From Research to Reality with Cici Muldoon

In this episode of Oxford+, host Susannah de Jager is joined by guest Cici Muldoon, the founder and CEO of Veritie Group as they touch on the intersection of science and society, the role of entrepreneurship, and the need for support and funding in the startup ecosystem.

They also discuss the challenges that Cici faced in setting up her company and the importance of integrity and transparency in scientific research. Cici also emphasises the significance of making a positive impact and leaving a legacy through scientific innovation.

(0:12) Introduction
(1:13) Founding Veritie Group
(6:31) Pivoting to medical diagnostics
(13:26) Challenges in the startup ecosystem
(27:47) Audience Q&A

About the guest:
Cici Muldoon is the founder and CEO of Veritie Group, an Oxford-based technology company specialising in the spectroscopic analysis of highly complex dilute liquids. Cici holds a degree in physics and finance from Princeton University, and a doctorate in experimental atomic and laser physics from Oxford University. She is also a qualified Oenophile, an amateur ballerina and a classic car judge.

Connect with Cici on LinkedIn

About the host:
Susannah de Jager is a seasoned professional with over 15 years of experience in UK asset management. She has worked closely with industry experts, entrepreneurs, and government officials to shape the conversation around domestic scale-up capital.

Connect with Susannah on LinkedIn

Visit our website to learn more and subscribe to our newsletter - oxfordplus.co.uk
If you have a question for Susannah, please get in touch - oxfordplus.co.uk/contact

Oxford+ is hosted by Susannah de Jager, supported by Mischon de Reya and produced and edited by Story Ninety-Four in Oxford.

Creators & Guests

Host

Susannah de Jager

Founder & Host of Oxford+

Producer

Matt Eastland-Jones

Founder & Producer at Story Ninety-Four

Editor

Nick Short

Podcast Producer & Audio Technician at Story Ninety-Four

What is Oxford+?

Welcome to Oxford+, the podcast series that explores the myths and truths of the Oxford investing landscape hosted by Susannah de Jager. Since moving to Oxford, Susannah has collaborated with experts, entrepreneurs, and government to shape the conversation around domestic scale-up capital. Oxford+ aims to inform, inspire, and connect. We'll talk to Founders, investors, academics, politicians, and facilitators and explore how Oxford is open for business.

Welcome to this episode of Oxford+.

This episode was recorded in front of a
live studio audience at Modern Art Oxford.

My guest is Cici Muldoon.

Cici holds a degree in physics and
finance from Princeton University and

a doctorate in experimental atomic and
laser physics from Oxford University.

Cici is the founder and CEO of Verity
Group, an Oxford based technology

company specialising in the spectroscopic
analysis of highly complex dilute liquids.

Verity Group is currently creating a
low cost, easy to use point of care

solution that uses a simple urine
sample to identify cancer and other

illnesses as early as possible.

A qualified Oenophile, Cici has
completed the bachelor level WSET

Diploma in Wines and Spirits.

She's also an amateur ballerina
and a classic car judge focusing

on the Ferrari mark and judging
at numerous international events.

Cici speaks five languages and is
originally from Guadalajara, Mexico.

Cici, thank you for
joining us this evening.

So I've described your company Verity,
but you've actually founded two companies

with this particular technology.

Can you tell us a little
bit about the first one?

Because I feel like it's interesting.

Yes, absolutely.

So basically I have gone in life
a circuitous route via quantum

computing in my PhD to analysing
wine, to analysing urine.

Basically, the reason for that was
I specialised in the interaction

of matter and light in my PhD, and
it's still a huge passion for me.

It's fascinating what happens when light
interacts with molecules, with atoms.

I ended up working in spectroscopy
post PhD briefly, and one day on the

way to work, I had this question pop
into my head, which was, why don't we

use spectroscopy, which is essentially
the study of matter with light to

look for cork taint in unopened
bottles of wine and the small niggling

thing became an obsession of mine.

