Hello and

welcome to this special episode of the CORDIScovery Podcast.

Today we're going to dive into some exciting innovations in health

research that could transform the way we prevent, diagnose, and treat disease.

We'll learn about efforts to make injections needle free.

New diagnostic tools and therapies for heart

conditions like arrhythmias and atrial fibrillation.

How wearable technologies are being harnessed to detect

life threatening conditions such as sepsis

and the influence of urban environments on our health.

I'm joined by representatives of five projects

that have received funding from the EU Horizon Europe program.

And these projects showcase how research can improve

lives and reshape healthcare for the future.

So a warm welcome to David Fernandez

Rivas from the BuBble Gun project.

Professor Stéphane Hatem, representing the project MAESTRIA, Doctor

Bruno Miranda, from the eMotional Cities project.

Doctor Andreu Climent, CEO of Corify Care, and Christoforos

Panteli from the Project SepsISensoR.

So, David, let me start with the BuBble Gun project.

Your project aims to develop needle-free methods to inject liquids.

What are the advantages in terms of patients wellbeing,

security and waste reduction?

Right.

Well, the main aspect, the environmental aspect that you are just mentioning,

we use too many needles and we are then on a quest to reduce the number

of treatments that require a needle because we generate a lot of waste.

The next, important, aspect of our technology is that

it can be personalized because we inject tiny droplets

in the very superficial layers of skin, and then we can do it in a very,

specific way that you receive only the doses that you require.

Okay. And how do patients feel about that?

Well, we haven't done yet test with living subjects.

We have done mostly laboratory tests.

The hypothesis is that it's so superficial that you never touch

the nervous system terminations that give the signal of pain.

And it also happens so fast

in such a small volume that you should not feel anything.

Okay.

And can you describe to us in relatively simple terms

what is the science behind this innovation?

The science begins by using very affordable lasers

now, diode lasers, everybody now has it in their lamps at home.

But a few years ago, it was still, you know, emerging technology.

So, we use that as an energy source to set the liquid in motion

by a phenomenon known as cavitation.

So, we make simply bubbles.

And that's why BuBble Gun and then the liquid travels at velocities

high enough

that it can make its way in between the space of the cells in your skin.

And why is now the right time for this?

Why hasn't this been possible before?

It's a combination of different factors.

The environmental element became clear during the pandemics.

The amount of waste that is generated with each injection,

because you have to imagine, is also the plastic, the metal,

manufacturing, sterilizing it, bringing it to the place of application.

And afterwards you cannot just simply throw it away.

You need to process it properly.

And, it's

a combination also of the knowledge we have, at the University of Trent,

in my experience in microfluidics and the emergence of new technology

like diode lasers

that make this whole combination of factors, into a portable device,

which is now, what we are working for the next steps.

Okay.

Thanks very much, David.

If I could turn to you, Stephan.

Your project aims to develop new diagnostic

tools and therapies for atrial fibrillation.

How big a health problem is that in Europe today?

It's a very big health problem because, first, atrial fibrillation’s

prevalence is increasing with the overall aging of the population, the lifestyles.

We anticipate an epidemic of atrial fibrillation.

And it's at the same time the first cause of stroke,

cardiac cause of stroke and heart failure.

So, it's a major health problem.

And today the difficulty is to better identify patients at risk.

When you have a first episode of AF, who's going to have a second episode of AF?

How much you are exposed to a risk of stroke?

And so, there's

difficulty today

to predict these two parameters.

So, we have created a digital tool

which is accessible for clinicians.

And this digital tool is using your models

that we have created using machine-learning approach.

And this model is using clinical parameters that you can obtain

during routine practice, CT scan,

echo, electrocardiogram.

So, the clinician, by connecting to this server,

get access to this model

and can obtain for each patient the prediction risk, such as what we call

now, the personalized medicine for a patient.

And how widely used is this digital platform right now?

Well, we are in the phase where we need to validate

this platform, to make it popular, to make it knowledgeable.

