Today’s Advertiser helped make the production and delivery of this episode possible. But the themes expressed by the guests do not necessarily reflect the views of Inside Reproductive Health, nor of the Advertiser. The Advertiser does not have editorial control over the content of this episode, nor does the Advertiser's sponsorship constitute an endorsement of the guest or their organization. The guest's appearance is not an endorsement of the Advertiser.
Who’s adding the most value in IVF today—and who might not be here tomorrow?
This week on Inside Reproductive Health, Dr. Cristina Hickman, founder of Avenue Center for Reproductive Medicine in London, breaks down the fertility field’s evolving landscape. As a PhD embryologist and clinic owner, she shares her perspective on industry leaders, automation, and the shifting role of technology in fertility care.
Tune in to learn:
Why some clinic networks might be overextending by bringing too many verticals in-house.
How automation could scale embryologist efficiency to 2,000+ cycles per year.
The surprising relationship between robotics and AI in embryology.
Which companies are providing the most value right now--in lab automation, EMR, financial management, and cryo storage and more
How new intelligence could challenge the current standard of single embryo transfer.
Listen now to hear Dr. Hickman’s take on where the field is headed—and who’s leading the way.
The Future of IVF Is Here—Fully Automated, AI-Powered, and Game-Changing
Meet AURA by Conceivable Life Sciences—the first robotics-driven IVF lab designed to revolutionize fertility care.
AI & Robotics: Precision-driven automation for every step of the IVF process.
Scalability & Efficiency: Higher throughput, lower costs, and consistent results.
Accuracy: Minimize human error and optimize embryo outcomes.
Accessible & Innovative: A bold leap toward the future of fertility care.
Be among the first to see what’s possible. Visit Conceivable Life Sciences today.
-
Dr. Cristina Hickman (00:03)
It will make you unemployed if you don't adapt to the new technological infrastructures and you don't acquire the necessary new skills that are needed for the embryologists of the future. Okay? So that generation of embryologists will be struggling to find a job, but all of us can learn, all of us can evolve, all of us can adapt.
Now with Conceivable, we finally get this level of efficiency that allows us to better understand, to better treat more patients per embryologist. And the numbers are great. We've now gone in this journey that I've just told you from 80 cycles per senior embryologist to 2000. It's a completely different scale.
Griffin Jones (00:57)
Who's on their way to becoming obsolete in the IVF space? Who are the players adding the most value in the fertility field right now? My guest names names, at least for the second question she does. I'm talking with Dr. Christina Hickman, the founder of Avenue Center for Reproductive Medicine in London. She's a PhD embryologist who, as the owner of her own practice, finds herself as the maestro of the orchestra. These seats in the IVF orchestra
are all of the different companies in the fertility sector, from AI clinical prediction tools to witnessing companies and every point solution in between. She explains the relationship she sees between different point solutions and the end-to-end ecosystem that the consumer-driven patient marketplace demands.
Dr. Hickman issues a warning to fertility clinic networks who are trying to take every last service in house. She explains why robotics improve AI, not just the other way around, and what new intelligence means for the concept of single embryo transfer and patient success rates. Does it flip the concept of single embryo transfer on its head as we know it today? She shares which companies she thinks are the best right now in each of the categories of EMR.
financial management, cryo storage, clinical prediction, and more. And if the status quo is 80 IVF cycles per embryologist per year, how is Dr. Hickman's clinic doing 500 IVF cycles per embryologist? What is she doing? And what did she see in her visit to Conceivable Life Sciences, the lab in Mexico City that's automating the IVF lab, that will scale that 80 cycles per embryologist number to 2,000? Enjoy.
This is my conversation with Dr. Christina Hickman.
Griffin Jones (03:05)
Professor Hickman, the conductor, welcome back to the Inside Reproductive Health podcast.
Dr. Cristina Hickman (03:11)
Thank you Griffin for having me, it's a pleasure to be back.
Griffin Jones (03:15)
Are we going to get to 10 million IVF babies born worldwide per year with point solutions, or do we have to blow the whole thing up and replace it with a new end-to-end solution?
Dr. Cristina Hickman (03:30)
Yeah, I definitely am on the end-to-end camp here. We've been trying the point solution for years and it's worked for us until today. you know, building up one solution for looking at sperm assessment, one solution looking at the egg assessment, having this artisanal approach to practicing embryology.
It's okay, but it's not going to allow us to scale to the level that we need to go to. So a full end-to-end approach is the only way that we're going to solve the entire journey that this patient is going through. Not looking at information in a siloed manner. Bringing all of it together so that we can make decisions which are specific to the entire concept that this patient is experiencing.
This for me has been something that throughout my career we've been trying to provide this end-to-end solution and Really it hasn't been until it clicked to me that this is not going to happen with a single company Doing the end-to-end it's too big a journey. The fertility is too complex We need to create this ecosystem of different companies working together So that we can tackle every single challenge at once
Griffin Jones (04:46)
So when I hear multiple different companies in an ecosystem, to me that sounds more like point solutions. Tell me about how you see the difference.
