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How MIM Fertility Is Building AI for Healthcare Decision Support
00:29:30
How MIM Fertility Is Building AI for Healthcare Decision Support
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- [00:01]
A
In fertility treatment, timing is everything, precision is everything. And the smallest detail can change everything. But what happens when even the most advanced fertility science still leaves room for uncertainty? In this episode, we sit down with Ula Senkowska from Mimi Fertility, a company using AI and advanced imaging technology to uncover what the human eye can't see, detecting microscopic patterns in embryos and patient data that can help fertility specialists make a smarter, more informed IVF decision. Because in a process where every decision carries emotional, physical, and financial weight, seeing more clearly could change everything. Let's get into it. Welcome to lead with AI. I'm Dr. Tamara Nall. In each episode, we will take you behind the scenes with visionary leaders. Shape the future of AI across public and private sectors. Join us as we explore groundbreaking projects and innovations that are transforming industries and making a real impact on people's lives. Let's dive in. Hello, everyone, and welcome back to lead with AI. I am your host, Dr. T. And I'm so happy that you can join us here this week to hear another great guest guest and an episode about a topic we all love to hear about, and that's fertility. Before we go into our wonderful guests, let me say thank you to each and every one of you for tuning in every week. Because of you, we actually hit number one in technology on Apple podcasts last year, as well as being a W3 Gold awardee for guests and interviews, and then most recently, a Webby honoree. And that would not be possible without you. The. But then, just as important, our wonderful guests. So today I am just so excited to have Ula. How are you, Oola?
- [02:10]
B
Thank you. I'm great, actually. Thank you for having me.
- [02:13]
A
Absolutely. And this is a topic that is so near and dear to my heart, even with my own fertility journeys that I've had and we have had, we've had one other guest that talk about AI and fertility, but I love talking about Mem Fertility as well because you have a different approach in terms of how you can help parents in their journey to expand their family. So we're going to get into it, but before we get into the technology itself, let's talk about who you are as a person. Who are you at your core? What are you passionate about? And at what point take us to that moment where you found a need for mimfertility.
- [02:58]
B
Well, thanks, Faces. Well, great question, actually. Who am I? At my core, I think. Well, I would like you to know that as well. A bit, but. Well, at my core, I think I'm actually quite simple as every one of Us. You know, I have dreams and I want to build something meaningful and I would like to do something that I truly believe in and I love doing it so well. MIM Fertility, it's actually very, very much connected to my personal story and this is how it started. As MIM Fertility, we are building AI tools for fertility professionals. In our mission, we have a sentence or we have a thought that we want to help patients, want to help, help people. We want to help couples to have happy families and to help them come their dream about the, the being a parent come true. Well, I, I'm ex patient myself. My personal story here, I don't want to kind of bore you with, with the story. However, definitely this is something that shaped me and this is something that pushes me every day and gives me power to do what I, what we do and to, to strive for more. So I've been fertility patient myself. I took it from thanks to this treatment and my road was pretty bumpy and I've experienced a lot and having already like building or at that time we had, we had a software house and exploring, you know, what AI can do or how AI can improve many things. There was the spark and this thought that guys, I mean at the time, team of eight people that we should do, we should move into healthcare. We should do something that really matters. We should leverage our AI knowledge, our terrific excellence and to help people to make this change and eventually decided to go into the human reproduction space to this industry. I cannot say I'm not regretting any of those. It's demanding, it's challenging. I'm not regretting this at a single moment. I think today I can proudly say that we already achieved a lot and we are changing the landscape of fertility care. So we're pushing and as a company, not only we are developing technologies, but we are also working very deeply scientifically here. We also are pushing scientifically this field and medicine forward. About mim.
- [06:02]
A
That's amazing.
- [06:03]
B
Yes. So talking about the change at MIM facility, we want to make a change and we truly believe that we can do it. In our DNA or mindset of here, of the whole team is something that we are kind of unstoppable. We, I truly believe in, in the team that we are building with our brains, our excellence. We can, we can, we can do a lot and this is every day is a hard work. However, it's very, very, very satisfying.
- [06:41]
A
Got it. Perfect. Now let me ask you about the holy smokes moment. Give us a story or tell us about a time where one of your customers, your partners, be it a parent or be it a clinician or a clinic actually use MEM Fertility. And it changed everything for them.