So, we have developed a cohort of patients with a number of investigators

throughout Europe, and we are going to validate with them

the use of this platform before extending the use to a larger audience.

And how, how is the

collaboration going with the different, stakeholders in the project?

So you have the clinicians as you described,

you have the patients, presumably you're working with industry as well.

How does that work?

First, this consortium follows a previous European consortium from FP7.

We are in fact a sort of European Community

in this field of atrial fibrillation and atrial myopathy.

So, we have built up this consortium, we’re used to working all together,

and we have aggregated for MAESTRIA

new partners from the industry, from patients.

But we have a source of matrice which is there, which is our history,

because it makes things much more easy.

Very interesting.

Thank you very much.

We'll come back to some of those points, I'm sure, in the discussion.

But let me move, to the eMotional Cities project.

So, Bruno, it aims to improve health through a better

understanding of the interplay between people in urban spaces.

That might sound a bit theoretical to some people.

Can you explain in a bit more concrete terms what what that means?

Yes. It's okay to think it's theoretical, but

what this means is that we are bringing a new perspective

into the field of urban planning and design by bringing methods

and also new technologies, from the field of neuroscience.

And the idea is that, when you think

about the complexity of the city and how people experience it,

you actually want to know, from the perspective of the individual,

what is the impact of all these exposures that city might have?

And so, we, of course, start with what we know about these two fields,

but we are moving forward

in a way that we integrate these two pieces of information

because we believe it's the way forward to change human behavior.

From the perspective of our environment influences the citizens,

but also how citizens might change their behavior.

And which cities are you working in for the research?

So, we selected, four case study cities

Lisbon, Copenhagen, London and

Lansing, in Michigan state of the United States.

Because we selected

these cities on the basis of their different layouts

on different properties from the demographics and urban design

perspective, of course, as well, taking into account

that there were partners working with us on the cities.

Okay.

And how have you been organizing the field work there?

So, we worked

from the perspective of the local community and tried

to adjust some relevant policy and local relevant questions and challenges.

So, for example, when we run real life experiments

by conducting some city works with wearable units, we selected

these places on the basis of what a spatial analysis from Urban Analytics

would tell us as informative, what type of hotspots are relevant.

But we also try to sense

what the local stakeholders actually were interested to know in terms

of new evidence or new information that they could afford to have.

Okay.

And, how could city planners, for example, or local elected

representatives, take into account some of the insights from your research

in order to improve people's health in an urban environment?

So, I think

from various perspectives, we still have the perspective

of a more micro level or geographic information system level.

So, you could still use a lot of the data statistics

that each country has from census and from surveys.

But we could go deeper in terms of,

the knowledge about how we could combine this information at the level

of the neighborhood but going even further at the level of the street,

so you could actually have very granular information

about what's happening at the street level of your community.

And so, this could have an impact and more importantly, it's human centered.

So, you actually will provide information that is much more accurate

than correlations that we might be using for some challenges.

Thanks very much, Bruno.

If I could turn to, you know, Andreu, SAVE-COR is an acronym,

the title of your project,

it actually stands for something quite complicated the stratification

of atrial and ventricular arrhythmias based on electrocardiogram imaging.

Can you explain a little bit what that means? Sure.

So first, thank you very much.

And it is a great opportunity to have the chance to talk after Stephane

because as he well mentioned cardiac arrhythmias is an epidemic.

As he's pointing out, one of the main issues

that we have in Europe is that almost 10 million patients are suffering

from cardiac arrhythmia.

Every single day, we are performing around 1000

cardiac interventions to treat these kinds of arrhythmias.

And it's great because we have at least these kinds of interventions,

but the worst is that we only succeed in 50% of the patients.

We put patients in the cath lab, in the surgery room,

we introduce catheters into the heart and then we try to stop the arrhythmia

by burning the region that has caused the arrhythmia.

But we fail.

And why?

We say

because we do not have the technology within the heart, the technology

to see where the arrhythmia was coming from.

