Firgun Ventures Podcast

Transcript


Dr Kris Naudts  00:00

Welcome to time to talk Quantum. I'm Dr Kris Knaudts, neuroscientist and psychiatrist, founder of culture trip and co founder of fear gun ventures. Today. I'm joined by Dr Lara Jehi, Chief Research Information Officer at Cleveland Clinic and Professor of Neurology at Cleveland Clinic, Lerner College of Medicine. Dr Jehi is the executive program lead for the discovery accelerator, which spans more than 50 projects focused on AI quantum computing, data science education and international initiatives. She is also a steering committee member of both the healthcare and life sciences quantum Working Group and the AI Alliance formed by IBM and meta. Dr Jehi also serves in advisory roles for industry and federal agencies. I'm also joined by John Morton, Professor of nano electronics and nano photonics at University College London, and director of the UCL quantum Science and Technology Institute. His research involves the coherent control of electron and nuclear spins in solid state materials and devices with a focus on quantum technologies. Professor Morton is a co director of the quantum biomedical sensing research hub, the UK's first quantum hub focused on health. He is also a co founder of not one, but two international quantum computing companies, quantum motion, developing quantum processors based on silicon transistor technology and face craft, the quantum algorithms company, it's time to talk quantum so the Cleveland Clinic, Lara. I mean, can you tell us a bit about its history and its status in the US and the world? I heard it's so big it has its own postcode, its own prison, its own police, or is that an urban myth?

Dr Lara Jehi  01:41

I love the above, except the prison we're working on that. No, you did your homework. So Cleveland Clinic is an organization that's 100 years old. We over 100 years old. We started in 1921 back then, it was with four physicians who had just come back from World War One and thought that there should be a better way of practicing medicine than just each clinician opening up shop on their own. You know, the tradition then was these clinics, the small private practices. So their innovation back then was that medicine should be practiced as a team, and we were one of the first group practices in the US. And from the very beginning, it was a tripartite mission, with research, clinical care and education. And since then, we have grown now to be 83,000 people strong that are distributed across the US in many states. Ohio is our mothership in Cleveland, but we have facilities in Florida and in Nevada and outside of the US too, in Canada and Toronto, a place that's focused there on more executive health and sports medicine. In Abu Dhabi that's a full fledged surgical MediCal program now with a new cancer center added to it. And in London, the Cleveland Clinic London is our latest, you know, addition to the health system now, just over two years old,

Dr Kris Naudts  03:28

okay, I associated strongly with cardiology and cardiac surgery. Is that? Is that right? Correct?

Dr Lara Jehi  03:34

Correct? The very first cardiac catheterization happened at the clinic. Many first actually, not just in heart. The first face transplant happened in Cleveland Clinic. The first uterus transplants in the US happened in Cleveland Clinic. Some fundamentals of medicine now, like, for example, serotonin, you know, the chemical that drives our understanding of mood disorders and all therapies for depression anxiety, that compound, that chemical, was discovered in Cleveland Clinic. So was the angiotensin, the main chemical that drives hypertension. Hypertension as a disease was defined in Cleveland Clinic back in the time. So biomedical research is really core to what we do, and because our research facility is right across from our hospital, then it always carries that clinical translation and that emphasis on team science with working with our clinicians who are innovating and how care is delivered and how clinical practice is happening, led, of course, with you know, through innovations in many disciplines. You mentioned heart. That's what we were. We were number one in the nation and in the world for almost three decades.

Dr Kris Naudts  05:10

I see, Oh, wonderful, congratulations. Yeah, you are also, aside from being a professor of neurology, you're also the Chief Research Information Officer. Can you tell us a bit more about that role and why you took that on Correct?

Dr Lara Jehi  05:22

Yes, I'm a I'm a clinician scientist specialized in epilepsy, so my clinical role in my personal research have always been in that space. But I've, you know, by virtue of doing research just I had to learn more about the infrastructure at the cureland clinic when it comes to data, biological samples, regulatory frameworks. So over the years, beyond my personal research, I did things like build an enterprise biorepository where we automated finding patients, consenting them and collecting samples for biological research. We enrolled over 40,000 patients, collected over a million samples in the span of three years, with one and a half coordinator, which is a fraction, like a small fraction of the manpower that's typically required because we automated all of it. So I was doing this kind, you know, this is one example, but I was doing many initiatives like that. And then this position for Chief Research Information Officer opened up. It was a new position for Cleveland Clinic, because as an organization, we recognized that computation in biomedical research is no longer something that can be done on the site. It had to be intentional, structural. We had to build capacity. So it was it was fortunate for me, because I matured in my personal journey at the same time as the organization acknowledging the need for such a role. And I remember looking at the, you know, the posting, and thinking to myself, well, I'm doing this now. I might as well have the job. And I took that on in early 2020, and let him that. I know, you know what came afterwards, but, yeah, that's how that came to be excellent.

Dr Kris Naudts  07:35

So when, when and why did the Cleveland Clinic embrace quantum and what is the idea? Is it envisaged to give you a financial return, or is this just on the frontier of technology that you want to operate? What was the driving force? Sure.

