January 5, 2023 • 44 mins
There’s huge value in integrating tech and bio. But many tech entrepreneurs don’t realize what they can bring to the field. Tech entrepreneurs: you can come to bio, if you learn to speak the language. Today, head of NFX Bio Omri Amirav-Drory sits down with his former co-founder at Genome Compiler, and Founder of Mana.bio Yogev Debbi. Yogev has bridged the gap between tech and bio several times in his career. Here’s how to build a culture of trust, leverage your fresh perspective, and build impactful companies at the intersection of tech and bio.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:08):
You cannot take, chemical engineer and making adata scientist and vice versa.
But if they understand each other and theyunderstand the context and they understand the
challenges, you will be amazed of theinnovation that they bring then to the table.
Hello.
My name is Omri.
(00:28):
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 showthem that they can start a tech biocompany and
change the world.
So with me will be Yogeb Debbie, founder andCEO of Manabio, He was my co founder, a Gillum
Copilot, the company we read together, a techguy starting in Intel, now doing his second
(00:53):
tech bio company, and he can explain all aboutthe 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 otherfor many years now.
You've been my cofounder, the chief operatingofficer.
So being together in the trenches, more thanfive and a half years that we got it done.
And what people don't know about you and, youknow, I'd be happy if you start with your
(01:15):
background is that you started in tech.
You didn't know anything about bio, and youmade the jump.
And now we see a lot of people, a lot of techPete.
They made their fortune in tech They want tohave the impact of bio coming back to bio.
The kind of joke is how do you make a smallfortune in bio?
It starts with a big tech Morgan.
So maybe we'll start with that.
Like, can you tell us more about yourbackground?
(01:36):
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, aperiod of science, as I said, and I actually
got jetting a water Intel corporate So Istarted as a software engineer, then became
team manager, program manager, really workingon real tech, wireless devices, you know, And
after, about almost 7 years at Intel, we Pete.
(02:00):
And you told us about this crazy idea of, youknow, DNA, like synthetic biology and synthetic
DNA.
And everybody is going to synthesize DNA andedit 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 wasdiscovered nobody knew what it was.
(02:24):
So I remember coming to your lab at Stanfordwhen you did your postdoc.
And we saw that, you know, the in luxurious labat 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 thishuge world of biology and starting to
(02:46):
understand the differences.
Yeah.
So you join me in this crazy journey and thepipetting 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 managerin detail to being a chief operating officer in
a software company for biology.
So how was that transition?
(03:07):
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'screate you know, dot Pete for DNA.
So that was the idea.
And I remember a few occasions where startingwith this episode that, Stanford when we saw
that, you may walk with Pete and paper, thenwhen we started creating the actual software
general compiler, and we showed it to users,and we were in this mind oh, everybody's gonna
(03:32):
use it for sure.
And then we presented it to lab scientists onthe 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 onthe 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 actualbooklet, physical booklets with tables and
(03:55):
charts and backgrounds, which they used to useon daily basis.
And when we show them, like, interactiveapplication 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 eventhough, you know, I didn't have any scientific
background, I honestly think I'm not smartenough to be a scientist at PhD.
(04:16):
It was great to know that, using engineeringmindset and software skills, you can actually
make an impact, you know, on these people andthen 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 ofthe 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
(04:40):
kind of product requirements, right, from theproduct Pete.
And they say, you know, this is how it shouldlook 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 canbe 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 arethe priorities.
(05:02):
In biology, there is the initial way.
Can it be done?
We didn't ask ourselves this when we came toOmri and we asked him, you know, should the
software behave like this or like that?
I mean, what's the what really the productrequirements?
What should the flow be?
And always like, well, in biology, sometimes itworks like that.
Sometimes it works like that.
I don't really know.
(05:22):
Nobody knows.
So it was like, okay.
How can we, you know, implement and develop anysoftware 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, anda learning experience, right, you know, five
and a half years in the trenches buildingsoftware for bioengineals seeing the price of a
synthesizing DNA going down along the way,being in all the scene by a Beller conferences.
(05:46):
It's been quite a ride, and then we were luckyenough to get acquired by twist bar sciences a
company making DNA where I became the head ofCOVID 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, youknow, you know, and we we talked about it a
(06:06):
lot.
We felt that we're, I joining this hugerevolution and finally when we joined forces
with, with another company that actuallycomplements us.
So that was great.
And think that one of the, interesting thingsthat happens also after the acquisition and for
sure, even before Indian Copilot was that, youknow, managing people that, come from these 2
different boards.
So on one hand, you have the, obviously,software engineers, the writing code that was
(06:29):
the competence of the team.
But on the other end, you had a lab scientist.
So, Omry, yourself, but then other people aswell, 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 betweenthese two worlds was something, you know, you
need to really give education to the 2 worldsof how to speak with each other and how to
(06:52):
accommodate the challenges, you know, of eachother.
Don't worry.
You came one day.
I thought it was 2 years before theacquisition.
You came back and you say, you know, this isthis new thing called CRISPR gonna change
humanity.
It's a gin genome editing, and it's gonna be aNobel 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,
(07:14):
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, itwas out there.
And I remember that you know, when trying toexplain people, so when I became the general
manager of Swiss Israel, part of my mission wasto also some kind of, give, you know, pictures
(07:35):
and talks about the new generation of geneticengineering.
We call it genetic engineering 2.0 or syntheticbiology.
And when explaining that to tech people andthat because, you know, migrate on this tech.
So it was easy for me to think as a techperson, you know, biology is really different.
Why is it different?
It's because that software essentially is madeby human, right, and, you know, we created
(07:57):
software.
So we will we understand it as complex asapplication can be and as complex as
challenging and challenging tasks that you as acomputer 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 thecode of life and, you know, nobody created it.
(08:18):
I mean, god created it of evolution, that isnot documentation.
And now we're trying to design it.
And now I'm explaining Pete, I'm talking to thetech people.
Imagine that you have a softer the Flintsoftware 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
(08:38):
that.
You have first, you have multiple programcounter, 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 environmentalparameters 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.
(08:59):
So 5 to 3, 8, 3 to 5.
Right?
So, you know, imagine how you can design on topof that.
And then, can you hack things like that?
So this is crazy.
And then come crisper and crisper aims tochange 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 sohappy it's coming to reality.
(09:20):
Yeah.
It's so funny.
You know, people, you know, I remember talkingto my partners about mom with Biosciences
before we decided to invest in them, and theytold 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 ofMabu'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 nodocumentation.
(09:40):
We didn't invent it.
It's the most complicated, most advancedtechnology on earth.
That's biology.
But the impact so humongous.
Like, the ability to feed people to kill peopleto provide for humanity and the environment is
just amazing using this technology.
So so you've been entwised at its peak morethan $10,000,000,000 company, and then you join
Monday and help them IPO and become a reallybig company.
(10:03):
And now you decide, you know, forget that.
I want to go back to biology, and you start acompany called MannaBio that, I'm very grateful
to be able to invest, close the loop, and be inthe ball great.
Now it's your time to suffer as a CEO.
That's great.
Hopefully, the next $10,000,000,000 pluscompany.
So can you tell us what made you go back tobiology?
And then if you can explain what mana is doing?
(10:23):
Yeah.
Of course.
After this journey, you know, I talked one daywith, 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 anew company.
We have 2 requirements.
1, it has to be something impactful andpreferably in the life science business.
(10:48):
And the other one is it has to be somethingwith software because we have the same
software.
