Broker Events

Sarah Goodwin
00:00
Welcome, everyone, and thank you for joining us. It's clear to see that genomics has moved rapidly from being a really specialist area of medicine to increasingly an important and critical part of mainstream health care. Advances in genetic testing, data analytics and AI a really helping clinicians to both identify risk earlier, make much more informed treatment decisions, and ultimately deliver much more personalised care.
Today we're going to discuss, genomics, and we're really going to try and separate the promise from the hype. We're going to spend some time exploring where genomics is already delivering value in prevention, in screening and treatment, but also where the evidence is perhaps still emerging a little and really critically, what employers should consider before introducing genomic services as part of their health and wellbeing strategy.
As ever, I'm joined by a panel who are here to make sure they're sharing their wisdom. So, I'd like to welcome the panel today. First up we have Corne Hurter, who is a medical director here at AXA health. Thank you for joining us. Thank you for having me. Florian Markowitz, who is professional of computational oncology at the University of Cambridge and also acts as senior group leader for the Cancer Research UK Cambridge Institute.
Thank you, Florian, for joining us today. And Anju Kulkarni, who is a member of the Genomic Review Board at HCA healthcare and a consultant clinical geneticist, both at Guy's and Saint Thomas's Foundation Trust as well as HCA. Thank you all for joining us today. Looking forward to an interesting conversation. So today, as we say, we're going to aim to leave you with a much clearer understanding of the opportunities, the limitations, and really, critically, the key questions to ask as you think about this as part of your strategy.
So, let's kick off. And I think a sensible place to start would be to try and, unpack what genomics actually means and really understand that landscape. There's lots of terminology. There's lots of different parts of this. So, I think before we go much further, let's start with the basics. Florian, do you want to kick us off with trying to understand the very basics of where we start here?
Professor Florian Markowetz
01:59
I can try that. So, I mean, one of the basic distinctions is between genetics and genomics. The best example I know is in breast cancer. There are two genes, BRCA1 and BRCA2, which are named after breast cancer. The way they were discovered is that, in the 1990s, researchers tried to understand why there were so many cases of breast cancer in certain families.
And compared families with lots of breast cancer against families with very little breast cancer, and they found that at the genome level, what set them apart were mutations in these two genes, BRCA1 and BRCA2. So that is genetics. That is detective work. It's about inheritance. It's about family trees. What it doesn't tell you is what the genes actually do.
And that's where genomics comes in. Genomics is about trying to understand how genes function and trying to understand what they actually do and how active they are. So, for example, after BRCA1 and BRCA2 were discovered, people followed up on them and they realised their function in the cell is that they help repair DNA damage.
All of our DNA gets damaged at every cell division and if you go out too much in the sun. But cells are really good at repairing this DNA damage. If you have a mutation, you can't do this. That gives you cancer.
So, genetics is family trees and history and risk, and genomics is about the function and how to treat, and what happens if you actually already have a cancer.
Sarah Goodwin
03:33
Okay. Really clear. Where do we take it from there? There's talk of single genes, multi-genes. Where do we kind of layer on top of that in terms of how we might use some of that? Anju, do you want to take us through that?
Dr Anju Kulkarni
03:44
Yeah. So, I think when we think about genetics and genomics, they can be used in very different stages of a pathway.
So, if you consider any individual, we're looking at risk assessment and that's kind of where we're looking for inherited risk potentially. Then you're looking at when somebody has a cancer, what prognosis does that cancer have? What kind of treatment options should they have? And then, you know, there are different stages, I suppose, to the patient pathway where different types of genomic tests will be appropriate, as pharmacogenomics as well, which is about choosing the right type of treatment for somebody based on their genetic makeup.
 So, all of those different aspects will require genetic testing of some description or genomic testing of some description. And the key is really which test to use, in which setting and for which patient.
Sarah Goodwin
04:33
That makes a lot of sense. And Corne, anything you would add, any terminology that we think is really important for our audience to understand where this fits in?
Corne Hurter
04:40
 So obviously coming from the insurer perspective, but from a clinical background, we have to understand the economics of this space. And that's got nothing to do with putting a price on a life or anything like that. So, we have to look at economics, health economics in a much broader spectrum really, and look at all the capitals at play. Human life is a capital in itself.
