The Future of Drug Development: 3D Vascularized Tissue Models in Clinical Trials

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
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Speaker 2 (00:24):
Pretty she had done d droll, people, she'd be telling lies.

Speaker 1 (00:33):
Okay, So today it is my pleasure to insto a
doctor valented CEO of vaux Cell bio Innovation. So in
hindsight of such a successful career, you can to start
with you taking us back and telling us us about
your background.

Speaker 2 (00:48):
Absolutely, so it's my pleasure to be here. Thank you
for taking the time. Karen So my background, I am
a chemical engineer by bachelora and master. So I did
my bachelor in Brazil and then moving to Portugal to
continue pursuing a master's degree, and and in Portugal doing
my master's degree in chemical engineering was like my first

(01:08):
contact with the biomedical area. So in there doing my
master's I was synthetizing new membranes for ECMO machines for
like blood oxygenator's machines. So that's when I kind of
fell in love with the bironmedical field. So then after
finishing my masters, I applied for a PhD in Canada

(01:30):
and then decided to come to the University of Victoria,
where my faculty right now. And the idea to do
the PhD was really to focus on oncology and really
to focus on the mechanical properties of the tumor micro
environment and how the environment of the tumor can really

(01:51):
prohibit I would say drugs should be delivered in a
very precise way, but it's also in a very system.
So that's where my focus on my PhD was with
studying these different parameters of the tumer micro environment and
how could we enhance drug delivery to that tumor area.

(02:12):
So a little bit of my background than engineering, mechanical engineering,
environmental engineering, chemical engineering. And I'm right now on top
of me a CEO voxtell Arma faculty at the Universal
Victoria teaching the biomedical program and also some of the
mechanical courses.

Speaker 1 (02:28):
Yeah, that's really interesting. So yeah, another question is, so
I've heard from some of your employees that you wanted
to do your postodcast Stanford and on your clinic in
and you weren't doing like your science I think, so
I was asking why did you did you decide to

(02:49):
box down self continuing your post Officeyeah.

Speaker 2 (02:52):
Yeah, that's a that's a great question. When I finished
my PhD with August twenty twenty, and by that point
I already had three offers. One was Washington University, the
other one was Stamped and then the third one was
the mail clinic, And the idea was to move to
the US to do the post bock. But of course

(03:13):
I fell in love with box Boxall had just been corporated.
I incorporated the company a week after I depend on
my PhD, so it was like moralized at the same time,
and that point the company was becoming more and more real.
So I didn't want to abandon and do it remotely.
I wanted to stay in Canada. So I had the

(03:33):
hard decision to say no to some of these posed
dog offers, which were very very good ones, and decided
to stay and run this company.

Speaker 1 (03:43):
Yeah all right, So yeah, my next question is, you know,
I know Voxdelle is kind of in drug development, where
you guess want to speed up all these rug trials.
So you know, what are you interested in, like drug
development and like speeding it up?

Speaker 2 (03:58):
Yeah, so I think some of thing interesting in the
area is the fact that it's still a very inefficient problem.
It's very inefficient process. So the goal is really to
understand is there anything that we can do to really
accelerate and to change the way that drugs are tested.
Right now, we have animal models almost as the gold

(04:20):
standards for this drug development process, but the data shows
the animal models, even though the other gold standard they
are highly adopted, they're not actually translatable to human data.
So the focus on these there is to find a
better gold standard model. Basically, can we find something that
more meaningfully will produce data before clinical tris that's the

(04:45):
goal with box.

Speaker 1 (04:45):
Cell, I see, yeah, yeah, So can you talk morbal
box Cell, Like what does Boxell do? Like, like what
products do you guys have?