Dr. Cristina Hickman (04:56)
Yes, so at the moment what we have is companies who are looking at focusing on what I call it the what's in it for me, right? So they're trying to build their own proprietary solutions to their patients. So I'm thinking of this at the clinic level. So rather than going off to bring in a commercially medical grade robust AI solution, they're trying to build it in-house with limited data, which leads to
all the challenges that we see associated with AI, know, biased information that's not generalizable, that doesn't provide an explanation and traceability. So this means that you're trying to kind of provide yourself with one, everything under one proprietary company. But what, what the approach that we've been giving is, okay, why don't we go out there and try to find all the different instruments in the orchestra, so to speak, right? So
who is the best violinist out there? Who is the best cellist out there? And put them all together. Now we need to orchestrate it all so that it doesn't feel like a single instrument playing. When you get everybody in an orchestrated manner, it now feels like a completely different music. And this completely different music is the end to end approach. So yes, there's multiple companies, each one focusing on an instrument to get you there, but...
The experience that you provide by stitching it all together allows you to provide a whole new experience to the patient, a whole new experience to the doctor. So that you're not just getting embryo assessment or sperm assessment, you're getting a holistic approach to the patient.
Griffin Jones (06:36)
So is it the clinic's role in your view to be the end-to-end solution and then every potential partner are those different point solutions that end up being the seats in the orchestra?
Dr. Cristina Hickman (06:47)
Not necessarily. The clinic could be one of the instruments as well. So in a truly community-based approach, it becomes less clear who is the maestro, because everybody is playing a role in that. what I say that determining who is going to still be alive in the future, who are going to be the dinosaurs who are going to cease to exist,
is going to be determined by how integrated in this ecosystem you are. it's now about, in the past it was about, I'm building my own proprietary thing. But the problem of doing that is that your own proprietary thing is no longer the best in the market. So it's really within this ecosystem that we start understanding what is the true end-to-end solution. And this is when we start looking at certain tools that provide you
this end-to-end in a way that has never been able to do before, such as the conceivable system.
Griffin Jones (07:49)
So who's the maestro or is the patient the maestro?
Dr. Cristina Hickman (07:53)
The patient is the one who benefits from it first and foremost. So we have everybody saying that they have patient-centered care, right? And so this is something that they say, a patient-centered care, but I'm not gonna use the best product in the market because I wanna use the one that we built ourselves, right? And this now means that you're not patient-centered care, you are clinic-centered care, right? I'm gonna keep the patient waiting in the waiting room because it makes me feel like an important doctor.
you're definitely not patient-centered care when you're thinking in those terms. I'm going to create a waiting room that doesn't feel like, that feels like a hospital because that's as cheap as I can get it. That's not patient-centered care. Patient-centered care is you're sitting down and you're thinking strategically, what is the best way to apply the global resources so that we can achieve the best for this patient? If what I've built,
is inferior to what's out there in the market, let's get that thing that's out there in the market. And now let's find a way that it doesn't feel like it's separated from everything else. Let's give the transparency of this information to the patient. And this means allowing things to become obsolete quickly. In a world of fast innovation, you need to be prepared to let go of things that are no longer at cutting edge, right? And in the world of digitization and AI,
this is happening incredibly fast. Right. So what, what analogy that I heard from, from Alan, from one of the founders of Conceivable, he was telling me, Chris, I don't care about where the puck has been. He was talking about hockey, right? I don't care where the puck has been. I care about where it's going. Okay. And then I care about being prepared for when it gets where it's going. Right. And it's this, this adaptability to be able to
to foresee where things are going and letting go of the past, letting go of the old technology and starting to embrace what is the way that we should be in the future. I know I'm using past and future tense at the same time, but that's the point. The point is that we accept that technology moves fast and this requires a community approach.
Griffin Jones (10:07)
So it's a lot more of an adaptable system. Is this what David Sable means when he says ditch the travel agent model of care where you used to have a travel agent plan your entire vacation and now you go to a Priceline or an Orbitz and you might get your rental car over here or you might get an Uber or Lyft over here. You might get a hotel over here. You might get an Airbnb over here or find some other accommodation and then you might get your
and you might bundle it in or you might get your airfare somewhere else. And so what I think what he's suggesting is that as opposed to having the everything done in one place that patients have a lot more to be able to shop if it's able to all integrate together. Is that the way you see it?
Dr. Cristina Hickman (10:53)
Yes, but also having it in a way that the patient has full visibility of what's going on. Gone are the days where it's a doctor-led approach. It's now consumer-led. And we need to figure out a way that we create this level of transparency that didn't exist before. And having this ability to get fertility care on the palm of your hands and empowering the patient to be able to make those decisions.
in a more involved manner, in a more data-driven manner, in a more visual manner, in a more engaging manner. This is the direction that things are going, right? So this is what I kind of expect and what our patients are expecting from us as well.
Griffin Jones (11:34)
You talked about conceivable life sciences and there are some people that probably seen some of what's going on with them in our news coverage and or on LinkedIn. And there might be other people that don't know what conceivable life sciences is. So I want to ask you about your visit. But conceivable life sciences is a venture automating the IVF lab from right after retriever retrieval to right up to the point that it goes back to the clinician for transfer from ICSI from
dish prep to everything that's happening in the IVF lab being automated by artificial intelligence and robotics. You just went to see their lab in action at a fertility center called Hope IVF in Mexico City. What was that like?