Dr Lara Jehi  07:50

Great question. I get that quite often. It's really more of the second point of what you mentioned. As I said, I was new in my role, and I was having to deal with urgent needs for biomedical research here, our data, for example, was ballooning. We were sitting back then at about 15 petabytes of data for research, and we were growing at the pace of three petabytes every year. So we had these big data needs. Everybody wanted to do AI, and still wants to do AI, but that was, you know, in a way, the bread and butter the now of how biomedical research happens. And we entered into an agreement with our local government, the state of Ohio and jobs Ohio, that's a public, private entity focused on economic development. So co invest with Cleveland Clinic about 500 some million dollars over 10 years to create an innovation district that's anchored on biotechnology. So I knew that all of those needs that I mentioned were going to just explode with this, a new partnership with the state. So I had to think of what do we need from a computational strategy perspective that would fit both what we needed in the present, you know, back then, which was the AI work, but that would also set us apart 510, years down the road, so that we are relevant in the future. You know, not just keeping up with the present, and it is with that mindset that I thought it's important that we invest in quantum because that is the next frontier. And the way we did that was with our partnership with IBM Research at the time, in this calculated risk approach where we get what we need. It as far as AI and infrastructure compute talent goes, but at the same time, this will allow us financially to take the risk with quantum to explore what that future would look like. Okay.

Dr Kris Naudts  10:14

Okay, got it. So you guys work with IBM, also with meta. I see your main competitor, for lack of a better word, would be the Mayo Clinic. I assume in the US they work with sandbox, indeed, Google. What's the main difference, you would say, between what you guys try to do at the Cleveland Clinic and What? What? What the Mayo Clinic focuses on?

Dr Lara Jehi  10:34

Yes, Mayo there. I mean, they're a great group. So for us, the one difference, not just with them, but with any other group, is that we are the only group in the world that has a quantum computer on site in the canteen. We would love to host you so you get come and have a look and see it in real time. That's what everybody gets excited about. It is actually in the middle of our cafeteria. That was because we had to retrofit it in existing space. And it's a finicky machine, as you know, you know, we needed certain limits with vibration and heights, and where can we put the machinery that needs to go with it? And they were, the choice at the end was either the canteen in the middle of the research cafeteria, or in our data center, which would be in another city. And we went with the canteen, because, as I told our finance officer, you're like all the committees back then, I said, Well, we're not buying a diamond ring and sticking it in a drawer has to be, you know, somewhere that's visible. But, you know, I have to say that was, that was great, because it was a change, right? You know, for these researchers, they we're a biomedical research group, so people haven't grown up with, you know, quantum computing and what it is and what it means. So having the machine be there was a great magnet for external partnerships and to build internal interest and activity around it that really sets us apart from any other group, because we're not doing quantum on the side. You know, we have, we, we have gone all in, you know, in a way, by having the hardware here and all the activity that comes with that, and

Dr Kris Naudts  12:49

what, what does the Mayo Clinic focus on versus you guys at the Cleveland is there a difference?

Dr Lara Jehi  12:54

Or, I think they're trying to figure out what they want to do, because they for that would be a great question to ask them, actually. But for I can tell you, from our side, we are, our journey has evolved since we've put the machine here at the beginning. It was more exploratory with let's define what could be promising. You know, applications for it, and we've come to classify those and buckets, you know. So we have our quantum chemistry work, and that is all the activity related to drug discovery. We have our quantum machine learning work, which is more along biomarker discovery, I would say the disease, you know, some diagnostic type work. And then there is the track that started a bit more recently, in the journey where we realized that it's not really about quantum versus AI or, you know, quantum versus machinery. It's about how all of these computational methods and approaches can work together. And for that, there is the, you know, the theoretical, you know, computational research side, but then there is also the hardware side, where we have teams that worked on connecting, say, our QP use our quantum processing units, with our GPUs, with our classical clusters. So there is now work that's going on with purely on the engineering side, with, how do you connect enable this type of computation? But what's driving all of this is the applications which we're doing with, you know, within our teams,

Dr Kris Naudts  14:54

okay, okay. Are there any other hospitals that you know in the US or in the world? I mean, I know that surah. Hospital in Tel Aviv together with Nvidia that is doing some work. Are there other hospitals who have embraced quantum at this part, at this point of the journey,

Dr Lara Jehi  15:07

not to this extent? Well, definitely none that has, you know, the hardware on site, like we do, and you're the only ones, and none. There is definitely great work. I mean, of course, there is academic work around quantum with quantum computing, with biology and chemistry and life sciences. In many great places, we have started this quantum enhanced care and life sciences working group with with IBM and many other groups. And that team meets quite regularly, and it has representatives from life sciences, industry and from academia in the US and elsewhere. And you know, that has been a tremendous group. We've put out some of the our initial publications were all white papers, and, you know, perspectives, it was necessary to get the lay of the land before we dive in with our original research since then. But, and you could see in those, you know, names like the Broad Institute and MIT, and, you know, Purdue University and University of Chicago, and you know, so we're working with with all of Those groups, and we're also bringing in partnerships with startups that are interested in looking at Quantum for healthcare and life sciences. We have a whole program around startups. We call it a catalyzer program. We launched that last year, and initially it was an experiment for us. What we awarded the startups was time on the machine, yes, and the three that we awarded, the one of them is algorithmic, which is this, finish, yeah, they do great work with photodynamic therapy and looking at Quantum applications there, we partnered with them around that work, which is now in the finalist group for the Wellcome leap with, you know, the Wellcome Trust initiative around quantum for biology. So that was one of the three that we supported. The second one, cador was a is a local, you know, US based startup focused on Alzheimer's disease, you know, with drug research. And they just published some work where, and there were specific examples where they surpassed Alpha fold three. And then the third company is still trying to find its way. But, you know, I would say two out of three. That was a good return. You know, that's pretty good, yeah. And then now, this year, our second iteration of this, we're doing this in a partnership with a Venture Capital Group, a q5 and we just selected our four winners, and we will be announcing them soon. And I'm so excited about the new craft coming up.