And so we tasked ourselves with finding thisnext challenge, and it was obvious that we'll
gonna need, another co founder, anotherscientific co founder, because we need someone
from the science background.
And so we went on for a few months of ideationtalking to Pete.
Right?
We we didn't think we're gonna bring the nextidea So we talked with many people, PhD
(11:13):
professors, and these people in the academiainvestors and entrepreneurs.
And eventually after a few months, think youactually introduced us to 2 professors from the
Technion, which is the kind of the MIT ofIsrael.
And one of them, Avish Schroeder is a chemicalengineer 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 ofthe academia on the idea of leveraging learning
(11:38):
and AI in order to predict lipids and lipidnanoparticle formulations for drug delivery of,
gene therapy of nucleic acid basedtherapeutics.
And we met together, and the first we fell inlove with the Pete, so Adi and Kira.
And then we also fell in love with the idea andunderstood this this.
For me, it's very exciting because theopportunity that we have here is that, you
(11:59):
know, for the past decade, I mean, peopleworking on this crystal and Beller biology, and
it's clear now.
Well, I I said before that people didn't knowhow 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 oftherapeutic and vaccine is going to be based on
(12:20):
the click, I'll see the therapeutics.
So whether it is crystal RNA, DNA, differenttypes of RNA, right?
But then apparently, the button like there isdelivered because it used to be the case for
other drugs that delivery was kind of not amust or you could use something generic.
But now with nucleic acid therapeutics, youhave to have something which is tailor,
tailored to the payload, tailored to the,target organ that you need to reach So you have
(12:44):
to have delivery.
I like to think about it as if you're on anastronaut, want to fix the space station.
Let's say the astronaut is like the crisper.
So you cannot just walk to the space, you needa space shuttle with oxygen, seed Beller, pass
the atmosphere, lens safely, etcetera.
So this business of building space shuttles, itreally needed on one hand, on the other hand,
it's really hard.
And when talking with illegally companies, theysay, you know, it's really hard.
(13:07):
As I said before, biology is not known.
The law the underlying logic is not reallyknown, not understood well enough.
So it's really hard to come up with the newdesigns of new space chat, especially if you
want to overcome great challenges.
Like targeting different organs in the body arewith 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 realscience, which is trying to rational these to
(13:31):
make it with rational design, which is reallyhard because we don't know the underlying
logic.
So what we do and our hypothesis is let'sleverage on the other end.
We have currently almost on the shelf machinelearning, AI, talented people that know how to
develop these algorithms.
So let's use that.
Apply that on data or relevant data, eithergenerate data take existing data and then come
(13:54):
up with a platform to predict new deliveryvehicles.
So new lipids, lipid nanoparticle formulations,and then we'll be able to actually the liver is
nucleic acid based therapeutics to differentorgans and cell types in the body.
So that's the idea.
We were really lucky to have you, as part of FXand leading all seed round about a year ago.
And together with Lambdael, which, by the way,Lambert also sits on this intersection of
(14:17):
software and life science.
So we'll really fortunate to have you guysinvested in on Pete round.
And today, you know, we're 1 year, like, justcelebrated on anniversary.
We have many achievements along the way, but Ithink, you know, this, kind of tech bio spirit
is really, really part of the company rightnow.
So just to clarify the delivery problem, right?
(14:40):
You know, when people think about drugs, theythink 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 thebody and it just works.
But then new modalities of drugs like proteinantibodies, and you cannot eat them because
they get degraded in your stomach.
You need to, you know, get them through an IV.
(15:00):
And then the new modalities of nucleic acids Ifyou try to eat them, then degrade.
If you try to put them through an IV, the bodywill 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 directthem to the right cell to affect that cell
(15:23):
type.
And that's the huge problem of delivery thatyou are trying to solve with a combination with
a real tech bio platform company that has acombination of AI and machine learning, but
also actually physically chemically as exercisefor smaller cues and testing them on living
things to see if it works.
And then closing the loop and learning fromthat and, you know, creating new delivery
(15:43):
options for patients.
Yeah.
Exactly.
And I think the point you hit on this sectionalintegration between these, 2 type of expertise,
I think that's the opportunity that we havehere because if you look around most the
companies, at least in the delivery space, as Isaid, they focus on real science, and it's
really hard.
And that's why they they told me, you know, wedon't understand the logic.
So it's, like, based on gut feeling orintuition.
(16:05):
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 muchtime and so much money to do it.
And so how hypothesis is to really shrink thetime 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 Ibelieve today to do that is the integration
(16:29):
between these two worlds of real scientists.
We still need, you know, wet lab andeverything, 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 leanon.
They don't need to be unleavened of some biaseson their, you know, history.
And so it's really funny to see that you know,sometimes it's really simple to make huge
(16:54):
steps.
You know, sometimes if you just make a simplescript of generating, numerous candidates to
test and then solve them in some way.
We'll save few days of work for, So we seethese on a daily basis where the software
engineers come and sit actually in the lab.
This is very important to, you know, integratethe people.
So the software engineers, they come and in thelab, they see the mundane work.
(17:18):
And, you know, the number one thing that mostlypuddles us, like tech people or software people
is that if when you say, you know, manual workhappens more than 1.
Even one is bad, but if something mundanehappens 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.
(17:40):
So tech people, they take laziness to the nextlevel, 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, andyou make life much more simpler.
So the scientists, they have now time, and theyhave their minds free to think about these
(18:04):
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 todayis because we go to academia and we see amazing
IP.
We see just its most incredible science thatcan really change the world and make huge
(18:24):
impact in people's life.
But the kind of culture we have in biology isnot very important in the world, and Pete are
missing the founder, the entrepreneur that cantake it out of the lab and run with it.
And we see a lot of people that got trained inentrepreneurship 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.
(18:45):
So somebody who's doing it, you don't havebiological background.
You have software background, and it's now your2nd tech bio company.
Like, what translates well?
What works?
And where do you need help?
Like, how can we make more people intake comeand start companies in bio?
Yeah.
So that's a very good point.
So first, the gap between the two worlds isreal.
I mean, the risk gap I think that a result of,what we described before that, you know,
(19:08):
software Pete, since the underlying technologyis 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, youcan own the same day.
You can see results from the it's amazing.
I mean, think about if you could develop a drugand see the reaction of the market after like,
(19:30):
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 Bellerscience.
It's really health.
But I think that in tech, what was developed inthe 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 manycultures evolved on the basis of not on, like,
(19:53):
doing curiosity driven science, but on doing,like, R and D, which is just how you make
things most efficient, the best userexperience, the best value for money, you know,
R and D etcetera.
So you have a lot of good concepts whichresults in impactful work and prioritized work
and focusable.
And I think when you take this into thescientific world, I mean, you cannot make a
(20:18):
scientist you know, just give you and walkestimate.
Like, it will be 2 days, and it will be 2 daysbecause it doesn't power because everything is
curiosity, but you can still push the Currierand you can ask questions, which will lead to
better answers in terms of the management, theself management of the person, like how you
manage yourself, how you wanna measureyourself, how you wanna spend resources.
(20:40):
So if we talk about tech, you know, Sinceeverything is so rapid and fast, there is a
huge competition, but you have great threeworlds and you have many people working on
that, and there is a lot of capital.
So in many cultures, you know, the culture iskind of, spend money and don't waste time.
Just let's save time and spend more money andget results faster.
I feel sometimes in science, in bio, people areworking from the, opposite way of let's save
(21:05):
money and on the expense of time.
And so even though it is still like realscience or not.
You know why?
The main reason is, you know, you do most ofthe science in academia.
