Silicon healers: Unleashing the power of semiconductors to drive healthcare innovation – transcript

Ideas to Innovation - Season Three


Peter Peumans: In my current position, I’m fortunate to be able to actually make that bridge, we say from lab to fab, because we can go all the way to academic insights, the latest, the greatest, and try and translate it using our technology competences to something that people can actually adopt. And that’s for me the sweet spot of where I think I should be.

Intro: Ideas to Innovation. From Clarivate.

Neville Hobson: Over the past 50 years, the semiconductor technology landscape has been evolving rapidly, underpinning the digital transformations we witness across various spheres of life today. Sometimes referred to as integrated circuits or microchips, semiconductors are the backbone of modern electronics. In devices of every type, from simple gadgets to complex systems like smartphones, computers, cars, and household appliances, semiconductors have led to them being smaller or faster and more reliable.

Evolution continues at pace. For example, semiconductors are now enabling major innovations in healthcare to flourish. With more people living longer and chronic diseases on the rise, traditional healthcare systems are pushing to their limits and demand for new solutions is steadily increasing.

One company, IMEC, stands as a vanguard in this area. Based in Belgium, IMEC leverages its state-of-the-art global R&D infrastructure and its team of more than 5,500 employees and researchers for advanced semiconductor R&D activities.

In the near future, IMEC’s work promises to enable smart health concepts such as precision medicine and genomics to be brought within everyone’s reach, resulting in personalized treatments with better outcomes and lower costs.

Welcome to Ideas to Innovation, a podcast from Clarivate with conversations that explore how innovation spurs people and organizations to think forward and achieve their full potential in areas such as science, business, academia, technology, sport, and more. I’m Neville Hobson.

IMEC is one of 36 companies in the Innovators to Watch report from Clarivate for 2023. The report identifies organizations that demonstrate both exceptional potential and consistent above-the-bar innovation excellence. We’ll hear more about this report a little later.

Let’s talk about IMEC and innovation in semiconductors, especially in one area, genomics. To help us understand why this is exciting and to guide us through some principle points, I’m delighted to welcome Peter Peumans, the Chief Technology Officer for Healthcare at IMEC. Welcome, Peter. Thank you for joining us.

Peter Peumans: Well, I’m glad to be here. Thank you!

Neville Hobson: So let’s start with your role at IMEC, which you joined in 2011. Although perhaps we should start with before IMEC, when you were a professor of electrical engineering at Stanford University in California. It’s quite a jump from academia to commerce. What drove you to that career change?

Peter Peumans: Well, I think it’s in my DNA. It’s always been, I guess we’ll talk about DNA later as well. But it’s always been in my DNA to think of things and to wonder about how you make things really useful in a sense that people adopt it. And so in an academic setting, you’re awarded for, of course, asking questions about the nature of reality, nature of science and biology, and physics and so on, engineering, but you’re always a little bit further removed from the actual implementation of what you learn towards adoption.

And at IMEC, I was able to get into a position where you can still work at the edge of what’s possible using the latest state-of-the-art toolsets  and insights, but at the same time, be quite close to the actual end users who then adopt the technology, and that’s… and I find great pleasure actually in working in that space.

Now that being said, I also still find great pleasure in working with academics because this is where new ideas arise, new insights arise. And actually some of the most fun projects at IMEC  actually have been engaging with academics, for example, folks in the medical school at Johns Hopkins to figure out how we from our technology perspective, and our connections in the industry, could actually make a difference in point of care diagnostics.

So in my current position, I’m fortunate to be able to actually make that bridge, we say from lab to fab, because we can go all the way to academic insights, the latest, the greatest, and try and translate it using our technology competences to something that people can actually adopt. And that’s for me the sweet spot of where I think I should be.

Neville Hobson: You mentioned… I think bleeding edge sometimes is what I think when I was looking at some of the things you’re interested in, and very much at the leading edge: genomics that I mentioned in the introduction. It’s an area of keen interest to you, isn’t it? I know from reading about your interest that is very much the case.

Tell us about that and perhaps start with a concise explainer for our listeners of what genomics actually is and where the close fit is with semiconductors.

Peter Peumans: Yeah, I think a simple way of looking at it is that genomics is all about understanding the code of life, which is encoded in our DNA. Now if you want to read DNA, you’re faced with actually a significant challenge because of course DNA is a linear molecule, it’s quite small and reading it is not that evident so we’ve only really succeeded in reading the human genome, so all of the DNA present in the human cell, in 2001.

So it’s only been recently that we’ve been able to actually read DNA. Now since that initial demonstration, we’ve come a long way and we can now reach DNA much more quickly, much more cheaply. And it’s really important because it’s also a paradigm change in how we look at biology.

You could say that before we were able to read DNA using modern genomic tools, it was all about… there was no direct way to read biology, but now we’ve got actually a way to digitize biology, to translate what’s inside a cell into code essentially, that we can try and interpret. So it really is a paradigm change in how you look at biology and how you try and understand biology.

And once you can read biology digitally, you can also start asking different questions and look at the data in an entirely different way. And so that’s why this… this movement to, or this change to the model we’re doing genomics was, is important.