So, I used to run the wine club
at Oxford when I did my PhD.

I was captain of the blind tasting team,
so queen of the nerds, and I have a

particularly sensitive nose to cork taint.

Which is actually a very small
innocuous little molecule called

2,4,6-trichloroanisole, which actually
blocks a neural pathway in your brain

and makes you smell wet dog basement and
disgustingness in wine and it ruins many

bottles and You don't know when you're
going to get it and I thought to myself,

well, it would be fantastic, why can't
we test it without taking the cork out?

So me being a little bit crazy, I
ended up actually starting a company.

Some of the people in this room, knew me
back then and I was the crazy wine lady

that went around Oxford and I figured
out at that point, I'd done the research,

that Raman spectroscopy was the way to
go, this technique, which, Actually, it's

quite old, so it's a technique that was
developed in 1923, discovered by a man

called Chandrasekhara Raman, who was the
first Asian Nobel Prize in Physics, 1928.

So that's how old we're talking, right?

This stuff has been used
since the 80s and 90s.

It's a workhorse in pharma, in airport
security, in defense, it's how they

identify stuff and I'd figured out that
Raman spectroscopy was a great way to

look at aqueous complex mixtures and so
off I went, basically to cut short so

that you can ask me another question,
off I went and I tried to get this

company off the ground and it was really
difficult because, what I was proposing

to do was do R&D in industry, right?

And so a lot of the answer I got was go
do a postdoc, because basically it's not

the spectroscopy that was the problem,
it was the fact that there's a dark,

curved, tinted piece of glass in between
what you want to see and analyse and

your spectrometer and basically I ended
up doing something that is, for many

years I was highly embarrassed about,
but it's very unconventional, which

is that I ended up funding it myself
and the reason for that was because I

had applied for an Innovate UK grant
with my then PhD supervisor, who didn't

think I was crazy, and we won the award.

But, as for many cases, we
didn't have the cash flow.

So the project start date was
ticking forward, and I found

myself saying, well, now what?

I was speaking to a lot of people, but
all the VCs said, too much technical risk,

you know, too early doors, all this, that,
the other and finally, we had a Christmas

dinner with my PhD supervisor and my
family was around and my dad just turned

around and said, for God's sake, let's
just fund it ourselves and so we did.

So I'm a little bit of a black sheep and
an exception, I realise in this startup

world, but it is a very difficult journey.

I know this is not the question
you asked me, but it is a really

difficult thing to get something
that is brave out there and prove it.

We did do that, five
years on Verovin worked.

We were analysing bottles of wine through
the glass and correctly classifying

them using machine learning and we could
distinguish down to different chateaus,

vintages, but we had three problems.

Problem one, the wine industry
is a very heterogeneous one.

So you've got people with big pockets at
the bottom that wanted to do thousands

of bottles per minute on a bottling
line, the producers, we couldn't do that.

The machine just doesn't work that way.

Top end, we had people that wanted a
really cheap, portable machine that you

could use one on one, the merchants and
we couldn't service everybody easily.

It was a very complicated business
model for a very heterogeneous industry.

Two, the fine wine industry, which is
where our business case really was,

actually doesn't want to know that
there's a problem, because our main

business case was we can weed out fake
and faulty, particularly counterfeit wine.

So we would train the algorithm and we
would say, here's a bottle of Lafite 85,

52 percent Cabernet Sauvignon, 48 percent
Merlot, metadata, metadata, metadata.

Here's a hundred mystery bottles.

Do they all cluster together?

Do they not?

And sometimes they wouldn't, and the
fine wine industry was our main goal

because we thought, well, they want to
know that they've got lots of fake wine.

Well, it turned out they didn't.

So we built a fantastic technology
solution platform consisting of hardware,

software, machine learning, much overused
term, but it is a real thing and it's not

magic, for a customer that didn't want it.

And the third problem we
had was a physics problem.