And academia, you don't have money and theworkforce and PhDs are for free So they don't
care.
Yeah.
And I think, correct me if I'm wrong, but Ithink that then in the bio, the culture evolves
(21:26):
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 evenmasters.
You don't really need that, you know, to besuper effective and you know, get well
compensated in the tech companies.
(21:46):
So after 3 years in Akadin, which is totallyjust undergrad, right, You are out for
industry, and you make all your career inindustry.
So you learn at the big companies, smallcompanies start at but it's all business
oriented.
And in science, you spend few good years inacademia on research even before you work in a
company.
So this is kind of you know, so it makes yourculture, the the DNA and the culture as in
(22:12):
academia.
So things like, you know, yeah, we know ittakes time.
You know, it's really hard even to evaluatepeople's performance because, you know, you're
making experiment, and then you get the resultsafter 6 months.
In tech, after 6 months, you already filed him6 times.
Like, it's a the Ohio, you know, great peoplein 6 months.
(22:33):
So the turnaround time from idea to results issomething which is meaningful.
Anyway, it makes tech people to be thinking inin a process oriented, which is like
structured, very process oriented, like, verystructured, and they all also invented all
these mechanisms because the problem with techis not like the problem inside.
(22:53):
Right?
The problem in tech is how to do it mostefficiently.
It's not like, as I said, not like whether itis possible.
So we invented and tech Pete.
They invented mechanisms of how to make surethat 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,
(23:19):
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 evenunderstand 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 amazingperson.
(23:40):
Amazingly, they're amazing and he said, no.
I mean, guys, you need to audit what's yourplan for today, even though, and it is okay,
you know, not to reach, I mean, yeah, youdefined the goal and you didn't reach it
because 1, 2, 3, still, you have to report itout.
You have to say, what are you going to achievetoday?
Even though this task.
I don't synthesize this molecule, whatever.
(24:02):
Yeah.
It's a 3 days walk, but breaking down in 2 daysand define what you need to do today.
So task breakdown, Beller planning, you know,better focus.
These are all concepts which, they were evolvedand got matured in the tech, but they certainly
have place in the bio in the scientific worldas well.
I mean, we see it every day.
(24:24):
This is so important to what you're saying herebecause I think, again, we're trying to get
more tech founders to come to bio and, youknow, their reactions what do we know about
bio?
And then my answer usually to them and to mypartners when they want to evaluate the bio
companies, 80% of the company is the same nomatter what the company is doing.
8 James and marketing and management andsupport and all of that.
(24:45):
And then if you're in a tech bio company andyou 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 biopartner to compliment you, and you can be a
CEO.
You can be a COO, you can be CTO of, of a techbio company, even if you don't have a
background in bio at least that's myexperience.
Does that fit well with your experience?
(25:06):
Yeah.
It's a good point.
You know, it's kind of, you're hesitated in thebeginning because you you're not, like, I feel
that I will not be the one that comes with thescientific innovation, right?
It will not come from it.
This will come from the science, it's fromscientists, and there is a gap.
I mean, obviously, you don't understand thematerial.
Right?
The way I think about it and and to mitigate itis first, you know, ask questions.
(25:27):
Be humble.
You know, don't assume that you know things.
And I think in the beginning, you know, in thetech days, back in the days, it was like the
senior people were kind of, they thought theywere the smartest.
It's not like that anymore.
So for a long time already in, even in thetech, people are humbled.
They're not, like, the smartest people in theroom.
So I think that we'll use to not be thesmartest people in the room.
(25:49):
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 dayI think, you know, this is the most important
thing is to get the right resources to learn.
(26:11):
Now I don't mean learn them because you need toreplace the scientists and these scientists
yourself, but learn in order to understand thelanguage so you can understand better when they
describe you a problem or whatnot, how you canBeller help.
And I think you're absolutely right on thegetting the right partner, which has the
scientific, you know, skill.
It could be a partner.
(26:31):
It could be just know, Pete in the team thateach one is an expert in his field.
So what you really need to do is to find thepeople that can help you vet and screen the
right people for the company because I couldnot hire, I mean, the lead chemist in our team.
What do I understand with chemistry?
You know, So we need to have the scientificcofounder for that to Pete and say, you know,
(26:53):
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 HRinterview for him.
That's it.
Right?
So I think that's a huge Beller.
And it helps in the that world, you know, thethe network is important.
So Pete, it's important even more because thenetwork 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
(27:17):
know, the the fact that I know to Morgan, talkwith investors, Morgan tell, you know, the
stories and stuff.
I mean, yeah, I had a huge ramp up to do in thescientific world.
And, you know, I think that in some point, bythe way, sometimes I feel in discussions that
it comes to my favor.
The fact that I'm not a scientist, because it'slike, okay, you know, I'm not a scientist, but
(27:40):
they appreciate the fact that I know enough tohandle 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 differentbecause that was shit you know, my position on
different, base of, skills and, you know, anachievement.
So I think there is even an advantage being atech, co founder or tech CEO working on by a
(28:06):
company.
It's a lot of the audience of the end effectspodcast are tech and entrepreneurs or just
general tech Pete.
Your experience, what do they need to learn tobecome a tech biophounders?
So number 1 is a hunger to learn, like, Bellerday use every opportunity, whether it is the
online courses or the mentors or just, peoplefrom the team.
I love learning from people from, in the team.
(28:27):
Because for me, it feels that, I learn from thebest resources because they'll be best.
And, also, it's kind of part of the culture ofthe company.
You know, it's like I don't know something.
I ask.
So it's role modeling for them is that it'sokay to ask, and there are no stupid questions.
So ask the people, leverage them, And then Ithink specifically between tech and bio is that
(28:48):
we need to appreciate that, you know, thefundamental thing is so different.
I mean, things in biology, it's notdeterministic the way we are used to.
So this is why everything, collapsed fromthere.
You know, the it's not known, experiments takeforever, It's not because the people are slow.
All lazy.
It's because sometimes it is the nature.
(29:09):
So we need to develop the patient for that andalso 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 canassess our performance, right?
Because I know if something should take thatamount of time or not, I know with with all the
people who are good or not in bio, I don't havethis.
(29:29):
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 programminglanguage or a different operating system.
It's a totally different world that we're Flintto it.
And one of the things that I'll say 2 morethings.
1, for tech people, especially I would say forCTOs or the or CEOs, which are more, kind of,
(29:51):
technical.
We love the mind challenge We love challenges,right, and we look for engineering problems.
And we want to solve them with most advancedand sometimes, it results in complicated
solutions.
In biology and biocompanies, I think sometimesbear in mind that sometimes simple is enough.
Sometimes when you produce a simple solution inthe software mindset, it will be a jump for the
(30:16):
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 solutionsbecause everything else is complicated enough.
I mean, now we have a problem in the lab thatsomething is not Morgan.
It's voodoo.
In software, we say voodoo.
(30:38):
Well, the I don't know real voodoo, but we somewhen we learn the sun, we say, there is a
voodoo in biology, there are a lot of voodoo orevery 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 makesure things are as simple as possible.
Well, I
(30:58):
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 isinterested 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,
(31:20):
experience, etcetera, on something which is sopurpose.
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 bea scientist in PhD, so I'm really grateful that
they can contribute my skills to do this, bumpin the wall.
This is great.
I think that the number 2, I will aim the, theCEO or the leaders that are going to, to start
(31:42):
the company or to lead the company, which isfrom these two worlds is it's essential and
important for actively working on bridging thegap between the two types of people in if you
have a tech by your team, it means financialthat you have people which are on 1 end
software engineers or coming from the techbackground.