Dr. Cristina Hickman (12:19)
It blew my mind. Honestly, I had seen all the previous creations from the same founder team in the tomorrow.
I have seen their proposals that we're going to be putting this together, but to see it in reality, you know, it's no longer just a slide on a PowerPoint. It's no longer a CGI. This is a three dimensional, full reality existing machine. And just to watch the capabilities and the potential, you know, we were just sat there just talking about, do you guys realize what you've created here? you know, give you some numbers. Okay. So the British society here.
They just published a guideline last year talking about how we should have 80 cycles per qualified embryologist. 80 cycles. I know this in my mind that was like no way because in the technologies that we've created we've published already at ASRM and also at Escherich that if you're using the AI solutions you can achieve 300 cycles per embryologist, right? Because you're removing a lot of that administration that is spending
precious embryology time. Now in avenues what we've done is a full end-to-end approach using the best products in the market, having everything talking to each other. So we achieve 500 cycles per embryologist. Why? Because we are making data-driven lessons, so we remove the administration. Everything is data-driven decisions, but you're still doing the artisanal work.
So if you ask the embryologists, what were they doing before avnios? They were doing administration. What are they doing now in the majority of their time? They're doing artisanal embryology. Now, when you move on to conceivable, you're not talking about 500 cycles per embryologist, you're talking about 2000 cycles per embryologist. Now, they're no longer doing the artisanal side. The artisanal side is replaced by robotics, but that data-driven approach remains.
And a data-driven approach now, the amount of information you're capturing because you removed the variation that comes from artisanal work means that you now have to spend more time doing more intellectual decision-making. So less artisanal, more intellectual.
And the ability for you to go to 2,000 cycles per embryologist, this is the solution. This is the true end to end that we need to achieve to be able to serve all the patients out there that need our support.
Right? So going the way that we've been going is not scalable to the level that we need it to be. Now with Conceivable, we finally get this level of efficiency that allows us to better understand, to better treat more patients per embryologist. And the numbers are great. We've now gone in this journey that I've just told you from 80 cycles per senior embryologist to 2000. It's a completely different scale.
But what really kind of made it special is when we started looking at the movement and precision of the robot. We started kind of coming up, wait a minute, there's more that we can do here. It's not just about efficiency. It's not even just about the precision, right? It's the possibility that we might be able to enhance embryos and not just use AI to predict what's going to happen.
we might be able to use AI to identify issues with the embryos that we might now be able to rectify. some of these potentials are only possible in a robotic scenario. So examples of that are at the moment in avenues when we're vitrifying and we're warming, every single procedure that we do, we record. We're very proud of the fact that we may not have the biggest data set in the world.
but we have the biggest number of data points captured per patient. So this means that we have videos of everything that happens in the lab. When they warm, when they freeze, when we icksy, when we biopsy, we have all these videos which are all geared towards training future AI. Now what you have here are some challenges that are, okay, so maybe the embryo just zooms in a bit more and it zooms less, you know, or maybe it's at the edge of the image as opposed to in the center.
And that's the issue with the fact that it's quite artisanal. So this makes it harder for our AI to learn from it, which means that we're slightly limited of how much AI we can apply because of this limitation of the artisanal aspect. The moment you apply robots, now you're able to capture every image with the egg in the center, every image with this level of focus, every image with this particular filter. You remove all the artisanal aspects. You bring a level of standardization.
that will now allow us to pick up things about these embryos that we've never been able to before. And one example of that would be like when we've done a lot of work where we use AI to track not just each embryo, but each individual cell of the embryo. We know that this cell derived from this one and the grandfather of this cell was this one. So we can do the cellular linearity tracking.
Many clinics do more for kinetics. We're doing something else, you know, looking at the cell lineage so that we can look at individualized care, not down to each embryo, but each cell in the embryo, which is pretty cool. You can't do that without AI, right? But the beauty here is that with the robotics, potentially, you might be able to identify these are the cells that are too far away from each other. Okay, so maybe a slight nudge.
on the embryo, a slight little hug, little squeeze on the embryo might be able to fix that gap between those two cells that might now lead to a blastocyst when before it wasn't going to be able to. And this level of intervention, this level of micromanipulation cannot happen without robotics. So this is when I saw the system that had been built by the conceivables team.
all of these ideas started popping up going, well, if you're able to do that, by doing just get the arm of the robot to do this movement instead, we now are creating a whole new way of practicing embryology. And that would be a complete game changer.
Griffin Jones (18:37)
How do you do this on the clinical side though, Christina? So I see in the lab side, you have human beings currently doing a lot of robotic tasks, and therefore it makes sense for a robot to do those robotic tasks. In the case of the clinic side, we're talking about human beings and a lot of different things going on, probably a lot more variables in the order of operations. How do you begin to get this level of efficiency and scale?
on the clinic side.
Dr. Cristina Hickman (19:08)
So really it's getting that balance between the three David Sabel parameters, right? Yes, we want efficiency.
