actual knowledge And I also agree that, most companies all similar in the same of, you know, the the fact that I know to Morgan, talk with investors, Morgan tell, you know, the stories and stuff.
I mean, yeah, I had a huge ramp up to do in the scientific world. And, you know, I think that in some point, by the way, sometimes I feel in discussions that it comes to my favor. The fact that I'm not a scientist, because it's like, okay, you know, I'm not a scientist, but they appreciate the fact that I know enough to handle the conversation. So run, I don't get too hard questions from, you know, be a potential media, opportunities and stuff.
And second, the conversation is different because that was shit you know, my position on different, base of, skills and, you know, an achievement. So I think there is even an advantage being a tech, co founder or tech CEO working on by a company. It's a lot of the audience of the end effects podcast are tech and entrepreneurs or just general tech Pete. Your experience, what do they need to learn to become a tech biophounders?
So number 1 is a hunger to learn, like, Beller day use every opportunity, whether it is the online courses or the mentors or just, people from the team. I love learning from people from, in the team. Because for me, it feels that, I learn from the best resources because they'll be best. And, also, it's kind of part of the culture of the company. You know, it's like I don't know something. I ask. So it's role modeling for them is that it's okay to ask, and there are no stupid questions.
So ask the people, leverage them, And then I think specifically between tech and bio is that we need to appreciate that, you know, the fundamental thing is so different. I mean, things in biology, it's not deterministic the way we are used to. So this is why everything, collapsed from there. You know, the it's not known, experiments take forever, It's not because the people are slow. All lazy. It's because sometimes it is the nature.
So we need to develop the patient for that and also to be mindful of this situation. So learn from other people. Is it okay or not? Cause if I would run into a company, then I can assess our performance, right? Because I know if something should take that amount of time or not, I know with with all the people who are good or not in bio, I don't have this. So I need to trust some network. I need to trust my little people, etcetera. So it's a different paradigm. That's what I like to say.
It's not only a different set of programming language or a different operating system. It's a totally different world that we're Flint to it. And one of the things that I'll say 2 more things. 1, for tech people, especially I would say for CTOs or the or CEOs, which are more, kind of, technical. We love the mind challenge We love challenges, right, and we look for engineering problems. And we want to solve them with most advanced and sometimes, it results in complicated solutions.
In biology and biocompanies, I think sometimes bear in mind that sometimes simple is enough. Sometimes when you produce a simple solution in the software mindset, it will be a jump for the bio aspect in terms of, solution. Because sometimes a simple script or simple, spreadsheet generation or something like that will solve days or weeks of folks. So don't jump into the 2 complicated solutions because everything else is complicated enough.
I mean, now we have a problem in the lab that something is not Morgan. It's voodoo. In software, we say voodoo. Well, the I don't know real voodoo, but we some when we learn the sun, we say, there is a voodoo in biology, there are a lot of voodoo or every day, but I mean, you order the chemical from a different window. You expect it to be the James. Suddenly, it's not the same, right? I mean, we know it. You put it next to the window. There is simply with the sun.
So it's not deterministic, and we need to make sure things are as simple as possible. Well, I think it is the turbanization. Very complicated and and dimensional. Okay. Yeah. It is determination. So you talked a lot about a lot of learning, but what would you say would be the one advice you give somebody from a tech background who is interested in tech bio. So I would say 2 things.
1, you're fortunate to find a way to really, you know, use your skills, background, experience, etcetera, on something which is so purpose. So, you know, keep that in mind. Be proud of what you do. And this is this is amazing. Like me, I I said, I I'm not smart enough to be a scientist in PhD, so I'm really grateful that they can contribute my skills to do this, bump in the wall. This is great.
I think that the number 2, I will aim the, the CEO or the leaders that are going to, to start the company or to lead the company, which is from these two worlds is it's essential and important for actively working on bridging the gap between the two types of people in if you have a tech by your team, it means financial that you have people which are on 1 end software engineers or coming from the tech background.
On the other hand, you have people right from, from the lab or scientists, ancient scientists, etcetera, these 2 groups of people, they are so different. I mean, so my advice is Pete, proactive effort on bridging the gap by educating, by bringing people sit in the lab, taking lab people, putting them in the office, you know, with the Pete and everything. Because these two groups, they have to speak in the same language. And I think the main gap the the basic gap is language.
And people need to understand themselves. People need to understand each other. They need to understand the challenges and the perspective and the different backgrounds from each other. And when doing that, you're not only, you know, smoothing the environment in the office and make a better teamwork and, like, make it easy. This is your opportunity to really make the teams suddenly create real new innovations because that's the real diversity that you have.