On the other hand, you have people right from,from the lab or scientists, ancient scientists,
(32:06):
etcetera, these 2 groups of people, they are sodifferent.
I mean, so my advice is Pete, proactive efforton 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 inthe same language.
(32:28):
And I think the main gap the the basic gap islanguage.
And people need to understand themselves.
People need to understand each other.
They need to understand the challenges and theperspective 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.
(32:50):
This is your opportunity to really make theteams suddenly create real new innovations
because that's the real diversity that youhave.
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, makesure that people start, I mean, you you cannot
(33:10):
take, chemical engineer and making a datascientist and vice versa.
But if they understand each other and theyunderstand the context, and they understand the
challenges, you will be amazed of theinnovation that they bring then to the table.
It's amazing.
I love to see it every day.
I see it and also started talking withchemistry, you know, when we used to laugh at
the genome compiler, some words that youbrought up, and we didn't standard awards and
(33:33):
we laughed about them.
But, you know, eventually, you see thiscollaboration 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 gapbecause, again, the gap exists, but bridging it
actually can create a lot of synergies and newinnovations.
So one thing that I really admire about Manathat came from your background in tech is how
(33:58):
fast you move.
You move really fast.
And people are amazed at how fast you got toresolve and how fast you're actually improving
your results.
So what other mindsets and skills can peoplebring from tech, to tech bio companies?
Yeah.
When I think about it, and, you know, it's it'sa good point that, we are moving fast And I
think it's also a combination coming from thetech industry, which is mostly like industry
(34:21):
focused and business driven and need to getresults fast, etcetera, and competitive
environment, and also, you know, beingexperienced, let's not forget that.
I mean, it's not the first time So when Roy andI were in this, ideation phase looking for the
next challenge and before we started Mana, weactually did the nice exercise.
We said, you know what, We already know fromour tech experience and experience in
(34:44):
entrepreneurship.
We know how the company should behave in termsof culture.
We don't know what we're going to work on.
We don't know what the purpose is, but otherthan, you know, we know that we want to work on
life science and so well, we know how thecompany works in terms of values.
And we sat down and actually written the valuesfor the company, which were, impact ownership,
(35:05):
quality and teamwork.
So impact is like, you know, make sure that youhave 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 needto make every decision in the company.
(35:25):
I think that this is very important because weknew we are going to enter into something that
we don't know enough And then we have to havepeople that have this kind of sense of
ownership.
Like, they know.
I'll like, the chemists, the chemical engineersin the company, they know that they have to
make decisions every day.
And they have to make these decisions in lightof the goal, in light of the purpose of what we
wanna achieve, but they have to own theirissues And obviously, you know, it's under the
(35:49):
context that we give them on, you know, budget.
They know, like, the the limits, etcetera, butit'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 somuch, tie in the industry, you know, amazing
companies, intelligent competitor, Twists,monday.com.
(36:11):
I'm in great companies, and we learned a lot.
And in the tech industry, again, since it's socompetitive and so fast, I think, you know, in
the tech, the, as a result of the fundamentalof how it works, it became a competitive.
I mean, you develop software so fast, and youget feedback so fast.
That it's in your nature.
So we get sick when things go slow.
(36:31):
And by slow, I don't mean like, okay, sometimesthings take time.
You know, it takes time to calibrate a newrobot 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 notfocused.
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.
(36:52):
Oh my god.
So we train people.
We don't whip them.
Like, this is what you should do on thecontrary.
We train people to test themselves whetherBeller, focus.
So whenever somebody is not focused, I startwith myself, and it's my problem because I
didn't communicate the focus well enough.
So this is the first step to make sure thefocus is communicated.
(37:13):
The goal is communicated.
Everybody in the company, by the way, they knowalmost everything.
Like, everything is concerned a side of, youknow, salaries and cap Beller, but people know
where we stand in terms of businessdevelopment, in terms of the, the plan, in
terms of even in fundraising.
I mean, they know you know, not all the bitsand bytes because just a lot of data, but they
know where we are.
They know where we're raising money, etcetera.
(37:34):
So people are kind of out of the headache thethe 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 greatideas.
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 ideabased on the context of the company based on
(37:58):
the goal that I defined, and they come withsomething 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 expectedfrom people to bring solutions.
(38:18):
Right?
Like, it used to be in in the early, earlydays.
Like, the manager was saying, you know, thisdepartment 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 Royand I believe Flint the in in Navient, like,
(38:42):
this is the real scalability, and this is thereal leverage that we have from the Pete,
because everybody in the team especially inthis 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, orsocial engineers, biotech, is this sense of,
hey.
(39:02):
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 ofsynthesizing 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 somethingthat, we learned in the industry.
(39:24):
It's now becoming more and more wide in thetech industry transparent, impact all of those.
I think that these values should be applied inthe culture of the company.
I have to say that you know, the bio people inthe team, they are sometimes are shocked.
I mean, they're they're not used to this kindof sculpture.
In the beginning, they were not used to it.
(39:44):
Like, it was a shock for them.
And we train them, and they saw all model, andthey saw that we are good with getting feedback
from them.
And now it's working, right, and I think thisis something which every tech bioethanol should
implement.
Great.
So hopefully, we already persuaded the techfounders in the audience that, they can become
a tech biopharma themselves.
(40:05):
But then the question I'm sure they're askingthemselves is, you know, how do we start?
How do we find the right sign?
How do we even know the science is interestingor 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, Ican do it.
But how do I know that this is the rightapproach and this is the right breakthrough
technology?
Yeah.
It's, tricky, of course.
(40:26):
So what we did, for example, we talked with ofprofessors 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 tokind of screen it And I think that what worked
really well for us was that, you know, with youguys and the other potential investors and just
throw on them, the ideas.
(40:48):
And so the So in some way, we leveraged thecombined knowledge and combined experience of
people that see these kind of crazy ideas everyday which is the bio investor, the biotech
investor.
So we'll detect bio investors even better.
And then you guys already did the marketplacesearch, right, use so many companies in the
space, and you can give some intuition whetherat least the market is there.
(41:11):
So, obviously, the team is on us, and thenthere is the technology part and then the
market part.
Right?
So team technology and market.
Market, you can do market research, but we usethe smarter people, or more experienced people
to tell us Pete the market is huge.
And then technology, that was the, theimportant part to kind and also whether it is
(41:32):
going to work or not.
So that's the the the deal that we did togetherwith 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 technicalpanel 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
(41:57):
skills.
And if not, Omri is here, you should talk withOmry and other investors.
And so I think that this is the technology thatyou should do.
And then on the team, you need to trust your SoI would say that one important aspect for that
is whenever you hit an idea, which is drivenby, 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?
(42:20):
Is he going to join you as a scientificcofounder, 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 thepuzzle.
I wouldn't start Mana on my own like miss Royalone.
We had to have, most Avian Kira involved there.
It's still in fault very much.
They're not full time in the company.
(42:42):
Not on the payroll, but, we made sure thatthey're involved, and they care about this.
And so, you know, that's the ramp up that thatyou 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 realimpact in hearing, feeding, providing for
humanity, just using the most advancedtechnology on earth, which is bio, to solve
(43:06):
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 youto start.
And don't hesitate to contact us if you havethis crazy idea and you want us to vet it or
other take by investors, but definitely you cando it, and we encourage you to do it.
We see too many bright minds going to optimizeads.