And so in a cancer journey or in a life journey, understanding what your risk is so that you can make better health economic decisions, i.e. less time in the sun, for example, eating better, investing in exercise or things that are going to make me a contributing and healthy part of a population group. That's really important, and I think genetics can help us get there.
And then in the genomic space, once someone has cancer, we don't want to burn through whatever capital they have in terms of their resilience and their baseline health by going through treatment cycles that don't really make them better because, for some reason, they don't respond to that chemotherapy.
So, in that space, you want to get them onto a treatment that matches the cancer that they have really early on so that they can go through their cancer pathway well and still remain viable within the context of their own health, their bigger family, or their bigger community.
So, I think that's why I'm really excited about this emerging field of identifying risk, engaging with that risk, and, when we don't manage to mitigate it, precisely treating this individual with treatment that we know is going to be effective.
Sarah Goodwin
06:30
Okay, really helpful to set the broad landscape, both in terms of the difference between genetics and genomics, but also where it sits across what I would call the clinical value chain, and the different uses and different tests at that point.
One really specific question for me, because it's a terminology that I've started to see coming up quite a lot. I'm not sure who wants to take this one, but PRS specifically. Who wants to try and explain exactly what that one means so that we can all properly understand that?
Dr Anju Kulkarni
06:54
So, when we think about risk assessment or we think about cancer risk, the vast majority of cancer is sporadic. It just happens due to a combination of age-related changes, predominantly damage to our cells accumulated throughout life, and many different environmental and lifestyle factors.
But in some families, there is inherited risk. Okay. And we can do genetic testing to identify that inherited risk. Traditionally, that's been monogenic testing. As we talked about with BRCA1 and BRCA2, there are over 100 different cancer susceptibility genes now.
And that is typically one specific change in a gene that is conferring a high level of risk. And what we mean by that is the penetrance of that gene change. So, penetrance refers to the likelihood that a disease will manifest in that individual.
With monogenic disease, predominantly, the associated risks tend to be moderate or high. Now PRS is different, we’re talking about polygenic risk. And we've known about polygenic risk for years, and we've been looking at it for many years. But it's come to the forefront recently because of some landmark trials and studies, particularly in the cancer sphere and the cardiac sphere.
What polygenic risk does is look at lots of different gene changes, some that may confer a little bit of risk or may even be protective. And we combine all of that together.
So, for 50, 60, 100, or more different gene changes, we come out with an overall prediction of risk. So that's what polygenic risk scores are, and they are an exciting area.
But they are very different to the established data. The data and clinical evidence we have for monogenic risk are very well established, probably less so for polygenic risk.
So, this polygenic risk score is the score that you get from having that test, looking at lots of different gene variants.
Sarah Goodwin
08:41
Okay, really clear. And that probably brings me quite nicely onto my next question.
So, you talked there about some areas of genetic screening that are much more established than others, with other areas developing very quickly at the moment. What do we need to understand about the areas where it is very well established, and perhaps some areas where the evidence is still emerging?
Dr Anju Kulkarni
09:41
Yeah. I mean, I think there are very well-established pathways in the NHS and in the private sector for monogenic testing in cardiac disease, cancer, and paediatric conditions.
And that's very well established. We have the evidence base for the clinical utility of those tests. So, if we find a woman with a BRCA1 mutation, we have the tools available to us to assess that risk clearly and to understand it.
And we have the evidence base for the risk mitigations that we can put in place.
We understand that if we remove a woman's ovaries and fallopian tubes when they have a BRCA1 mutation, it can influence mortality. It has a long-term benefit for that woman. That's very clearly established.
And the pathways to access those interventions are very clearly established as well.
Polygenic risk scores, however, have generated a lot of excitement. And I think the difficulty in that setting is that we don't yet have very clear data, particularly on the population level.
What is the correct target population? Identifying that is important because I think PRS has some value in some tumour types, but maybe not for others.
There may be benefits in certain populations, but we know that PRS data is very much based on Northern European and Western populations. We don't have the same depth of data in other populations.
So, we shouldn't be extrapolating those findings directly across populations.