So, at the end, we are empirically burning the same gradient in every patient.

I was an engineer.

I was in the academy, working in hospitals

trying to help the clinicians to see what was going on.

And we said, okay, what if we could map the heart globally,

non-invasively, in a safe and efficient way?

And that was the origin of Corify.

This is a company that's a startup

thanks to EIT Health, to the support of the European Union.

And six years ago, we jumped from this is a prototype into a product.

And right now, we already are in the market.

We already have CE Mark.

We are in three half three countries around Europe.

More than 1000 patients per year map with our technology

and growing and growing.

Because at the end, this is the thing

we need to identify the arrhythmias, but we need to be sure that we can offer

the best treatment to every single patient.

And perhaps, I mean, a similar question to the to the one I asked a moment ago.

You know, why does the technology now allow you to do that

in a way that wasn't possible in the past?

It's a great technology. Great question.

So, in fact, this technology we developed originally set in really

basic research

is scanning the thorax of the patient and reconstructing the electrical activity

from a 3D reconstruction and generating digital twins.

Ten years ago, it took us something like one week

from the recordings to get a digital twin.

Right now, it's a matter of seconds

for an individual digital twin.

It's real time, bit to bit.

And it is thanks, first, to better algorithms which are unique;

artificial intelligence is helping a lot but also computing capacity.

So right now, we have some computer capacities within the hospital

in real time that was something difficult to dream of just a few years ago.

Yeah.

And presumably this is less invasive for patients as well.

At the end, the technology right now we are using it within the hospital

during the interventions because it's what we really want to be sure that it works,

but it's fully noninvasive.

So, we already are developing a simplified version of the system

to use it in any visit to the cardiologist or hopefully, one day sooner than later

in the emergency rooms to detect infarct or in every check-up when you go to

the cardiologist and instead of an EKG, that is 100 years old technology,

making a real digital twin of yourself that can show to the clinician

how is your heart and how to prevent any potential arrhythmia

that you may have in the future.

Okay, amazing.

And last but not least, I turn to Christopher as,

from the SepsISensoR project.

You're working on a wearable to be used

by vulnerable people to assess biomarkers that could indicate sepsis.

First of all, how dangerous is the condition

and how many people in Europe are concerned?

Potentially. Sure.

So let me first make a correction.

It is not a wearable sensor.

And the reason it isn't a wearable sensor is because

the definition of a wearable sensor is something that we can wear

when our everyday life like a smartwatch.

But the vision we had for this kind of device for people in ICUs.

And the reason for that is sepsis kills 11 million people every year.

Is that a global figure?

Oh, yes. And if we do a calculation, it's

about every 2.8 seconds someone dies from sepsis.

And so, yeah, it's a big problem.

And we're trying to solve it via exhaled breath.

And the reason for that is when sepsis is

being detected is after the clinical symptoms appear.

But that's already too late.

And so, we thought could these

signals, these biomarkers, appear in breath

while the sepsis is being developed before the clinical symptoms.

And the idea came from

the fact that the bacteria are growing inside the body causing infection.

Then infection spreads in the blood, in the organs.

And obviously he's coming out of the breath.

Okay.

And you've clarified so quite rightly that it's not a wearable

in the sense of, a smartwatch or something of that kind.

But what can you describe what physically it looks like. Exactly.

So, in a situation where someone is sitting in the ICU,

after surgery or any condition,

the chances of developing sepsis are quite high.

So, we imagine a mask on the face, with the equipment

on the side of the bed, monitoring their exhaled gases.

But towards our goal, we haven't done any clinical trials yet.

We’re in the in-vitro stage.

So, this in-vitro on bacteria, then in vivo with mice and finally human trials.

But the in vitro tests were quite encouraging.

We're able to detect the infection

in bacterial cultures much faster.

So we can detect infection between 2 to 8 hours, depending on the amount

of infection, of bacteria, whereas the current protocol takes overnight.

