Latest / Deep Tech Germany – AI, Robotics & Frontier Innovation by Startuprad.io™ / Tumor-on-a-Chip Biotech: CanChips Rebuilds Cancer Drug Testing

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Tumor-on-a-Chip Biotech: CanChips Rebuilds Cancer Drug Testing · Deep Tech Germany – AI, Robotics & Frontier Innovation by Startuprad.io™

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If you're a biotech founder, investor or pharma innovator
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trying to accelerate drug screening beyond outdated
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models, here's the challenge. Traditional tumor models
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are slow, costly and unreliable. Ghazalay,
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founder and CEO of Can Chips GmbH has built a
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microfluid tumor on a chip platform from
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the Potsdam Science park ecosystem backed by national
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startup awards and a mission born from a personal oncology
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journey. Today we'll break down how her tumor on a
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Chip innovation can help you bring personalized cancer
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therapy, animal free drug development and
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predictive tumor microenvironment models into
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real world impact so you can leap ahead in the competitive
0:47
biotech space.
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Welcome to Startupradio,
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your podcast and YouTube blog covering the German
1:01
startup scene with news, interviews and
1:04
live events.
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Welcome to StartupRadio. Our guest today is Ghazali
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Madani, co founder and CEO of Can Chips, a
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Potsdam based biotech startup revolutionizing
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cancer research with its tumor on a chip
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microfluid platform. Actually, you'll explain to
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us what that means soon, right? With Masters of Biochemistry and
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Molecular Biology from the University of Potsdam and a
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Bachelor's in Medical Laboratory Science from Isafan University,
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Ghazali brings rigorous science, entrepreneurial vision and
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personal motivation. Her mother's cancer journey led
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directly to her founding mission. Since 2023, Can
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Chips has developed human cell co cultured 3D
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microfluid tumor models, achieved major awards
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including Newcomer of the Year at the German Startup Awards 2025.
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That's why you are here. Congratulations. And is
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positioned at the cutting edge intersection of personalized
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medicine and non animal high predictive
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clinical testing. Today she joins us to unpack
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how tumor on a chip microfluids,
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angiogenesis modeling and biosensor
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integration combine to create the next frontier in
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oncology drug development and what that means for founders,
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investors and former partners alike. Ghazali, welcome
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to the show and have a to really explain a lot.
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I do have an audience who listens from time to time to biotech content,
2:37
but I have to admit it's quite
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unique. What you are doing?
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Can you take us along your journey? You started in medical laboratory
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science in Iran, moved to Masters in
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Biochemistry and Molecular Biology in Germany and then founded
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Can Chips in 2023. I bet when you started your bachelor
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you never imagined that you would go
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through this once upon a time moment when you realized that tumor
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on a chip was the entrepreneurial path you felt compelled to
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take. And can you please explain what a tumor on a chip is?
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Yes, of Course, first of all, thank you very much for having me.
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That's an honor to be involved in such wonderful
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podcasts. And yeah, I mean, then I go back and think
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about my bachelor. I could never imagine that I am here, here in the
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position that I am today. And the moment, once
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upon a time for me was actually during my master degree with
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the idea of can chip that we were collecting data from like 2D models.
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And then we were doing animal trials and some of them were working really good.
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And then I was realizing that they are clinically really not relevant.
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We were relying on models that they do not behave like
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real human tumors. And that was disconnecting me from the
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point that tumor on a chip can stop being just
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a dream or being in academia and become a
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mission for me. What is tumor on a chip? And since we are not doctors,
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can you tell us why this model
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behavior that differs from the real human being?
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Why this is a big problem? Yeah, when we are having like the
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preclinical data for the pharma companies and biotech companies, they
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normally have 2D models. What is a 2D model is like a
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flat cell culture where the cells are growing and they are
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not acting as they can act in human body because we don't have a
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flat organ. They are all like
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3D. And the other
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thing is that they are testing them on animals. And animals cannot behave like
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humans. And they are the reasons that so many of the drug
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developments fail in clinical phases. And that is
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very expensive to develop a drug that is time consuming to develop a
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drug. And what these tumor on chip models do is that they are
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3D. They have the microenvironment of the tumor.