There are still some unanswered questions about how we can implement PRS in a clinical setting. That's not to say it won't potentially be beneficial, but I think we've got a little way to go before we can really demonstrate consistent patient benefit from it.
Sarah Goodwin
10:51
Okay, just really interested. You know, that makes a huge amount of sense. And I guess across the whole spectrum, there's something we need to think about in terms of how you use this screening and use this testing effectively. And, Conor, this is a lot of what you spend your time thinking about.
So, what do our audience need to know about screening and testing in particular, and how you implement that in a way that is really fair and focused on clinical value?
Corne Hurter
11.13
I think we all want to know the future. We all want to know our futures, and we want to know the futures of our children. That's very, very important. And if there's any harm on the horizon, we want to know how to avoid it, how to mitigate it, how to miss it. And where we have those clear pathways, like Anju said, it is an absolute gift.
But when we don't have care beyond the coding, it is a curse. And I think we have to be clear about that.
When we give a parent of a small child a risk, they don't necessarily have an experience to which they can anchor that information, and they can't translate what that means on Monday morning when they're packing a lunchbox for their child, or when they've been invited to a birthday party.
Do they get to eat sweets? Do they get to have cake? Do they get to play? Do they get to swim? Do they get to have a sleepover?
We haven't matured enough in all of those day-to-day areas where we need to provide advice and guidance on what childhood looks like now that we know you've got this risk.
And I think if we get ahead of ourselves and we code everyone with a blanket risk and assign a number, then we are paying a price, unintentionally, that we probably didn't factor into the equation when it started out.
So, I think we have to get beyond that hype. That's where the clinical geneticist is so important because they manage those expectations.
But we don't want to be so cautious that we smother the work that people are doing that is absolutely essential in these cancer pathways and delivers real quality and real solutions in very particular areas of the cancer journey.
Sarah Goodwin
13:11    
So, it feels like there's a lot of balance to be struck here. Making sure the evidence is at the right level, making sure that the right support is around it, and ultimately, it's when that balance is right that you would all say there is huge value in delivering these interventions. But it is always about keeping that balance.
Is there anything else we should know specifically about screening, or should we move further on in the value chain?
Dr Anju Kulkarni
13:31
And, you know, I was just going to add that we also have to bear in mind that these tests are one piece of the jigsaw puzzle, and we need to be holistic in the way that we approach risk assessment, treatment, whatever it is, and whatever part of the pathway we're looking at. It's never just going to be one thing.
Even in somebody who carries a high-risk gene change, you will see different outcomes for different family members who carry the same gene change because they're also influenced by environmental and lifestyle factors, and many other aspects.
Often with some of these tests, particularly direct-to-consumer tests, you just get that result for that individual without any clinical guidance around what that really means for them.
Without somebody looking at the broader picture for that person, you really can't interpret that result properly. So, I think it's important to highlight that as well. 
Sarah Goodwin
14:21
You need support around these results rather than focusing on a single risk factor.
Dr Anju Kulkarni
14:23
Genetics is just one risk factor, albeit an important one.
Sarah Goodwin
14:24
 And to use your example, it's one that people can become very focused on. Whereas, in reality, there are other risk factors that should be managed and are often much more lifestyle-related and potentially easier to address. So, I think it's about having that support, that balance of information, and the knowledge to be able to use this risk information properly.
So, we've talked a bit about screening. I'm really keen now to come on to the next part of the value chain that we talked about earlier, which is genomics within treatment.
Florian, particularly within computational oncology, which I know is your area of expertise, what do we need to know about the use cases and the ways in which genomics is being used, particularly in your field?
Professor Florian Markowetz
15:08
I mean, I can give you one particular example based on the BRCA gene that we discussed at the beginning.
The function of the gene is to help repair DNA. And if it's mutated, it doesn't repair DNA properly. That creates an opportunity because cancer cells that are not good at repairing DNA damage become vulnerable. If you overload them with DNA damage, we can kill them.
Normal cells that don't have that mutation, or don't have that impairment, may survive better. So, there is a link between particular mutations and particular treatments. What genomics does is create biomarkers from the genome that exploit these relationships between the genome and the treatment. For example, the pathway or mechanism in the cell is called homologous recombination repair. If that pathway is deficient, it's called HRD, or homologous recombination deficiency.
