Top 10 Emerging Companies Solving Cancer with AI 2023V3 1.pdf

April
Issue 01
2023
AIE
Incorporating Data Science in Medical World
AI to the Rescue
The Role of Emerging
Companies in the
Fight Against Cancer
Revolutionizing
Cancer Treatment
How Emerging
Therapies are
Transforming
Oncology Care
Alexandru Floares
Founder and Chief
Executive Officer
AIE
Companies Solving
Cancer
Top Emerging
10
with AI 2023

Helping Technology
Technology
Technology
Work With You &
For You
For You
For You

Editor’s
Note
he field of cancer care is rapidly evolving, and
Temerging companies are at the forefront of
developing innovative solutions to tackle this
complex disease. One of the most promising areas of
innovation is using artificial intelligence (AI) to improve
cancer diagnosis, treatment and outcomes.
AI algorithms can analyze vast amounts of data from
different sources, including medical images, genetic data
and patient records, and identify patterns that may be
difficult for human clinicians to detect. This can help
physicians personalize treatment plans for individual
patients and improve their chances of survival.
Emerging companies are harnessing the power of AI in a
number of ways. Some are developing AI-powered
diagnostic tools to analyze medical images to detect
cancerous lesions that may be too small or difficult for
Leading the
Way with AI in
Cancer Care

human radiologists to see. This can lead to earlier detection
and more effective treatment.
Others are using AI to develop personalized treatment plans
for cancer patients based on their genetic profiles. By
identifying specific mutations and biomarkers that are
unique to each patient's cancer, AI algorithms can help
clinicians choose the most effective treatment options.
AI is also being used to streamline clinical trials for cancer
drugs. AI algorithms can identify patients most likely to
respond to a particular drug by analyzing patient data,
including genetic data and medical history. This can reduce
the time and cost of clinical trials and improve the chances
of success.
With advances in technology, the potential for AI to
revolutionize our way of approach to cancer treatment is
becoming increasingly clear. The companies highlighted in
this edition are at the forefront of this exciting field,
harnessing the power of AI to develop innovative solutions
for cancer detection, diagnosis and treatment. Their
groundbreaking work is changing the way we think about
cancer care and offers hope for a brighter future for cancer
patients around the world.
In Insights Care's latest edition, Top 10 Emerging
Companies Solving Cancer with AI 2023, we will explore
the unique strategies and technologies of each of these
companies and highlight the impact they are making in the
fight against cancer.
Hope you have an inspiring read!
- Pooja Shah

AIE
08
Ctts

Aicl
18
Oncobit
Imagine the Potential of Diagnostics
Enabling Personalized Cancer Care
26
Prognica Labs
Advancing in Early Detection
of Breast Cancer
Companies in the Fight
Against Cancer
AI to the Rescue
22
How Emerging Therapies are
Transforming Oncology Care
32
Revolutionizing
Cancer Treatment
36
Synaptiq
Easing Diagnosis and
Imaging Processes with AI

Editor-in-Chief Chidiebere Moses Ogbodo
Co-designer Paul Belin
Art & Picture Editor Deepanjali Jena
Art & Design Head
Visualiser David King
Mrunalinee Deshmukh
Circulation Manager Tanaji Fartade
Research Analyst Eric Smith
Anna Smith, Jack Miller
Business Development Executives
Emily Jones
Business Development Manager
Sales Executives Mike, Carl, John
Marketing Manager Bill Thompson
Technical Consultants David, Robert
Technical Head Jacob Smile
Assistant Technical Head Prashanth Hiremath
SME-SMO Executive Gemson
Digital Marketing Manager Alina Sege
Assistant Digital Marketing Manager Sagar Lahigade
Managing Editor Pooja Shah
Executive Editor Saloni Agrawal
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April, 2023
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Description
Featuring
Person
Company Name
AIE
aie-op.com
Alexandru Floares
CEO
Headquartered in Idaho with locations across the
country, AIE is your one-stop-shop for new and
refurbished medical, vet and dental equipment
for small, medium, and large clinics.
Inspirata
lipotype.com
Satish Sanan
CEO
Inspirata, Inc. helps patients fighting
cancer—and the clinicians they trust—to make
every moment matter.
iCAD
icadmed.com
Jessica Burns
PR
iCAD is a global medical technology leader
providing innovative cancer detection and
therapy solutions.
MedSol AI Solutions
medsol.ai
Kathryn Malherbe
CEO
MedSol AI Solutions’ artificial intelligence software
allows an accurate and speedy diagnosis of breast
cancer to allow quicker turnaround times to
surgical intervention.
Oncobit
oncobit.com
Claudia Scheckel
CEO
Oncobit is a medtech UZH Spin-off, enabling
personalized cancer care by matching patients
to the best cancer treatment available.
Synaptiq
synaptiq.io
Mihai Cata
Co-Founder
Synaptiq is revolutionizing cancer treatment
through AI-driven radiotherapy solutions.
Prognica Labs Tech
prognica.com
Khalid Shaikh
Founder and CEO
Prognica Labs Tech, an AI powered health-tech
company, aims to improve clinical outcomes and
accelerate the discovery of breakthrough
advancements in the fight against cancer.
Telefónica
telefonica.com
Rodolfo Campa
CMO
Telefónica have the best infrastructure, as well as
an innovative range of digital and data services;
therefore, they are favorably positioned to meet
the needs of its customers and capture growth in
new businesses.
Tribun Health
tribun.health
Lorine Marcoux
MM
Tribun Health powers the digital
transformation of cancer diagnosis by
designing innovative solutions.
Veru
verupharma.com
Martin Tayler
OP
Veru is a biopharmaceutical company focused on
developing novel medicines for COVID-19 and
other viral and ARDS-related diseases and for the
management of breast and prostate cancers
Top 10 Emerging Companies Solving Cancer with AI 2023