- [07:06]
B
Oh, well, I think it's. There's not such a dramatic, you know, like, wow moment. However, for me personally, it's always a wow moment when I discuss, when I. When I. When I'm learning all that another new clinic, another huge chain of clinic or whatever it is in the world or small clinic, is using our systems so that we've entered again to another, another clinician's world and we are helping people out. For me, this is a wow moment when we have on our feedback calls, we hear, guys, it works. It really helps me. It makes my life easier as a clinician. And now I see that I have more structured data, I can work better, I'm more efficient, I can give more to my patient, and the patient experience is much better with your tools. So for me, this is a wow moment.
- [08:07]
A
You know, we have very curious listeners. We want to know how it works. So talk to us about how MEM Fertility works. If we were to open up the hood and look at the brain, what makes it give the results that it gives.
- [08:21]
B
All right, under the hood, under the hood of our technology, I don't know if I can hear. Talk a lot about it, about the technology itself. Of course, under the hood, what we've got is, you know, it's all about AI models, it's data pipeline, it's, you know, training, data sets. So but from the human perspective, I would really talk about one things help people feel more confident in the decisions that they're making. So we're giving the doctors context, we're giving the doctors signals how to operate and more structure, how to be more structured and equations. So, well, first of all, we have to have data. And I think what we achieved, and I'm really proud of that at MIM Fertility, we took, we have gathered in order to build our technologies, a lot of data from different parts of the world, which makes the data more robust. And we call it bulletproof. So it should work. The system should work in every single so. And here we come to like building the product. The technology is just like you are halfways, because then you need to validate it and you need to integrate it. Validation is a key. Integration is like the half of the success, the successful integration. So we validated several times our technologies inside the company and as well outside the company. For example, Ambrose of the embryo of decision support tool has been validated in Valencia, in the independent Institute. It went very well. We were really happy with the results, with the outcomes, and talking about the integration as well. We had to develop, in a way, in the sense that it seamlessly integrates existing systems of the clinics. So this is again, something that we truly lies in our hearts because we know that we should solve the problems of doctors and fertility professionals and not give them. And take away the burden and give them time. So it must just work seamlessly in the background so they just can operate, use the tool, but truly have the value without. Without having the extra stress. Right. So this is, for us, very, very important. So this is under the hood. I would need to take the, you know, our leaders of our AI teams here on board with me today to explain more about the AI models that we are using. However it works, we have a fantastic team of machine learning and deep learning experts, Polish, Polish data scientists. And yes, this is how we operate as an entity.
- [11:22]
A
Got it. And do I understand it correctly that a lot of it is driven based off image technology?
- [11:32]
B
Correct.
- [11:32]
A
Got it.
- [11:33]
B
Image technology, image recognition. However, we also take into account right now we develop tools that not only on the image, however, data sets, like on data from patient, data from emr, so electronic medical records.
- [11:49]
A
Okay, got it. Okay, perfect. That's what I want to make sure on that. Now let's move on to like a section that I call Real World Magic. Earlier, you gave me an example of how a clinician came to you and said, oh my gosh, this changed everything for me and my decision making with my patients. Tell us about an opportunity where you, as the first founder, was like, oh, my gosh, I can't believe that Mim did this. I created this. Like, this is really making a difference for so many parents and their fertility journeys. So take us to that moment where you were wowed by what you've built.
- [12:26]
B
Sure. No, happy. Thanks for this question. Happy to share the story. I have to just kind of, kind of small revise. I always think we and the team, our data science team developed that. And as I say, we always work in teams. So my personal wow moment was, is it truly happening? When a doctor from Mexico called me and she was explaining to me that they had a patient with only one embryo. And there was a. There was a whole team of embryologists that was looking at this embryo and they decided actually to discard this embryo. So not to transfer the embryo, not to give the patient the chance, the chance to. Because in their assessment, embryo was not good enough. Let's say someone of the highest quality embryo and they opened our application. And our application was essentially saying that this embryo has a chance to implant and it can. Let's say there is a chance. And they decided eventually, after seeing the assessment of our artificial intelligence, they decided to transfer the embryo. And the lady is pregnant and she has now a baby. So, you know, it was. It's such a story that even today when I talk about this gives me shivers. And I'm really proud of that. And I think we moved not only a needle, but we really help, Help, help patients, we help people. And I truly believe that we bring this value into the clinics. And I'm super happy. I'm very, very happy about this.