There are lots of HRD tests available, and they all work by looking at the whole genome, identifying patterns, and trying to understand whether particular types of DNA damage have accumulated that would normally have been repaired if this mechanism was working properly.
If the test is positive, then there is evidence that treatments such as platinum therapies and PARP inhibitors may be effective. So, you have a direct indication of which treatments should work. A large part of genomics research, and what people like me are doing, is trying to establish similar relationships for other drugs and other cellular mechanisms.
Sarah Goodwin
16:41
So, it's all about precision and really understanding what's going to work for that patient. So, you see this as really transforming the treatment that you're able to deliver?
Dr Anju Kulkarni
16:49
Absolutely. And I think it's an exceptionally exciting area.
But I think it comes back again to the question of utility, the right population, and making sure that you're offering that test at the right stage in the patient's cancer pathway, and for the right patient as well.
Because these tests are still expensive. Coming back to your point, it's an expensive test, and we need to make sure we're not doing them simply for the sake of doing them. We also need to consider the psychological impact on the individual patient of doing a test that isn't actually the right test to be doing, and what that might mean in terms of their treatment plan.
Sarah Goodwin
17:53
So, I assume there's a high bar, Florian, in the work that you do that says: "Is this at the right point to transfer into clinical delivery?"
I mean, we spoke before we started about making sure that you're delivering something that genuinely benefits the patient. You really want to make sure that the treatment you're recommending is actually going to work for them.
And, Conor, from an insurer perspective, I'm sure this takes up a lot of your time, thinking through where that value equation sits. What are the areas that you spend time thinking about, and where are the potential challenges in this area of treatment?
Corne Hurter
18:06
So, if you think about cancer specifically, when we have a patient who comes with a cancer diagnosis, there is already a decision based on various preparatory tests and laboratory work about what the treatment pathway will be.
We know that, although with the best will in the world we work through lines of chemotherapy and treatment, increasingly we're able to match treatments to the genomic patterns that we see in cancer cells.
What is emerging is this distinction between the wet lab and the dry lab.
We know the wet lab is where you look at the cells and the samples. The dry lab is where you get the math geniuses to come and look at that and do computational assessments. And you should really be speaking about this because I'm moving into an area, I know little about, but I am very enthusiastic about.
For me, as an insurer, I don't want to be insuring people against an unmitigated risk. I want to know that when that risk materialises, there is something that is going to work. I want to know what effective treatment, healing, or recovery looks like.
Increasingly, I'm beginning to think that when we have those multidisciplinary teams, where we already have radiologists and oncologists involved, I also want a computational oncologist sitting there saying, "Have you thought about trying this?"
Because the big problem is that this science is still sitting in the hallowed halls of Cambridge University, when really it should be sitting around the clinical table at HCA, or wherever we're delivering clinical care, so that we can make a difference for patients in real time.
Sarah Goodwin
20:14
And how do we move towards that? Because that sounds fantastic. I mean, Florian, I know you spend some of your time thinking about how we can do this safely at scale. How do we move from academic research to making this expertise part of the treating team?
Professor Florian Markowetz
20:31
I think there are already lots of activities like that all over the UK. The whole field is moving in this direction.
The big problem is that unless we figure out how to prioritise all these different tests, we risk overloading clinicians.
If I walk into a multidisciplinary team meeting and say, "Here's a DNA sequence, I've run all the computational analyses I can, and here are another 100 data points for you to review," nobody needs that. We have to become much more practical in testing and evaluating the clinical utility of these approaches. Currently there's a huge gap between academic research and clinical practice.
Every time I write a paper, I'm claiming that it will revolutionise healthcare and medicine. But usually, my papers never help anyone directly because there is a huge gap between the research and the clinic. Partly that's because, as a professor, nobody incentivises me to help people in the clinic, so my career is largely based on writing more papers. And secondly, there are no systematic pathways that allow me to bring my research into the clinic. What I need is a buddy in the clinic, hopefully that single person champions it, but that's not very systematic. This is a funnel, where lots of research goes to die. 
Sarah Goodwin
22:27
So, there's a huge opportunity in implementation. And have you seen it work well in certain settings where you do find that champion.