I mean, think about it's not a disadvantage. It's an advantage. To have this kind of, multidisciplinary team. So take the advantage, educate the team, make sure that people start, I mean, you you cannot take, chemical engineer and making a data scientist and vice versa. But if they understand each other and they understand the context, and they understand the challenges, you will be amazed of the innovation that they bring then to the table. It's amazing. I love to see it every day.
I see it and also started talking with chemistry, you know, when we used to laugh at the genome compiler, some words that you brought up, and we didn't standard awards and we laughed about them. But, you know, eventually, you see this collaboration between the team Beller. This is amazing. That, like, that would be my number one advice. Is to take it all the way. Don't try to separate. Many people try to separate the groups. Don't do it.
It's a great advice how to bridge the gap because, again, the gap exists, but bridging it actually can create a lot of synergies and new innovations. So one thing that I really admire about Mana that came from your background in tech is how fast you move. You move really fast. And people are amazed at how fast you got to resolve and how fast you're actually improving your results. So what other mindsets and skills can people bring from tech, to tech bio companies?
Yeah. When I think about it, and, you know, it's it's a good point that, we are moving fast And I think it's also a combination coming from the tech industry, which is mostly like industry focused and business driven and need to get results fast, etcetera, and competitive environment, and also, you know, being experienced, let's not forget that.
I mean, it's not the first time So when Roy and I were in this, ideation phase looking for the next challenge and before we started Mana, we actually did the nice exercise. We said, you know what, We already know from our tech experience and experience in entrepreneurship. We know how the company should behave in terms of culture. We don't know what we're going to work on.
We don't know what the purpose is, but other than, you know, we know that we want to work on life science and so well, we know how the company works in terms of values. And we sat down and actually written the values for the company, which were, impact ownership, quality and teamwork. So impact is like, you know, make sure that you have an impact to everything that you do to be impacts of the company towards the the goal. Etcetera, and ownership also.
It's like something which is, hey, you know, this is the way for us to move fast because it's not, that me, like myself or Roy, we need to make every decision in the company. I think that this is very important because we knew we are going to enter into something that we don't know enough And then we have to have people that have this kind of sense of ownership. Like, they know. I'll like, the chemists, the chemical engineers in the company, they know that they have to make decisions every day.
And they have to make these decisions in light of the goal, in light of the purpose of what we wanna achieve, but they have to own their issues And obviously, you know, it's under the context that we give them on, you know, budget. They know, like, the the limits, etcetera, but it's very Morgan. And, same for, quality and trust, you know, like, people have to work, in high performance, etcetera, and Tmall, which is obvious.
So for us, you know, I think that being so much, tie in the industry, you know, amazing companies, intelligent competitor, Twists, monday.com. I'm in great companies, and we learned a lot. And in the tech industry, again, since it's so competitive and so fast, I think, you know, in the tech, the, as a result of the fundamental of how it works, it became a competitive. I mean, you develop software so fast, and you get feedback so fast. That it's in your nature. So we get sick when things go slow.
And by slow, I don't mean like, okay, sometimes things take time. You know, it takes time to calibrate a new robot that just arrived in the lab. You know, it takes time. People need to come. You know, it's okay. But what makes us sick is when people are not focused. And this is for us, like, it gives me, like, it's it's itchy. It's like, oh, no. You're walking with the wrong thing. Oh my god. So we train people. We don't whip them. Like, this is what you should do on the contrary.
We train people to test themselves whether Beller, focus. So whenever somebody is not focused, I start with myself, and it's my problem because I didn't communicate the focus well enough. So this is the first step to make sure the focus is communicated. The goal is communicated. Everybody in the company, by the way, they know almost everything.
Like, everything is concerned a side of, you know, salaries and cap Beller, but people know where we stand in terms of business development, in terms of the, the plan, in terms of even in fundraising. I mean, they know you know, not all the bits and bytes because just a lot of data, but they know where we are. They know where we're raising money, etcetera. So people are kind of out of the headache the the leadership head, right? So they're part of that.
It gives them motivation, and it also also, makes sure that they'll focus and they know. And by the way, they also come with great ideas. And sometimes, you know, they bring ideas, which, you know, are great and so sure better than my ideas. And I love it. I just love it when people come with new idea based on the context of the company based on the goal that I defined, and they come with something which I didn't think of. Wow. It makes my day.
It makes me there because that's scalability, that scalability. That's great. We have this culture of, transparency. Yeah. So unspancy really makes the team again, they're motivated, and they know what the problem is. So it used to be the case what was expected from people to bring solutions. Right? Like, it used to be in in the early, early days. Like, the manager was saying, you know, this department is the solution. Go in next Right?