Alexandru Floares
Founder and Chief
Executive Officer
AIE

AIE
I first felt that all our
work was in vain. However,
looking more carefully, I realized
that our MCED is much better
(e.g., having a breast cancer detection
rate of 99% instead of 33%).
Cover Story

ictional movies impact the viewers in various ways.
FAnd, out of many, the most popular scenic moment
people have held with them is to have a personal
genie. While, for obvious reasons, it is difficult to have a
real wish-fulfilling human, but a possible solution is offered
by technology through its platform of artificial intelligence.
Though the avenues offered by this are used to aid a wide
range of human progressions, it is becoming the most
popular in the healthcare sector. From diagnosis to
treatment, AI has been taking care of every minute thing
required in the contemporary health setting.
Today, the foremost medical challenge is the spiraling
incidence of non-communicable diseases, in which cancer
ranks second place after cardiovascular diseases.
According to the International Agency for Research on
Cancer, globally, one in five people is affected by this
disease. Many doctors state that the main cause behind this
is the delay in the detection of cancer, along with almost ten
to twenty percent chances of misdiagnosis.
As an effective solution to this, many companies are
calibrating scientific methodologies to converge human
intelligence with technology in the healthcare industry to
help doctors identify malignancies in their early stages.
One such company is AIE, which is transforming
biomedical problems into Data Science problems that are
improving accuracy in early recognition of cases along with
its first Multi-Cancer Early Detection test to save and
improve numerous lives.
This solution was pioneered by its Founder and CEO –
Dr. Alexandru Floares, who holds an MD and a Ph.D.
degree in Biophysics and is leading the medical field with
his research-driven AI-based diagnosis and prognosis
initiative.
Let us read more about their inspiring work!
The How's and the Why's of their Journey
AIE was founded in 2017 as a spinoff of a private research
NGO, Solutions of Artificial Intelligence Applications
(SAIA). All SAIA founders were physicians, including the
founder – a neurologist with a solid mathematical
background.
At SAIA, they started in 2004 to transform biomedical
problems, especially in the cancer field (as the co-founder
Carmen Floares was an oncologist), into Data Science
problems and tried to solve them with AI.
Dr. Alexandru shares, “At that time, we did not realize that
our approach was pioneering the actual paradigm shift in
biomedicine. In 2008, we started a collaboration with MD
Anderson Cancer Center aiming to diagnose bladder
cancer early by using the circulating (liquid biopsy) miRNA
and AI.”
This test performance established a new state-of-the-art,
inspiring them to continue in this direction with two other
similar projects. A plethora of free clinical studies data
became available, enabling AIE to develop its first Multi-
Cancer Early Detection (MCED) test in 2012 (unpublished
results).
In 2018, Alexandru found a paper about an MCED test,
highly acclaimed in the media. He says, “I first felt that all
our work was in vain. However, looking more carefully, I
realized that our MCED is much better (e.g., having a
breast cancer detection rate of 99% instead of 33%).”
This determined the leader and the team at AIE to entirely
focus on an accelerated go-to-market with their MCED test,
to their knowledge, the best one.
The Marvel of AIE
Alexandru's journey started as a clinical neurologist with a
solid mathematical background when he realized that

despite his hardworking, the fate of stroke patients is not
significantly changed by his or his colleague's treatments.
But at the same time, he was excited by the newly emerging
AI.
He made the hardest life decision – to quit neurology and
follow his dream, AI. He says that he knew more about
what he did not want to do than what he would do. He
considers it the best decision of his life.
He founded SAIA and followed a pretty successful
scientific research career. In 2017, his job was still
ascending, and he had a lot of research plans. He then
realized that their Multi-Cancer Early Detection (MCED)
was way better, but he needed a startup to develop it further.
He was facing the tough dilemma of leaving his career
midway. But he decided to start again from zero, as a
businessman this time.
This thought was just the beginning for him.
Then, he and his team won some competitions where
business training was an important part. He found that
professional business management is closer to Data Science
with AI than he had expected – use data, define metrics,
experiment, optimize, etc.
Thus, AIE naturally became an AI-driven company.
Considering that their research is flourishing, and their
startup is growing fast and hence for him this decision was
good too. The only price, he feels, is working twelve hours
per day, 6 – 7 days per week, but that was always his
working program, which talks aloud of his dedication put in
his work to achieve what he had dreamt of.
The Mission of Life and Company
First, both co-founders worked directly with patients with
severe illnesses like stroke or cancer. Alexandru shares,
“We know what suffering means and when patients place
their lives and hope in your hands. I used to think that my
personal ambitions strongly motivated me too.”
We know what
suffering means and when
patients place their lives
and hope in your hands. I used
to think that my personal
ambitions strongly motivated
me too.

However, his recent visit to the Vatican for a talk about AI
in Cancer made him feel that was a proper place to meditate
on the meaning of one's life.
Sharing his experience, he says, “I realized that I quit
neurology because I could not save and improve lives but
could surely do it with our cancer tests. My ambitions could
not be satisfied only by publishing some papers about the
best cancer tests. I understood that if my tests remained just
brilliant intellectual exercises, instead of saving and
improving lives, my life would be a failure, and failure is
not an option.”
This contemplation led him to make his mission the
company's mission as well, which is also reflected in the
company's offerings.
Services Delivering Reliability
Talking about the elements of the company's services,
Alexandru opines, “We started to think that non-invasive
tests should be preferred to invasive ones for the benefit of
the patients. The tests should be data-driven - let the data
speak instead of imposing a model on it.”
To assure its customers about credibility in data, AI is being
used as it understands high-throughput data better than any
human being does.
This strength of AI may not always reflect the true versions.
Explaining further about this, Alexandru says, “No matter
how attractive a specific molecular alteration looks from
the biological knowledge viewpoint, let AI check if this is
informative or not for a given biomedical problem. As AI
only extracts the existing information in data, if these
alterations are not very informative, the performance will
be necessarily low. Moreover, living systems are
functionally redundant.”
To put it simply, Alexandru believes that the same function
could be performed in different but equivalent ways at the
molecular level, making them highly robust. This has a
substantial impact on biomarker discovery and predictive
model development.
To comprehend this further, he put forth an instance. He
says, “For example, in a small cohort of patients used for
learning, AI can find a pattern of alterations, but in another
one, a different but functionally equivalent dominates. This
means the model will not generalize to new unseen cases
well.”
Continuing to give deeper insights, he says, “The situation
is even worse when you have many variables and few cases.
Small studies are inconclusive, so we collected more than
10,000 cases. What is statistically irrelevant, e.g., highly
Putting it all together,
we defined and followed the
ART criteria – our tests (models)
should be highly Accurate,
Robust, and Transparent.