Dr Anju Kulkarni
22:28
I think the translational piece is critically important. Moving the amazing work that Florian and teams like his are doing into the clinic has always been a stumbling block. Ultimately, it comes down to resources and how we connect researchers with clinical teams that have access to patients. And again, it's a bit of a lottery as to which institutions have those links. That creates inequity for patients as well. So, it’s a bit of a minefield in that way. So, I completely understand the challenge.
Sarah Goodwin
23:08
Yeah, it feels like there's some real alignment here. As insurers, we run on data and evidence, so it feels as though there's an opportunity for coming together around that. Ultimately, Corne, you're always looking for evidence of efficacy and evidence that something is genuinely moving outcomes forward. As you can probably tell, you're all very excited by the opportunities that come from this work.
Corne Hurter
23:32
I think that's the role of the insurer. I'm not saying it's the traditional role, but genomics has opened a new door in this market. We don't want to be part of a hype cycle. We want to make a genuine difference. We want to connect the right people within our sphere of influence. So its about partnering with research where we think its important. That's how we came across Florian. I loved the work that he does. The philosophy of his research group is incredible because it is genuinely patient-centric.
But that also needs to feed through into how we plan, create policy, and design propositions and services.
Sarah Goodwin
24:36
So, Corne, you referred to this as a growth journey. I think it's fair to say that, as AXA, we're already on that journey.
Can you tell us a little more about that?
Corne Hurter
24:48
Where there is strong evidence that a genetic test can either validate a diagnosis, confirm a particular tumour type, or direct treatment decisions, we've already established that the key question is whether there is sufficient evidence for funding.
Our medical policy team actively monitors this area. We have someone dedicated to horizon scanning developments. When they identify something that has strong evidence and appears capable of improving outcomes, we try to incorporate it into our funding pathways as quickly as possible. We also have a strong relationship with clinicians, who often tell us when new pathways or services become available.
Part of what our medical advisers do is cultivate those relationships so that we remain proactive, create the right policies, establish funding pathways, and support our members.
So yes, absolutely, we're already doing this.
What we'd like to see is that portfolio continue to grow in a healthy way, alongside a robust evidence base that helps us make the right decisions for our members.
Sarah Goodwin
26:19
Okay, so it's really about that flow of information, but that flow is already working.
Yeah, there are definitely areas where we see the evidence, see the clinical support, and AXA would fund those interventions for patients.
Corne Hurter
26:28
100%.
Sarah Goodwin
26:30
We’ve done a brilliant job at describing what is a minefield. If you were an employer, where would you start with the questions needed to understand what you should and shouldn't do within this space?
Corne Hurter
26:59
So, what I would start with is: what do we know for sure today?
Okay, so let's say we're talking about lung cancer pathways or breast cancer pathways. If we want to have assurance as an employer that our employees are benefiting from the best possible thinking in this space today, what does that look like?
So, if there are clear pathways that Florian's team or computational oncologists have identified as areas where computational oncology can really make a difference to a person's cancer pathway, I would want reassurance that, as a healthcare payer and as an employer, we understand this, understand the benefit and value of it, and make sure those pathways exist for our employees.
If they are suffering from lung cancer or breast cancer, we want to make sure they have access to services where this is a priority, where it is articulated and embraced.
So, that's dealing with the present.
When we're looking at the future, we want to understand that the horizon scanning undertaken by payers and partners like us is healthy, that we have a healthy attitude, that we are asking challenging questions, and that we are taking advice from people like my colleagues on the couch, who have a sober and broad understanding of both the opportunities and the pitfalls in this space.
The advice we take needs to be credible, and it needs to make a difference to patients today and patients in the future.
So that's kind of how I see it.
Sarah Goodwin
28:44
Okay. This is really about understanding exactly what it is and where the evidence is strongest. Where are the particular pitfalls here? Are there particular questions that you would say employers should always ask? Are there areas where you've seen people make choices that perhaps weren't quite right because they didn't ask the right questions upfront, and therefore the support didn't come through as planned? Is there anything you'd particularly advise an employer at this point? Anju?
Dr Anju Kulkarni
29:11
I think it's about governance of the pathways.