Speaker 2 (04:59):
Absolutely. Vouxer is a startup located in Victoria, BC, and
we are using bioprinting technologies to create what I like
to call it artificial biopsy samples. So it's almost artificial
human samples that we create using our bioprinter and our
bioprinter is combined with our bio inks that is our

(05:20):
printers cartridge and combined with our software. So what you
see as a result is a model that contains well
cancer cells at full red structure and an artificial vassa culture.
So Vouxer is commercializing these fisial models as a screening platform.
So the idea is to inject the different drugs through

(05:41):
the vast flucture of this model, very similar to what
happens in the human body. But we also sell our
inks that is our printers cartridge as consumable and the
beauty of our inks is we made them to be
very applicable to any type of bioprinter. So for example,
if you have a printer at home, you need to

(06:01):
buy that specific cartridge for that specific printer. We stopped that,
so we made a cartridge that was universal and can
be plugged the most bioprinters. So that is the beauty
of our bio ink. So vox I was commercializing the
tissues and also the bio inks and also just walking
with partners. We just want to make partnerships with great

(06:22):
companies out there that want to have the drug screened.
So that's something that we can help in house right now.

Speaker 1 (06:29):
Yeah, and then so you know other than your I
guess you could say your tissue bottles, Like, there's other
things that are doing drug development, Like for example, organoids
are one, and then I heard like AI it is
also like one. So absolutely, yeah, So how like, first

(06:51):
of all, hours are three tissue models different from organoids.
And my second question is I think the CEO sat
like AI drug trials could happen around this year, So
is that going to be a big competitor to box
cell or or or guys going to like like adapt
to AI trying to incorporate AI to your product.

Speaker 2 (07:16):
Absolutely, So let's start with the organoids first. So the
organoids they came as an advancement from the spheroids. So
let's talk about spheroids first. Spheroids were a way that
scientists created to get closer to what happens in the
human bold in terms of the three DA structure. So
what the spheroids were is they take the cells, the

(07:37):
human cells, make a little balet and analyze how that
little pellet is interacting with the drugs. Then we took
a step further and create organoids. So the difference between
the organoids, is we are putting that a little balet
in a material that is similar to bio ink and
letting the cells to self assemble and create what we

(07:58):
call organoids. That is this time the organs, right. The
challenge with the organoids is the self assembly. So the
self assembly means that in one side, which is positive,
the cells are assembling the way that they should. But
on the other side you have a very heterogeneous population
of samples because the cells are self assembling. So if

(08:20):
you want to have a very controlled experience experiments or
in which you are comparing the different drug concentrations different
drug responses, they're organoids. The heterogeneous population of the organoids
may be a challenge. So going from them, what the
field started doing with the organs on the chip? Can
we create organs on the chip in which you have

(08:42):
some kind of device in which you can organize yourselves
in a certain way and the cells will always look
and behave that same way. So that was the organmachip.
So what vox I was doing is the next generation
organ on a chip where we are allowing the cells
to be in a certain configuration as we want. So

(09:03):
we are putting the cells in a certain configuration, but
we are taking a step further from the organ chip
by creating three D. So, for example, when you're seeing
maass culture in or government chip, that vas culture is
fully two deep, and that's not how the human body is.
The human body is fully treaty. So vox cell is
the next generation organiment chip, taking the vast culture, taking

(09:23):
the cells and putting them all intreating in a very
similar environment as it happens inside of the body, and
also focus on the ink which is mimiting the extras
matrix material to really focus on having the correct mechanical
properties and the correct chemical properties for that environment. So
the cells are very coosantly behaving through how they behave

(09:45):
inside of the human body. When we think about AI especially,
I don't see AI companies being a competition. I actually
see them being a potential customer, so I or the
whole in silical field, what they are doing is they're
trying to streamline the beginning right, trying to do those simulations,

(10:06):
so you're limiting how those potential molecules which could become
potential drugs, how those potential molecules are interacting with the environment,
and doing all that simulations to spit it up. So
what we see is that simulations can go all the
way to at some point those molecules that were selected,
they need to be synthetized and they need to be tested.

(10:28):
So we see Vauxell's platform as being the perfect platform
to test those mlicles. So in cilical testing to be
done needs to be tested at some point and that's
where a vaux Cell's platform would come. So we see
them as as potential customers. We see as an alliance,
not as much as competition I see.

Speaker 1 (10:49):
But like you guys aren't going to incorporate AI into
your software and stuff or something, right, It's.

Speaker 2 (10:54):
Not not at this point. So what we are looking
the way that the software right now, which we use
physiological constrains, meaning that we have the size of the
average blood vessel for that type of tissue, how much
is the density and so on, So that's how we
are generated the blood vessels for each tissue. We will

(11:15):
see the software evolving over time. We want to make
sure that the vas culture is being optimized for that
specific tissue that is being behaved, that is being created.
Both so far we are not in corporate we don't
see the benefits of incorporating AI at this point.