- [14:32]
A
That is so amazing. That's so amazing. I love these stories. They just really soften my heart because so many people are going through fertility issues. And so knowing that there are companies like MEM Fertility out there to help is just absolutely heartwarming, to be honest. Now you, as you mentioned, you're working with a lot of data training, data image technology, and clinicians are making recommendations to families on which embryos to use. How are you thinking about ethics in all of this?
- [15:12]
B
Very important, very important question. And I think a lot of discussions goes around ethics and AI, which is, I truly believe, very important. So. Well, in healthcare, decisions are just always technical, right? They carry real consequences for real people. So we have to be really responsible. And as MI fertility, we know that our goal is not to automate decisions, right? So to make them more consistent and more informed for the. For the doctor as well for the patient. So we protect the human in the loop. So eventually our technologies are built in a way that the decision, the final, ultimate decision, is always made by the human. So the human is always in the loop. So this is like the first rule or our ethical attitude to what we are building. Secondly, security of data. We do follow all gdpr, HIPAA and other regulations. We have compliance and regulatory officer on board. She takes care of it perfectly, that, you know, the data stays where, where it should stay, that it's anonymized and so on and so forth. And eventually we need to certify our technology so that as a software is a medical device. So we need to comply with all the regulations. Is it EU or now in us, we have, we have been for fully scanned. We did get the FDA clearance. I'm very happy about this. So we can move forward and then we can, we can launch our technologies on the US market.
- [17:17]
A
Got it. And tell us again where. I mean, you just got approval in the US for one of your technologies and I imagine is many, much of your work is in Europe, etc. Give us. It sounds like it's almost like worldwide. I think you had mentioned Africa, Australia, New Zealand, now the U.S. is that true?
- [17:39]
B
That's correct. We're entering markets. We're also in Middle east. We just entered Saudi into Saudi Arabia. So cloud based systems. And you can integrate I wouldn't call easily, but pretty easily. So we even can without doing the integration on site. We integrated with Australia, you know, not going there, not traveling to Australia even so we are striving to put our technology in every in the world. And we believe that every clinic, no matter what market, can use it and can have it can bring value to every single clinic all over the globe. So because eventually it should have patients. So yes, we are practically in all of the regions, as you were saying, Latin America, especially Brazil and Mexico and Argentina, the US and Europe. We are here in Europe, our headquarters and Asia and Australia, so. Correct. And as I mentioned, Lise.
- [18:55]
A
Okay, and how are you thinking about the future? Where do you see mem fertility in 2030?
- [19:03]
B
Well, it's actually around the corner almost. But taking into account how many things can happen like you know, just in the spectrum of one or two years. So I see MIM facilities definitely we are well global player. We are already however, I see that we developed. Well, we are now supporting decision making in some parts of IVF treatment. So we think about supporting more and more decisions. And there are so many decisions to take in IVF treatment by experts in the clinic. So we would love to support clinicians with our AI tools on almost on every step of this patient journey. This is where we are heading with MIM Fertility. So building actually an AI layer to the clinic so that it's like, it could be like one, I wouldn't call it like one holistic platform that gives you this incredible boost and it makes you more efficient, more consistent, more standardized and gives you the power to give better or even increase the standard of care and fertility. I think this is the goal and this is where we are heading as a company.
- [20:37]
A
Okay, that's amazing. Now let me ask you, if our users want to experience infertility this week, what's the best way for them to do that?
- [20:51]
B
Well, from the very practical point of view, you would need to go to one of the clinics that is using our AI systems. Of course. However, if I would like to give recommendation how you can or to our listeners, you know how or how to try or to explore or to taste our AI, I would start actually in a very simple way. So take one process that you think from your daily work, which is repetitive, subjective and could be time consuming, and try to look at it through a different lens. So ask yourself what data is behind your decisions, for example, and how cautious are you really? So you don't need to build AI from scratch from the one. But if you start to identify that where inconsistency or manual work is in place, you are already thinking in the right direction. So this is actually where exactly the AI systems bring the biggest value. So where, you know, where there's a lot of data, a lot of manual work and time consuming, we can speed it up and we can make it work faster and we can take from the human, from the expert, or from you, from the listener, and just automate it or give a recommendation or build a prediction system that will ease the work and give you better outcomes.