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So that is really a mini tumor on a biological
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platform that can be used for testing the
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medications that are in development. In that area,
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we do not need animal trials anymore. So much so we are reducing
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the animal trials and they are also having more reliable
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results. At the end of this story.
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In the everyday status quo of cancer drug development,
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which, which is a very, very difficult field
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because we don't know a lot of what actually causes cancer. So
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that's always a question, how to treat it. We still rely
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heavily on animal models and like you said, the 2D
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cultures. How does your system, the tumor on chip,
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challenge that status quo? And what is the biggest limitation you saw
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that led you to build this platform?
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The way that we challenge the stethoscope per day is by creating the
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micro environment that actually behaves like human tissue with
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perfusion with co culture with real time function results. And
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that means that we have a dynamic platform like the blood is
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going through the organs, the medium for the cells is going through them. And the
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results that we have, they are the results that you need to develop a drug.
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And it's just not a smaller model, it's a human model. And the
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limitation that we saw to lead us through that is as I said,
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the results that we get sometimes are a fantasy in 2D model.
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And we are like wow, we just developed a new drug and when it goes
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to the clinical trial with human that is not working. And that is
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the huge limitation because we are talking about millions
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and billions of euros that yearly is being spent on drugs. And we
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are talking about 14 years that one drug is taking
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from the beginning of the drug development to when it's ready to
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be released to the market.
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I see, I see. And
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that's basically where your
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tumor on a chip really gets
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started. So. And actually that was all
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triggered as we already said in the intro, by your personal experience,
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a personal catalyst. Your mother was diagnosed with
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breast cancer and that inspired your mission. How did
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that emotional driver shape your scientific
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focus and your founding strategy for cancer?
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I mean the cancer was for me always when I was also in my bachelor
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degree was for me always a very big question mark. But I
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realized that when my mom was diagnosed with breast cancer, the
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science was one of a sudden for me, personal. And
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I understood that every delay that we have in preclinical
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phase of the drug development translates to real suffering,
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real world suffering. That means later drugs, later
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personalized medicine. And it sharpened my focus that
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accelerating a realistic cancer model isn't a scientific
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ambition. That is responsibility that someone like me has when they have an idea
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and they have passion to bring it into the real world. I mean that's that
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that's like being so realistic
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at the same time being also so emotional. Because I
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can say that each of us had someone in the family that was fighting
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for cancer or in a different crisis and know what a story
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is that and when we are one step more forward through personalized medicine,
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then that is personal for all of us. And
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due to this catalyst, you chose to integrate two
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human cell what you call co cultures, perfusion
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microfluids and multi
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omics readouts. You gotta explain what that
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is into chip design. What were the major
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engineering biological PIV pivots you
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encountered by developing the tumor microenvironment
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model. So meaning that setting up a model that
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the tumor really behaves like a tumor in a human body.
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Exactly. I mean the point is that when we are talking about these microfluidic
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systems, you can imagine a resin base that we are working with or
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some other companies like a microplastic and so on. And we had to think
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about it, that the chip cannot behave like a plastic or a resin, that
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should behave like a tissue, that should behave like a human. And making that
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micro environment to be in that area that was balancing like
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biology and engineering. And we are really
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biologists and biochemists by heart and by practice.
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And that was the irritation that we had to mix these two
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together. And that was the moment that I was like,
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okay, that is what can be really good because we found
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a way to have zero drug absorption in our platform, to have a
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transplant transparent platform and to have this
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engineering to come in the real world. Data that we don't talk about just
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the chip, we talk about like real tissues. We're also
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going to record a founders world, of course. And you once told in an interview
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that we need a quick shift towards personalized cancer medicine
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and we must leave our comfort zone. You'll dare
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share moments when you personally pushed yourself beyond that comfort zone
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and what that meant for can chips growth.
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Until finally after prototyping and validation, can chip
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achieve proof of concept for what you call tumor on a
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chip models and secures its first awards and partnerships? What were the
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breakthrough milestones you hit and how did you validate
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your platform to pharma and biotech collaborators.