Speaker 1 (11:31):
M yeah, so you know, just so let's say a
company wants to test their drug or therapeutic in there.
How long would they get the results because I know,
like for animal models it's sometimes a week or even
a month or two months. So how long is it? Yeah,
animal model?

Speaker 2 (11:50):
Animal model results can take months actually, so it's it's
multiple weeks because you need to grow to the animal.
Then you need to do all the post processing after
you inject your drug in today animal. The idea with
box cell is you're shipping us your drug, for example,
if that's a partnership model, and in a week you

(12:10):
have the results from that drug. So it is a
much faster process to get that information. And right now
what we are trying to do with the tissue models
is one week is when you have information on day
seven of how that drug is behaving. But we are
trying to extend those testing to multiple weeks. What the
benefit of that is is that allow for drugs to

(12:33):
be tested multiple times. So what I'm trying to say
with that is there are some drugs that require multiple doses.
It's not just one those that it's going to kill.
So extending the lifetime of our tissues through up to
a month. That's what we are trying to do right now.
Will allow us to do this type of studies that
require multiple those injections and tracking over a longer period

(12:56):
of time, which again is another advantage of box Cell's
platos compared to the organized and the ORGANMA chip where
you can only use once and it's a very short
period of time that you can use those temples and
remain viable temples. Right.

Speaker 1 (13:12):
So, yeah, you mentioned like box Cell, you guys generate
custom of vessels, like blood vessels particularly, So let's say
a company wants to test something right and they want
like a specific measurement, So how do you So would
you guys implement that specific measurement into the system.

Speaker 2 (13:31):
Absolutely, so that's definitely possible. So the way that it
works for a customer tissue, it would be an interaction
with the customer first, so we understand what type of
tissue they are trying to mimic. Let's say long for example,
So if they are trying to mimic to lung cancer,
we will then show how the tissue would look like
and the proposed blood vessel structure, and that is a

(13:52):
conversation with the customer according to the type of drug
data developing. So, for example, if the customer developing chemotherapy
drugs though that are small molocus vests, biologics which are
larger models and should be taken to consideration according to
the bus culture design. And then after that, once the
design's approved, we start printing and testing those drugs and

(14:14):
then doing the multiple assets that we have proposed and
are in agreement with the partners. A lot of the
partners that we are interacting right now, it's because they
have some kind of data, whether that is animal model
data or too deep tell mono layer data and they
want to compare and so that's the type of partnership

(14:34):
that has been working quite well for both cells.

Speaker 1 (14:38):
And do you guys mainly claorate with companies. Do you
collaborate with like academia labs?

Speaker 2 (14:44):
Maybe absolutely, absolutely So we have completely open to collaboration
with academia research labs, so private and public organization, so
we are open to everything.

Speaker 1 (14:54):
Yeah. So, I mean your first product is focused on
breast cancer, so hm, they asked why you chose breast
cancer and not like, oh, like well, like lung cancer
or maybe Alzheimer's.

Speaker 2 (15:08):
Yeah, absolutely, why breast cancer. So I my PhD with
a thousand breast cancer, so that's the cancer I have
the most expertise. My mom has breast cancer and she
has recently passed in October due to the cancer have
spread and metastas everywhere in the body. So breat cancer

(15:30):
comes with that, that personal touch, that personal connection to me.
The reason why we pursued breast cancer on VODA, especially
triple negative breast cancer is triple negative breast cancer for
the people hearing and they don't know what that means.
It's some cells have some receptors at the surface, and

(15:51):
if they have those receptors, for example, estrogen receptors, progesterone receptors,
that means that it's a little bit easier to treat
those cells because you can use type of drugs that
are target for those receptors, which are called hormonal therapy drugs.
But triple negative breast cancer means that does not have

(16:13):
any of the receptor for hormonal therapy. So the only
way to treat this cancer if radiation is not effective,
is through chemotherapy, and it's really really hard to do.
Patient derived znograph models out of triple negative breast cancer.
So the idea of starting with this bread cancer is
specifically triple negative is because right now there is no

(16:36):
model that works well in the drug development process for
this cancer. So we are just not just tackling that
personal story, but tackling a real problem that is happening
right now with people using triple negative models for drug
development process.