But because we've got so much savings because of technology that we're incorporating our end-to-end solutions, can let go of some of that efficiency in order to provide better convenience to the patients, right? So it's a balance between the two. So an example of that is, yes, our embryologists are not doing as much administration, but they spend more time with the patients. So the patients get full access, they get to see their embryos developing live, okay? So they're sitting at home and
through their phone, they can see the moment that the cells have divided, the moment that it reached the eight cell stage. Now a lot of embryologists tell me, don't your patients get anxious? Don't your patients get, know, does this actually help? Well, we know from data, including from KindBody, including from Institutes Smart Cares, including from our own clinic, that around, on average, across these clinics, around 78 % of patients see this as reassuring and help them better understand their care.
a fifth of patients, they find that it makes them anxious. So it is true that it does make patients anxious, but it's a minority of them. The majority of them, this allows them to better understand their care, but it cannot be offered to the patient on its own. So we use the time from the embryologists that we would otherwise have wasted on administration to be face to face with the patient, having a call just like we're having now because they're sitting at home. And then we share the screen.
with the embryos developing using the fertility system and showing all of the different things that AI is highlighting for you. Right? And that extra information may not get that patient pregnant, but it's going to help them better understand their care and better understand their personal fertility potential. Right? So this is kind of where we see the shift in time of the embryologists. So when I see Conceivable coming in,
I see there being a further switch where we are going to be capturing so many more data points on these particular embryos. We're going to have these huge data centers where embryologists sitting watching all sorts of camera and additional data points about these embryos and eggs that will need an additional level of explanation and human contact. It's getting that balance right between technology and compassion.
Technology on its own does not work, not in reproductive care. It's too human, it's too important a moment in your life. You're creating a person during this care. So this means that we're going to have to have more compassionate embryologists in the future who are not hidden away in a locked up lab. They're going to be involved in this communication of this data and information coming over to the patient.
Griffin Jones (22:02)
You have an embryologist speak to every patient who's going through IVF?
Dr. Cristina Hickman (22:07)
multiple times. So on day zero, on the day of our collection, this is when we find out whether this is going to be one of the 22 % of patients who don't want to see their videos live. So we give the patients, we personalize whether they get access to the link or not. So that happens on day zero. So let me explain what is going to happen the next few days. Then on day three, that's a video call. On day one, we give a phone call and we release the link.
On day two, we may do a call or not, depending on whether the patient wants daily updates or not. But what's routine is a day three call. On day three, we sit down with the patient and we can already tell them accurately, is this going to form a blastocyst or not? And then at this point, we already giving them some further determinations of an example would be I got a patient with 17 eggs.
and we can tell them already with certainty either day two or day three we tell them we don't think you're going to get blastocysts. I know you have 17 eggs but looking at the AI assessment the chances of or our level of confidence that a blastocyst will be formed is extremely low. And then we have another patient who has one egg and that patient we get a score of 10 so we tell them we're extremely confident that this is going to form a blastocyst.
Usually I would have given that advice the other way around to these patients, but now I can manage their expectations better. Avoiding that roller coaster of emotions, right? And this means that I can have this discussion with them with all the little color coding showing on the embryos. Here's your inner cell mass and here's a morphokinetics that was right or wrong. You just need to understand the traffic light system to know this is green, this is good, this is red, this is not good, right?
so, so we're able to kind of sit down with the patients. It's not about alarming or raising concerns, but it's about managing their expectations with their own data. And this maintains the trust in the clinic. Now imagine doing that, not just on the embryology side, imagine doing that with bits of information that's coming from the cumulus, from their uterus, from their follicles, from their, so this is kind of going,
with that complete package to the patient so that for that two thirds of patients that don't go home with a baby, have a reason, we have the key information, this is what we're going to do next because we have all this information from your past, right? So every cycle becomes a diagnostic tool that contributes towards making the right decision within the journey of this patient.
Griffin Jones (24:42)
So what if the patient has questions that are more on the clinical side than the embryology side? So the embryologist explains it's day three, it doesn't look like this is gonna grow to blast. And what if the patient asks a question like, well, how are we gonna change my protocol next? And it's a question for the REI. Is the embryologist just stuck saying, sorry, you're gonna have to wait to talk to the doctor?
Dr. Cristina Hickman (25:03)
So the beauty is that within our ecosystem, we have the communication tool with the members of the team. So the patient has access through their app to the different departments. And within that, we can very easily connect the patient with the relevant departments to support. Because it might be a genetics question that we can send to the genetics. It might be a donation. Can you tell me more about the donor eggs that I've just received? I know they've been matched. It might be a...
It might be looking at, okay, can you tell me how this compares with the cycle I've had in the past? You know, so this sort of thing allows us to have this direct contact with the different members of the team. And this...
Interestingly, we give the patients the option that they can call us or they can use a chat like function within the app. And the chat like function is by far the preferred method of communication by the patients. This I found surprising, but they like it because they have everything that they can refer back to what's been written. So even when we do a verbal communication with them, we have the AI tool that's recording it and then create a little summary to them so that they know what's been
communicated to them in writing at all times, which is extremely helpful for the patient.
Griffin Jones (26:18)
Have you been able to measure yet what this has done to conversion to treatment? Or patient dropout?