correlated variables, and eliminated by the AI algorithms,
could be biologically relevant.”
AIE dual set of problems to be addressed, which Alexandru
says are, “We avoid aggressive feature selection as it results
in models not generalizing well and secondly, physicians do
not trust a model unless its predictions are transparent and
intelligible.”
Hence, it uses Explainable AI (XAI). Alexandru says,
“Putting it all together, we defined and followed the ART
criteria – our tests (models) should be highly Accurate,
Robust and Transparent.”
Testing it Early with MCED
AIE's MCED test belongs to the new generation of digital-
only medical tests and makes a highly accurate early cancer
detection routine. It has the highest performance of 99-100
percent accuracy at an affordable price. It is technology-
agnostic, working on NGS, microarray, PCR and
Nanostring data.
Giving words to the test's performance, Alexandru says, “It
is personalized – AI offers a personalized explanation of the
diagnosis in terms of altered circulating miRNA. In
addition, the test can monitor the response to treatment.”
Answering through Technological Intelligence
AIE's AI platform results from more than fifteen years of
research and continuously evolves as high-throughput
technologies and AI progresses. It combines bioinformatics
pipelines to process the raw omics data and transform it into
the format required by AI to develop predictive models.
According to Dr. Alexandru, most existing bioinformatics
pipelines consist of steps that make (unrealistic) statistical
assumptions about the data and simplifications and perform
optimizations.
He says, “There are theorems stating that a neural network
can approximate (discover) any function. Post some
“crazy” experiments, we had a revelation. We found that
neural networks can discover better bioinformatic pipelines
than we would do – making no assumptions or
simplifications and having a single optimization process,
e.g., a diagnosis accuracy. The result is an end-to-end
solution consisting of data transformations giving the best
accuracy.”
Their platform is disease-agnostic and works with the most
available omics data. However, he comments, “There are
still some questionable beliefs in the field. For example, a
study should end with the differential expression of omics.”
Questioning the current practices, he enquires, “So why do

Machine Learning (ML) practitioners not perform this step
in other areas?”
Presenting an answer to this query, he says, “Because ML
algorithms always ignore the inputs with no differences
between two or more conditions, being uninformative.
Another belief is that we need just a list of biomarkers to
solve practical problems. However, with the same list of
biomarkers, one can build the best or the worst model.”
Therefore, Alexandru asserts, “There is a need to discover
from data a subset of the differentially expressed omics and
the relationship (predictive model) between them and the
output, e.g., a diagnosis, prognosis, or response to
treatment.” And this could be fulfilled with other Hi-tech
avenues.
Aligning with Recent Upgradations
In the last few decades, the most outstanding healthcare
progress was due to the enormous impact of ICT on
medical imaging and molecular biology. For example, the
old radiography became computed tomography.
Similarly, conventional molecular biology technologies
became high throughput.
Complementing such innovations in the field, Alexandru
comments, “Both are big leaps, but the huge one has just
started – AI becoming structural to healthcare. We can say
that healthcare is in the high-throughput data age.
However, our mindset is not yet in this age but is facing a
paradigm change.”
Genetic information is distributed and accessed in parallel.
The biological reality at the molecular level consists of
complex and intricate networks of molecules. He says, “Not
long ago, we asked what gene is responsible for a complex
disease. However, an organism where a single gene could
be so important will hardly survive natural selection.”
Adding on, he says, “However, we still think about a couple
of tens of molecules we can list and “mechanistically
explain.” AI-powered medical imaging will evolve fast as
the algorithms for computer vision which will be easily
adapted to medical imaging.”
He emphasizes the fact that the world has to understand that
the above-mentioned adaptability is not true for the high-
throughput omics data, as they have specific peculiarities
not present in the non-biological world where the AI/ML
algorithms were developed. Hence, Dr. Alexandru
comments, “Until we comprehend this, most predictive
models and corresponding biomarkers will not generalize
well to new data.”
He believes that the time is not far when hospitals will
become virtual distributed organizations crossing the walls
and even national borders, and human teams will
collaborate with their digital counterparts, improving
patients' outcomes and saving resources.
The team at AIE is working now on what they see as the
solution where they will firstly automate the healthcare
workflows. Then, will implement Intelligent Systems (AI)
capable of taking inputs from all kinds of data (multi-
modal), including omics and images, and giving results
from diagnosis, prognosis, response to treatment prediction,
etc. (multi-task). The workflow indications (best practices)
and all predictions will be expressed as intelligible rules.

A Message to Ingrain
As the sector is expanding, more such innovations would be
needed to reduce the global disease burden. And to walk the
steps of success, deeper insights and guidance become
essential for persons desiring to venture into this field.
For this purpose, Dr. Alexandru spreads his words of
wisdom to young entrepreneurs where he advises, “As we
are in the middle of a revolution, you should think
differently, revolutionarily. Do not consider the actual
biomedical knowledge as almost complete and almost
perfect. It will be heavily challenged by the knowledge we
will extract with AI from rapidly accumulating high-
throughput data. This will impact not only the technology
but also the business models. You should disrupt both,
thinking about the patient's and physician's problems.
Imagine yourself as a surfer. Big waves are coming. Be
prepared to see them, catch them and ride them.”
Expanding in 2023 and Beyond
After a time of hard-working without visible results, they
were suddenly blessed with a forty-two times growth in
funding (grants and investments), allowing them to enlarge
both – the R & D and the business team.
As their AI-powered platform is disease agnostic, together
with a top EU consortium, they are planning to enter the
psychiatry field – depression treatment optimization and
personalization. They also intend to extend to other areas,
e.g., cardiovascular diseases and health wearable sensors.
They have launched their Biomedical Data analysis
services, combining bioinformatics and AI, accelerating
their go-to-market journey for the MCED test.
Dr. Alexandru shares, “We will further develop our
consistent portfolio of ideas and proof of concepts,
becoming a solid catalyzer of the actual healthcare
revolution. We are riding big waves.”
Imagine yourself as
a surfer. Big waves are
coming. Be prepared to
see them, catch them, and
ride them.
Awards and Accolades
“Clearly, this could be not only the best multi-cancer test on
the market but also a paradigm change in the whole field of
molecular diagnostic.”- George A Calin, MD, Ph.D.
Professor, Departments of Experimental Therapeutics
and Leukemia Co-Director, The RNA Interference and
Non-coding RNA Center at MD Anderson
The company has won various accolades in its journey. A
few notable ones are mentioned below:
Ÿ AIE was mentioned in the book - Top Disruptors in
Healthcare Report.
Ÿ AIE won the European Innovation Council Seal of
Excellence with its Breast Cancer early detection
project (VINCI; 6M Euro) and, in a consortium, a
Horizon Europe 10M Euro project on optimizing and
personalizing depression treatment with AI.