It was that we could only see through 70
percent of the bottles that we tested.

30 percent of the time, and it
wasn't predictable which 30%, the

spectrometry would just get nothing out.

So we turned around and
said, you know what?

In this journey, we have tested all
manner of highly complex dilute liquids.

We tested olive oil, injectables, manuka
honey, perfume and our chairman, Steve

Davies, turned around to me and said,
you've never wanted to look at blood

and I said, no, quite frankly, no,
because I don't want to be Liz Holmes.

I mean, I already get the Theranos
comparison all the time, but it planted

the seed and off we went and we started
looking into blood and soon thereafter,

we sort of tripped upon a bunch of
literature where people were using a

variant of Raman Spectroscopy called
Surface Enhanced Raman Spectroscopy, which

is a little bit more complicated, but same
idea and machine learning, emboldened by

machine learning, because this is what's
happening to these, you know, old tools

in physics that are being emboldened by
machine learning and they were correctly

classifying urine as disease, non disease
and there are papers all over the world,

academic institutions, mainly, most
of them in the US, China, South Korea,

but everywhere and they're looking
at pancreatic cancer versus prostate

cancer, they're looking at hematuria,
they're looking at UTIs, they're looking

at gestational diabetes, you name
it, people are using this technique.

But it's all in academia.

Pre-eclampsia is another one, which is a
project that we're quite passionate about

and we turned around and said, well, we've
got this platform that we built for wine.

Wine, 85 percent water, 12-14 percent
ethanol, 1%, 1, 000 different organic

molecules, which kind of all look alike.

Urine?

You know, 90 percent water and then
lots of little organic molecules that

all look alike, and we were like, yeah,
they're actually not that different

and at the end of the day, that's
the real beauty of the technique,

is that it doesn't really care what
liquid it's looking at, what biofluid,

it can be plasma, it can be saliva.

The machine itself doesn't care, right?

And the algorithm doesn't care
what metadata it's getting.

It doesn't care if it's looking for cancer
of the left nostril because all you're

doing is you're telling the machine,
this is the metadata, learn on this.

It's really interesting, thank you, and
the people it does matter to, and I know

this cause I've looked on your website,
we've spoken about it, we've spoken

about the values within your company.

Those are hugely different applications
and one of them has a sort of an impact

and a legacy, which I know is something
you're really passionate about and

the other, quite frankly, it's very
important to my own palate, but as you

have pointed out, and indeed the industry
pointed out, perhaps less required by

society, if I were to put it that way.

How do you feel it's different now
that you're setting up a company

that has those different qualities
in terms of its application and

their importance in society?

I mean, it is for me, it has been
a transformational two years.

It's been about two years since we
decided to pivot and I know it sounds

like a bit grandiose and exaggeration,
but I feel like I found my calling

in life, because my passion is for
taking science out of the lab, like

I want to take this great tool.

I see, like, these two
worlds waiting to collide.

There's sort of the world of spectroscopy
over here, with all the tools, and

there's, like, the biotech, biomed
world and they're just waiting, I think.

So our goal is we want to displace wet
chemistry with advanced photonics and

machine learning, because most things
nowadays, when you get a diagnosis,

most of us in this room will have been
touched by IVD and vitro diagnosis

at some point in our lives, we have
something diagnosed and it'll be

either imaging or most likely a blood
test, which means full venous blood

sample, which hurts, requires a trained
phlebotomist, is expensive, and then

moreover that sample has to be transported
to a lab to be tested in a lab.

So all of that process is expensive.

It's a weight on the healthcare
system where there is one.

It's costly in different ways for
patient, payer and the physician.

So we see that these two worlds
coming together are a huge

opportunity and for me, it's a
personal passion to take science out.