Dr. Cristina Hickman (26:25)
So yes, do have, the beauty of what we have at the moment is the live KPI system. So all the information, all the data that's being captured during the care goes into this live. We don't have to wait for the KPI meeting at the end of the month to know what our FERT rates are or how many cycles that we have or how all the conversions are. And we can see the differences between the different doctors and so on. And there are...
actually widely different from one doctor to the next. We're able to identify who needs further support, who needs further training, and so on. So this is the beauty of the live KPI system. I haven't been able, what I haven't done is done a comparison of before and after because we've developed the clinic around this technology and infrastructure. So it's the first clinic in the world to be fully end-to-end AI driven. So this has made
it's hard for me to be able to answer your question to prove improvement. What we have is a lot of feedback from the patients going, wow, compared to my previous clinic, I seem to know more about my care than I knew before. you know, having this approach to the patient of seeing their journey as a whole, not on a per cycle, not per embryo transfer, we're looking at, we're going to do a triple-I collection for this particular patient. We're going to, or the other one,
to just do frozen embryo transfers for her or for this one we're going to cancel these embryo transfers because AI is telling us the chances are so low let's go straight to another egg collection to save on time. So we're making some some more bold decisions regarding the journey of the patient. For me the measure of success
is does this patient go home with a baby within two years of knocking on your door? So nine months of that is lost with carrying the baby. And then so this leaves you with a year and a bit to get this patient pregnant. And this includes them going on holiday, having a break in between cycles. But you need to have that patient with a baby in their arms, every single one of your patients within two years. And this is something that I think should be the measure of success for everybody.
Griffin Jones (28:26)
I was gonna say it's a much more patient centric way of thinking about it, isn't it? Because you wouldn't report to SART that way, you wouldn't report to the CDC that way, and that's the way we often think. But of course, that's the way the patient thinks. How long is it going to be before I have the bundle of joy in my arms, including pregnancy, including all of the things that might disrupt life during that time?
Dr. Cristina Hickman (28:40)
Yeah.
And we use that from a financial perspective as well, right? So how can I reduce the cost of care by not spending the patient's time on transferring a DUD embryo, right? So an example of this is our measure of success in the UK that ranks all the clinics is per embryo transferred. But if the AI is telling me this got a low chance of implanting,
The best odds are either I cancel the transfer altogether or at least transfer a couple of embryos because we know that they're not going to get twins with these particular embryos. Our AI is giving us confidence in that. But I'm not going to waste their time doing two transfers with two embryos that are not going to lead to an implantation. Right. So we start making these decisions that if that is the right decision to the patient, but in terms of the success rate that the UK uses per embryo transfer, that's going to put us lower in the rankings.
but that is not the right success rate to use, right? So if we're making the right decisions in identifying these embryos should be transferred in pairs and these embryos should be transferred in single, and I am 100 % accurate in identifying when multiple pregnancy will not take place, then this should be the better measure of success for the patients. Do they go home with a baby later? And I don't want them going home with twins and I want them to be healthy babies on their arms.
Griffin Jones (30:11)
this AI clinical decision making tool might be one seat in the orchestra. Do you think that it should generally be different companies occupying different seats in the orchestra? Do you think it's a mistake for one company to try to occupy every seat in the orchestra itself?
Dr. Cristina Hickman (30:29)
I think that the approach, if you look at it as a model, the Apple approach, they didn't try to go out there and build every single app. They created a platform that the other apps came in and used the Apple system as a platform. So this is what we should be focusing on. If you consider the clinic using conceivable, so conceivable coming in as an example, that's a change in your orchestra, right? You're going to be removing all of those traditional
laboratory equipment that you have in the lab and you're to replace it with this robot that does everything. Right? So this is one change in your orchestration that's going to happen. But there are other examples as well, because yes, it might be that you're using the conceivable tool to do the assessment of the egg, but then I don't know, fertility might come in and they have a better way of assessing the embryo.
So this ability to plug and play and interplay between the different companies allows you to get the best of all the systems and also puts the pressure on the companies. It is up to them to stay cutting edge. It's up to them to maintain the evolution. Are they still using old fashioned AI or are they using LLMs now? Right? LLMs are going to become obsolete very, very quickly. What's the next thing that's coming in? Right? So
what the way that we've been building AI five years ago, that's gone. You know, the RCT that they did on the VitroLife tool, by the time the RCT finished, they're using two versions later, right? There's no point in us delving in digital tools for more than one or two years. And that timeframe is going to get shorter and shorter. And for companies to survive, they're going to have to focus on a certain niche. And then that niche,
needs to go into this bigger platform that brings it all together. And so for me, that's how I see the future of our ecosystem coming. It's going to be lots of companies willing to work in an integrated manner. No more of those old fashioned EMRs that are not integrated with anything, right? Those are dying. are, their days are counted. Now it's not thinking about a digital solution. It's thinking about
an integrated approach of non-proprietary, lots of open source materials that come together to create a whole new synergistic approach to patient care. And that's not, I don't say that as something that should be in the future. This is happening today. This is how we work here at Avenues. And I just see like what Conceivable is bringing as a whole new layer of exponential evolution.
to what has already come into play.
Griffin Jones (33:13)
Who gets to be Apple?