Dr Kris Naudts  18:36

Yeah, brilliant. Very much. Looking forward to that. You also collaborate with Novo Nordisk in Denmark, who, in their own way, are pioneering, of course, in quantum, really pushing an ecosystem out of the ground there. What is the nature of that collaboration?

Dr Lara Jehi  18:48

Yes, we are very happy about our relationship with the Novo Nordisk group. They're really very forward thinking, and their investments in quantum go all the way from they want to define what is the hardware that's going, you know, to work best. So they have that whole initiative. And of course, they had their big investment in Nvidia on the AI side. Our relationship with them is purely on the quantum and AI applications, and so Cleveland Clinic as an organization, has a long history with Novo Nordisk foundation. You mentioned how you know, you mentioned our history and heart disease, metabolic disease. So we have a lot of work already with the Novo Nordisk you know, company and foundation over time. So when we got interested in quantum, it was a natural fit with their interest in that field. What we do with them is this fellowship program, which they fund a postdoctoral fellowship exchange and. Yeah, where we send our trainees for to Denmark to work there with labs around AI and, you know, quantum projects, the fellowship funds each postdoc for up to four years. So you have time to do meaningful work. And it's not just like a, you know, a quick rotation here and there and vice versa, you know. So they could send also their postdocs here for collaborative work. So we're that has been, they've been a great group to work with. So we're looking forward to see how that pans out.

Dr Kris Naudts  20:42

Okay, fantastic. I'm going to bring John in here a bit more as well. So John, you founded two quantum companies. They're on your way to be the Elon Musk of quantum people told me, I mean, perhaps not temperamentally, yeah. And you're also the director of the quantum biomat hub. Could you maybe tell us a bit about the two companies you co founded, and then also, of course, what you're doing at the quantum biomat hub. Yeah, sure.

Professor John Morton  21:05

So, I mean, I would say in quantum computing, the big challenge is, how do we bridge this gap between the early quantum computing prototypes that we have today and these really exciting, transformative applications, such as the one that Lara's been talking about, and we can address this from two different sides. One on the one hand, we need scalable quantum computing technology. We need ways to build quantum computers that can reach the level of hundreds of 1000s, even millions of qubits, and that's what we're trying to do in quantum motion using the same silicon transistor technology that powers smartphones and laptops a day, and use those elements as the building blocks of the quantum computer. But there's also big gains to be made by making the algorithms more efficient and within face craft. That's the challenge looking at ways in which quantum algorithms can be made more efficient, so that you can get more out of quantum hardware today, and bridge that gap between the two.

Dr Kris Naudts  22:08

Okay, and then at at the sensing hub, can you tell us a bit more?

Professor John Morton  22:12

Yeah, so quantum sensing is this. It's really exciting opportunity that comes out of this big drive that we've had in developing quantum technologies like quantum computing, and we've we figured out new ways to harness nature at the quantum level, at single photons or single atoms, single particles, and we've found ways in which that can be used to develop new types of sensors that can be applied in biomedical and health applications, and in some cases, that can just radically advanced the limits of sensitivity, and in other cases, it means that we can get the same level of sensitivity for which you need a specialized laboratory test, but you can now do that in the low resource setting. What does that mean? It could be in a GP surgery, in a shopping mall or in a rural area. So quantum sensors really have the capacity to impact a wide range of different healthcare challenges.

Dr Kris Naudts  23:03

Okay, and where does this fit within the wider UK quantum strategy? Why was it chosen to solely focus on sensing?

Professor John Morton  23:11

Well, the UK has had this quantum technologies program going back almost 10 years now, and funding these research hubs in different areas, computing, communication, sensing and timing. And we felt the time was right when the hub was was proposed, when we proposed the hub last year to do something that was really focused around the health care and biomedical space. Because I think to to get the most out of these technologies and make sure that you're addressing the most pressing questions, you need to be a sector focused so that you're working with clinicians and and finding out where can quantum sensors really help. So so we took what, at the time, was a radical approach. We weren't just going to cover all of quantum sensing. We were specifically focused in the healthcare space, and we brought a large number of clinicians working alongside the quantum physicists to find that common language and fine tune the quantum sensors to these different applications, whether that's medical imaging, in vitro diagnostics, new kinds of surgical tools enhanced by quantum sensors, or the kind of quantum sensing technologies that can be used in fundamental life sciences to understand disease mechanisms and

Dr Kris Naudts  24:19

it's research focused, or it's also meant to seed startups. Or how do we think about that?

Professor John Morton  24:24

The Hub ultimately is is focused on on research, but a key part of that, if it's success, is making sure that that research gets successfully translated. So it begins with a dialog with clinicians to make sure that we're addressing the right challenges and we have the right target specifications. The you know, the typical physicist just carries on making the sensor more and more sensitive and doesn't necessarily know when to stop at what point is it good enough to actually start being applied? So our first mission is, is that clinical engagement that allows us to define the needs right? And then. Then there's the research element, which is, of course, the sort of major part of where we're putting our efforts, but, but then there's the translation side and the regulation side, and so we have a significant port portion of our funding focused on those turning that research into proof of concepts that can go into preclinical trials, and then, and then also to seed startups through some of the seed funding that we have in the hub before it can be taken over by the traditional investment and

Dr Kris Naudts  25:32

the hub. Or the funding for the hub is there open endedly, or is it 10 year project? Or, well,

Professor John Morton  25:36

it's, it's a five year funding in the in this initial phase. It's a 24 million pound project. It's something that could potentially be renewed. And it's also part of a much larger mission that the UK has set in quantum technologies. And one of these three missions is focused around quantum sensors for health. So we see ourselves as a key part of delivering that mission, and that sets this really challenging objective of by 2030 getting these quantum sensors into NHS Trusts around the UK.