And then there was an evolution and people say, like, manager saying, this is the problem. Find solution. Right? But I'm saying, you know, this is the goal. Go find the problems. Like, go find what would not work. And that's a real, I believe, you know, in Roy and I believe Flint the in in Navient, like, this is the real scalability, and this is the real leverage that we have from the Pete, because everybody in the team especially in this early stage, but even later stage.
And by the way, it doesn't matter in this case. It doesn't matter whether it is, scientist, or social engineers, biotech, is this sense of, hey. You know what? This is the goal. The problem is, like, go find me the problems. And you're the chemist. So you know what the challenges are of synthesizing these molecules. You're the formulation guy. You know what the problem is. You know what equipment to order. So I should trust your judgment. Right?
So I think that, transparency is something that, we learned in the industry. It's now becoming more and more wide in the tech industry transparent, impact all of those. I think that these values should be applied in the culture of the company. I have to say that you know, the bio people in the team, they are sometimes are shocked. I mean, they're they're not used to this kind of sculpture. In the beginning, they were not used to it. Like, it was a shock for them.
And we train them, and they saw all model, and they saw that we are good with getting feedback from them. And now it's working, right, and I think this is something which every tech bioethanol should implement. Great. So hopefully, we already persuaded the tech founders in the audience that, they can become a tech biopharma themselves. But then the question I'm sure they're asking themselves is, you know, how do we start? How do we find the right sign?
How do we even know the science is interesting or really breaks? Right? You know, how can we evaluate the business? It's a new business for us. So as a tech person starting in bio, yeah, I can do it. But how do I know that this is the right approach and this is the right breakthrough technology? Yeah. It's, tricky, of course. So what we did, for example, we talked with of professors we talked with, CTOs, and it was hard to evaluate. I mean, we couldn't evaluate ourselves. So, sure.
At some point, you have to have the network to kind of screen it And I think that what worked really well for us was that, you know, with you guys and the other potential investors and just throw on them, the ideas. And so the So in some way, we leveraged the combined knowledge and combined experience of people that see these kind of crazy ideas every day which is the bio investor, the biotech investor. So we'll detect bio investors even better.
And then you guys already did the marketplace search, right, use so many companies in the space, and you can give some intuition whether at least the market is there. So, obviously, the team is on us, and then there is the technology part and then the market part. Right? So team technology and market. Market, you can do market research, but we use the smarter people, or more experienced people to tell us Pete the market is huge.
And then technology, that was the, the important part to kind and also whether it is going to work or not. So that's the the the deal that we did together with our co founders, and that's what the people should really do is I would recommend, you know, talk with people. Talk with the people that offer this idea. Talk with potential, invest. So if you're already experienced a technical panel getting into bio, it means that you have some network.
Most of your network are probably tech related, but hopefully, some people that have some bio skills. And if not, Omri is here, you should talk with Omry and other investors. And so I think that this is the technology that you should do.
And then on the team, you need to trust your So I would say that one important aspect for that is whenever you hit an idea, which is driven by, some, let's say, PhD or postdoc or Fresco and, could be, what's not, make sure, like, what's the availability of this person? Is he going to join you as a scientific cofounder, is he not going to join you at all and he just want to out license you the IP? I think that's the, very important part of the puzzle.
I wouldn't start Mana on my own like miss Roy alone. We had to have, most Avian Kira involved there. It's still in fault very much. They're not full time in the company. Not on the payroll, but, we made sure that they're involved, and they care about this. And so, you know, that's the ramp up that that you have to do. Great. So you heard it first, stakeholders, You know, you made your, big fortune in tech. You wanna make your small fortune in bio.
And, more importantly, you want to have real impact in hearing, feeding, providing for humanity, just using the most advanced technology on earth, which is bio, to solve some big problems. You can do it. You know, your Gabe did it. And he's doing it right now with Mana. And you could do it, too, and I encourage you to start.
And don't hesitate to contact us if you have this crazy idea and you want us to vet it or other take by investors, but definitely you can do it, and we encourage you to do it. We see too many bright minds going to optimize ads. There are huge issues that can be solved with biology. You can really help feed people, kill horrible diseases, and we encourage you to do it. You can do it. So thank you so much, you give, for, you know, showing people that it it can be done.
And being my partner for so Morgan, and especially in this new company that I'm sure would be amazing. And, hopefully, this discussion will help encourage more tech founders to come to take a bottle and help change the world. Thank you very much.