(43:26):
There are huge issues that can be solved withbiology.
You can really help feed people, kill horriblediseases, 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, andespecially in this new company that I'm sure
would be amazing.
And, hopefully, this discussion will helpencourage more tech founders to come to take a
(43:51):
bottle and help change the world.
Thank you very much.
You cannot take, chemical engineer and making adata scientist and vice versa.
But if they understand each other and theyunderstand the context and they understand the
challenges, you will be amazed of theinnovation that they bring then to the table.
Hello.
My name is Omri.
(00:28):
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 showthem that they can start a tech biocompany and
change the world.
So with me will be Yogeb Debbie, founder andCEO of Manabio, He was my co founder, a Gillum
Copilot, the company we read together, a techguy starting in Intel, now doing his second
(00:53):
tech bio company, and he can explain all aboutthe 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 otherfor many years now.
You've been my cofounder, the chief operatingofficer.
So being together in the trenches, more thanfive and a half years that we got it done.
And what people don't know about you and, youknow, I'd be happy if you start with your
(01:15):
background is that you started in tech.
You didn't know anything about bio, and youmade the jump.
And now we see a lot of people, a lot of techPete.
They made their fortune in tech They want tohave the impact of bio coming back to bio.
The kind of joke is how do you make a smallfortune in bio?
It starts with a big tech Morgan.
So maybe we'll start with that.
Like, can you tell us more about yourbackground?
(01:36):
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, aperiod of science, as I said, and I actually
got jetting a water Intel corporate So Istarted as a software engineer, then became
team manager, program manager, really workingon real tech, wireless devices, you know, And
after, about almost 7 years at Intel, we Pete.
(02:00):
And you told us about this crazy idea of, youknow, DNA, like synthetic biology and synthetic
DNA.
And everybody is going to synthesize DNA andedit 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 wasdiscovered nobody knew what it was.
(02:24):
So I remember coming to your lab at Stanfordwhen you did your postdoc.
And we saw that, you know, the in luxurious labat 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 thishuge world of biology and starting to
(02:46):
understand the differences.
Yeah.
So you join me in this crazy journey and thepipetting 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 managerin detail to being a chief operating officer in
a software company for biology.
So how was that transition?
(03:07):
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'screate you know, dot Pete for DNA.
So that was the idea.
And I remember a few occasions where startingwith this episode that, Stanford when we saw
that, you may walk with Pete and paper, thenwhen we started creating the actual software
general compiler, and we showed it to users,and we were in this mind oh, everybody's gonna
(03:32):
use it for sure.
And then we presented it to lab scientists onthe 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 onthe 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 actualbooklet, physical booklets with tables and
(03:55):
charts and backgrounds, which they used to useon daily basis.
And when we show them, like, interactiveapplication 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 eventhough, you know, I didn't have any scientific
background, I honestly think I'm not smartenough to be a scientist at PhD.
(04:16):
It was great to know that, using engineeringmindset and software skills, you can actually
make an impact, you know, on these people andthen 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 ofthe 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
(04:40):
kind of product requirements, right, from theproduct Pete.
And they say, you know, this is how it shouldlook 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 canbe 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 arethe priorities.
(05:02):
In biology, there is the initial way.
Can it be done?
We didn't ask ourselves this when we came toOmri and we asked him, you know, should the
software behave like this or like that?
I mean, what's the what really the productrequirements?
What should the flow be?
And always like, well, in biology, sometimes itworks like that.
Sometimes it works like that.
I don't really know.
(05:22):
Nobody knows.
So it was like, okay.
How can we, you know, implement and develop anysoftware 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, anda learning experience, right, you know, five
and a half years in the trenches buildingsoftware for bioengineals seeing the price of a
synthesizing DNA going down along the way,being in all the scene by a Beller conferences.
(05:46):
It's been quite a ride, and then we were luckyenough to get acquired by twist bar sciences a
company making DNA where I became the head ofCOVID 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, youknow, you know, and we we talked about it a
(06:06):
lot.
We felt that we're, I joining this hugerevolution and finally when we joined forces
with, with another company that actuallycomplements us.
So that was great.
And think that one of the, interesting thingsthat happens also after the acquisition and for
sure, even before Indian Copilot was that, youknow, managing people that, come from these 2
different boards.
So on one hand, you have the, obviously,software engineers, the writing code that was
(06:29):
the competence of the team.
But on the other end, you had a lab scientist.
So, Omry, yourself, but then other people aswell, 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 betweenthese two worlds was something, you know, you
need to really give education to the 2 worldsof how to speak with each other and how to
(06:52):
accommodate the challenges, you know, of eachother.
Don't worry.
You came one day.
I thought it was 2 years before theacquisition.
You came back and you say, you know, this isthis new thing called CRISPR gonna change
humanity.
It's a gin genome editing, and it's gonna be aNobel 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,
(07:14):
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, itwas out there.
And I remember that you know, when trying toexplain people, so when I became the general
manager of Swiss Israel, part of my mission wasto also some kind of, give, you know, pictures
(07:35):
and talks about the new generation of geneticengineering.
We call it genetic engineering 2.0 or syntheticbiology.
And when explaining that to tech people andthat because, you know, migrate on this tech.
So it was easy for me to think as a techperson, you know, biology is really different.
Why is it different?
It's because that software essentially is madeby human, right, and, you know, we created
(07:57):
software.
So we will we understand it as complex asapplication can be and as complex as
challenging and challenging tasks that you as acomputer 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 thecode of life and, you know, nobody created it.
(08:18):
I mean, god created it of evolution, that isnot documentation.
And now we're trying to design it.
And now I'm explaining Pete, I'm talking to thetech people.
Imagine that you have a softer the Flintsoftware 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
(08:38):
that.
You have first, you have multiple programcounter, 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 environmentalparameters 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.
(08:59):
So 5 to 3, 8, 3 to 5.
Right?
So, you know, imagine how you can design on topof that.
And then, can you hack things like that?
So this is crazy.
And then come crisper and crisper aims tochange 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 sohappy it's coming to reality.
(09:20):
Yeah.
It's so funny.
You know, people, you know, I remember talkingto my partners about mom with Biosciences
before we decided to invest in them, and theytold 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 ofMabu'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 nodocumentation.
(09:40):
We didn't invent it.
It's the most complicated, most advancedtechnology on earth.
That's biology.
But the impact so humongous.
Like, the ability to feed people to kill peopleto provide for humanity and the environment is
just amazing using this technology.
So so you've been entwised at its peak morethan $10,000,000,000 company, and then you join
Monday and help them IPO and become a reallybig company.
(10:03):
And now you decide, you know, forget that.
I want to go back to biology, and you start acompany called MannaBio that, I'm very grateful
to be able to invest, close the loop, and be inthe ball great.
Now it's your time to suffer as a CEO.
That's great.
Hopefully, the next $10,000,000,000 pluscompany.
So can you tell us what made you go back tobiology?
And then if you can explain what mana is doing?
(10:23):
Yeah.
Of course.
After this journey, you know, I talked one daywith, 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 anew company.
We have 2 requirements.
1, it has to be something impactful andpreferably in the life science business.
(10:48):
And the other one is it has to be somethingwith software because we have the same
software.
And so we tasked ourselves with finding thisnext challenge, and it was obvious that we'll
gonna need, another co founder, anotherscientific co founder, because we need someone
from the science background.
And so we went on for a few months of ideationtalking to Pete.
Right?
We we didn't think we're gonna bring the nextidea So we talked with many people, PhD
(11:13):
professors, and these people in the academiainvestors and entrepreneurs.