So, it takes 24 hours for a microbiologist to see

the bacterial culture grow and be able to tell whether it's an infection or not.

Whereas with real time and gas sensors, we can detect it much faster.

To what extent is artificial intelligence, big data, machine learning,

and so on, enabling you to make progress in your different projects?

Well, I think that's something that we all have is skin.

And it's very personal.

Depending on how old you are, your ethnicity, and weather conditions.

So, in the follow up project that we are now executing,

FlowBeams is a spin off company from part of the research that I did

with my ERC Grant, there we have a work package where we are

co-developing AI tools that can help us understand

how skin reacts before, during, and after a needle free injection.

And that is crucial because, well, when you are younger or are hydrated,

your skin would react differently with the technology that we are developing.

So, we need it to make sure that we can have

that personalized treatment that we are claiming.

Right.

And Stéphane, for example, in your project,

how significant is artificial intelligence there?

The biomedical research in different fields is facing a huge challenge,

which is big data generated by omics, by clinical imaging.

So, AI is becoming an essential tool for research

to manipulate this data, to analyses this data, to cluster this data.

And there is, I mean, all the projects that we are conducting now

must have a data scientist or computer scientist on board

to really bring together this expertise

for new research on biomedicine

and the fields of atrial fibrillation, cardiac arrhythmia and diagnostic tools

in this

new dimension of biomedical research

And other particular safeguards you have to put in place because,

I mean, obviously,

this is quite sensitive personal and medical data that you're dealing.

Yeah.

So, it's one difficulty of this type of research program.

So now we get in this data sharing space in Europe,

the Gaia-X space, which facilitates a lot because it has delayed

the beginning of the project to have to share data.

So, it's a major question,

a major issue in Europe which I think is partially resolved now.

Yeah.

Andreu, may I ask you,

because I have the impression that you're quite far advanced in your project.

What advice would you have for other colleagues around the table or

others who might be listening to us?

If they want to bring their research breakthroughs

to the next step in commercialization and application security.

Thank you.

It's true

we already are 40 people

or almost 40 people in the company, and we are already in several countries.

And the truth is that I come from the Academy,

from making papers and research and of course applying for grants.

But in the end what they clearly see is that if you are doing something

that solves a need, solves the problem of someone,

a clinician or a company, then there is a market for you.

And you should understand the market as soon as you start

having the ideas in the research;

you need to understand who is going to benefit

from your research,

on who is going to pay for what you will produce in your research.

I think that it should be mandatory that as soon as we are doing this,

we should be trained in understanding these kinds of questions.

And Bruno, maybe I think many of us, live in cities ourselves.

What can we do at a personal level to make sure

that we have the best experience and look after our health

when we're moving around in the urban environment?

Well, from our perspective at the eMotional Cities, I believe,

is to actually be more critical about the current evidence that we have.

So, we have to push policymakers and politicians to go further

in the data that we might provide.

Because, at the moment, even if we face a climate

change issue, we actually tackle it

by statistical correlations, by doing inference on the data.

But we do not actually have evidence

from a human perspective.

What's the actual impact of going on my street and walking on my street?

So, I think that's the empowerment that the citizens will have to push

for more evidence based,

driven, policymaking, and decision making.

And perhaps the last word from Christoforos,

you described your project as being at the in vitro stage.

What do you think it would take to bring it to the next level?

And how do you see the project evolving over the coming years?

Yeah, that's a very good question.

For the project to evolve better and then coming to life,

we need few more experiments to collect a bit more data.

Fortunately, or unfortunately, we haven't used AI yet.

We have a completely different algorithm called change point

detection that so far is very robust and quick.

And so, we want to make that

algorithm handle more data and ensure

that we can detect the infection, but also the bacterium that causes infection.

That's the next stage for us.

And after that, we're developing a prototype

smart incubator that microbiologists and

hospitals can

use to speed up this detection of infection.

Great. Well, thanks very much.

Thank you all, guests, for joining us.

And, to you for listening into this episode.

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