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Oncobit
Imagine the Poten al of Diagnos cs Enabling
Personalized Cancer Care
Cancer is not only a leading cause of death today, but
it also takes a toll on the life of the patient. It is a
painful, difficult and uncertain journey overall.
While these patients have the utmost right to be given
personalized therapy suitable to their physical and
emotional needs, the traditional methods of diagnosis keep
them from having it.
Oncobit eliminates this gap of limited options to diagnose
and monitor cancer patients. Through highly sensitive
diagnostic and monitoring tools, the company delivers the
most appropriate treatment selections to the physicians, thus
enabling personalized treatment for cancer.
In an interview with Insights Care, Claudia Scheckel, the
CEO, shares in depth about Oncobit's use of non-invasive
technologies to enable personalized disease monitoring.
Following are the excerpts from the interview:
Please brief us about the company and its inception.
Personalized cancer therapies are being developed at an
increasingly rapid rate. To offer personalized therapies,
diagnostics must keep pace to provide the necessary
information. Yet current solutions are not sensitive and
specific enough, and diagnostic data analysis and
interpretation are becoming increasingly complex. These
unmet needs were quite apparent to two of my co-founders,
who study cancer and are Professors at the University and
University Hospital of Zurich. To address them they
developed a more specific and more sensitive diagnostic
test for melanoma. And that's how we founded Oncobit.
Kindly tell us about yourself and your professional
journey so far.
I have been living my passion for science and analytical
thinking for almost 20 years. After obtaining my Ph.D. in
biochemistry from the University of Basel (Switzerland), I
worked for almost a decade in leading biomedical research
institutions in New York (The Rockefeller University) and
Zurich, Switzerland (University Hospital Zurich).
During that time, I had several entrepreneurial touchpoints,
got a degree in management, and ultimately joined Oncobit
as Co-founder and CEO in the spring of 2020 to actively
transform my knowledge into medical advances for the
benefit of patients.
What are the key products and services offered by the
company and how is it impacting the demographic
concerned?
We have built a portfolio of three tests that accompany
cancer patients throughout their history. For diagnostics, we
have developed two cancer-specific sequencing assays that
provide a comprehensive profile of the patient's tumor,
TM TM
using either tissue (Oncobit Dx) or blood (Oncobit LB)
as input. This allows us to provide more tailored therapy
decision support compared to the common "one-size-fits-
all" solution.
Additionally, we have developed a radically simplified
TM
personalized monitoring solution (Oncobit PM), detecting
and quantifying cancer-specific markers in the patient's
blood. The test is minimally invasive and can be applied
repeatedly and longitudinally to monitor therapy response
and cancer recurrence.
All our products consist of an assay and software, and the
unique combination of technical know-how, proprietary
software, and close clinical collaborations allow us to
develop more comprehensive and sensitive cancer
diagnostic and monitoring solutions. To date, we have
focused on melanoma, but we have a scalable approach and
are currently expanding our portfolio to other cancer types.
What are the core values of the company? How are you
driving the company to achieve its mission and vision
statement?
At Oncobit, our vision is to enable personalized cancer care,
by providing highly sensitive and comprehensive solutions
to find the best cancer treatment for each patient. We use
state-of-the-art technologies to provide physicians with
cancer-specific, innovative and high-quality diagnostic and
monitoring tests and therapy-decision support.
18| April 2023|www.insightscare.com

Claudia Scheckel
CEO
Oncobit
At Oncobit, our vision is to
enable personalized cancer
care, by providing highly
sensi ve and comprehensive
solu ons to ﬁnd the best cancer
treatment for each pa ent. We
use state-of-the-art technologies
to provide physicians with
cancer-speciﬁc, innova ve and
high-quality diagnos c and
monitoring tests and therapy-
decision support.
Our mission is to work closely together with clinicians to
develop tests that are useful for the clinic, and therefore
ultimately the patient. Oncobit is a science-driven company
founded out of an urgent need and can therefore accurately
understand and respond to the needs of our customers with
high precision. Honesty and transparency are important
to us and win-win is not a slogan but a prerequisite for
any form of cooperation with us. Tolerance of other
opinions, religions, sexual orientations and life
models and respectful communication is
essential for us.
In your opinion, how is AI increasing
the survival rates among cancer
patients? How is your company
using this technology in unique
ways to deliver the best results?
AI-assisted therapy selection is a
key driver for improving patient
outcomes. Based on patients'
clinical, genomic and outcome

information, AI can learn patterns that are associated with
positive therapy results.
At Oncobit, we are involved in two aspects of this process:
on one hand, we are providing the products for deriving
TM
high-quality genomic (Oncobit Dx and LB) and outcome
TM
(Oncobit PM) data, which are key for training high-
performance AI models. On the other hand, we are using
these models to suggest the best possible cancer therapy for
patients.
In addition, we use AI in the development of all our core
products, such as for the design of optimal gene panels or
the analysis of complex genomic data.
What are the key challenges in the industry and how are
you infusing your leadership skills to turn them into
opportunities to chart the company's growth upwards?
Personalized therapies are constantly evolving and are
becoming the standard of care for cancer treatment. Yet,
ensuring that the right therapy regime was selected, requires
sensitive, rapid and, above all, cancer-specific diagnostic
and monitoring solutions. In addition, the analysis and
interpretation of the data of these tests are becoming
increasingly complex.
As a start-up company, we have the flexibility, knowledge
and capacity to develop practical and market-oriented
solutions that precisely meet these unmet needs. Our
TM
minimal invasive blood-based Oncobit PM test is a good
example.
We have applied our technical expertise to develop a
quantitative cancer-specific assay, applying an ultrasensitive
method, digital PCR. Yet, when applying such ultrasensitive
methodologies, standardized data analysis is critical to
eliminate biases, provide more robust results and achieve
optimal sensitivity and specificity. Our test, therefore,
includes a proprietary software solution that takes healthy
data into account when classifying patient samples, while
enabling automatic data analysis, interpretation and
reporting at the same time.
As an experienced leader, what advice would you like to
give to aspiring entrepreneurs and enthusiasts who wish
to venture into the competitive industry that you are
serving?
I strongly believe that close collaboration with physicians is
critical in developing products that will be used in the
clinic. At the same time, the healthcare market is highly
complex, and it is not sufficient to only fulfill the needs of
physicians and patients. Regulatory agencies, hospitals and
health insurances are critical stakeholders, and on top of
that healthcare systems between countries are rarely alike.
This complexity can be quite daunting, especially for a
small startup.
Yet with the right team, good advisors and the right strategy
everything is manageable, and finding and setting up a good
support system is therefore essential. One then quickly
learns how to break down complex problems into
manageable parts, focus on what is important and how to
quickly gather just enough information to make a decision.
Resilience, pragmatism, decisiveness, high intrinsic
motivation, and above all, passion for what you do are key
qualities that help you navigate even complex industries.
What are the future goals of the company? How does it
envision scaling up its operations and reach in 2023 and
beyond?
We are currently expanding our personalized monitoring
test to additional melanoma markers and will expand to
other cancer types later this year. With our proprietary
software solutions being an integral part of all our products,
our approach is easily scalable. In the long run, we want to
become a worldwide leader in cancer diagnosis and
monitoring.
Give us a few testimonials from your clients or
customers, and awards or recognition that accurately
highlight your company's position in the market.
We have won several start-up competitions and awards,
which was an important recognition of our company, our
products and our team. The fact that we get to work closely
with leading dermato-oncologists is a testimonial that we
have the right approach. Although there is still much for us
to do, I am very proud of what we have already achieved,
including ISO 13485 certification of our quality
management, and regulatory approval for our first product.