And eventually after a few months, think youactually introduced us to 2 professors from the
Technion, which is the kind of the MIT ofIsrael.
And one of them, Avish Schroeder is a chemicalengineer 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 ofthe academia on the idea of leveraging learning
(11:38):
and AI in order to predict lipids and lipidnanoparticle formulations for drug delivery of,
gene therapy of nucleic acid basedtherapeutics.
And we met together, and the first we fell inlove with the Pete, so Adi and Kira.
And then we also fell in love with the idea andunderstood this this.
For me, it's very exciting because theopportunity that we have here is that, you
(11:59):
know, for the past decade, I mean, peopleworking on this crystal and Beller biology, and
it's clear now.
Well, I I said before that people didn't knowhow 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 oftherapeutic and vaccine is going to be based on
(12:20):
the click, I'll see the therapeutics.
So whether it is crystal RNA, DNA, differenttypes of RNA, right?
But then apparently, the button like there isdelivered because it used to be the case for
other drugs that delivery was kind of not amust or you could use something generic.
But now with nucleic acid therapeutics, youhave to have something which is tailor,
tailored to the payload, tailored to the,target organ that you need to reach So you have
(12:44):
to have delivery.
I like to think about it as if you're on anastronaut, want to fix the space station.
Let's say the astronaut is like the crisper.
So you cannot just walk to the space, you needa space shuttle with oxygen, seed Beller, pass
the atmosphere, lens safely, etcetera.
So this business of building space shuttles, itreally needed on one hand, on the other hand,
it's really hard.
And when talking with illegally companies, theysay, you know, it's really hard.
(13:07):
As I said before, biology is not known.
The law the underlying logic is not reallyknown, not understood well enough.
So it's really hard to come up with the newdesigns of new space chat, especially if you
want to overcome great challenges.
Like targeting different organs in the body arewith 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 realscience, which is trying to rational these to
(13:31):
make it with rational design, which is reallyhard because we don't know the underlying
logic.
So what we do and our hypothesis is let'sleverage on the other end.
We have currently almost on the shelf machinelearning, AI, talented people that know how to
develop these algorithms.
So let's use that.
Apply that on data or relevant data, eithergenerate data take existing data and then come
(13:54):
up with a platform to predict new deliveryvehicles.
So new lipids, lipid nanoparticle formulations,and then we'll be able to actually the liver is
nucleic acid based therapeutics to differentorgans and cell types in the body.
So that's the idea.
We were really lucky to have you, as part of FXand leading all seed round about a year ago.
And together with Lambdael, which, by the way,Lambert also sits on this intersection of
(14:17):
software and life science.
So we'll really fortunate to have you guysinvested in on Pete round.
And today, you know, we're 1 year, like, justcelebrated on anniversary.
We have many achievements along the way, but Ithink, you know, this, kind of tech bio spirit
is really, really part of the company rightnow.
So just to clarify the delivery problem, right?
(14:40):
You know, when people think about drugs, theythink 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 thebody and it just works.
But then new modalities of drugs like proteinantibodies, and you cannot eat them because
they get degraded in your stomach.
You need to, you know, get them through an IV.
(15:00):
And then the new modalities of nucleic acids Ifyou try to eat them, then degrade.
If you try to put them through an IV, the bodywill 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 directthem to the right cell to affect that cell
(15:23):
type.
And that's the huge problem of delivery thatyou are trying to solve with a combination with
a real tech bio platform company that has acombination of AI and machine learning, but
also actually physically chemically as exercisefor smaller cues and testing them on living
things to see if it works.
And then closing the loop and learning fromthat and, you know, creating new delivery
(15:43):
options for patients.
Yeah.
Exactly.
And I think the point you hit on this sectionalintegration between these, 2 type of expertise,
I think that's the opportunity that we havehere because if you look around most the
companies, at least in the delivery space, as Isaid, they focus on real science, and it's
really hard.
And that's why they they told me, you know, wedon't understand the logic.
So it's, like, based on gut feeling orintuition.
(16:05):
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 muchtime and so much money to do it.
And so how hypothesis is to really shrink thetime 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 Ibelieve today to do that is the integration
(16:29):
between these two worlds of real scientists.
We still need, you know, wet lab andeverything, 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 leanon.
They don't need to be unleavened of some biaseson their, you know, history.
And so it's really funny to see that you know,sometimes it's really simple to make huge
(16:54):
steps.
You know, sometimes if you just make a simplescript of generating, numerous candidates to
test and then solve them in some way.
We'll save few days of work for, So we seethese on a daily basis where the software
engineers come and sit actually in the lab.
This is very important to, you know, integratethe people.
So the software engineers, they come and in thelab, they see the mundane work.
(17:18):
And, you know, the number one thing that mostlypuddles us, like tech people or software people
is that if when you say, you know, manual workhappens more than 1.
Even one is bad, but if something mundanehappens 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.
(17:40):
So tech people, they take laziness to the nextlevel, 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, andyou make life much more simpler.
So the scientists, they have now time, and theyhave their minds free to think about these
(18:04):
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 todayis because we go to academia and we see amazing
IP.
We see just its most incredible science thatcan really change the world and make huge
(18:24):
impact in people's life.
But the kind of culture we have in biology isnot very important in the world, and Pete are
missing the founder, the entrepreneur that cantake it out of the lab and run with it.
And we see a lot of people that got trained inentrepreneurship 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.
(18:45):
So somebody who's doing it, you don't havebiological background.
You have software background, and it's now your2nd tech bio company.
Like, what translates well?
What works?
And where do you need help?
Like, how can we make more people intake comeand start companies in bio?
Yeah.
So that's a very good point.
So first, the gap between the two worlds isreal.
I mean, the risk gap I think that a result of,what we described before that, you know,
(19:08):
software Pete, since the underlying technologyis 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, youcan own the same day.
You can see results from the it's amazing.
I mean, think about if you could develop a drugand see the reaction of the market after like,
(19:30):
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 Bellerscience.
It's really health.
But I think that in tech, what was developed inthe 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 manycultures evolved on the basis of not on, like,
(19:53):
doing curiosity driven science, but on doing,like, R and D, which is just how you make
things most efficient, the best userexperience, the best value for money, you know,
R and D etcetera.
So you have a lot of good concepts whichresults in impactful work and prioritized work
and focusable.
And I think when you take this into thescientific world, I mean, you cannot make a
(20:18):
scientist you know, just give you and walkestimate.
Like, it will be 2 days, and it will be 2 daysbecause it doesn't power because everything is
curiosity, but you can still push the Currierand you can ask questions, which will lead to
better answers in terms of the management, theself management of the person, like how you
manage yourself, how you wanna measureyourself, how you wanna spend resources.
(20:40):
So if we talk about tech, you know, Sinceeverything is so rapid and fast, there is a
huge competition, but you have great threeworlds and you have many people working on
that, and there is a lot of capital.
So in many cultures, you know, the culture iskind of, spend money and don't waste time.
Just let's save time and spend more money andget results faster.
I feel sometimes in science, in bio, people areworking from the, opposite way of let's save
(21:05):
money and on the expense of time.
And so even though it is still like realscience or not.
You know why?
The main reason is, you know, you do most ofthe science in academia.
And academia, you don't have money and theworkforce and PhDs are for free So they don't
care.
Yeah.
And I think, correct me if I'm wrong, but Ithink that then in the bio, the culture evolves
(21:26):
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 evenmasters.