Speaker 1 (16:54):
Yeah, so all of folks are your second product, I think, yes,
just recently launched. It was a long three detation model.
So again first of all, right, why like why was
launch your second product? And has any company been using
your lung models?

Speaker 2 (17:13):
Absolutely so, So the reason for going from our goal
is to stay with stiff cancers right now. So what
that means is stiff and on top of that high incident,
high mortality. So what that means is breass pro state
color rectal long as being the top one in terms

(17:34):
of mortality. So going from breast to long with that
with that mentality in mind, and on top of that,
we met two companies from Germany. So one is a
private company, the other one the research Institute, and together
they became all partners in the development of this no
small lung cancer tissue and the idea with this tissue

(17:57):
is to test their own therapeutics, so they are developed
detail therapy, so they're in the immal on collogy space
and testing that in our tissues with almost like the
perfect partnership to continue developing our tissue models but also
testing therapeutics. So this tissue has been developed due to
this collaboration, but it's also now commercially available.

Speaker 1 (18:22):
Yeah, so uh no, regarding just just in general, right, absolutely,
do you think like biotech startups are probably going to
save more money using your product than using animals because
a big issue the bout tech sector right now is
that you have all these startups right they raised one
hundred billion, three hundred million dollars, but then they keep

(18:44):
burning at a really fast rate to the point like
they're rather bankrupt, or they get acquired by some big
pharmaceutical So do you think this product to help a
lot of Baltic starups like survive or and even potentially
have their own products so they could grow.

Speaker 2 (19:01):
Absolutely. So our initial focus right now has been small
to medium farmer, So that means it's small companies that
are developing their therapeutucts and just looking for a better
platform to test that something that would indicate more of
a human like result. And I understand that we were
talking about the animal models should the gold standard, but
that doesn't it does not necessarily mean that we should

(19:25):
continue with that. We haveing a shift with the FDA
Modernization Act to get to a point where we are
getting we are decreasing animal models, not eliminating Act, but
decreasing animal models. So I would say, if someone has
a limited amount of money and resources to put into
a technology, VOX sales, TISH models would indicate efficacy and

(19:49):
information on self viability and the relationship between that thoseselves
with the drugs that you're tasking much more easily than
animal testing, and on top of that much faster. True.

Speaker 1 (20:02):
Yeah, and so you said said the STA right now,
So so US in Canada has something similar to it,
but maybe it's just me. So are they also on
board with with this this.

Speaker 2 (20:20):
Exactly? Yeah? So Canada had something an institution, it's called
Health Canada. So Health Canada follows the FDA regulations. So
everything that is happening in Canada is very closely related
to how we run things in the US. So, and
it's different than the EMA, which the European division. What
we see is the FDA Modernization Act two point zero,

(20:43):
that's the one that got approved in twenty twenty two,
that is the one that helped Canada is also trying
to follow. That is the one to not eliminate animal models,
but to find alternative in vitro testing. And in that
bill it was referred as AI models as an alternative
for example, but so as bioprinted tation models. So we

(21:05):
started seeing a lot more traction from people have to
recognize that bioprinted tstion models could be one of the
alternatives to tell the drugs. The EMA, which is the
European division. What we are seeing there is they are
a lot more proactive, i would say, into actually replacing

(21:26):
animal models. So they do have metric goals to replace
animal models completely. So so we having seen a lot
more traction with European companies than North American companies because
of that mentality of really trying to replace animal models completely.

Speaker 1 (21:45):
Yeah, I think the European side, and I think it's
I think UK as well. They allow like themselves, emb
reals to be used in research, but known America it's
not allowed, so many it's.

Speaker 2 (21:57):
Not allowed yeah, so there are different regulations according to
the regulatory body. Absolutely.

Speaker 1 (22:04):
Yeah, So I don't know. Your science is a pot field.
There's a lot of research into it, whether it's large,
it's large small companies or some some lab group. So
are you guys going to move also have like move
towards the brain more yes.