Companies
Fight Against
in the
Cancer
AI to the Rescue
Introduction
Cancer- A devastating disease that affects millions of
people globally.
While advancements in medicine and technology
have improved the diagnosis and treatment of
cancer, the disease remains complex, and its
treatment requires a multi-disciplinary approach. One of the
most promising developments in recent years has been the
application of artificial intelligence (AI) in cancer care. By
leveraging machine learning algorithms and big data
analytics, AI has the potential to revolutionize cancer care
by enabling more accurate and personalized diagnoses,
improving treatment outcomes, and increasing the
efficiency of clinical trials.
Emerging companies are playing a crucial role in the
development and application of AI in cancer care. These
companies are nimble, innovative, and are driven by a
mission to use cutting-edge technology to solve complex
problems in cancer care. They are leveraging AI to develop
innovative solutions that can help clinicians diagnose
cancer earlier, design more effective treatments, and
manage vast amounts of oncology data. These companies
are often at the forefront of innovation, working in close
collaboration with academic institutions, research
organizations, and other stakeholders in the healthcare
ecosystem.
Let's discuss the ethical considerations that must be
considered when using AI in cancer care.
Precision Medicine
Precision medicine involves using genetic data to
tailor treatment plans for individual patients. AI
algorithms can analyze a patient's genetic data to
identify specific mutations and biomarkers
unique to their cancer, which can be used to
develop personalized treatment plans.
Emerging companies like Guardant Health
are developing liquid biopsy tests that use AI
algorithms to analyze DNA in the
bloodstream and identify mutations and
biomarkers unique to each patient's cancer.
This information can be used to develop
personalized treatment plans, such as
targeted therapies that specifically target

the genetic mutations driving cancer. This approach can
improve patient outcomes by reducing the likelihood of
treatment resistance and minimizing the risk of side effects.
Cancer Diagnosis
Medical imaging plays a vital role in cancer diagnosis, but
interpreting medical images can be challenging, even for
experienced radiologists. Emerging companies like
Paige.AI use AI algorithms to analyze medical images and
improve cancer diagnosis accuracy. Paige.AI uses deep
learning algorithms to analyze medical images and identify
cancerous lesions that may be too small or difficult for
human radiologists to detect. This can lead to earlier cancer
detection and improved patient outcomes. AI can also help
radiologists identify patterns in medical images that may
indicate specific types of cancer or cancer progression.
Clinical Trials
Clinical trials are critical in developing new cancer
treatments, but they can be time-consuming and expensive.
AI algorithms can help streamline clinical trials by
identifying patients that might respond to a particular
treatment. Emerging companies like Berg Health are using
AI algorithms to analyze patient data, including genetic
data and medical history, to identify patients most likely to
respond to a particular cancer drug. This can help reduce
the time and cost of clinical trials and improve the chances
of success. AI can also help identify potential side effects
and drug interactions, allowing researchers to develop safer
and more effective cancer treatments.
Oncology Data Management
The amount of data generated in oncology research and
patient care can be overwhelming, and traditional data
management methods may be unable to keep up. Emerging
companies like Syapse use AI algorithms to manage and
analyze oncology data. Syapse has developed an AI-
powered platform that can analyze large amounts of
oncology data and identify patterns and trends to help
clinicians personalize treatment plans for individual
patients. AI can also help identify potential areas for
research and development, allowing researchers to focus on
areas that are most likely to lead to breakthroughs in cancer
treatment.
Ethical Considerations
As AI becomes more influential in decision-making, it is
essential to be used transparently and ethically. Emerging
companies must be responsible for the developing and
using AI-powered solutions, and patients must be informed
about how their data is being used. Privacy concerns are
also important, to protect patient data from unauthorized
access or use. It is essential to strike a balance between the
potential benefits of AI in cancer care and the ethical
considerations that must be considered.
Conclusion
Emerging companies are using AI to improve precision
medicine, cancer diagnosis, clinical trials and oncology data
management. AI has the potential to transform cancer care
and improve patient outcomes, but ethical considerations
must be taken into account to ensure that AI is used
responsibly and transparently. It is important to strike a
balance between the potential benefits of AI in cancer care
and the ethical considerations that must be addressed. With
continued investment and collaboration between emerging
companies, clinicians and patients, the use of AI in cancer
care will undoubtedly grow in the coming years. This will
lead to more personalized and effective cancer treatments,
improved clinical trial success rates, and better oncology
data management. AI is a powerful tool in the fight against
cancer, and emerging companies are at the forefront of this
revolution.
-Pooja Shah

Prognica Labs
Advancing in Early Detection
of Breast Cancer
Breast cancer impacts 21 million women each year
worldwide, among which 1 in 8 women will
develop invasive breast cancer in their lifetime. In
these circumstances, accurate detection and prevention
cannot be compromised as it is estimated to have a 98%
survival rate if detected early.
Pertaining to the hope, Prognica Labs is committed to the
advancement of technology that will improve breast cancer
survival rates worldwide. Its AI-powered platform,
PrognicaMMG and PrognicaUSG analyze medical images
and generate medical reports from anywhere, thus enabling
accurate and early detection of breast cancer.
In an interview with Insights Care, Khalid Shaikh,
Founder and CEO, talks about the company's innovative
solutions for saving, celebrating and leading the fight
against breast cancer.
Following are the excerpts from the interview:
Please brief us about Prognica Labs and its inception.
The idea for Prognica Labs was born out of my personal
experience with breast cancer survivors and a strong
passion for working toward society. I realized that there was
a significant need for more accurate and accessible breast
cancer detection solutions, especially in developing
countries where resources are limited.
To address this need, I founded Prognica
Labs with a mission to develop innovative
solutions that would help doctors and
patients detect breast cancer early and
accurately. The company's current products,
PrognicaMMG and PrognicaUSG, are AI-
powered breast cancer detection solutions that use
deep learning algorithms to analyze mammograms
and breast ultrasound to identify suspicious lesions with
high accuracy.
concerned?
Prognica Labs is a medical technology company that
specializes in developing AI-powered diagnostic tools for
breast cancer detection and treatment. The key products and
services offered by Prognica Labs include:
Ÿ Personalized Breast Cancer Risk Assessment:
Prognica Labs' web-based platform uses advanced
machine learning algorithms to analyze mammogram
and ultrasound to provide breast cancer diagnostic and
risk assessment. This can help healthcare providers
identify individuals who may benefit from earlier
screening or more frequent check-ups.
Ÿ Computer-aided Detection (CAD) Software: Prognica
Labs has developed CAD software for mammography