Dr Kris Naudts  26:07

That would be amazing that could be delivered, indeed. What does it compare to? Is it similar to QB in Chicago, for example?

Professor John Morton  26:15

Yeah, this, this. It's actually, there's a number of different centers around the world that have recognized this potential for quantum sensors. Definitely, Chicago is a big area, also Ulm in Germany and in Australia. I think each of these brings a different angle, probably where we see as one of our strengths is that level of clinical engagement that we have that is well balanced between the quantum physicists and engineers and clinicians, and our focus around these different the breadth of different medical applications, where we see these quantum sensors being deployed,

Dr Kris Naudts  26:50

the hub also collaborates internationally. You have partnerships with some of these. Yes.

Professor John Morton  26:53

I mean, of course, we've had very nice discussions with Cleveland Clinic, and we hosted a Cleveland Clinic at UCL to explore potential applications and collaborations, but we're certainly looking internationally about where we can see complementary strengths and start developing these technologies together. If you look,

Dr Kris Naudts  27:13

indeed, a bit to bring it briefly, briefly back to startups. I mean, according to the Tony Blair Institute, they published a report fairly recently. There is about 500 quantum startups in the world, and about 150 sit in the US, unsurprisingly. But second in the world comes the UK, with about 65 what proportion of that of these numbers are sensing startups, really? Or are there mostly on the computing side or the cryptography side?

Professor John Morton  27:36

Yeah. I mean, I say from my personal experience, the UK has been a fantastic place to develop the quantum computing stock startups, the National Program and the investment landscape has been has been brilliant, and also plugging into the wider European landscape has been critical. But it's certainly true that perhaps counter intuitively, the I would say the majority of my feeling is that there's a majority of quantum startups within the computing space. And yet, sensors are now finding this, these early applications for quantum technologies. And so I think we're going to see many more quantum startups coming out in the quantum space. The thing, the thing to sort of balance that against is, is, of course, from a from a commercialization or investment perspective, the diagnostics are not always the most attractive quantum startup proposition. You know, it's all very well to tell someone that you've got something, but really, you know, potentially, the biggest returns are in providing then the remedy,

Dr Kris Naudts  28:38

Yeah, true. Very true. Could you tell our audience also a little bit more about the actual technology that is quantum sensing in general, and perhaps with with also some details on Diamond sensors in particular?

Professor John Morton  28:51

Yeah, I think this is one of the challenges that we have with quantum sensors, because it's so broad, right? With quantum computing, we have a fairly well defined definition of the machine. Quantum sensors describe a really wide range of different ways in which we're using quantum systems to sense properties more accurately. But two of the big front runners are nitrogen vacancy centers in diamond and optically pumped magnetometers. I'll focus mostly on on the in the diamond to start with. And here, if you take, if you take diamond, naturally occurring diamond, and has a bit of color, that's because it's not pure diamond. There's not pure carbon, there is a few atomic defects. And through the development of quantum technology research, we found a way to isolate the signal from individual atomic defects within the diamond. Now, why is that powerful? Because diamond can also be produced in this nanoparticle form, in these nano diamonds, at relatively low cost, and this means that they can be functionalized to bind to particular biomarkers, and they can therefore be used in diagnostics. So. We're all, unfortunately, very familiar with lateral flow tests and the red line from covid, that red line, maybe, you know, is made out of gold nano particles, and that's what that comes up, is red. But you can also use nano diamond, and that can be more sensitive, and by manipulating these atomic defects within the Nano diamond, we can go one level further in sensitivity. And actually we showed a few years ago that you can improve sensitivity by over 100,000 fold and therefore detect a single copy of an HIV virus. And this is a platform technology you can then apply to many different types of biomarkers. We've shown it since the hub started for covid using clinical samples from the UCL age, and we're just beginning to explore the different types of biomarkers and diseases that we can use for this kind of sensing technology. And it's a great example of something that then could be deployed in a GP surgery, as I said, in a shopping mall, or in other kinds of settings that allow for faster point of care testing.

Dr Kris Naudts  31:13

Yeah, as a former clinician, this strongly speaks to me, and I'm sure the same is true for you, Lara, when you see these things that we could replace ECGs and all the mess that comes with it with a simple sensor. Of course, it's amazing. I mean, I also saw and that speaks more to your field, I think some detection, or early detection of Parkinson's. There's been some TPC or tuberculosis testing. What are some of those that you are excited about with your particular clinical hat on?

Dr Lara Jehi  31:37

You know, as a neurologist, I have to be excited about the applications that allow us to diagnose different types of brain conditions early. There is a transformative step in epilepsy, for example, was the development of Meg magnetoencephalography as a, you know, as a tool that allows us to both, to merge both electrophysiology and structure, right? We have an MRI, a detailed picture of the brain, and then we overlay on top of it where the abnormal electrical activity is happening. This is, this is a unique capability, but now only few hospitals have it, and it's a very complex thing to set up with, magnetic shielding special rooms. It's costly, it's difficult, so a the potential that we have with quantum sensing to make all of this portable and available in the community, say, for sports teams after head trauma while, you know, playing football or in in the defense setting, you know, for head trauma on the Battlefield or, you know, those are things that have always been very difficult to ascertain on the spot, and situations where time is of the essence, right? You have a window to intervene before the damage is a reversal. So these types of applications where treatment is time sensitive, diagnosis is difficult because of the location where the injury happens. The potential of portability that we have with the quantum sensing approaches is tremendous.