Speaker 2 (22:22):
So absolutely so. When when I was proposing my post
or proposals, they were all related to brain and to
get to a point where we are creating our ziomers
on a dish for example, So we are thinking from
a lot of farmace for companies. What we are doing
right now is engaging with the customers. We don't want

(22:43):
to create something that they don't want right we can.
We want to create something that is useful for them.
So we are letting almost these conversations with the farmer
companies to define what our next issue is going to
look like. And there has been a lot of conversations
right now around the brain and mimicking the brain, also
cardiac tissues, so so hard tissues has been a lot

(23:04):
of conversations around. So it seems like our focus for
twenty twenty five, on top of commercializing and really focus
on driving revenue is really defining what comes next. So
around brain cardiac that is what is looking like there
will be our next tissue models.

Speaker 1 (23:22):
Yeah, and a lock to that hut, you know, like
like like you said, you're trying to move into neuroscience
and cardiology, Like, do you think those two fields would
eventually like the tissues for those two fields, would they
be probably your most best selling product?

Speaker 2 (23:41):
It could be. Right now, brain is a very challenging
tissue to mimic, right, and also all the brain drugs
that have been approved, which are not many, they need
to cause their broad blame b aria, which is the
hard as far. So, I think the brain has a
very high potential to be one of our life hardest issues.
I would say, like the most interesting one, just because

(24:04):
there are no good models for brain right now, and
animals don't have Alzheimer's right, so we are inducing that
into the animals. So creating a model that could replace
that is definitely something that would make it very attractive
for us but also for potential customers.

Speaker 1 (24:22):
Yeah, well, what round are you guys in so.

Speaker 2 (24:25):
Right now, Voxell, it's four years and a half. We
just closed our steed two round and we are going
to be going for our series day very soon. So
so far in four years we have raised about around
ten point five million so far and so so Sery
day is what comes next.

Speaker 1 (24:47):
So how hard was it to get investments right? Like?

Speaker 2 (24:55):
I think at the beginning was harder to require honest
than it is now. Right now we have enough data,
we have a solid thing, We have a facility, like
people can come here and see our science is real.
But I think in the beginning when we were explaining
these two people was very science fiction explaining all we
are creating these three differnted issues. They have blood vessels.
So a lot of the people that have been with

(25:17):
me since the beginning, whether there is employees or investors,
it's because they truly believed or what I had in
my mind and we made the real. So especially like
early stage investors, those are people that are stew on
my board to today, and those are people that I
trust because seen they have invested in the company when

(25:39):
we were an idea and right now we are physical products.
So I would say it's getting easier over time. I'm
not saying the market conditions are getting easier, though, I
think market conditions are getting harder to raise money, But
it's getting easier to make investors understand the science and
understand the goal of Oxfel and physically show them a

(25:59):
sample and how it looks like.

Speaker 1 (26:02):
Yeah, so, by your investors in general, are they all
from Canada or are you also getting from the US
or maybe in Germany or something.

Speaker 2 (26:11):
Yeah, so right now I would say majority Canada and US,
so institutional investors mostly from Canada, and then we have
a few engine investors from the US. And we also
have Team Draper on our CAF table. So Team Draper
invested on VOXA. We weren't in the show called The

(26:33):
Drapers Associate, So Meet the Drapers that's the name of
the show. And we received the two hundred thousand dollars
US dollars investment from Team drapery, which is fascinating.

Speaker 1 (26:44):
Yeah, but you guys are ready to like approach the
VC firms in the.

Speaker 2 (26:49):
US, absolutely, And we're already raising money from vcs right now.
And we imagined our Series A round, which is a
larger round that is going to be mostly vcs. Yeah.

Speaker 1 (27:02):
Yeah. And you know, in box Cell, do you think
box Cell will become like IPO in the future or
do you think it's going to be acquired.

Speaker 2 (27:13):
Yeah. Yeah. Exit exit strategies for biotech companies are mostly
as you said, M and A, it's a merger and
axibition or IPO. I think baux Cell has a better
chance on an M and A kind of situation. And
of course the IDEO is the Holy Great So I
don't know what is going to happen, but we are
open to all the possibilities. Our goal, whether there is

(27:35):
an IPO or an m and A is to really
impact people's lives, to really make a difference with our technology,
so independence on the route we go. Our goal is
really to make an impact on the drug development process
and allow from a cetual conference to put those drugs
on the market sooner into the hands of people who
need them.