Dr. Cristina Hickman (33:14)
Who gets to be apple? Do we need to have a single apple? Can we be multi-sourced? I think there's going to be an apple in each area, right? There's going to be an apple of who is in front line with the patient. There's going to be an apple that's doing the robotics aspects. So I think Conceivable will obviously corner the robotics side of things. But I see others playing the role of kind of being the maestro.
Traditionally, the person who or the entity that controls what reaches the patient and what doesn't is the clinic. But now we're seeing more consumer led brands coming in who are actually connecting with the clinic, with the patients better and bringing them to the clinic. So they're partnering with the clinics so that the clinics are no longer the maestro in that scenario.
At the end of the day, determines what meets what reaches a patient or not is the front, the trusting face that the patient has chosen for them, which increasingly, I don't know if that's a good thing or a bad thing, we can have a whole debate on this, but increasingly we're seeing more diverse front lines than just the traditional doctor.
Griffin Jones (34:28)
So I'm seeing your point that there might not have to be an apple, that if everyone is able to integrate with everyone else, then you wouldn't necessarily need to have that central sort of apple. But then the analogy breaks down if everybody's an apple. And it seems to me that some of the fertility clinic networks, maybe particularly in the United States, are trying to occupy that apple space.
Dr. Cristina Hickman (34:54)
Thanks.
Griffin Jones (34:54)
where they
themselves are the ecosystem. And so now we're making our own EMR, and now maybe we're making our own AI solution, and now maybe we have our own genetics
Dr. Cristina Hickman (35:05)
the irony there is that the more they try to be the apple, the less of the apple they are.
Okay, because the more that you're trying to make it what's in it for me what's in your proprietary the more that they trying to to say I'm going to build my EMR and I'm going to be the clinic and I'm going to be the the robot and I'm going to be the more they try to do all of that the less they're good being the best at any particular aspect so in comes somebody else who who turns around going who's the best in robotics I'm going to use conceivable who's the best on embryo assessments I'm going to
is fertility. Who's the best on X, Y, and Z, right? So you start putting it all together, that can now create something that feels different to the patient. Remember, we're leading into consumer-led. So if this becomes noticeable to the patient, that, wait a minute, but they can see the eggs with a completely different visual. They're giving me an explanation to why I am not getting pregnant. You're just giving me a ranking, right?
So when you start getting this difference in care, the market eventually notices it. And this is why I think that this approach of, I'm going to do, this is a difference between the what's in it for me and the consumer-based, sorry, the community-based mindset. So what's in it for me is going to lead to the dinosaurs of tomorrow. The consumer-based mindset.
The maximized interconnectivity within the existing best technologies in the market is what's going to maintain you in existence for the future.
Griffin Jones (36:40)
What about in your view the limited concentration of buyers? Does that disrupt this ability to have a community type of orchestra where you have so many different companies innovating in different seats because you might have a really good EMR solution, for example, but if 60 % of the clinics are owned by six or eight companies, then it's really hard to get that scale as an EMR company.
to where previously maybe you would have had 500 to 1,000 buyers and all you need is 20 and so you could carve out your own little niche. But now getting 20 clinics or especially if there are certain volume of cycles, that's a lot harder to do because of this limited concentration of buyers. How will these companies in this community based system be able to get through that?
Dr. Cristina Hickman (37:33)
Yeah, so the roles of each of the community players are going to become more more defined and the niche of each of the community players is going to be very, very focused. So I do see that as being the case, but I'm not saying that nobody should have the ambition to be able to fulfil the whole role. I'm just saying that if you're going to do that, make sure that you have the right instruments in your orchestra, right?
It's a big gamble and I've tried doing it myself and I've tried doing it with companies that raised more than a hundred million and when you start putting it all together, all the different companies that we put in our ecosystem, it's billions of investment that have led to the ecosystem that we have brought to the patients, right? But it's not feasible to raise billions to be able to build an equivalent product in the market. And I think that's why
It's not either we're going to see a change in mindset or we're going to cease to exist because they're players now who are doing the whole community approach. It sounds like a socialist approach. I'm not a socialist, okay? It's just trying to think not at the level of what's best for my company, but look up from a field and say, if I were to put the best players in these different places, how can I get the maximum return for the patients?
How can I get the maximum KPIs from David Sabel in terms of the convenience and the cost and the success rates? How can I really kind of play those to the maximum level? And you're going to have to do that through partnerships.
Griffin Jones (39:03)
do you label these different seats in the orchestra either in your head or on paper somewhere? Like do you think, okay, this is the cryo storage seat and this is the patient triage seat and this is the clinical AI seat. How do you think about that?