It's making sure that if you are going to choose to offer a particular test through a policy or healthcare programme, you understand what the outcome of that test will be and what the next steps are.
It's not just the test. It's what happens afterwards. And it's about having a very robust governance pathway in place so that people don't fall through the cracks. I think, in the monogenic space for example, for many years I worked closely with HCA to set up really robust follow-up pathways for people. Because the problem is that if you don't have those pathways in place, people are left with information about risk but no idea how to deal with it.
They worry about that risk. There can be significant psychological morbidity associated with having that information. And they may not be able to access support through the NHS because the pathways simply aren't there. So, I think it's about making sure you have that wraparound care, and also that you're offering the next steps in an evidence-based way. 
Let's say you have a PRS for a breast cancer risk, and they are at high risk. What does that really mean?
What are the screening recommendations? What does it mean in terms of risk-reducing surgery? Where will they access those risk-reduction tools? Will that be through the private sector and the employer-sponsored scheme, or will responsibility shift back to the NHS, which may not have capacity for it? If you haven't planned all of those next steps and you're simply providing a test result and then leaving the individual in limbo, that is far from ideal.
Sarah Goodwin
30:59
It's really about thinking everything through and making sure all the support mechanisms are there alongside the testing.
And I'm assuming there are also considerations around data, privacy and the sensitivity of that information that need to be properly thought through.
That's very sensitive information.
Dr Anju Kulkarni
31:13
Absolutely. And there are also the financial implications. We know there is a moratorium in place between insurers and the government, that they’re not allowed in terms of the predictive genetic tests. So, if you’ve got a familial mutation - you’re having a predictive test -so  we're talking about an individual who does not currently have cancer but is having a test to understand their future risk - there is a moratorium in place - what does that mean in the setting of new tests such as PRS that are coming in? I don't think we fully understand that yet.
So, it's not only about the clinical implications. There may also be longer-term financial and insurance implications that need to be understood.
Sarah Goodwin
31:48
Sounds interesting. And in terms of understanding the evidence, not all of us are geneticists or professors of computational oncology. What sort of things should people be looking for?
Should they be looking to their insurer to make sure that some of this homework has already been done and that the evidence can be clearly articulated?
Is there anything in particular about the evidence base that you think is worth noting?
Corne Hurter
32:11
Well, the teams responsible for medical policy within AXA are experts in evaluating evidence. They are very clear about the threshold required before something is adopted. They want to see randomised controlled trials and other high-quality forms of evidence. We also make use of external resources such as the Oxford Centre for Evidential Medicine to help us evaluate what good evidence looks like. That's important not only for sustainability within the healthcare system, but also for patient safety.
For us to be confident and comfortable in this space, our medical advisers, together with the external expertise we draw upon, play a critical role.
When we're looking at something like computational oncology, we might reach out to somebody like Florian and say:
"I haven't got a clue what this means. Can you explain it to me in plain English?"
That understanding is then fed back into our system. Our actuaries look at it. Our proposition teams look at it. The knowledge is distributed throughout the areas of the business that need to be informed. Once people understand it, they can translate that knowledge into insurance products, funding decisions, pathway design, or ways of working with healthcare providers. So, it's an ecosystem that's alive. These aren't static documents. They respond to what's happening in the environment around us. We are constantly trying to increase our knowledge, increase our confidence, and work with expert partners who can support us on that journey. 
Sarah Goodwin
34:13
So, it sounds like "ecosystem" is exactly the right word. What I would take away as an employer is the need to ask questions about everything built around the test itself.
You can trust the evidence. You can trust the experts who have had conversations with Florian and his team and others working in the field. But it's important to probe what happens next. Is the support structure broad enough? Is it going to place the patient in a situation where the information is genuinely useful and actionable, rather than becoming information they don't know what to do with?
Fascinating. Okay. We've been the voice of caution throughout all of this, and now I think it's time to throw caution to the wind, at least for a moment. Obviously caution remains important. But what excites you, as people working in this field right now?
If we came back here in five years' time, what would you hope we'd be talking about? What developments can you see coming that might genuinely live up to the hype and transform this space? Who wants to go first?
Professor Florian Markowetz
35:09
I mean, one thing that would be transformative is becoming truly serious about tailoring treatment to the individual. Rather than giving everyone the same chemotherapy, we could ask: will this actually work for this specific patient?