By using AI technology
to improve the accuracy and efficiency
of breast cancer detection and treatment,
Prognica Labs is helping healthcare
providers provide better care to patients.
Our personalized breast cancer risk
assessment can help identify patients who
may be at higher risk of developing breast
cancer, allowing for earlier detection
and intervention.
Khalid Shaikh
Founder CEO
Prognica Labs

that uses machine learning algorithms to analyze
medical images and flag areas that may need further
examination. This can help radiologists save time
detecting abnormalities or signs of cancer that may be
difficult to detect with the naked eye.
The impact of Prognica Labs' products and services is
significant for the demographic concerned. By using AI
technology to improve the accuracy and efficiency of breast
cancer detection and treatment. Additionally, our CAD
software can help radiologists detect abnormalities that may
be difficult to detect with the naked eye, leading to earlier
diagnosis and better patient outcomes.
Overall, Prognica Labs' products and services have the
potential to make a significant impact in the fight against
breast cancer, ultimately saving lives and improving
outcomes for patients.
statement?
As an AI-powered medical technology company
specializing in breast cancer detection and diagnosis,
Prognica Labs is guided by the following core values:
Ÿ Innovation: Prognica Labs is committed to driving
innovation in breast cancer detection and diagnosis by
leveraging the latest advancements in artificial
intelligence and machine learning.
Ÿ Accuracy: Prognica Labs prioritizes accuracy in all of

its products and services, ensuring that patients receive
the most reliable and precise breast cancer diagnosis
recommendations possible.
Ÿ Patient-centricity: Prognica Labs places the patient at
the center of everything it does, working to improve
patient outcomes and experiences through its technology
and services.
Ÿ Ethics and integrity: Prognica Labs operates with the
highest level of ethical standards and integrity,
prioritizing patient privacy and security in all aspects of
its business.
To achieve its mission and vision of improving breast
cancer detection and treatment through AI-powered
solutions, Prognica Labs is driven by a number of strategies
and initiatives. These include:
Ÿ Investing in research and development: Prognica
Labs invests in research and development to stay at the
forefront of the latest advancements in AI and machine
learning for breast cancer detection and diagnosis.
Ÿ Partnering with healthcare providers and
organizations: Prognica Labs collaborates with
healthcare providers and organizations to expand access
to its technology and services and to ensure that its
products are meeting the needs of patients and
healthcare providers.
Ÿ Focusing on quality and accuracy: Prognica Labs
prioritizes quality and accuracy in all of its products and
services, working to continually improve the reliability
and precision of its breast cancer detection and
diagnosis solutions.
Ÿ Promoting awareness and education: Prognica Labs is
committed to raising awareness and educating the public
about the importance of breast cancer screening and
early detection, working to increase screening rates and
improve outcomes for patients.
you turning them into opportunities for growth?
Some of the key challenges that Prognica Labs faces
include:
Ÿ Regulatory compliance: The healthcare industry is
heavily regulated, and it can be diﬃcult to navigate
complex regulatory requirements, particularly when it
comes to developing and deploying AI-powered
solutions.
I'm the founder and CEO of Prognica Labs, a
healthcare technology company that specializes
in developing AI-powered solutions for breast
cancer detection and treatment.
Here's a brief overview of my professional journey
so far:
I'm a serial entrepreneur, author, technocrat and
business strategist. I'm also the founder and
CEO of Prognica Labs, an artificial intelligence-
powered health-tech company. For this I have
received numerous awards for his innovations in
healthcare.
In addition to my professional commitments, I
also give back to the aspiring entrepreneur
community by serving as an advisor and mentor.
I have published and lectured extensively on
healthcare performance improvement,
digitalization and innovation, and authored the
book: Artificial Intelligence in Breast Cancer
Early Detection and Diagnosis, and several
research articles published in peer-reviewed
journals. I'm also an Advisory board member for
a few startups.
Since its inception, Prognica Labs has become a
leading player in the healthcare technology
industry, with a strong focus on AI-powered
breast cancer detection solutions. My leadership
and vision have been instrumental in the
company's success and I continue to drive
innovation and growth, while remaining
committed to improving patient outcomes and
making healthcare more accessible and
affordable for all.
CEO's Journey:
In His Own Words

Ÿ Data privacy and security: Healthcare providers must
comply with strict data privacy and security regulations
to ensure patient information is kept confidential and
secure. This can be particularly challenging when
working with large amounts of medical data, as is often
the case in the field of cancer detection and treatment.
Ÿ Limited access to data: While there is a wealth of
medical data available, it can be difficult to access and
use this data for research and development purposes.
This can make it challenging to develop accurate and
effective AI-powered solutions.
To address these challenges and chart Prognica Labs'
growth upwards, I am infusing my leadership skills in the
following ways:
Ÿ Building strong partnerships: I am working to build
strong partnerships with healthcare providers and
organizations, as well as regulatory bodies, to ensure
that Prognica Labs' AI-powered solutions are compliant
with regulations and can be effectively deployed.
Ÿ Prioritizing data privacy and security: I am
committed to prioritizing data privacy and security in all
of Prognica Labs' products and services, working to
ensure that patient information is kept confidential and
secure.
Ÿ Investing in research and development: I am focused
on investing in research and development to improve the
accuracy and effectiveness of Prognica Labs' AI-
powered solutions, even in the face of limited data
access.
Ÿ Nurturing a culture of innovation: I am working to
create a culture of innovation within Prognica Labs,
encouraging all team members to think creatively and
take risks to drive the company's growth and success.
beyond?
At Prognica Labs, our vision is to transform breast cancer
detection and treatment through the power of AI. To
achieve this vision, our future goals include—Expanding
our product portfolio, increasing our reach, enhancing the
accuracy and effectiveness of our solutions, and addressing
new markets.
Our goal is to continue to lead the way in AI-powered
breast cancer detection and diagnosis, driving better
outcomes for patients and transforming the way cancer is
diagnosed and treated around the world.
Give us a few testimonials or recognition that accurately
highlight your company's position in the market.
Prognica Labs has received several awards and recognition
that highlights its position as a leader in AI-powered breast
cancer detection solutions within the healthcare industry.
Some of these include:
Ÿ Arabian Business Achievement Award 2023 in Science
and Medicine.
Ÿ World Economic Forum 2022 as Global innovator /
contributor for Youth Mental Health Challenge
Ÿ Etisalat SMB Award 2021 for Best Artificial Intelligence
Startup.
Ÿ Tahawultech Transformational Leadership Awards 2021
for Best Deployment of Machine Learning in
Healthcare.
Ÿ Tahawultech Transformational Leadership Awards 2019
for Technology Rising Star of the Year.
Ÿ Ras Al Khaima Business Excellence Awards 2019 for
Best Startup of the Year