Dr Kris Naudts  33:37

Yes, it's very easy to get excited about it. Also, it's such a demonstration of quantum for good, and it's not even extremely long term, and it's right in front of us now. Yesterday, I did a recording of an episode here on quantum and defense, which indeed is the other use for sensing. I don't know how you feel about that as a doctor, as a clinician, about defense applications. Do you think about that in this line of work? Do you? John. I mean, I might ask you, first Laura, seeing it, I opened it to you.

Dr Lara Jehi  34:05

You know, we have not just in medicine. I think we're living now in an era where an a technology advanced in one field ends up whether it wants it or not. That's never intentional, I believe. But you know, at the end of the day, it ends up benefiting other fields in ways that nobody imagined, right? Like, I don't think whenever the laser was first invented that people thought its biggest application would be scanning groceries in the grocery store. But yet, you know, that's how it happened. And a lot of the wearable technology that we have now in medicine, what initially started on with defense type applications, because vital signs and, you know, function had to be monitored when people are when so. Soldiers are deployed, for example. And it is that same technology that now we have in our Apple watches and people tracking their heart rate to see if they're exercising enough, you know. So there is just the way I look at it is, there's no limit, either good or bad, right? So any technology as it's, as it's develops, and we cannot fight it to stop it, what we can, nor should we. What we should do is look at what good can come out of it, and then see how we can apply it in our own discipline. So I have no doubt in my mind that whatever is being worked on in defense could have some aspects that would benefit medicine and humanity.

Dr Kris Naudts  35:46

Okay, great. What do you think about that? John,

Professor John Morton  35:48

yeah, I agree. I think that many of these are platform technologies and a sensor that is developed for some kind of health application. Of course, there are potentially ways in which technology can be applied in other ways. And quantum computers another great example of something which is a general purpose technology. So but I think for me, the tricky aspect comes when that potential security defense application then begins to limit international cooperation, which I think is really critical for the development of these technologies and and so where we need to be careful is is maybe not over emphasizing these kinds of security applications and we and we remember that there are still big challenges in developing these technologies, and to do that, we need to be working with the best people around the world and collaborating to make these a reality.

Dr Kris Naudts  36:37

Yes, I agree with a lot of the coverage in the media is also alarmist and talks about decryption and military and often the site for good is not highlighted enough,

Professor John Morton  36:45

yeah, but, but it was, you know, it was one of the first motivations for quantum computing. It was when the field really shot up, when Shaw's algorithm came along and realized that this RSA, 2048, encryption could be broken and and so, you know, it's a good example of where a kind of security or defense application then seeded this, you know, hugely powerful platform technology that we're expecting to have a big impact across many sectors. Very true.

Dr Kris Naudts  37:17

Changing topic a bit before we go to drug discovery, one of the things that I'm also very interested in as a doctor and former clinician, and I'm sure the same is true for you. Lara, our education as doctors is not software orientated at all, let alone, let alone Quantum. How are you finding that when you're bringing quantum in the workforce, there in the Cleveland Clinic, or I mean, I'm sure people are receptive, but where's the skills and how do you go about that?

Dr Lara Jehi  37:43

Yeah, critical question, I have to say. And it was one that we, you know, you can't really address it in just one approach. So we had many, initially, workshops, seminars, open houses, just, you know, that's why say having the machine was good, because, like, we would organize some of our post docs. Even organized a weekly lunch. It was on Thursdays around the machine, and they called it cube bytes, you know, as a play on the Yes of the word with cubits. So we had to be, I mean, like bend over backwards with coming up with different approaches to to educate and communicate. We worked with our medical school here in Cleveland Clinic. We have our College of Medicine, and it's one of the few medical schools in the US where research has its own year, you know. So there is the four year medical school curriculum. There is an additional year in ccrcm, which is purely research, okay, so we worked with the curriculum development team to add a data science education course right before that research year, and we embedded some self paced quantum education in it. To start there, we worked with our local school systems in Cleveland so that we start in middle school and high school with presenting what you know quantum is and what it can do. Our latest education exercise was, is partnering with one of our public school, state funded schools in Ohio called Miami University. There they developing a bachelor's degree, a master's degree and a PhD purely in quantum science. There's, of course, many PhD and master's programs, but this will be the first bachelor that I'm aware of where you just get trained in quantum technologies, and all of their students, part of their curriculum, will spend. A summer plus the semester that follows. So a total of about nine months in our labs, applying this quantum education and biomedical research. So it's in all of this is laying, you know, the ground work for instilling this education throughout our system, you know, from kids all the way to PhDs, and then offering them all opportunities to practice what they're learning, working at the Cleveland Clinic, in our research labs and with our clinicians, it's a it's a lot of work, but it's essential. Because if there's this technology and nobody knows how to use it, I don't know how useful is that.

Dr Kris Naudts  40:47

Yeah, exactly, exactly. How are you experiencing us as clinicians? To talk with John, you hinted at you guys, not always knowing where sensitive, but tell us more.

Professor John Morton  40:56

Well, I mean, yeah, the first step is really finding the the right language. Because I was actually remember being around a coffee table when we were first cooking up the Q biomed project, and we were all talking about sensitivity. And we were all using three completely different definitions, you know. So the physicist was using, we were talking about these nano diamond sensors. And as a physicist, I was talking about a sensitivity in Femto Tesla per root, Hertz, you know, some magnetic, some physical quantity. And the biochemists that we were with were talking about how many nanomolar or picomolar, so some concentration of a particle. And the clinician from Greg Ormond Street was basically saying, you know, how much blood do I need to extract from this child to get a measurable signal. And, you know, so the first level is, just as you say, understanding what, what, what is the sensitivity that matters, what, you know, where do, what's the current bottleneck, and where can quantum sensors help? But I think that, you know, since launching the hub, we're now well into, well over a year into into the hub, we're getting much more sort of inbound interest. The profile of the hub and quantum sensors has just been shooting up in the UK. More and more funding schemes to bring on new projects. And so now I think our big challenge is prioritization. You know, we develop these platform technologies, we end up growing long lists of different ways in which they can be applied. Some cases, it could be transformative, but for a very specialized disease that just affects a handful of people, in some cases, it may be offers a small improvement, but over something very broad, like dementia. And so, how are we going to prioritize all of these things, where are going to be the earliest wins? That's, I would say, the kind of challenge that we're grappling with at the moment.