Speaker 1 (27:55):
Yeah. So as I don't know if you know, but
we've got stem Cell Technology CEO also one of all
these podcasts. Yeah, and all these companies pretty big in Canada.
They say they're the largest bollotech there. So regard like
Canada general, like is Baltic ceter is not as strong
as the US right now? So like what do you

(28:17):
think of some steps makes like Canada's bootech sector is
going to be stronger. Do you think the funding is needed, Like,
do you think there should be more like funding kind
of like what the US have, would the uh like
the funding from the government, Like so yeah, so.

Speaker 2 (28:35):
Let's let's just start start talking about Canada first. So
the biotech field is the largest growing field in Canada,
so we are definitely growing considerably. And British Columbia have
been one of the hubs for designs, so it's definitely
something that is growing considerably. What I think is missing
in Canada it's two things. First, as you mentioned, more

(28:58):
government encouragement, so basically more support from the government to
get this company's growing. What I see here is a
lot of support for the early stages where you don't
really know what you're doing. You need to get your
few brands in the beginning, but ideally what you want
is also support for that growth period. That is a

(29:19):
period that Boxer is right now, and I feel that
that is a gap right now. And then what leads
to my second point, which is investment. So you see
a lot of angel investing in Canada. It's really really strong,
but if you think about the VS and the large
VS checks, that is very very limited. So that's another

(29:40):
gap that they see in Canada right now is there's
a lot of support for when you're starting a company,
but not necessarily for that growth period and you need
more money on that area. So that's what makes companies
to go and go to the US to raise the
money because that is definitely a gap here in Canada.

Speaker 1 (29:59):
Yeah. And also what I discussed with the step Cell
Technology CEO two is like I don't know if you
noticed this, but there isn't like there's not as many
pharmaceuticals like lord, absolutely, yeah.

Speaker 2 (30:10):
Absolutely, yeah, yeah, yeah.

Speaker 1 (30:14):
So what he was saying was customers and also the
fact that like a lot of them get acquired by
US companies and yeah and then.

Speaker 2 (30:21):
Just moved, Yeah, just move. Yeah. Yeah. So retaining in Canada,
retaining that knowledge, keeping eating Canada, it's something that also
should be should be the focus. M Yeah.

Speaker 1 (30:32):
So man, yeah, so I know you also do some teaching,
so I'll just find your schedule. Is it really busy
for you because you have to teach a course and
then you have to run a company, right that's also
startup that's also getting more bigger, so like yeah, it's
a kind of like is there schedule kind of busy basically.

Speaker 2 (30:54):
Yeah, So my the way that I tell people right
now that I don't walk eight or four. I walk
to eight. So that's my schedule is four to eight.
So my day starts around four for thirty am. I
start by answering my emails early morning. Then I go
teach my classes, and then later in the afternoons when
I come to box and the continue running my day

(31:18):
and around them to eight pm. So that's my day.
The beauty of teaching together is doing this job is
a lot of the company hires were actually my students,
so those were people that I trained personally, and I
know they will come in here and they will grow
this company with me, And no one walks for me.

(31:38):
Everyone walks with me to grow this company. So that's
the beauty. And also the teaching keeps me up to
date on technologies that are also very important to box A,
So I think they go hand by hand. But it's
definitely a very busy life to say the list.

Speaker 1 (31:55):
Yeah, and and do you ever think of out like
maybe doing like starting your lab in your college right now,
like is that going to be a possibility? And maybe
after vox cell guess acquire or or becomes like it
or it goes up on the stock market. Do you

(32:16):
think that's going to be something if you're going to
pursue in the future.

Speaker 2 (32:19):
Absolutely. So my goal is teaching is something I love,
and I mean by teaching, not just teaching courses, for
teaching people in general and whether that is here a
voux Cell, teaching them about our technology, teaching them what
we are, why, what's the reason when we are doing though,
so amplifying that teaching ability is definitely something that I

(32:40):
have in mind for the future, whether that is with
the university, voux Cell, or another company, is definitely something
that I like to continue personally. Is the science, the research,
and the teaching aspect of it.