Transforming
Therapies
How Emerging
are
Oncology
Care
Care
Care

C
ancer is a complex and devastating disease
affecting millions of people worldwide. The earlier
we intervene in cancer treatment, the better the
results for patients, according to scientific evidence. Prior to
the pandemic, there had been a steady decline in cancer-
related deaths worldwide, largely as a result of better
screening, earlier detection and treatment developments like
personalised medicine. Over the years, oncology care has
evolved significantly, with researchers and medical
professionals constantly seeking new and innovative ways
to combat this disease. Emerging therapies have been a
major driving force in this evolution, with several
groundbreaking treatments transforming the landscape of
cancer care.
Developing new cancer therapies has provided hope to
millions of cancer patients, their families and loved ones.
These therapies have significantly improved the quality of
Revolu onizing Cancer Treatment

life for cancer patients, offering better treatment options and
longer life expectancy. Moreover, these treatments are
constantly being improved, with new research and clinical
trials leading to even more breakthroughs in cancer care.
Let's explore the latest advancements in cancer treatment,
focusing on emerging therapies that are revolutionizing
oncology care!
We will examine the benefits of these treatments, the
conditions they are best suited for, and their potential
impact on the future of cancer care. By understanding these
emerging therapies, we can gain a deeper appreciation for
the progress that has been made in cancer treatment and the
promise that these treatments hold for the future.
Immunotherapy
The body's immune system is used in immunotherapy, a
type of cancer treatment, to combat the disease. It functions
by either triggering the immune system to attack cancer
cells directly or by suppressing the signals that cancer cells
use to avoid being detected by the immune system.
Numerous cancers, including melanoma, bladder cancer
and lung cancer, have responded well to this therapy.
Compared to conventional cancer therapies like
chemotherapy and radiation, immunotherapy has a number
of benefits, including being more targeted, having fewer
side effects, and having the potential to produce longer-
lasting effects.
Targeted Therapy
Another cutting-edge cancer treatment is targeted therapy,
which focuses on particular molecules required for the
growth and division of cancer cells. Targeted therapy can
stop the growth and spread of cancer cells while sparing
healthy cells by concentrating on these molecules. Breast
cancer, lung cancer and melanoma are just a few of the
cancers that this therapy has shown promise in treating.
Compared to conventional cancer treatments, targeted
therapy typically has fewer side effects and is well
tolerated.
CAR T-Cell Therapy
A novel and cutting-edge therapy for blood cancers like
leukaemia and lymphoma is CAR T-cell therapy. It entails
removing T-cells from a patient's blood and genetically
altering them so they can identify and combat cancer cells.
After being altered, the T-cells are injected back into the
patient's bloodstream, where they can hunt down cancer
cells all over the body. Clinical trials for this treatment have
yielded astoundingly high success rates, with some patients
achieving complete cancer remission. Although CAR T-cell
therapy is still in its infancy, it has the potential to replace
current standard therapies for specific types of blood
cancers.
Gene Therapy
Gene therapy is an emerging therapy that has the potential
to revolutionize cancer treatment. This therapy involves
altering a patient's DNA to fight cancer. Scientists can use
gene therapy to either replace or modify genes in a patient's
cells. This can help fight cancer by either making cancer
cells more susceptible to treatment or boosting the body's
immune response to cancer. Gene therapy is continuing in
the early stages of development, but it has shown promising
results in clinical trials.
Liquid Biopsy
A non-invasive diagnostic procedure called a liquid biopsy
has the power to revolutionize how cancer is discovered
and treated. This test involves looking for cancer cells or
DNA shards released by cancer cells in the patient's blood.
Liquid biopsy can detect cancer early on, track the disease's
development, and find mutations that may impact how the
disease is treated. Although this test is still in its early
stages of development, clinical trials have yielded
encouraging results.
Conclusion
In conclusion, emerging therapies are transforming the field
of oncology and offering new hope to cancer patients
worldwide. Immunotherapy, targeted therapy, CAR T-cell
therapy, gene therapy, and liquid biopsy are examples of
innovative treatments that are changing how we approach
cancer care. With continued research and development, we
can expect to see even more advances in cancer treatment in
the years to come. These emerging therapies offer new tools
for healthcare professionals to fight this devastating disease
and provide hope to cancer patients and their families.
-Pooja Shah

Synaptiq
Easing Diagnosis and Imaging Processes with AI
he first step before prescriptions is an accurate
Tdiagnosis. As easy as this look, it isn’t; researchers
reveal an estimated mortality rate of 40,000 to
80,000 patients every year due to misdiagnosis.
Noting the gravity of this challenge, leaders around the
world are inventing solutions to ensure healthcare systems
with tools that help in the accurate diagnosis of any ailment
and aid the mission of saving lives. These efforts are given
further thrust by advancements in technology, especially
with Artificial Intelligence. AI has provided the healthcare
ecosystem with the seeds of effective disease diagnosis,
amplified rate of drug discovery, and much more.
One such company, amalgamating teamwork with
technicalities of AI is Synaptiq, which was cofounded by
Diana Andritchi – the Co-founder and Chief Business
Officer of the company.
Synaptiq is improving medical imaging processes with the
help of automation and artificial intelligence. For this, it has
also developed its unique software – Mediq that helps
doctors identify and delineate cancerous tumors and organs
at risk. It is able to accurately delineate organs at risk and
target volumes for all areas, the contouring helping doctors
to precisely distribute dose volumes of radiation.
Through the interview highlights below, let us dive into the
world of Synaptiq and its solutions!
Please brief us about Synaptiq and the ideas and
developments that led to its inception.
Synaptiq is a start-up company based in Cluj-Napoca,
Romania. Our main field of activity is represented by the
development of software based on artificial intelligence for
automation and improvement of imaging processes in the
medical field.
Our start-up is formed by a team of fifteen AI enthusiasts
with expertise in various areas, from economic to technical
backgrounds. The partnership that stays at the basis of our
start-up is one of the company’s main assets and values.
Our current focus is to develop robust, accurate and user-
friendly software, while establishing strong partnerships,
identifying potential customers, and becoming known on
the market. “Mediq” is the software we develop to help
doctors identify and delineate cancerous tumors and organs
at risk.
We have set
a clear plan. We test our
product at our partner
radiotherapy clinics, we will
gather feedback and improve
the product. Moreover, we
expect to obtain the certification
for our product in 2023 and to
acquire customers not only
from Europe.