However, that said, obviously, you know,
getting behind saving lives versus saving

fake wine, you know, saving someone
from drinking fake wine, absolutely,

but with it comes huge responsibility
and that's where the values come in

because me telling you that your wine
is plonk, whatever, but if I tell you

that, you know, if I'm going to enable,
have a technology that's going to enable

a doctor to give an earlier diagnosis
of whatever disease state it is that

we might be looking at, and we do
have focus areas by the way, but it's

something that I feel ethically very
responsible for and if anything, I think

the experience of Elizabeth Holmes, whom
I kind of, you know, through suppliers

and through sort of personal connections,
I sort of knew closely about, it just

puts a huge shining light on the fact
that science needs to be vetted, right?

So one of our values is integrity.

So, complete intellectual honesty.

The science doesn't lie, and you
don't lie about what the science says.

I mean, everyone at work
knows this and says it.

Because when I did my PhD,
I did an experiment where we

were trapping single atoms.

We were meant to trap single atoms,
move them around to implement a quantum

bit and I got to a point where I had
built this experiment from scratch

myself, and I trapped 1.5 atoms.

I did all the calculations back and I got
to 1.5, and I went to Axel, my supervisor,

and I said, can I round down to one?

And he said, Cici, what does 1.5 round to?

Two.

And that's what we published.

But for all intents and purposes, had
I gone in that paper and written one

atom, who's gonna come and recreate that
experiment, quantum optics, with all of

the vacuum chamber and the optics and the
electronics, and tell me that I was wrong?

So science, scientists have a huge
responsibility to be ethical and to

be transparent and to communicate.

I, you know, I try to explain
to people when they ask me, I

say, do you have five minutes?

Because I'll explain Raman Spectroscopy,
I feel more comfortable if you do.

So that's one of them.

The other one we have is legacy, you know,
I want to make a difference with this.

I do believe it can actually really
help in healthcare and I haven't

drunk the Kool Aid, I just believe
in, you know, it's profit driven

philanthropy, right, in some way.

It's doing some good, and then
commitment, because it requires

a huge amount of commitment.

We're now a team of 16 people
who I'm immensely proud of.

One of them's in the audience.

They are all really talented and
actually much more accomplished than me.

You know, there's a guy that used to
run Point of Care at John Radcliffe, you

know, somebody who is CFO of Siemens who's
sitting in the audience somewhere, you

know, very talented people and I feel that
they need to all be committed to make this

happen together to get it somewhere and
then the last value, courage, because it

takes a huge amount of guts to go up there
and say, there is no pattern recognition

based medical device on the market yet.

Going to regulation, 510k, CAC
mark, is a massive journey.

Just getting samples, you know,
that's, we've got a fully functional

lab now that can handle, store,
thaw, freeze, and test with our tech,

human disease, human urine samples.

But sourcing those samples
is massively difficult.

So, you know, the whole undertaking
is so titanic that without courage and

commitment, we wouldn't be able to do it.

We've spoken a bit about this, but you've
just referenced a few of them through

the conversation already, you know, the
lab space that you've got, it wasn't just

there, ready, waiting, and I'm sure lots
of people will be familiar with this, but

it had to be built, it had to be built
bespoke, it had to be made, you wrote

your own patent, you had the experience
of people not kind of supporting the

first application of your technology.

Every time I speak to you, I feel like
there's another reason that lesser

people probably would have given up
and on the one hand, that's kudos

to you, on the other hand, if we're
looking at the ecosystem, there is

that question mark of, oh God, how do
we make sure that more people can sort

of slip through the proverbial net?

And I'd be really interested to hear
your perspectives on perhaps some of the

things that you found difficult that you
just don't think needed to be, and that

actually the university or the ecosystem
could have been there either kind of

supporting physically or with kind of
lab space or with money, and I don't

know if there's anything obvious to you?

I mean, the thing is I had a
generation, I think, the current

generation has a lot more support.

I think there's a lot
more going on from...

That's reassuring.

So, no, no, I mean, 'cause when
I first tried to set VeriVin up,

we were talking around 2017 was
when I was going around trying...