Dr Kris Naudts  42:47

Yeah, very interesting. One is there any learnings? Are there any disciplines that are more receptive to this whole development?

Professor John Morton  42:54

One of the benefits that we've had is we've had clinicians within the hub from the beginning, so they understand the right way to engage. They understand the huge time pressures that clinicians are under, and so knowing what those entry points are right, trying to create new workshops and getting people to come is extremely challenging, finding out where they're already meeting, and going into those opportunities is using that to showcase I think that's that's been a key learning that has helped us make with early engagement. But I think once we've been able to start those conversations, we found clinicians extremely receptive and excited about this kind of new technology. And yeah, I guess for me, I'm learning a huge amount every day in these discussions, which makes it a

Dr Kris Naudts  43:35

lot of fun. And we learned from you guys, too, obviously. I mean for you, you Shay Shor's algorithm. We don't know what you're talking about. At first. We say cytochrome p4, 50. You don't know what we are talking about. There's every day that sort of dialog, and I'm sure Laura, you have it as well plenty of times.

Dr Lara Jehi  43:49

Yeah, absolutely. I really relate to John's point about learning the language. An example I always use is I show people who've heard me speak before heard it already, that when we started with putting those research teams together, you know, the biomedical researcher or the clinician together with the physicist or computational scientist, whomever is on the other side, it was like I had it all, where the one half say speaks only German, the other half speaks only Chinese. And I'm asking for a document in English. It was people really they know their field really well, but then it's really hard for them to open up and, you know, get that other expertise. Yes, it's always, for me, it's the most interesting and challenging part of the whole thing. Actually, it's building the right team.

Dr Kris Naudts  44:49

Yes, no. And I personally love these intersections very much, I mean, and they are everywhere. With quantum, it intersects with AI, with finance, with the healthcare world, it's super interesting to develop these languages that then. Both halves indeed end up speaking. Now, one thing that everybody always gets excited about, lay people, doctors, physicists, is drug discovery. As you say, it's a bit more popular, perhaps, than diagnosis, purely when we look at that world. Or Lara again, talking to you as a fellow medic. I mean, in pharma, there is Beringer Ingelheim in Germany that is very active in quantum probably, probably pioneering, if you like. There's Novo Nordisk, there's Eli Lilly. But then to our point that we just made drug discovery is also very much now a software and technology undertaking. Some people would say that NVIDIA is the biggest health company in the world. How do you look at that? Where do you see that go? Pharma tech and who extracts the value of these companies that are being built?

Dr Lara Jehi  45:48

Yeah, it's the million dollar question, isn't it? But you know, the whole field is so pharma companies are also moving in the same direction where the exercise of drug discovery is a lot more computational now than it ever was. You know, the the days when, say, I went to medical school or was doing residency 20 years ago, where most discovery in general was happening with bench research at the lab and, you know, trying different compounds to see what each one of them will do. Nobody does work this way. Now you know the potential the computation. This is not now a hypothetical. This is the way drug discovery happens. It is heavily computational at the beginning, in its initial phases, whether it is, you know, identifying the leads, optimizing the leads, finding the targets, all of it is really simulation at this point. And that is great for our patients, actually, because instead of wasting years building compounds and then trying them out, only to see that they don't work. At least what we can do now with computer simulation, you know, molecular dynamics, molecular modeling, however, you know all these different aspects, whether it's happening in a biomedical research facility like the clinic, you know, or in a pharma company, on what it's doing. It's skipping steps, you know, it's it's simplifying the process where we are prioritizing what the compounds that need to be prioritized so that we can take them further down. So I think the biggest value from a, you know, societal benefit, hopefully is going to be accelerated drug discovery and safer drugs. You mentioned the cytochrome p4 50, right? If we can simulate the metabolism of our drugs more accurately, then you know better preempt toxicity, efficacy, safety, then that will be tremendous. Now from a financial revenue perspective, who is going to recover most of that? That is very variable, I would say, across economies, across healthcare systems, structures and, you know, financial constructs, it will be, you know, it's the same as what's happening now in gene therapy, for example, right where we have these, you Know, the CRISPR technology and other technologies that can potentially cure a disease with just one application. So that is wonderful in theory, but they're so expensive that patients cannot afford them, right? So what did you end up doing at the end? Are we helping society or not? Over time, all of these technologies become cheaper. So I have no doubt in my mind that over time, it will all become affordable. But the challenge is this interval period where it's difficult, where, how do you deploy these innovations and maintain some equity, where the people who need it will get it, not just the people who can afford it, will get it.