You don't really need that, you know, to besuper effective and you know, get well
compensated in the tech companies.
(21:46):
So after 3 years in Akadin, which is totallyjust undergrad, right, You are out for
industry, and you make all your career inindustry.
So you learn at the big companies, smallcompanies start at but it's all business
oriented.
And in science, you spend few good years inacademia on research even before you work in a
company.
So this is kind of you know, so it makes yourculture, the the DNA and the culture as in
(22:12):
academia.
So things like, you know, yeah, we know ittakes time.
You know, it's really hard even to evaluatepeople's performance because, you know, you're
making experiment, and then you get the resultsafter 6 months.
In tech, after 6 months, you already filed him6 times.
Like, it's a the Ohio, you know, great peoplein 6 months.
(22:33):
So the turnaround time from idea to results issomething which is meaningful.
Anyway, it makes tech people to be thinking inin a process oriented, which is like
structured, very process oriented, like, verystructured, and they all also invented all
these mechanisms because the problem with techis not like the problem inside.
(22:53):
Right?
The problem in tech is how to do it mostefficiently.
It's not like, as I said, not like whether itis possible.
So we invented and tech Pete.
They invented mechanisms of how to make surethat 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,
(23:19):
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 evenunderstand 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 amazingperson.
(23:40):
Amazingly, they're amazing and he said, no.
I mean, guys, you need to audit what's yourplan for today, even though, and it is okay,
you know, not to reach, I mean, yeah, youdefined the goal and you didn't reach it
because 1, 2, 3, still, you have to report itout.
You have to say, what are you going to achievetoday?
Even though this task.
I don't synthesize this molecule, whatever.
(24:02):
Yeah.
It's a 3 days walk, but breaking down in 2 daysand define what you need to do today.
So task breakdown, Beller planning, you know,better focus.
These are all concepts which, they were evolvedand got matured in the tech, but they certainly
have place in the bio in the scientific worldas well.
I mean, we see it every day.
(24:24):
This is so important to what you're saying herebecause I think, again, we're trying to get
more tech founders to come to bio and, youknow, their reactions what do we know about
bio?
And then my answer usually to them and to mypartners when they want to evaluate the bio
companies, 80% of the company is the same nomatter what the company is doing.
8 James and marketing and management andsupport and all of that.
(24:45):
And then if you're in a tech bio company andyou 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 biopartner to compliment you, and you can be a
CEO.
You can be a COO, you can be CTO of, of a techbio company, even if you don't have a
background in bio at least that's myexperience.
Does that fit well with your experience?
(25:06):
Yeah.
It's a good point.
You know, it's kind of, you're hesitated in thebeginning because you you're not, like, I feel
that I will not be the one that comes with thescientific innovation, right?
It will not come from it.
This will come from the science, it's fromscientists, and there is a gap.
I mean, obviously, you don't understand thematerial.
Right?
The way I think about it and and to mitigate itis first, you know, ask questions.
(25:27):
Be humble.
You know, don't assume that you know things.
And I think in the beginning, you know, in thetech days, back in the days, it was like the
senior people were kind of, they thought theywere the smartest.
It's not like that anymore.
So for a long time already in, even in thetech, people are humbled.
They're not, like, the smartest people in theroom.
So I think that we'll use to not be thesmartest people in the room.
(25:49):
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 dayI think, you know, this is the most important
thing is to get the right resources to learn.
(26:11):
Now I don't mean learn them because you need toreplace the scientists and these scientists
yourself, but learn in order to understand thelanguage so you can understand better when they
describe you a problem or whatnot, how you canBeller help.
And I think you're absolutely right on thegetting the right partner, which has the
scientific, you know, skill.
It could be a partner.
(26:31):
It could be just know, Pete in the team thateach one is an expert in his field.
So what you really need to do is to find thepeople that can help you vet and screen the
right people for the company because I couldnot hire, I mean, the lead chemist in our team.
What do I understand with chemistry?
You know, So we need to have the scientificcofounder for that to Pete and say, you know,
(26:53):
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 HRinterview for him.
That's it.
Right?
So I think that's a huge Beller.
And it helps in the that world, you know, thethe network is important.
So Pete, it's important even more because thenetwork 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
(27:17):
know, the the fact that I know to Morgan, talkwith investors, Morgan tell, you know, the
stories and stuff.
I mean, yeah, I had a huge ramp up to do in thescientific world.
And, you know, I think that in some point, bythe way, sometimes I feel in discussions that
it comes to my favor.
The fact that I'm not a scientist, because it'slike, okay, you know, I'm not a scientist, but
(27:40):
they appreciate the fact that I know enough tohandle 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 differentbecause that was shit you know, my position on
different, base of, skills and, you know, anachievement.
So I think there is even an advantage being atech, co founder or tech CEO working on by a
(28:06):
company.
It's a lot of the audience of the end effectspodcast are tech and entrepreneurs or just
general tech Pete.
Your experience, what do they need to learn tobecome a tech biophounders?
So number 1 is a hunger to learn, like, Bellerday use every opportunity, whether it is the
online courses or the mentors or just, peoplefrom the team.
I love learning from people from, in the team.
(28:27):
Because for me, it feels that, I learn from thebest resources because they'll be best.
And, also, it's kind of part of the culture ofthe company.
You know, it's like I don't know something.
I ask.
So it's role modeling for them is that it'sokay to ask, and there are no stupid questions.
So ask the people, leverage them, And then Ithink specifically between tech and bio is that
(28:48):
we need to appreciate that, you know, thefundamental thing is so different.
I mean, things in biology, it's notdeterministic the way we are used to.
So this is why everything, collapsed fromthere.
You know, the it's not known, experiments takeforever, It's not because the people are slow.
All lazy.
It's because sometimes it is the nature.
(29:09):
So we need to develop the patient for that andalso 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 canassess our performance, right?
Because I know if something should take thatamount of time or not, I know with with all the
people who are good or not in bio, I don't havethis.
(29:29):
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 programminglanguage or a different operating system.
It's a totally different world that we're Flintto it.
And one of the things that I'll say 2 morethings.
1, for tech people, especially I would say forCTOs or the or CEOs, which are more, kind of,
(29:51):
technical.
We love the mind challenge We love challenges,right, and we look for engineering problems.
And we want to solve them with most advancedand sometimes, it results in complicated
solutions.
In biology and biocompanies, I think sometimesbear in mind that sometimes simple is enough.
Sometimes when you produce a simple solution inthe software mindset, it will be a jump for the
(30:16):
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 solutionsbecause everything else is complicated enough.
I mean, now we have a problem in the lab thatsomething is not Morgan.
It's voodoo.
In software, we say voodoo.
(30:38):
Well, the I don't know real voodoo, but we somewhen we learn the sun, we say, there is a
voodoo in biology, there are a lot of voodoo orevery 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 makesure things are as simple as possible.
Well, I
(30:58):
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 isinterested 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,
(31:20):
experience, etcetera, on something which is sopurpose.
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 bea scientist in PhD, so I'm really grateful that
they can contribute my skills to do this, bumpin the wall.
This is great.
I think that the number 2, I will aim the, theCEO or the leaders that are going to, to start
(31:42):
the company or to lead the company, which isfrom these two worlds is it's essential and
important for actively working on bridging thegap between the two types of people in if you
have a tech by your team, it means financialthat you have people which are on 1 end
software engineers or coming from the techbackground.
On the other hand, you have people right from,from the lab or scientists, ancient scientists,
(32:06):
etcetera, these 2 groups of people, they are sodifferent.