Speaker 1 (32:52):
Mm hmm yeah. So what advice did you received during
your career that shared your professional development or success?

Speaker 2 (32:59):
I would say especially when you're a young entrepreneur and
it's your first time doing that. So a lot of
people ask me in the beginning, like how many companies
have you founded in this is my first company, right,
so a lot of people are looking for more experience
in CEOs. But some of the advice that I received
from early investors is you just shake it off and

(33:20):
you do it again. Some days are going to be good,
some days they are going to be bad, and that's
what normalizes start up life. Some days are fantastic, some
days are really really bad, and sometimes it's all mixing
one day, but it's you bring some repeat and you
wake up tomorrow with the same attitude to advance science,
to advance this field of oncology, which is a field

(33:41):
that requires some advancement, and you just bring some repeat
and keep up the good work. And something that I
really live by is transparency. So that has been beneficial
to me since the beginning, and that's something that's who
I am, and that's something that I recommend to founders.
It's operating a very resparent way. Don't try to make

(34:02):
something look bigger than they actually is. Sell the vision,
sell the mission, but also sell the reality because the
reality is what they are invested in. Right now.

Speaker 1 (34:14):
Yeah, and I just all have a question. So your
your your training is a mechanical engineer, right, you don't
have this business degree or something. So so when you
so when you learn like the financial language, of course,
like was it like how like how hard was it was?

Speaker 2 (34:33):
It was? It wasn't too hard to befure honest, it
wasn't too hard. I think. I think from someone from
a technical field, like I am learning the business, it's
a little bit easier than going the other way around.
So for example, your very business focused, you're very heavy
focused technical field. So I don't think it was very hard.

(34:54):
But I also will say that I learned with the
practice right. It wasn't untue. I had to do it
that force need to learn the term. So I would
say in the beginning of box Cell, we really were
participating in a lot of like incubators programs and things
like that that really really helped to kind of split
up that learning and spit up not just the learning

(35:15):
but also practice and putting into practice into vox cell.

Speaker 1 (35:20):
About managing people, like, was that also something you had
to learn to.

Speaker 2 (35:25):
Managing people is too I would say the hardest part
of any job, it is managing the difference personality. It's
something that I learned in the beginning, which was really
interesting because I did not know that is you we
hire a lot of engineers, for example, and in paper
they all have the background that you need, but the

(35:46):
reality is in practice some of them are a lot
more feed For larger companies, best the startup, and that's
something that I'm learning in the beginning that is not
every engineer is a fit for voux Cell, for example,
because so it's growing, it's evolving, things are changing, Priorities
are changing. So walking with people that can handle those

(36:07):
shifts in priority is something that is very important, which
is not very common in a well established company where
you have the setup and you have procedures and you
have everything is in a pipeline of development. In our
case here, things are changing, So having to work with
people that have that personality, that are flexible with those changes,

(36:30):
it's very very important.

Speaker 1 (36:31):
Yeah, and I think also discussing some other scientists people
that there's also like the drive right a startups.

Speaker 2 (36:39):
Oh absolutely, in the science, we can teach all the science,
but we can't. I always say this, we can't teach
the science, but we cannot teach attitude. So having the
correct attitude is something that is very important for our startup.
And part of that attitude is drive. Because you are
wearing multiple hats the startup. You're doing your job, but

(37:01):
you're also helping here and there, and that comes with drive.
Drives is really really important.

Speaker 1 (37:08):
Yeah, and also it's more like the form of student calls. Right,
they're so largely have so much money, right, so it
doesn't quite matter. But for someone like you're working a startup,
Yes we raised ten million, but that's gonna like dry
up pretty fast, right.

Speaker 2 (37:22):
Absolutely, and you're not. When we hire someone, every team
member has a purpose, so they're not just a number.
They are someone that we really want in here, and
it has a purpose to be here and has an
expertise and has an ownership on that expertise. So it's
a very thoughtful process in hiring someone.

Speaker 1 (37:42):
Yeah, so yeah, thank you very much for being on here. Yeah,
I think I think I also learned a law and
I think my audience as Welso, thank you very much.

Speaker 2 (37:53):
Thank you Karen for having me. It's a plisure to
be here.

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