Helsinki-based AIATELLA, a medtech startup, introduced that it has secured €2M in funding led by Helsinki-based Nordic Science Investments.
Nordic Science Investments is a VC fund devoted to reworking groundbreaking scientific analysis into globally profitable corporations.
“AIATELLA is tackling probably the most important alternatives in medication: utilizing AI to remodel radiology. The corporate is completely positioned to guide the shift from reactive to preventative cardiovascular care and to interchange outdated, handbook workflows with clever, automated diagnostics,” says Alexandra Gylfe, Accomplice at Nordic Science Investments.
Different buyers, together with Specialist VC, Harjavalta Ventures, Enterprise Finland, and a syndicate of angel buyers, joined the spherical.
Fund utilisation
The Finnish firm will use the funds to speed up the event and scaling of its AI-powered cardiovascular imaging expertise.
The funding will assist the corporate conduct scientific trials and develop its ultrasound-based preventative screening, which detects and quantifies carotid artery narrowing in minutes.
AIATELLA: Scaling AI-powered cardiovascular imaging instruments
Led by Jack Parker, AIATELLA goals to revolutionise radiology by automating the gradual, handbook processes concerned in medical imaging.
Cardiovascular illnesses are the main reason for loss of life globally, however as much as 80 per cent of those deaths are preventable via early detection and therapy.
AIATELLA’s multi-modal Automated Picture Measurement (AIM) expertise makes use of pictures from prevalent applied sciences like MRI, CT, and ultrasound to analyse vascular imaging, not solely detecting but in addition quantifying abnormalities and modifications over time in at-risk sufferers.
Explaining the AIM expertise to Silicon Canals, Jack Parker, CEO and Co-Founder at AIATELLA, says, “Whereas most AI imaging instruments in medtech deal with detection – primarily flagging potential points for physicians to analyze – AIATELLA goes past detection to automation of scientific workflow. The crucial distinction is that we remove the time-consuming handbook measurement course of that follows detection.”
In cardiovascular imaging, detecting aortic abnormalities is just step one.
Nevertheless, radiologists then face the tedious, variable process of manually measuring aortic dimensions – probably the most labour-intensive features of cardiovascular radiology. This handbook course of is just not solely time-consuming but in addition susceptible to inter-observer variability.
“AIATELLA automates these exact measurements, delivering standardised, correct dimensional information on to the doctor. As a substitute of simply saying ‘there’s a possible illness right here,’ we offer the whole quantitative evaluation physicians want for fast scientific decision-making,” he provides.
The shift to preventative care
Along with AIM for medical professionals, the corporate can be growing an ultrasound-based transportable screening expertise, enabling mass screening of individuals earlier than signs seem.
“Our transportable ultrasound integration with AIATELLA is meant to allow a basic shift from reactive to preventative cardiovascular care. By decreasing the experience barrier for carotid stenosis detection and danger (of stroke) stratification, we’re democratising entry to specialised cardiovascular screening that was beforehand confined to main medical centres,” explains Jack.
AIATELLA needs to make its transportable screening expertise an everyday a part of well being checkups to assist detect cardiovascular illnesses early.
“That is notably transformative for rural and underserved populations who face important boundaries to cardiovascular care – lengthy journey distances, restricted specialist availability, and delayed prognosis till signs develop into extreme. Our transportable resolution brings screening instantly to those communities, enabling early detection when interventions are simplest and least pricey,” provides Jack.
In accordance with the corporate’s claims, this expertise can be utilized in numerous conditions, similar to office well being assessments, insurance coverage checks, and, together with cellular blood banks, vaccination campaigns, and illness prevention efforts.
Why does information variety matter in AI medical imaging?
By enabling screening in numerous settings, the expertise helps take away boundaries to early prognosis and helps broader entry to preventative cardiovascular care.
“Numerous demographic illustration is key to AIATELLA’s mission and scientific effectiveness. Cardiovascular anatomy and pathology differ considerably throughout age, intercourse, ethnicity, and different demographic components, but most medical AI has been educated on datasets that don’t signify minority and underserved populations. This creates harmful accuracy gaps exactly the place healthcare disparities are already most pronounced,” continues Jack.
With screening at scale, the corporate additionally goals to realize important insights into variations in how cardiovascular illnesses current and progress between totally different ethnicities and sexes, as signs typically current in a different way between folks.
“We’ve made inclusive information assortment a core precedence, not simply to fill proof gaps, however as a result of equitable healthcare entry is central to our mission. Our multi-site scientific validation technique intentionally targets numerous affected person populations, guaranteeing our algorithms carry out equally nicely throughout all demographic teams. Once we deploy transportable screening in underserved communities, we’re concurrently bettering entry and strengthening our coaching information for these populations,” he continues.
“Our transportable ultrasound initiative particularly targets these communities as a result of it’s the place the expertise can have the best impression and the place we will guarantee our AI works for everybody, not simply the demographics historically represented in medical analysis,” provides Jack.
The transportable screening expertise has already been utilized in partnership with medical professionals at screening occasions in Finland and the UK, and helped determine tens of people doubtlessly in danger, who had been then referred to healthcare professionals for additional analysis.
Scientific trials and regulatory milestones
AIATELLA’s expertise began with the aorta, the physique’s largest artery, and the corporate goals to increase its use to all blood vessels.
The corporate is presently in medical approval processes in a number of nations throughout Europe and North America, together with the UK, France, and america.
“We’ve taken a strategic method to regulatory complexity by designing AIATELLA to fulfill EU MDR requirements from the outset – essentially the most stringent international necessities. This basis permits us to adapt documentation for FDA 510(ok) or MHRA pathways extra effectively, fairly than retrofitting compliance after improvement,” explains Jack.
Jack believes the true problem isn’t navigating totally different regulatory frameworks, however managing the operational complexity of multi-site scientific validation.
“Every scientific web site presents distinctive technical integration challenges: various PACS methods, totally different imaging protocols, inconsistent information high quality requirements, and numerous IT infrastructure capabilities. We’ve discovered that site-to-site variation in technical necessities typically exceeds country-to-country regulatory variations,” he provides.
Supporting radiologists, not changing them
Radiologist burnout largely stems from the limitless repetition of handbook duties that eat time with out leveraging scientific experience.
The Finnish firm instantly addresses this by eliminating the hours spent on tedious mouse clicks and measurements required for cardiovascular prognosis.
As a substitute of spending hours measuring pixels with an intense deal with technical precision, radiologists can consider what they educated for: sample recognition, scientific correlation, and sophisticated diagnostic reasoning.
“We envision AIATELLA as a part of a broader transformation the place AI handles routine quantitative duties, permitting radiologists to deal with high-value scientific work and affected person session. This doesn’t exchange radiologists – it makes their experience extra beneficial and their work extra sustainable, finally reshaping hospital workflows to prioritise scientific pondering over handbook labour,” concludes Jack.