- [22:33]
A
Got it. All right, so now we're going to move to our question from one genius to another, which I totally love. And, and our last guest or one of our previous guests has a question for you. And that is if you could use AI to change one world problem right now, what would it be?
- [22:55]
B
Well, very good question. What I actually dream of, and I think this will happen eventually, is that, you know, with AI, with AI systems I always think about, of course, something in healthcare sector that, you know, accessibility to the same standard of care will be possible all over the globe. So no matter where you're born or if you are rich or poor or are you in Africa or, you know, Australia will, you will have kind of a very good, just because your clinic or your hospital is using, you know, very, a very good and very high level technology which is also included AI systems. So I think accessibility to the treatment and that everyone can afford. So actually I'm talking about, you know, democratizing the healthcare. The medical care is something that can move really forward and can help with. So yeah, I don't know.
- [24:09]
A
Got it. All right, perfect, perfect. So now let's move into our bonus rapid round. I'm going to ask you four quick questions and you're going to give me the first answer that comes to your mind. Starting with what is the most overrated AI or tech trend?
- [24:30]
B
Overrated. All right, so, well, I think I do travel a lot and go to different conferences, of course in human reproduction and for sure at the beginning especially. But till today I kind of get a question, will AI replace us? And will AI replace, you know, take away our jobs, embryologists are asking me and doctors and I think this is kind of overrated trend because I think this narrative is a bit dangerous. I truly believe it won't take the jobs away and eventually it will even make more work for us humans because what it's only doing, taking the burden of pretty simple tasks and that AI can take away and the whole complicated or the creativity is left for humans. So integral also decision making. So I still believe that more sophisticated jobs and you know that we will need even for example embryologists will not be anymore as a treated or this technical part of the work will be taken away. However this creativity scientific work and working with the patient will be, will be left and there will be more time even to concentrate or on more demanding tasks. So this is how I feel.
- [26:14]
A
Yeah, what about the most underrated tech trend?
- [26:19]
B
Probably is something that is kind of, you know those, those boring AI systems that improve the workflow. So we are not talking about this. It's nothing like wow. It's you cannot see it in a demo like saying wow effect. However, those systems already work in many organizations, many hospitals, many clinics and they can save up to I don't know either 15 or an hour on a day of an expert and they're working in the, in the back scene collecting data, structuring data, giving you know, making the workflow more efficient. So these are so called Boeing AI systems that you know. Yeah, well there's nothing like yeah wow effect. However I think this kind of you know, underhyped AI breakthroughs that already in place.
- [27:14]
A
What's a book we should all read?
- [27:17]
B
I'm not prepared for this question. However the book I've read last time I was reading the pricing roadmap.
- [27:25]
A
So Ola, my last wraparound question is wow us, surprise us. What's your big prediction for the future?
- [27:33]
B
Well, the prediction is that there is no prediction actually that you know, you cannot predict the future. But if you ask me what will happen and this I think that eventually, you know the organizations in the healthcare sector will not only compete with the numbers of doctors or the equipment or location, they will actually compete on the quality of their decision making systems. So how they collect data and how they use the data and how they learn to improve the outcomes from their data.
- [28:07]
A
Awesome, awesome. So this has been a very interesting and wonderful conversation. How do people get in contact with you? What are all the social media handles for both you and mimfertility?
- [28:18]
B
So you can find us@mimfertility AI, this is our webpage. You can find us on LinkedIn and Instagram. You can contact me anytime@ulaimfacility. AI this is my email address and you can also email us on any inquiry you wish. It's info. Happy to help you. Happy to support you.
- [28:48]
A
Thank you so much. Ola thank you so much for being a guest here. We really enjoy the conversation and thank you for all. Absolutely, absolutely. To help parents on their fertility journey. And I can't wait to all the little babies that are going to be created because of MEM Fertility. So thank you so much.
- [29:07]
B
Thank you very much. Thank you. It was an honor.
- [29:10]
A
Thanks for tuning in to Lee with AI. I'll see you next time as we continue exploring the cutting edge innovations shaping AI across the public and private sectors. Until then, keep leading with AI.