Not that long ago.

Not that long ago, but the
idea came much earlier.

I then went off and did the WSET
diploma 'cause I basically could,

I didn't know how to start.

I was like, you know, what do I do first?

And how do you know?

And how do I...?

That in itself is
something I keep hearing.

It's like people almost don't, you
know, obviously we've got incubators,

accelerators, but there needs to be more
of a road map almost, like, where are you?

Are you at idea stage?

Are you at needing funding stage?

Are you needing this?

And just helping people with great ideas.

I mean with entrepreneurship, and I've
only, this is my second time doing

something, obviously, so it's not like
I speak from great experience, but we

have a saying in Spanish that says,
"Andando se hace camino", which means,

walking you make the way and I think in
some ways you just gotta go through it

and learn from it, you know, there isn't
a perfect magic, you know, equation.

I do think, you know, we
could improve probably the

funding in the ecosystem a bit.

When I was trying to get VeriVin off
the ground, I did go eventually to the

incubator, to OUI and OUI suggested some
really useful things, which was to apply

for Innovate UK grant money and then
they suggested some that weren't quite

right, like go to VCs, for whom this
was too much of a technical risk and we

had one particular VC who reviewed the
tech and they misunderstood a conceptual

thing about how we look at spectra.

So basically when we get our spectra
from via wine, urine, whatever.

We get the combined Raman Spectrum of
all those thousand molecules kind of

multiplied together and it's not like
you can un multiply them and unpick them,

because essentially what's happening
is you're shining all this light in,

all these molecules are, for a period
of time, bouncing their photons off

in their own way, each of them will
give a chemical signature of their own

and all those photons are traveling
together to the detector, right?

So it's not like you can unpick this
one that came from there or there.

You separate them by frequency, which is
something called a diffraction grading,

they land on the detector, and you can't
un-multiply where they came from, right?

So what we do is, instead of trying to
unpick them and look at single biomarkers

or single molecules, we look at an
ensemble of them, and we use machine

learning to basically do a mathematical
expression for this group of things.

Point being that this person had
understood that the photon from

one molecule would basically
affect the next molecule.

He thought it was like a linear addition
and when they sent me their sort of review

of the points, it was like, green, green,
green, and then it was red on the tech.

But it was red on the tech for reasons
that were like, he misunderstood physics

and the problem I had is that then,
I have heard that person then spoke

to another VC, that we all, and then
spoke to another one and then I heard

it from OUI, that, you know, so it was
okay, like, all these conversations have

gone on and nobody, like, came to me.

Validated it.

Yeah, but look, it's really
difficult with these things.

I understand them because they're
being asked to invest in stuff that is

so out there, like quantum computing.

If you asked me if I would invest
in a quantum computing company,

I'd be like, ciao baby, no way, no,
like, and I did a PhD in it, right?

And I think people just
don't understand it at all.

I mean, people use these terms like
AI or machine learning or, you know,

quantum computing, and they have
not the first clue what a photon is.

How can you possibly understand
what quantum bit is if you don't...

So then taking that, you know, something
that one has seen for instance,

in Cambridge with R and Capital
is that they have real brilliant

scientists, you know, Nobel laureates.

I was joking on a previous podcast
and we were saying, you know,

casually have a few Nobel laureates.

But I have heard in various interviews
I've done about this thing of, you

know, you do need the experts in
the room, you do need people that

understand what they're looking at.

It's a tricky dynamic because you
can't have the depth in everything.

I've also heard people say, well, I've got
a PhD in physics, but you know, actually

I look over here and it's not in my
wheelhouse and so nobody's ever going to

be an expert in everything, but I think
your point is really valid and how can

we supplement what's there to improve it?

Scientists be better communicators,
genuinely, I think, I do, because I think,

I mean, we did this, we practiced pitch
to somebody in London yesterday and of

course it's a really valid point that
all the people putting money in care

about at the end of the day is what's
the sensitivity and specificity of the

test and does it exceed the predicate
test that you're going up against.