Dr Kris Naudts  49:39

Exactly. John, yeah. I

Professor John Morton  49:40

mean, I think this, this is a wonderful application of quantum computing, perhaps even the first one that Richard Feynman spotted. You know, he said, nature isn't classical, dammit. And if you want to build a simulation of nature, such as what you want, if you want to design drugs in a computer, then you've got to make the computer quantum mechanical. And I think that. One of the challenges is, in order to do this properly, we're going to need very large quantum computers. There's some really interesting near term ways to solve the problem. Face craft has developed a technique called Quantum enhanced density functional theory, which is a way to split the problem of modeling molecules by giving some of the hard problems to the quantum computer, but otherwise using, let's say, existing classical techniques. But still, I think to really realize this kind of potential, these are the kinds of problems that will need quantum computers at the sort of million qubit plus level. So I think there we have exactly the challenge that Laura mentioned is, if this is a billion pound machine, and these problems take a long time to run, how are the economics going to work? And it's a fascinating question, then, how is the value of that going to be shared with with drug companies? And I think if, who knows exactly how that's going to turn out, but clearly, if it's a if it's an accelerating and transformative technology, quantum computing companies will find a way to value but hopefully we're going to find ways. And indeed, it will be essential that we find ways to build quantum computers in a cost effective way, even at that scale, so that you can really use them for these kinds of applications, and that may require different kinds of quantum computing hardware than we have at the moment.

Dr Lara Jehi  51:30

Yeah, I totally agree with that. You know, the way we're doing the way we're doing our part here is we have mobilized our we have a Drug Discovery Group here in Cleveland Clinic, our Center for it's more, you know, it's experimental therapeutics, and we do everything from, it's mostly small molecules for the most part, and some biologics too, and some targeted immunotherapy, car T cell therapy for lung cancer and other types of cancer. So all of this is happening now in Cleveland Clinic, and we have a group that does develop vaccines. We just developed a vaccine for breast cancer. So all of those groups that are already doing drug discovery type work are the ones that have partnered with our computational, you know, the quantum chemistry team that we have, and we, the way, what we're doing is we're basically dissecting all of these different steps on the computational side that have to go to enable these simulations, and we're building platforms around each one of them, Right? So, like, in a way, you take the work that we're doing and you see the papers coming out, each one of them is addressing a very specific computational challenge around that, that whole problem set, you know, that needs to be developed, and we're chipping at it step by step, so that whenever the hardware is ready, you know, like John is saying, we wouldn't be fully ready for it. And what we're realizing along the way is that there are all these opportunities to optimize where, in a say, even if we have hardware that can take in, you know, that has a million qubits in it, or, you know, that can take in so many such heavy computation Do we really need it to do that? You know, the fact that it can do it doesn't necessarily mean this is the way we should go. So we're doing a lot to figure out what of those steps really need, quantum versus what can how far can we go with advanced AI approaches right to so that, you know, we take the most advantage out of whatever hardware exists At any point in time,

Dr Kris Naudts  54:01

why has AI not quite delivered though? I mean, if you look at, say, DeepMind, I mean, I mean, how could you not be excited when alpha fold came out? It was such a game changing thing. I still remember it. It's almost like, as a medic, it's like goosebump material, almost. Then the billions have gone in isomorphic labs, for example. But we're still not there the clinical trial that was held out to be there by the end of 2025 and we all know we can have hold ups, but it doesn't seem to be necessarily within reach that first AI synthesized drug. Why is that, in your opinion? I mean, John, maybe you can.

Professor John Morton  54:34

Well, I probably Laura can say more with in terms of how, yeah, in terms of the existing efforts for for computation driven drug discovery, but maybe Feynman was right, right? Yeah, there are elements which are extremely difficult. And if there are, you know, if, if, if there's an, if we're limited to interpolating between what, let's. Limited classical simulations are giving us, then maybe we miss something, and maybe that's the key ingredient that we need a quantum computer to provide in order to support more more successful AI driven drug discovery.

Dr Kris Naudts  55:13

Yeah, could easily be, yeah. What do you think? Lara,

Dr Lara Jehi  55:16

yeah. So there are just inherent challenges with the way you can simulate drug with AI technologies. So, for example, you are in just the technology. You cannot simulate transitions and state really well. We, whenever we simulate drugs with AI, we assume a fixed structure. You know, this is the chemical compound, and this is how it looks like in but that's not really how the body works. You know, proteins change and receptors change, and all of these bindings are happening in fluid that they're not happening in vacuum, right? So it that is only one of the issues. There's many issues like that, rare diseases, that's a huge gap that, again, AI by definition machine learning, it's the output depends on how good the input was, whether it's diversity or depth of the data, right? So you train a model, alpha fold or others, on what is known well. So what is known is not really the the enough about the receptors and targets in rare diseases. So you will come up with predictions that don't really fit that well what you're wanting to address, I mean, those are exactly the challenges with AI based drug discovery that are fueling the interest in looking at what quantum can do.

Professor John Morton  56:49

That's an excellent example, and it sort of highlights the importance of time dynamics in materials discovery, which is perhaps one of the earlier applications in quantum computing, there's some recent papers that have been coming out claiming quantum computational advantage. We're looking exactly at this, at this problem of time dynamics, of modeling the time evolution of a material. And it's exactly that kind of element that that Lara is referring to, in terms of the dynamics in molecular dynamics that may be challenging for existing AI models, but where quantum computers are already showing advances in materials.

Dr Kris Naudts  57:31

Okay, could you clear something up, John for our audience? Because I feel that in the media, this gets constantly confused. So on the one hand, the media talks about the million qubit computer, and it's never said whether it's logical or physical compute qubits, and what these ratios even are? So that's one question. Second point is, in many ways, drug discovery, material sciences might very well be the low hanging fruit. And we might, we don't need a million logical qubits to do some decent work there. Could you? Could you demystify the qubit counting a bit in this particular context of drug discovery?