Diana Andritchi
Co-Founder & Chief
Business Of cer
Synaptiq

concerned?
“Mediq” is the software we develop to help doctors identify
and delineate cancerous tumors and organs at risk. We aim
to achieve this solution using Artificial Intelligence. This
technology distinguishes itself from traditional technologies
in healthcare through its ability to gather data, process it in
a sophisticated manner, and give a complex analysis to the
end-user.
Our solution satisfies a crucial need and it solves an
important bottleneck within radiotherapy treatment
planning.
The existing solutions on the market are helpful to radiation
oncologists, but the important problem (the big amount of
time needed for contouring) still remains. A doctor needs
around 4 hours for the contouring/ delineation process per
patient and the result is very subjective. In this case, a
software that has AI at its basis could come with a huge
difference.
With the help of AI, tumor identification can be done in a
fraction of time, with higher accuracy and objectivity. This
will speed up the process, increasing the patient's survival
rate.
statement?
Our mission is to empower radiation oncologists to save
more lives.
We aim to achieve this potential by:
1. Using unique AI-based software architecture
2. Having a well-balanced team of prepared experts
3. Establishing strong partnerships with research and
healthcare institutions
Our core values are – Teamwork, Passion, Integrity,
Innovation
In your opinion, how is AI increasing the survival rates
among cancer patients? How is your company using this
technology in unique ways to deliver the best results?
Nowadays, delineation is generally clinically performed
with little (if any) machine assistance, even though it is
both time-consuming (it can take up to 4 hours per patient)
and prone to interobserver variation (the overlap between
contours made by 2 different radiation oncologists rarely
exceeds 75%).
In order to achieve faster radiotherapy treatments while
avoiding potential errors, it is imperative to make tumor
identification and delineation less subjective and observer-
dependent.
The groundbreaking innovation appears together with the
possibility of having a software assistant that you can teach
the same way you would teach a student. Machine Learning
algorithms do exactly that. They mimic the learning process
of humans by making use of prior information inferred
from many previous use cases. At the same time, they are
also capable of learning the algorithmic behavior of their
less intelligent, but worthy predecessors.
Being able to make use of this new learning paradigm they
can access prior clinical expertise by training on huge
amounts of medical data. Given access to performant
hardware, Deep Neural Network can learn in days what
would take us years.
We develop the software using AI (Machine Learning
algorithms). Artificial Intelligence is a solution that could
help doctors make more informed clinical decisions
regarding patients. Moreover, AI can process images and
patient health records with more accuracy and expediency
than humans are capable of, lessening physician workload,
reducing misdiagnosis, and empowering clinical staff to
provide more value.
you infusing your leadership skills to turn them into
opportunities to chart the company’s growth upwards?
Healthcare remains one of the least digitalized industries,
leaving room for huge opportunities that manage to fill this
gap.
Mediq is the
software we develop
to help doctors identify
and delineate cancerous
tumors and organs
at risk.

At Synaptiq, they are a team of 15 innovation
enthusiasts. Their awarded physicist CEO transformed
his dream into a plan, and gathered a talented team in
the pursuit of merging medical analysis with Artificial
Intelligence. The idea came to his mind when he was
working at the German Cancer Research Center.
Having discussions with various doctors, he
understood what the important bottlenecks in
radiotherapy area.
Dragos Duse is the CEO of Synaptiq. He is a Machine
Learning expert, an awarded Physicist and a
passionate Researcher. He graduated Chief of
Physics promotion following a Master in
Computational Physics at Heidelberg University. He
designed AI algorithms at National Center for Tumor
Diseases and German Cancer Research Institute. He
gained experience as a computer scientist at
Fraunhofer IPA, in Mannheim, Germany. At Synaptiq,
he plans to use his knowledge for revolutionizing the
Healthcare Industry.
To be successful in such an ambitious project,
bringing together a highly qualified and passionate
team is essential. This is why they constantly study,
explore different perspectives and grow their
expertise, by attracting the best professionals to join
their cause.
First who resonated with this thought was Mihai, back
then, researcher at Romanian Institute of Science and
Technology. The team then started working on
product development and made some progress, but
they needed someone to focus on business
administration and also to develop a business plan,
and raise capital. With this in mind, Roxana and Diana
joined the team and started to work on this project.
They both have master's degrees in business and
experience in multinational companies.
When they got their first investment, they decided to
further grow their technical team. Three more people
joined the cause, with the extraordinary experience
behind them. At the moment, they are a team of
seventeen passionate people, including six of the best
radiation oncologists in Romania. Together their
mission is to empower radiation oncologists to save
more lives.
The Team of Synaptiq Looking at the newest trends, we can see that AI
engineering and Hyperautomation are used for solving real
business problems and exploiting new opportunities. We
believe that these can easily be transposed into healthcare
applications and bring real added value.
AI is giving mometum to medical diagnosis with its
potential to incite drastic improvements to hospital
processes. Among the most promising clinical applications
of AI is - diagnostic imaging.
The combination of AI with medical imaging will lead to
the transformation of modern medicine.
As an experienced leader, what advice would you like to
give to aspiring entrepreneurs and enthusiasts who wish
to venture into the competitive industry that you are
serving?
Two important lessons we learned during our journey are:
you need to know the market, and you need a well-balanced
team.
Regarding the first lesson, it is really important to perform a
proper market research before starting to build the product
(a very common mistake).
For the second one, the team always is crucial, even more
so when the company is very young. We’ve really tried to
bring in a nice mix of skills and expertise to cover all of our
needs, and have always prioritized quality over quantity.
beyond?
We have set a clear plan. We test our product at our partner
radiotherapy clinics, we will gather feedback and improve
the product. Moreover, we expect to obtain the certification
for our product in 2023 and to acquire customers not only
from Europe.

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