Yes, of course, proof needs to be in
the pudding and of course they care

that the machine learning is correct
and the spectrometer works, yes.

But they care about the end result.

However, I would personally feel
uncomfortable investing in something that

I didn't at least kind of understand.

So, I think scientists often just go like
this and they go, it's really difficult,

you're not gonna, it's arrogance, you
won't be able to understand and actually,

if you as a scientist got out of your
way to explain it in layman's terms, you

understand it better, and that person
then probably feels more confidence.

I mean, you described something else,
which, you know, I think is a danger in

any group of investors, and I've seen
it coming from a slightly different

background myself, but, which is just
groupthink to a degree, where people

sort of are relying upon one another
to corroborate things and create,

hopefully, kind of rolling balls
gathering moss on the positive, but it

has this danger that you've identified
on the other side, which is something

can be written off, and then written
off by more people, because it's...

Yeah, I mean, to be fair, I do ask, I
have tried to put myself in the shoes of

somebody running a fund and thinking...

Limited time?

Well, you know, it's like it's on you
and like, yes, it's, you know, it's

somebody else's money, first there's
a responsibility there and you don't

want to be the first and I totally
get why they don't because it's like,

well, okay, but somebody else has
gone and then it's kind of derailed.

It's gambling, right?

It's, we're all in a casino gambling
on whether something's going to work

or not and I'm not ignorant to the
fact that one in 10 startups fail.

So, yeah, of course there's
groupthink and I think it's, in

some ways it's unavoidable that if
you're in an ecosystem, you will

have groupthink to a certain degree.

But it's important to reach
out and actually, like, open

your eyes to the wide world.

Yeah.

At some point when VeriVin was flailing
and I got very distracted doing car

stuff, I also started a small angel
syndicate, and I wanted to expose the

Oxford ecosystem to foreign investors.

I have a lot of contacts in, I'm Mexican
by the way, I'm not American, but in the

States I've got a lot of contacts, and
I thought there should be some brilliant

people that would be very interested in
the Oxford ecosystem, back when there

was lots of money floating around.

And, you know, I didn't have the
time to do it in the end, but I do

think that we would benefit in Oxford
from perhaps a bit more openness...

Diversity.

Yeah, diversity.

It's really interesting to hear you say
that and funny enough, you know, I was

just circling something down here, which
I don't know if you would agree with this,

but, you know, you were saying how, much
of a moonshot so many of these things are,

and yet, we all agree that they're in the
public interest for money to be put into

them, and it does seem, and in fairness,
you know, there are government grants and

funds for these things, but perhaps not at
the scale that, certainly not at the scale

that the U.S has, where you know, everyone
seems to have forgotten that Silicon

Valley is a major defense project that's
ongoing, you know, they pump millions, and

by the way, you know, the IRA that they've
announced is 365 billion that they're

just gonna pump in because of inflation.

But, you know, there's so much money
going in from the state, and yet, in

my own experience here, these are sort
of public goods and yet the government

is like, it's a private sector issue.

We don't want to put money into this,
it's not ours to fix and it does seem

to me that there's a call for money that
isn't just chasing that return and that

is a bit more kind of community focused
on things like what you're doing now.

I completely agree because there is...

So there's a fundamental mismatch in
incentives between the people who fund,

you know, and it's obvious, right?

I mean, because it's all big Ponzi
scheme because you're waiting until, you

know, when you can flip it so that your
portfolio value goes up and you make your

commission and then it goes to somebody
else and it gets sold on to somebody else.

Nobody actually cares whether the damn
thing works at the end of the day, right?

They care about whether they
make their money out and

that's totally understandable.

There are some people that need to do
that and, you know, in this world, but if

you want to do like proper philanthropy?

Well, yes, then it has to be government,
I suppose, there'd be no other way,

Yeah.