Dr. Cristina Hickman (39:19)
So we do, but what I find is that sometimes what I thought was one seat gets split into five different seats. So what I thought was the equivalent to the patient facing app, I now find a whole bunch of other tools that I incorporate into that to try and create more, a different experience to the patient, right? To get a different dynamic. So for instance, yes, there's
a place where all the data gets recorded from the consultation, but it's a completely different player that's doing the recording and then turning that into summary notes that get sent left, right and center so you don't have to use the old-fashioned dictaphone. So the communication that we're having with the patients going back and forth, having that in a centralized data set that now uses a completely different tool that measures the positivity and negativity of each word.
so that we can predict when a patient is going to think about maybe having a complaint. So these are what I thought was one tool, which was a patient app, turns out to be a dozen tools within that. So I don't want the patient having to write their name during the registration. So we have a different partner that all the patient does is take a picture of their passport. And from the passport, it takes their name, the date of birth. No more incorrect data names, no more having to...
you're on the area with an I, not a Y, you know? So this is something that you take the information directly from the source every step of the way. And this then allows you to have a a more streamlined, less mistakes. You're spending less time on these mistakes. And the patient is not seeing mistakes coming from your side, which gradually erodes the trust as they're going through care, right? So yes, we do have very specific seeds.
but we find ourselves that the number of increases as new technology comes in. We had somebody else who just popped in into our ecosystem where they're working on WhatsApp tools that communicates with our central database, creating new ways to communicate with the patient. So this wasn't a seat before, but it's become a seat as this new technology kind of emerged.
Griffin Jones (41:29)
So you are the maestro because you're the one saying who's playing in a given seat or not. And I remember in conversation you told me that if you're not the best violinist, you're out of the orchestra. Tell me about a time where you've made a decision like that.
Dr. Cristina Hickman (41:40)
Right.
We've changed our data capture point. We've changed the patient app has changed. The EMR has changed. The AI tools that we're using in the clinic have changed. I don't want to name the companies that have been replaced, but we have had several examples where we've made major changes in our ecosystem.
and sometimes quite central. Very recently we changed the central core of the data because the data set was not being stored in a manner that would allow us to use AI to learn quicker. It made it harder to integrate into. I'm not even talking about EMRs now. I'm talking about two generations later after EMRs where we modified the entire central structure. We had before...
Each of our individual doctors had their own sub-dataset. We've now created a system where they've all merged into one, still providing the independence and the and the privacy within each of the doctors within their ecosystems. So we have already replaced, I mean, we've only been open for a year. We've just had our first birthday cake, first year birthday which is aligned with a lot of the...
the babies coming through as well now. It's a nice stage to be at. But the point is you have to have this mindset of being comfortable with change. And we recruited a team here at Avenue's that is not just comfortable with change. They're looking for the next change. They're excited about the next change, right? They're going, woo-hoo, look at this tool that we have just...
Griffin Jones (43:00)
I bet it is.
Dr. Cristina Hickman (43:22)
brought into our ecosystem two months ago, but there's something better coming in and they celebrate it. But there's also a way for us to be able to feedback the companies that have been removed from the ecosystem. come back to them to say, go back and I needed to get better. The bar has raised. Okay. I needed to get better. So we actually provide the feedback to say, this is what you need to go with next. Okay. Why don't you focus on this particular niche?
I have an empty seat on our orchestra. I need that seat taken by someone. Why don't you guys focus on that? You're really good at something slightly off. You divert your attention to this. You can come back to the orchestra. So we have violinists that become cello players, right? And this is something that, look, I know you're not the best anymore in the market for this, but you have this particular strength in your team. Use it. Okay. And we will, we will provide you the data to help you develop that.
We will provide, we will open our doors. I'll put a team of my embryologists sit down with you to help you develop it. Right? So it's creating that relationship with the suppliers so that we are here at their beck and call to help them succeed. Cause if they succeed, we succeed. Right? So this, is kind of the approach that we've had all the way through.
Griffin Jones (44:38)
Who would you say are some of the best players in the orchestra right now? And you can name names of companies and we know that we're recording this in February of 25 and it might not be the same answer as what you have in February of 27 or even February of 26. But right now in February of 25, who would you say some of the best players are?
Dr. Cristina Hickman (44:58)
Sure, fertility is one that's full disclosure. I have worked with them for two years as their chief clinical officer. I don't work with them at the moment. Now I am their customer. And I think when it comes to embryo assessment and egg assessment,
and they are by far the best ones in the markets in terms of the experience we can create to the patient in terms of the efficacy of their tools. The patient facing side we're using Wawa at the moment, so Wawa Fertility is one to look out for. I like the ability to create these customizable
notes all the way through. So our team likes the fact that they can just create their own templates. So it's not as rigid as a traditional EMR. But we're able to pull the relevant information that we need from that. Their financials and their billings work really, really well. In terms of managing our financials, we're going with Xero. So Xero at the moment, I still think is the best product in the market, but we're still no lookout for other tools out there.
When you look at the follicular assessment, believe Folliscan is the leader in the market at this point in time. Also when it comes to the assessment of your endometrium, that would be with Folliscan. Tomorrow is still the leader for cryo storage. So the robot captures the data in an automatic manner. We have the full traceability coming through and then you can connect it back with Wawa.
to provide the patient-facing cryostores. Right now, in terms of time lapse, we're using the embryoscope, but I believe that this will then be replaced with the conceivable system. So this is just some of the many, many players. RFID, we're using the RI witness, but not using the RI witness in its traditional sense. We've rigged the backend of the data capture.
so that the embryologist no longer needs to go to computer to document their procedures and so on. So effectively we have this whole range of tools. We have Fertile Eye at the moment who looks at their assessment and determining what is the right day of doing your egg collection so they can maximize success rate whilst improving your efficiencies on your day-to-day operations in terms of volume of egg collections per day. So these are, it's not...