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After this. Time of the prototyping and so on, we
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were really in a point that we were ready to go. And I have to
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say that our, our breakthrough was consistency. There are so many challenges,
10:49
daily challenges that you have in biotech and specifically when you
10:53
are managing to have a unique and innovative
10:57
platform or a service, then we
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reproduce the same drug response curves in
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independent runs. We could show the biotech and pharma companies that
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this platform is ready. You can trust it because the data that we have,
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they are clinically relevant because the data that they have shows that you can
11:15
reduce the animal trials and you can have better results faster. And that
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was the moment that we were coming to talks with biotech and pharma companies
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to understand their need to also push them a bit out
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of the comfort zone and tell them let's make it a bit bigger together.
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And I mean that was a journey, but that was
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going good.
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I see from your platform's perspective,
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what, what are the tactical frameworks you deploy when
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designing those 3D tumor on a chip models,
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for example tumor and co cultures, perfusion
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settings and real time biosensing. How does
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this differ from the standard approach?
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The way that we do it is normally with mixing some points
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together. For example, that is the architecture part. As you said, we have
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all the micro environment, we just have the tumor cells because that
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doesn't work as it should. We have the tumor cells, we have the endothelial
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cells, we have the immune cells that should be included. Then we have the
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perfusion model that we have the translation of
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the flow that we have like in human body with the
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blood. We translate it into the tumor on chip model and
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we have it on for the drug development. Because the absorbance will be different,
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the effect and side effects that it has, it will be different. And then
12:39
was the validation and the readout. The difference that is with the
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standard assays is that that is more complex so that there
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are different questions that can be answered with using that platform.
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For each type of tool for our audience.
12:53
Because I believe you and me, we had way more touch
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points to cancer than we would ever like
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to have. You hopefully mostly in professional manner.
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For everybody who's not with a medical background in oncology.
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How many types of tumors out there? I do
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believe there's so many that even oncologists encounter
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from time to time a type of tumor they've never seen before. That's
13:20
true. I mean they are really for each type of tumor there are
13:23
so many types of sub tumors. When someone has for example
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colorectal cancer, the other one also has it. The subtypes
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can be totally different. That is genetic based, that is based on the
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mutation that the cancer has. And I say it always, if
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100 companies at the same time work with the platform that we
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have, still each of us has so much to do because there are really
13:46
so many areas of cancer that they are non touched, that they are
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the cancers that you understand at the end of stage and you cannot do something
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about it. So I really have to look it up exactly
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how many types of more we have. But I can assure you that there
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are plenty. And so many of them are still so much unknown to us.
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It's quite incredible how many different types of team one can have and
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everyone, every subtype even needs to be treated
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differently. So it's, it's a huge field
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and a lot can be gained by, by having the right therapy.
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So I'm going a little bit back to can chips. What
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are some of the scaling challenges you faced both
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biologically and operationally?
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I mean biologically I have to say we didn't have so many validation
14:34
problems, you know, the reproducibility of the system and so on. Because my
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co-founder also had so much experience in the cancer research and
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microfluidics, we were really going a bit more faster. But the biological
14:45
challenge that not us, but so many of the companies have is
14:49
that the variability of the primary human cells that when you are
14:52
working and saying I am developing a pancreas cancer on chip, you are
14:56
developing one of the pancreas cancer models or sub models that
15:00
is even possible to study on and there are many, many different more to
15:03
go. And that was also the maintaining the barrier
15:07
integrity across the chips. You know that you want to have so many different
15:11
cells on the chip, each of them grow differently. So you have to control
15:15
some of them, you have to let them grow freely and they are the
15:19
biological aspect of that. And operationally of
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course that regulatory talks because we know that
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FDA also accepts these non-animal models. But there is
15:30
not a golden pathway that you can say if I go this direction, everything's
15:34
accepted. The good point is that because we are in the
15:37
preclinical phase, we do not have so many regulatory aspects that we
15:41
have to go through. But still if you want to convince biotech and pharma company
15:45
to do less animal trial and come to this non animal
15:48
models, they need to know which direction they are going. We are
15:52
active in this area with fda, with EMEA to really
15:56
try to make it a pathway for all of us. But I have
16:00
to say operationally these regulations and convincing
16:04
is a challenge. And
16:08
will you talk about FDA and so on that are actually the
16:12
regulatory bodies for Europe? Yes, exactly.