So in terms of your investors that you
have now, again, for the size and the

scale that you're at already and the
business, you've actually got quite

an unusual cap table now, because...

yes.

Tell us more.

Cici's laughing by the
way for anyone listening.

Well, no, I'm laughing because I've
basically, the gist of it is we've

got, our cap table is very small.

I mean, without having to divulge
a bit, but we've got, our chairman,

who's invested personally,
another private American investor

who's invested personally, OUI
strong there, and my family.

So, I've put my money where my mouth is
and the way I like to put it to people

is, so basically, getting the tech up
to where it is to date, and I include

VeriVin and its pivot or failure, see
how you will, we did it with 3.5 million

all in so far, which is a shoestring,
and it's because when we were doing all

the R&D for VeriVin, if we had, like,
a 3D printer that broke, it would go

back to Amazon, and I'd be like, get
a return, because it was my money.

So it's kind of, it's a
very different feeling.

Because I'm sitting there
going, like, let's be honest,

I'm spending my inheritance.

Yeah, so it's just very different.

It's really interesting because,
you know, I asked earlier and,

tragically, you didn't have an answer
for me to this question, but, you

know, what could be improved to let
more people slip through the net?

But again, we're kind of talking about
that attitude that you have that embeds

through the company, that it's your
money and that you care about it and

that you have this value, this integrity,
this commitment to everything you're

doing and you want to create a legacy,
which arguably is your inheritance.

But, and just that whole kind of
owner mindset, not just founder

mindset, but owner founder mindset.

I've spoken to quite a lot of people
that have said, you know, there's a real

risk with taking on external capital,
that people, the first thing they want

to do is sort of pull out the exec team,
you know, and they change a lot of that

and on the flip side, I've heard a kind
of, you know, opinions obviously vary

on this, but people saying that often
is because people are looking for the

playbook, they want to flip it, they
want to get it out of the portfolio

because that's what it's gone into and
that there's less ambition attached

to that whole model because they're
not trying to build something larger.

So in terms taking outside
external funding, right?

It gives you external validation, which is
really important and then from a personal

perspective, it de-risks the thing.

But your point about the team
being artificially inserted,

that's an Oxford problem I see.

This is just my personal opinion, but
I think what happens often, which is

the disconnect and where things go
wrong, is you have brilliant academic,

fantastic idea, go to OUI, sort out, go
to OSC, set everything up, external team

gets put in and that CEO will not have
necessarily the depth of knowledge about

the tech or the passion to drive it and
so there's a little bit of a disconnect

there and then I've seen often that can
lead to, for example, the text starts

not working and it doesn't percolate
through and then by the time that like

the person that comes in that goes,
what the hell this thing is like, you

know, it's makes it more disconnected.

So I don't know if there could be
any way to bridge that gap more.

I don't know.

I agree with that, by the way, I think
that's valid and I think that from

your perspective, I wouldn't have that
perspective, but something else that

one thinks if you're thinking bigger
and you're thinking kind of UK PLC

Oxford ecosystem, it's just bad for
the ecosystem if things aren't being

grown by the people that want to make
them larger or as large as they can be,

that have that ambition beyond a sort
of five year exit and when I was doing

Boost, which was alluded to earlier, we
did a lot of interviews as part of the

kind of consultation and this ambition
gap between the US and the UK, but also

just full stop really came through.

and I think that for Oxford itself, it's
something that we could be more ambitious

and I don't know, I mean, in terms of
Oxford itself, how was your experience?

Because, you know, you've got some
areas that you clearly weren't

hugely helpful, and others that
you're hugely positive about.

I mean, I personally, I,
look, I live here as a choice.

I live in Oxfordshire now, in Coombe.

But, I love my alma mater.

If I'm honest, I don't have
any passion for Princeton.

Princeton was a great education,
undergraduate education, but I'm

not really, like, brouhaha, but,
whereas Oxford, I really genuinely

feel like it made me who I am, my
PhD, and I love the university with

all its quirks and its bureaucracies
and its administrative delays.