Professor John Morton  58:00

Yeah, no, the it's not only that, I know, but yeah, it's a really interesting you know, the challenge is, how do you, how do you take all of these different quantum computers around the world, and what people try to do is say, How can I describe their performance with a single number, right? And, of course, we don't do that with normal computing. We have clock speed, and we have RAM, and we have all of these other factors. So the fact is, you need to look at a number of different aspects. It's tempting to look at physical qubit count. In fact, that's one of the most simple in general methods. But as you say, in order to solve these deep quantum circuits and lengthy quantum algorithms, you need to wrap up these physical qubits into logical qubits, which are more robust, of course, one of the challenges there is, there is no single thing as a logical qubit, right qubits. Logical qubits don't suddenly become immune for the rest of eternity. You have, you have fairly rubbish logical qubits that may, may be a little bit more robust than their sort of physical qubits. Or you may have, you may group together large numbers of physical qubits to make much more robust logical qubits. So I'm not, in general, a big fan of the of the logical qubit definition, because it's just, it's it's too open ended. You know, it's like saying, how many applications can your computer run? Well, it depends. Are we talking about one really difficult one or lots of tiny ones. So, you know, I think that, generally speaking, when I talk about a million qubits, I'm talking about physical qubits. And the reason it's a large number is then we need to take, take these into group them up to make the kind of really strong logical qubits that can run a long algorithm like a like a problem in drug discovery, it's certainly possible that we can start to get some gains earlier using these kinds of quantum enhanced methods. And. Um, but I, you know, I would say that all these kinds of applications that have people really excited, you know, we need to show a route towards building quantum computers at the at this, at the level of a million physical qubits, and to do so, so that, you know, they don't take up the the GDP of a small country to build. You know, the kind of that they are in a form factor and a cost that we can, we can make many of them and put many of them into places like the Cleveland Clinic.

Dr Kris Naudts  1:00:30

Okay, wonderful. I'm gonna have a few more quick questions, because I'm aware of the time, one country that's also emerging, or has emerged very strongly in biotech, is obviously China, and it also is investing heavily in quantum and AI for drug discovery. Wanted to bring the process down from years to hours, is what I lost. Read, how do we, how do we follow that, and how do we, how do we know what is going on there, and is it safe, what is going on there? How should we, how should we try to follow it?

Dr Lara Jehi  1:00:59

Lara, yes. Well, I mean, of course, we're all supportive of international collaboration, and science is always a race, but we have to live within certain geopolitical, you know, limits that govern what we do. And there is a limit to how much you know the quality of what you can provide if you're cutting corners right so a we we can only follow what we're allowed to follow, and what gets published and what is made available to us, and you know, see what we can about what types of guidelines and principles in, you know, on being there,

Dr Kris Naudts  1:01:53

you follow the signs as well. You try to read papers about that they publish, at least in international journals.

Professor John Morton  1:01:58

Yeah, try to, but, you know, I think, yeah, it's always difficult. You get asked, What about the stuff that you don't know about? Well, I don't know about them, you know, I think it's, it is certainly impressive, what's, what's being done in quantum computing. But you know, if I, I, if I look at the quantum computers that are out there that we can access and run on the you know, they're still mostly in the US, I would say in terms of the most advanced systems,

Dr Kris Naudts  1:02:31

okay, prediction markets. We talked about it before a little bit. There's a couple out there. There's this poly market as Cal sheet poly market, the quantum stuff that you find there is on, you can make bets on, in what quantum companies, the US will take stakes. That's what, that's what they focus on, on Cal she It was indeed the the cracking of the shores algorithm, or indeed the ability for a quantum computer to simulate cytochrome p4 50, or indeed iron, molybdenum co factor. What do you think of that? I mean, have you put some money in or

Professor John Morton  1:03:06

does this count as insider trading?

Dr Kris Naudts  1:03:08

It does not. Yeah, I noticed it count

Professor John Morton  1:03:13

as investment Exactly. You know, I think it's it's interesting that, you know, the kind of dates that they were looking at this sort of threshold of where quantum where you get this inflection in really significant commercial returns and advantage, you know, the there seem to be values between the market consensus was Somewhere between 2030, and 2035, and and then you have efforts like this, DARPA quantum benchmark Initiative, a really fascinating international competition where DARPA is asking the question, not just can you build a quantum computer, but can you build one which is worth building, right where the cost addresses the value. And DARPA's timeline for that, their deadline is 2033 so it sits right in between those two extremes. So I don't know some somehow it all seems to be consistent.

Dr Lara Jehi  1:04:13

Lara, I would say that is safer and faster ways to make money than to bet on you. Yeah, I'll have to wait till 2035, and then, you know, maybe some return comes.

Dr Kris Naudts  1:04:28

But, no, but, but see the but it's interesting that it sits there. It's interesting

Dr Lara Jehi  1:04:36

in on the serious side. I was very encouraged to see that, and that, at least there is this is now so mainstream and so so so in the like realm of reality that there is like this catchy where, you know, people are betting on it, versus years ago, where this was science fiction in. For as a conversation. So just its presence, I think, is proof of how far the field has gone.

Dr Kris Naudts  1:05:08

Yeah, I agree. And I find talking with the two of you also, and just immersing myself more in the subject matter this heartwarming what quantum could do and how it could help the field forward and us as humans, contrasting that indeed, with some of the stuff that today comes out of the US, with the MaHA movement and drinking raw milk and Moon juices, sex dust, it at least this gives a bit of hope. And I do really hope that the cleavage clinic continues to contribute, and I'm sure we on our side of the Atlantic will do our bit, and I look forward to the to the future we're all building. Thank you so much, Laura, for your time, and thank you so much John as well. Thank you so much.

Dr Lara Jehi  1:05:43

Thank you. Thank you.

Professor John Morton  1:05:44

Thanks. It was a pleasure

EPISODE ENDS