16:16
Whenever a drug is wanna come into a market, they should
16:19
definitely have the FDA approval to be allowed. That means that they pass,
16:23
they pass the preclinical test, clinical test and the drug is safe
16:27
to be in the market for patients.
16:32
I was wondering for our audience if you're working on college
16:35
R&D or biotech investments and you're in, you're hearing
16:39
this. What would you ask Ghazalie right now
16:43
about tumor-on-a-chip models that can impact your own project?
16:47
Guys, we'll be right back after a short break. Dive into
16:51
strategic decision making and customer partner wins. That
16:54
really propel Startupradio forward.
17:11
You mentioned you are working with patient derived
17:15
tumor cells and integrating biosensors for real time
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drug response monitoring, which is actually pretty cool that one can do that.
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Can you walk us through a case study or partner collaboration where
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this played out? Of course we have a very, very
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good collaborator that really trusted us from the very
17:34
beginning, that we use the patient derived colorectal tumor cells on our
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chip with continuous perfusion and we were monitoring the drug
17:41
response in real time through the sensors that we are integrating
17:45
and also that time through the gene expression and so on.
17:48
And we could discuss these manners,
17:53
how the cells are reacting with that partner. Instead of waiting days
17:56
for the results, we could have in 48 hours,
18:00
72 hours, the primary results that we wanted. And that is
18:04
gonna change the decision making, that is gonna change the personalized
18:07
medicine, what we want. I am gonna say it so often in every
18:11
interview till we see a change. We want more collaborations from
18:14
hospitals in Germany to go through personalized medicine. That is not
18:18
a one man show. We have to work all together. We receive samples from Sweden,
18:22
from Romania, from all the Europe. But when it comes to
18:26
Germany, they are like this protection of the data, even though
18:29
we don't need the data. And that is the place that we really can
18:33
develop the personalized medicine. So we have to keep it together.
18:38
You were talking about a 48 hour time frame here
18:42
with current methodology, not your tool. How long does it take.
18:47
In general, when we are integrating models that is a bit dependent. When we have
18:51
a patient drive and they are really well biopsied
18:54
and we see that there are cancerous cells inside, they can directly
18:58
go to the chips. And in 42 hours to 72
19:02
hours, we have the base that we wanted to have it.
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But sometimes we may need longer because some cells are not growing
19:10
in the speed that we want them to grow. But I always say we
19:14
will have a two week time since the patient
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is operated and the tumor is out to the time that they are ready
19:21
and recovered for the therapy. And in these two weeks we can
19:25
answer so many questions that can help them. For personalized
19:28
medicine. We're here on
19:33
StartupRadio where more than 90% according to our
19:37
audience survey, at least listen for professional reasons. So let's drive
19:41
a little bit into your strategies. What
19:44
growth methodologies did you adapt in your early
19:48
startup phase to integrate science, engineering and startup execution?
19:52
Because. Many note that
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they're saying in startups, yeah, move fast and break things, but that is
19:59
not really working in cancer treatment. So
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what can a biotech founder learn from that? What
20:06
did you learn? I mean, I have to say a
20:10
very, very early point is that the startup founder should be
20:14
brave enough to be loud about what they are doing. Because if you are developing
20:18
the coolest product but no one knows you, there is no worth
20:22
for that product. And I learned it in a hard way because our investor was
20:25
like, you have to go out and tell their story what you are developing.
20:29
So being loud is the first thing that I always say to the
20:32
founders as then is to be fast. You know, you cannot be perfect.
20:36
You have to get out the first prototype, let the end users try it,
20:40
even in a pilot study. Then you understand what is the issues, what is
20:43
the challenges and you can make it. And of course the co-development
20:47
with users. You know, I always say that it's not a one man show. You
20:51
need collaborators, you need people in academia, in other industry
20:54
to help you understand what is the need of the market even.
20:58
And of course a very good business developer to get in touch with potential
21:02
customer because you can develop something for them and that is
21:06
not what they wanted. But if you can ask them what is
21:09
your need, what do you want? Then the product that you're going to develop develop
21:13
is the thing that they're going to be interested at the end of this story.
21:19
And now dive a little bit into your strategic decisions.