I actually really, I really love Oxford.

I think, you know, and I think, you
know, what was good, I did get support

and I think it's a tough one, right?

We're not the US.

We're a small little island, like
we don't have the funds and all our

companies go list in the States.

You know, I mean, like, all our IP flows
that way, so it's almost like I can

understand why the university's kind
of like, no, because, it just all goes.

Yeah, I don't, I really
don't know, I don't have the

answer to what you could do.

Get more people to stay here.

Yeah.

Keep them here.

Cici, thank you so much.

This has been a wonderful conversation.

I am now going to throw it out
to the crowd and see if there

are any questions that anyone
particularly wanted to ask Cici.

Sorry, I'm Adam.

I was there with Cici at the beginning.

Building on your point, yes, a lot of our,
alma maters, alumni go off to the States.

We're not particularly good at keeping
our successful entrepreneurs in Oxford.

So what could we be doing differently
to encourage them to come back?

Go for a second or third or fourth
time like you see in America.

I don't know, because I've never
made it and gone to the States yet.

Ask me when I make it, Adam!

Speak to the, AIM market and improve it.

Make it cost less to list here.

I think she's answered your question.

I could give you a longer
list if you'd like?

No, I think we really need a recycling
of talent and you talked about it earlier

because you were saying that you weren't
speaking to somebody that understood the

tech and one of the virtues of the US
system is that so often entrepreneurs are

the ones that are reinvesting and it's
such a positive loop and so the answer

is there's lots of things that we should
be doing to encourage people to stay

here, to come back here perhaps, we need
really good HQs in Oxford that we get

tax subsidies to encourage them to put
them here, we need pension fund money,

that's my big drum that I bang all the
time, there is movement, it's just...

Can I speak?

So I'm not, this is obviously I'm
not a finance person when I say the

finance bit I did at Princeton was
like financial modeling, like Black

Scholes Equation stuff, not real.

But what I always think is, how in the
world is it that there's so many ultra

high net worth out there with like, who
look for, like, I know a guy in London

who's sole job it is to find super
billionaires ways to spend what they no

longer know how to, they like, they've
got everything and you think with all

that money, like, why can we not redirect?

This is such a naive physicist thing
to say, but I'm like, why can't we

redirect some of this stuff, you know?

And yeah, you could say all sorts
of things about taxes and I don't

know, perhaps, okay, that's one.

Maybe there should be more
kind of family office or super

angel investment looked at.

Yeah, and I think Oxford could do a lot
to welcome in family offices, sovereign

wealth funds, to really create a pipe
that comes in here and says, you know,

you're so welcome, we're going to lay
out the red carpet for you, we're so

excited to have you here and somebody
said something wonderful to me today, that

apparently Irene Tracy describes Oxford
as a federation, and she's not CEO of

a single corporation and I think that's
such a good point because it is lots of

little parts that make up the whole and
therefore it is unwieldy but, you know,

part of the aim of this podcast, and not
to sound too grandiose, is to have these

conversations in the public domain because
most of them aren't insurmountable.

It's just an attitude shift that we can do
something differently and that's what kind

of, you know, not quite gets me out of bed
in the morning but I think it's exciting.

We can move the needle on this
and particularly, you know, as you

start smaller and then build from
there, it's something we can do.

But I mean, and also let's not be totally
negative because the UK is, you know,

they have championed quantum tech.

They are championing machine learning.

Innovate UK is a great tool, it really is.

I mean, it like, and there's a lot of
grant funding out there and there's

a lot you can do and R&D tax credits
are really good, I mean, they've

helped us, so it's not all bad.

SEIs, exactly.

not all bad.

It's not all bad.

Okay, well listen, thank you so much.

You've been very patient with us.

Yeah.

Thanks for listening to this
episode of Oxford+, presented

by me, Susannah de Jager.

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