Currently, many chemotherapy treatments are given as first-line therapy even though they may only work in half, or perhaps two-thirds, of patients. That means many people are essentially being poisoned, with the hope that the chemotherapy damages the tumour faster than it damages the person.
If we had more genomic information and better integration of different data sources, which is often where AI comes in, we could make much more personalised treatment decisions for each patient. That's something I think could realistically be achievable within five years.
Sarah Goodwin
35:59
Fantastic. You beat me to it. I'm a strategist, so we have to talk about AI. Does AI exponentially increase our ability to solve some of these problems and address some of the capacity challenges we face? Are you excited about the opportunities it creates?
Professor Florian Markowetz
36:13
I think the most practical change is that AI has made everyone much more interested in data, how data are stored, and how different datasets can be connected.
There isn't a magical button where AI simply gives you the answer. What often happens in healthcare organisations is that people realise their data are inaccessible, fragmented, and disconnected. Because AI has become so prominent, organisations are recognising that they would be much better off if all those data sources were connected. I think that's the real game changer.
Once you have the data connected, you don't necessarily need sophisticated AI to begin seeing value. The AI simply sits on top of that connected infrastructure and helps support decision-making. Creating those connected datasets is achievable, and it will be transformative.
Sarah Goodwin
26:57
Fantastic. Looking forward to that. And Anju, in a clinical setting, what do you hope will emerge? Perhaps things that currently appear in research papers but haven't yet made the transition into routine care?
Dr Anju Kulkarni
37:04
I think there are a number of exciting areas.
One is identifying high-risk populations and finding better tools to mitigate risk. To link this back to treatment, can we start using targeted cancer therapies in preventative settings? There is already research looking at high-risk individuals and asking whether some of the drugs currently used to treat cancer could also be used preventatively to reduce risk before cancer develops. That's a very exciting area.
Another exciting area is cancer early-detection testing in high-risk populations. We now have multi-cancer early-detection blood tests. Can we use these effectively in high-risk populations? But to do that, we first need to identify who those high-risk individuals are. I think we've only scratched the surface in that regard. That's really the key unlock.
Sarah Goodwin
38:08
Corne, clearly, you're passionate about this as well. What do you hope we'll be talking about in a few years' time?
Corne Hurter
38:10
I've been a clinician for a very long time. What always excited me about my work was the teams I worked within and the way they approached healthcare, or a child in difficulty, or whatever challenge they were facing.
The other thing that excited me was access to expertise and super-specialists. What excites me, and what will continue to excite me in the next five years, is how we bring these teams together.
How do we reduce the distance between payer, provider, and researcher? How do we rebuild those connections and create strategies together that allow us to deliver a healthcare environment in the UK independent sector that genuinely makes a difference for patients every single day?
Being a facilitator in that space, almost the catalyst that brings all those elements together, is hugely exciting to me.
I'm relatively new to insurance. I've had a clinical career for a very long time. I worried that I might lose some clinical relevance and that years of experience would become less important. But what I've actually found is that there is tremendous value in that experience, both my own and that of my colleagues. 
AXA has a great team. They are curious, they ask questions, and they genuinely want to build a better future for their members. That's what excites me most at this moment in time. It's a huge opportunity. And I think there's a dream team forming here of insurer, researcher, and clinician, all bringing their expertise together.
Sarah Goodwin
39:59
Absolutely fascinating. And I hope we're back here in less than five years to talk about how far all of this has progressed.
Thank you all for your time today. I think we can conclude that genomics is no longer something confined to the future. We've heard that loud and clear today. But there is a real challenge in understanding where the science is mature, where the evidence is still evolving, and how to distinguish meaningful innovation from noise. I think you've all done an excellent job of unpacking that. So, thank you.
If I were to summarise one key takeaway for those watching at home, it would be that the value doesn't come from the information alone. It comes from what you do with that information, how you build pathways around it, and how you support patients through the journey that follows. I've learned a huge amount from this session. Thank you for your time.
Thank you, Corne. Thank you, Florian. And thank you, Anju. This has been fascinating. Thank you all for sharing your insights. And thank you for joining us.