21:23
For example, for you it's a strategy
21:27
decisions. What cancer types to target first.
21:31
I think high on your wish list was of course a breast cancer. I'm very
21:35
virtual about this. Also setting your peace strategy,
21:39
prioritize co cultures and so on.
21:43
What decisions did influence your roadmap from 2023
21:47
to let's say next year, 2026. And beyond for
21:51
us was the choosing of the cancer type and
21:54
targeting was really dependent on the unfortunately I
21:58
have to name it trend. That's a very sad story of the
22:01
sicknesses and cancer types that they are getting more and more and they need really
22:05
more studies. That is colorectal cancer that is coming to younger generations generation
22:09
pancreas cancer and the cancers that they are mostly in the pipeline
22:13
for treatment for pharma and biotech companies. And that was for us the point
22:16
that we said okay, we will start from that point. The IP strategy for us,
22:20
I mean we already filed the first patent in 2024 because that
22:24
is also a thing that we are doing is novel. So why shouldn't we
22:28
protect it? And the plan or roadmap that we have for
22:31
2023-2026 for us was influenced by
22:35
really making something big that different companies, if they
22:38
are smaller, if they are big, if they are universities, that they can benefit
22:42
from that and that the goal is to really get away from
22:46
animal trials. And we are also influenced by that mindset as
22:49
well. What
22:53
customers or partner wins stand out for you Like University
22:57
Labs here. Oswald Farmer and how do you quantify
23:00
the value your tumor on a ship platform
23:04
delivers to those collaborations? The partners
23:08
that we have till now really valued our models because
23:12
they are less variable and they are more
23:15
predictable. And the reason behind that is that we have customized
23:18
models. So we ask them what is your need? And then we will design
23:23
the platform based on their need. And that is what a
23:27
bit all the standards and one group like reduce the time
23:30
that they had to put on the animal trials by around 30%. The other
23:34
one gained functional readout that they couldn't do. And they are the things
23:38
that we can quantify the value of the tumor and should be the
23:41
feedbacks that they gave us. They said I could understand a problem in my
23:45
drug development that I am struggling with since years with animal
23:48
models and I couldn't see where the drug is going. So they are
23:52
the ways that we understand that we are in the right pathway.
23:58
When I was putting this interview together, I had to
24:01
admit I have not the slightest idea of what people
24:06
you need for such a, such a
24:09
cutting edge technology. So I'm considering funding and team building.
24:13
What are key criteria and talent profiles you're
24:16
prioritizing now? Especially given that
24:19
specialized nature of microfoods, biotech and
24:23
oncology. I'm very sure you won't find a lot of
24:26
bachelors and masters people with a specialized,
24:31
with a specialized track for this specialties, right?
24:35
Yes, of course. I mean that is an
24:38
area that is really needed like education
24:42
in that area and also lab work in that area. So when we
24:46
are, I mean we are also planning or expansion and our team is going to
24:49
definitely be people that they have already worked with tissue
24:53
models. So if they don't have experience in microfluidic, that is not an issue. We
24:57
can bring it for them. And research is that they are
25:01
in the translational model. How can we translate these in
25:04
vitro models, the models that they are happening outside of the human body
25:08
to the clinical models that what is happening inside human body without
25:12
directly testing it. So these are the areas that we mostly
25:16
look for our expansion and of course business developers. Because as I
25:19
said, if you are developing the coolest product, no one out there knows
25:23
what you are doing. So you cannot really bring it to the market.
25:28
Understood. Let's go a little bit in the future
25:32
outlook. How do you see the tumor
25:36
on a chip and organ on chip markets evolving by something
25:39
like 2030? Where does can chip position itself in that
25:43
landscape? I have to say that
25:46
organ on chip will mature itself from innovation to
25:50
infrastructure. That is where the regulatory affairs are also going.
25:54
So I think and I hope that by 2030
25:57
it will be a standard in early drug discovery because since
26:00
2024 so many things happened from the day
26:04
one that the FDA said I am going to accept these models and we position
26:08
Can chip as a leader in realistic tumor on chip models
26:12
ready for precise oncology and ready to have customized
26:15
solution for pharma and biotech companies by 2030 we are
26:19
a leader. I'm
26:23
always trying to tease out a little bit of contrarian view here.