I mean, so my advice is Pete, proactive efforton 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 inthe same language.
(32:28):
And I think the main gap the the basic gap islanguage.
And people need to understand themselves.
People need to understand each other.
They need to understand the challenges and theperspective 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.
(32:50):
This is your opportunity to really make theteams suddenly create real new innovations
because that's the real diversity that youhave.
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, makesure that people start, I mean, you you cannot
(33:10):
take, chemical engineer and making a datascientist and vice versa.
But if they understand each other and theyunderstand the context, and they understand the
challenges, you will be amazed of theinnovation that they bring then to the table.
It's amazing.
I love to see it every day.
I see it and also started talking withchemistry, you know, when we used to laugh at
the genome compiler, some words that youbrought up, and we didn't standard awards and
(33:33):
we laughed about them.
But, you know, eventually, you see thiscollaboration 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 gapbecause, again, the gap exists, but bridging it
actually can create a lot of synergies and newinnovations.
So one thing that I really admire about Manathat came from your background in tech is how
(33:58):
fast you move.
You move really fast.
And people are amazed at how fast you got toresolve and how fast you're actually improving
your results.
So what other mindsets and skills can peoplebring from tech, to tech bio companies?
Yeah.
When I think about it, and, you know, it's it'sa good point that, we are moving fast And I
think it's also a combination coming from thetech industry, which is mostly like industry
(34:21):
focused and business driven and need to getresults fast, etcetera, and competitive
environment, and also, you know, beingexperienced, let's not forget that.
I mean, it's not the first time So when Roy andI were in this, ideation phase looking for the
next challenge and before we started Mana, weactually did the nice exercise.
We said, you know what, We already know fromour tech experience and experience in
(34:44):
entrepreneurship.
We know how the company should behave in termsof culture.
We don't know what we're going to work on.
We don't know what the purpose is, but otherthan, you know, we know that we want to work on
life science and so well, we know how thecompany works in terms of values.
And we sat down and actually written the valuesfor the company, which were, impact ownership,
(35:05):
quality and teamwork.
So impact is like, you know, make sure that youhave 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 needto make every decision in the company.
(35:25):
I think that this is very important because weknew we are going to enter into something that
we don't know enough And then we have to havepeople that have this kind of sense of
ownership.
Like, they know.
I'll like, the chemists, the chemical engineersin the company, they know that they have to
make decisions every day.
And they have to make these decisions in lightof the goal, in light of the purpose of what we
wanna achieve, but they have to own theirissues And obviously, you know, it's under the
(35:49):
context that we give them on, you know, budget.
They know, like, the the limits, etcetera, butit'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 somuch, tie in the industry, you know, amazing
companies, intelligent competitor, Twists,monday.com.
(36:11):
I'm in great companies, and we learned a lot.
And in the tech industry, again, since it's socompetitive and so fast, I think, you know, in
the tech, the, as a result of the fundamentalof how it works, it became a competitive.
I mean, you develop software so fast, and youget feedback so fast.
That it's in your nature.
So we get sick when things go slow.
(36:31):
And by slow, I don't mean like, okay, sometimesthings take time.
You know, it takes time to calibrate a newrobot 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 notfocused.
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.
(36:52):
Oh my god.
So we train people.
We don't whip them.
Like, this is what you should do on thecontrary.
We train people to test themselves whetherBeller, focus.
So whenever somebody is not focused, I startwith myself, and it's my problem because I
didn't communicate the focus well enough.
So this is the first step to make sure thefocus is communicated.
(37:13):
The goal is communicated.
Everybody in the company, by the way, they knowalmost everything.
Like, everything is concerned a side of, youknow, salaries and cap Beller, but people know
where we stand in terms of businessdevelopment, in terms of the, the plan, in
terms of even in fundraising.
I mean, they know you know, not all the bitsand bytes because just a lot of data, but they
know where we are.
They know where we're raising money, etcetera.
(37:34):
So people are kind of out of the headache thethe 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 greatideas.
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 ideabased on the context of the company based on
(37:58):
the goal that I defined, and they come withsomething 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 expectedfrom people to bring solutions.
(38:18):
Right?
Like, it used to be in in the early, earlydays.
Like, the manager was saying, you know, thisdepartment 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 Royand I believe Flint the in in Navient, like,
(38:42):
this is the real scalability, and this is thereal leverage that we have from the Pete,
because everybody in the team especially inthis 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, orsocial engineers, biotech, is this sense of,
hey.
(39:02):
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 ofsynthesizing 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 somethingthat, we learned in the industry.
(39:24):
It's now becoming more and more wide in thetech industry transparent, impact all of those.
I think that these values should be applied inthe culture of the company.
I have to say that you know, the bio people inthe team, they are sometimes are shocked.
I mean, they're they're not used to this kindof sculpture.
In the beginning, they were not used to it.
(39:44):
Like, it was a shock for them.
And we train them, and they saw all model, andthey saw that we are good with getting feedback
from them.
And now it's working, right, and I think thisis something which every tech bioethanol should
implement.
Great.
So hopefully, we already persuaded the techfounders in the audience that, they can become
a tech biopharma themselves.
(40:05):
But then the question I'm sure they're askingthemselves is, you know, how do we start?
How do we find the right sign?
How do we even know the science is interestingor 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, Ican do it.
But how do I know that this is the rightapproach and this is the right breakthrough
technology?
Yeah.
It's, tricky, of course.
(40:26):
So what we did, for example, we talked with ofprofessors 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 tokind of screen it And I think that what worked
really well for us was that, you know, with youguys and the other potential investors and just
throw on them, the ideas.
(40:48):
And so the So in some way, we leveraged thecombined knowledge and combined experience of
people that see these kind of crazy ideas everyday which is the bio investor, the biotech
investor.
So we'll detect bio investors even better.
And then you guys already did the marketplacesearch, right, use so many companies in the
space, and you can give some intuition whetherat least the market is there.
(41:11):
So, obviously, the team is on us, and thenthere is the technology part and then the
market part.
Right?
So team technology and market.
Market, you can do market research, but we usethe smarter people, or more experienced people
to tell us Pete the market is huge.
And then technology, that was the, theimportant part to kind and also whether it is
(41:32):
going to work or not.
So that's the the the deal that we did togetherwith 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 technicalpanel 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
(41:57):
skills.
And if not, Omri is here, you should talk withOmry and other investors.
And so I think that this is the technology thatyou should do.
And then on the team, you need to trust your SoI would say that one important aspect for that
is whenever you hit an idea, which is drivenby, 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?
(42:20):
Is he going to join you as a scientificcofounder, 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 thepuzzle.
I wouldn't start Mana on my own like miss Royalone.
We had to have, most Avian Kira involved there.
It's still in fault very much.
They're not full time in the company.
(42:42):
Not on the payroll, but, we made sure thatthey're involved, and they care about this.
And so, you know, that's the ramp up that thatyou 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 realimpact in hearing, feeding, providing for
humanity, just using the most advancedtechnology on earth, which is bio, to solve
(43:06):
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 youto start.
And don't hesitate to contact us if you havethis crazy idea and you want us to vet it or
other take by investors, but definitely you cando it, and we encourage you to do it.
We see too many bright minds going to optimizeads.
(43:26):
There are huge issues that can be solved withbiology.
You can really help feed people, kill horriblediseases, 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, andespecially in this new company that I'm sure
would be amazing.
And, hopefully, this discussion will helpencourage more tech founders to come to take a
(43:51):
bottle and help change the world.
Thank you very much.
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