I'm sure I feel like I'm in the Oscars trying to name everybody who was involved in the movies. I'm sure I have missed a lot. But there are some fantastic tools out there and a lot of these that I'm naming are startups, right? They're not huge companies that have been with us for the last decade. So I think this is the thing to look out for, looking out for tools that are new, that may not quite be as robust.
Griffin Jones (47:18)
It is like that.
Dr. Cristina Hickman (47:38)
as we wish it to be, but we can fill that extra little gap that will bring it to the level of medical robustness that we want that our patients deserve.
Griffin Jones (47:47)
So you really have these different seats and pulling people and you talked a lot about conceivable in the beginning and how much that blew your mind. How close to a prototype does it seem to you versus how soon do you think we're gonna see conceivable automating the IVF lab all over the world?
Dr. Cristina Hickman (48:09)
I went down there expecting to see a prototype.
When I got invited to come and see the system, was, I'm going to see a prototype. It's going to be like, you know, band-aided together and some things will be working and some are not. No, it was a fully functional system end to end. Patients were already stimulating to have the first cycles through. They have a hundred cycles planned to provide the demonstration of the level of robustness. So I can't call it a prototype. It was a fully functioning.
egg collection, to sperm preparation, to dish preparation, to vitrification. It was quite impressive. You're going soon, right?
Griffin Jones (48:49)
I'm going down in less than two months to see for myself.
Dr. Cristina Hickman (48:53)
Okay, don't expect a prototype, but I also feel like I am spoiling the end of the movie for you. You're about to come and see the best movie that you've ever seen, and I've already told you the ending. But it's more robust than I expected it to be. And I expect this to be in clinical use elsewhere. Later in 2025 or early 2026, we're not talking about five years down the line.
we're talking about within the next, so this first birthday that we've had, by the next birthday, I want to see this here in our clinic.
Griffin Jones (49:27)
That blows my mind because when you think about how quickly things have moved to this point, but one, you answered a question that I've had out for a little bit and, and I've sort of wondered, okay, once humans are no longer being robots and right now, embryologists are treated like robots for a large percentage of their jobs, what do they do once they're not robots?
You answered that question of this is how you have embryologists be humans and interface with other humans in addition to advancing the science. I'd never heard that before and I imagine that somebody's listening to that and being like, there's no way that I want my embryologist talking to all of the patients about the growth of their blastocysts. How would you respond to that skepticism?
Dr. Cristina Hickman (50:12)
Look, there's been a letter that's gone out from the ARCs, this is the British Society for Embryologists, And this was a letter that went out which...
exemplified to me the biggest challenge of technology entering the market, the biggest challenge of technology reaching the patients, which is the human factor. It's the human barrier to technological implementation. It's the fear of change, it's having this mindset of positioning technology as a competitor to the humans. There's been no example in the human innovation era
where technological innovations have led to unemployment. They have led to a shift in the workforce. They have led to a diversification on the skill sets that had to be acquired. But look, if you look at our own innovations in our field, I don't miss the days where, yes, I've been around long enough now, I'm going to be displaying my age, but I've been long enough.
that I was pulling my own pipettes and I was mixing my own culture media, right? I don't miss those days where I was doing those swans with my glass pulling, right? I love the fact that I've got now commercial tools that are much better than what I've had access to before that made me more successful in making babies than before. And, you know, quite frankly, I am still busy.
I still don't have enough hours in the day to do everything I want to do, despite the fact that those aspects of my professional life have been automated. And I know it's hard for us to, as embryologists, to see that somebody has created a robot that goes from 80 cycles per embryologist to 2000 cycles per embryologist. And the first thing that comes to your mind is, is this going to make me unemployed? And the answer is a flat out no.
It will make you unemployed if you don't adapt to the new technological infrastructures and you don't acquire the necessary new skills that are needed for the embryologists of the future. Okay? So that generation of embryologists will be struggling to find a job, but all of us can learn, all of us can evolve, all of us can adapt. And this is what I see should be the responsibility of the letters going out to the membership.
So I disagree with what ARCS has set out in the letter they've sent. They should have sent out, this is how we embrace the new technologies coming in. you know, this is how we support, we understand the challenges that human artisanal embryology leads to or cause. And we embrace technologies that start eliminating a lot of these challenges. And this is good for embryologists, these technologies.
It's good for patients. It's good for doctors. It's good for everybody. Right? So the fears that we're having are not reality and there's absolutely no basis for them whatsoever.
Griffin Jones (53:16)
Dr. Christina Hickman, think it's been two years since I last had you on the show. And as we're talking, I'm thinking it can't be two years before I have you on the next time. It's going to be much sooner than that. I look forward to following you as this changes. will send you some updates when I'm down in Mexico City of what I'm seeing. And thank you so much for coming back on the program.
Dr. Cristina Hickman (53:35)
Thank you for your time and we appreciate the invite.
Now with Conceivable, we finally get this level of efficiency that allows us to better understand, to better treat more patients per embryologist. And the numbers are great. We've now gone in this journey that I've just told you from 80 cycles per senior embryologist to 2000. It's a completely different scale.
Avenues Social Links
LinkedIn
Dr. Cristina Hickman
LinkedIn