26:27
Many believe larger animal based preclinic models will always
26:31
dominate due to regulatory inertia. Why do you
26:35
think that belief is broken and what evidence do you have to
26:38
challenge it? I mean the regulatory inertia is
26:42
always real but the science is stronger and we don't have to forget that
26:46
the science is moving very fast lately. Animal models
26:50
simply do not replicate human body anymore. They do not
26:53
replicate patient response enough. The field is moving
26:57
toward human relevant system and regulators are also
27:00
acknowledging that. And when we think about combining the AI
27:04
data that we can have around patients, all models and
27:08
genetic models all together then none of the animal models
27:11
can really compete with that. That is my point of view on
27:15
this case.
27:21
For our listeners tuning in, I would be
27:25
curious what is one immediate question
27:28
you would challenge yourself to act on this week?
27:32
If you would be in Cazalus Seed, be bold. Leave
27:36
comment here. Let's talk a little bit about
27:39
advice for founders. If you're listening to
27:43
scientist, entrepreneur or deep tech founder, what are three
27:46
mistakes they should avoid and
27:50
three practices you should adopt to navigate
27:54
translation from a lab to commercialism
27:57
to commercialization?
28:04
I mean there's three points that I would really really
28:08
would tell them to avoid is to wait for the perfect data. There is no
28:12
perfect data. To not overbuild the tech before
28:16
talking to users. Sometimes there are some platforms that they are
28:19
so complicated that they cannot even work with it and
28:23
underestimate the complexity of the manufacturing and the steps that
28:27
you have to take. That is always even if it's about time or if it's
28:30
about cost, make it a bit more than you think it's enough
28:34
and points to adopt is early pilots to bring your
28:38
product or prototype out to see what is going on. The
28:42
IP strategy of course to think about it and really
28:45
secure it. That is going to save you and prioritize the
28:49
things that are important for the company without thinking about what is
28:53
going to happen if and if this prioritization is really
28:57
gonna make a huge difference.
29:01
We getting very close to the end of our interview and
29:05
I would be interested if Can chip over
29:08
achieves what is the one breakthrough in
29:12
personalized oncology we look back
29:15
on in 2030 and say ah, that came from cant
29:19
chips. Yes. That would be the drug response
29:23
prediction that matches the patient. That is what I always say. That is
29:27
matching the patient. That is not matching the animal. That is not matching a 2D
29:30
model. That's how personalized oncology become real. That we
29:34
can say this patient needs this specific drug. They get
29:37
it, they will get so healthy and the cancer will never come
29:41
back again. That will be great because a lot of people are
29:45
still dealing with
29:49
with, with cancer coming back and coming back and coming back. That's.
29:54
Really a tough spot to be in because it always gets harder to fight back.
30:00
That was depressing Note. I'm so sorry. We usually close our
30:03
interviews with two standard questions. So number one,
30:07
are you open to talk to new investors? Yes.
30:11
I learned it also that I should not close any doors, you know, because that
30:14
is not just about money. That is about the network. That is about the
30:18
knowledge that the investors also bring. So for a talk I am always
30:22
open. Uh huh. And of course the
30:25
usual question. Are you looking for talented employees? I
30:29
have to say that I have enough cvs that I can hire
30:33
minimum 10 people by tomorrow and they are highly educated. And
30:37
the point is that because we are an English speaking company
30:41
that makes it easier for them to approach to us because this language barrier
30:45
is real here. And I am, I mean we are
30:48
expanding but I already picked the people that I want to hire.
30:53
Aha. And we learned a pretty good secret. Pretty
30:57
big secret. You get good talent here in Germany if you are
31:00
an English speaking company. Aha. Aha.
31:04
Aha. So we finally teased something really cool out.
31:08
Thank you very much. Best of luck for your future mission for can
31:12
chips and and congratulations again for being
31:15
one of the winner of the German Startup Awards 2025. Thank you
31:19
very much. Thanks a lot.
31:25
That's all folks. Find more news streams,
31:29
events and
31:30
interviews@www.Startupradio.IO.
31:35
remember, sharing is caring.
31:38
Sam.