Maybe I’ll also add that this space is a space where semiconductor technology has an important role to play because it really is about reading a lot of data from a biological system. As if you want to do this in a reasonable amount of time, you need a high throughput system. You need to be able to process many bits per second. And that’s of course where some semiconductor or chip technologies excel at.

Neville Hobson: Maybe to break that down further, the more direct question I have is, what specific problems are you trying to solve with genomics? And maybe we could make that strong connection. And how will the technology you’re involved with every day address that? What can you tell us in that context?

Peter Peumans: Well, so there’s many angles, right? So I think a simple angle is that in a newborn who’s displaying some distress, for example, you want to understand if there’s some underlying genomic defect. And then of course you might go on to sequence the genome of that newborn to understand if there’s a mutation that actually is harmful to that newborn so you can go and try and fix it.

But it’s, of course, much more than that. I think an application that really speaks to the imagination is where you would actually take DNA that’s present in the bloodstream, for example, and you would actually read enough of that DNA so that… and once you’ve read enough of it, you might actually find a rare piece of DNA that’s not supposed to be there.

Could, for example, be, could, for example, originate from a tumor. So that is… growing in your body that’s not detectable yet using classical imaging technologies, but this idea of DNA-based surveillance could actually spot that tumor. So it might be a good way to actually look for cancer, a good way to screen and diagnose cancer. So there’s many ways in which you can conceive actually using DNA to our advantages.

And we haven’t even touched upon simply using our understanding of the genome, just to… or our ability to read the genome to get a much deeper understanding of the underlying biology. So we can actually come up with ways to cure people who are in, who’ve got a disease.

Neville Hobson: Got it. So I mean, this sounds phenomenal, what you just said, even, even for me in an area I’m not familiar with, you’ve explained it quite well. I’m just wondering, it sounds so amazing. There’s got to be downsides to this. What are the principal ones if there are any? I mean, there are, of course, right? What are they?

Peter Peumans: Well, so of course, the information that’s in your genome, in your DNA is of course, private information that you might wanna keep away from employers, insurers, governments and so on. And it should of course never be used in a way that’s discriminating. But in that sense, the information in our DNA is not that different from the information we display like our skin color or perhaps our religious preferences.

But we need to make sure there’s a framework, a legal framework, so we make it illegal to use our genomic information in a way that is not intended or good for the individual.

Neville Hobson: What about cost? These new treatments must be a fortune, right? So how is that in the picture?

Peter Peumans: So we haven’t spoken a whole lot yet about treatments of a patient’s  genomics, but just the piece of actually reading somebody’s genome used to be quite expensive. But at the same time, the cost has come down dramatically over the past 20 years. And today the cost of sequencing a human genome is actually very close to $100 per human genome, where it used to be much, or the magnitude higher, than that.

So the costs have come down and that is actually enabling more and more applications. And so we’re seeing actually, today we’re witnessing the fact that genome sequencing, so reading the DNA, has sort of become a commodity. The costs have come down so much that it’s no longer the main concern when we think about applying genomics.

And that will have implications on our ability to treat people based on genomic information because it has become a commodity and we can actually count on the information being available to look for the best possible treatment.

Neville Hobson: Before we… when we were preparing for this conversation, Peter, you talked a bit about an example with T-cells, you mentioned that the tumor cells, where you can harvest them, you take cells from a patient, you can harvest them and you program them, right. And so you do that, and then you put them back into the patient, and they’re programmed to home in on the tumor cells and essentially kill them.

Peter Peumans: That’s right. 

Neville Hobson: Have I explained the whole story there? Or what more can you tell us about that? Because that sounds pretty amazing to me!

Peter Peumans: Yeah, so that is indeed pretty amazing. That is really the next level.

So first we learned how to read a genome, and it gives us insights into how cells work and insights into several functional cells. Then you can actually start putting together new functions.

And so the therapy you just spoke about, CAR T-cell therapy, is one of those examples of where what you do is you indeed take an existing T-cell list, which is part of your immune system, and you actually go and add a new gene and we’ve learned how to do this because we’ve looked at enough genomes. And so we can cut out a piece of genomes and combine it and stick a new piece of code actually into these T-cells.

And the new piece of code essentially does two things. It allows these  T-cells to specifically recognize a protein that’s displayed on the surface of a cancer cell. So it allows the  T-cell now to home in onto those cancer cells. That’s one.

And once it has homed in, it allows the T-cell to actually launch a kill program to essentially release chemicals that will actually kill the tumor cell and also recruit other T-cells to do the same.

And so this is a good example of how our ability to read the genome and now more recently, our ability to actually modify the genome, is allowing entirely new therapeutic modalities that are much more powerful than the instruments we had before.

And today these CAR-T therapies are making a huge difference in the lives of cancer patients. There’s still a lot of work ahead in making sure that these CAR-T therapies are going to be useful across many types of cancer and also in making sure that we can contain the cost of manufacturing these T cell therapies.

But on both of those fronts advances are being made every day.

Neville Hobson: That’s a great starting point. I mean, the word to me, innovation, screams, listening to what you’re saying. Classic example that fits exactly with the kinds of topics that we’re very, very interested in having conversations about. So thank you for that example.

At this point, I’d like to bring in Ed White and introduce Ed to you who joins us. Ed is vice president and principal analyst for IP and innovation research at Clarivate, leading the Innovators to Watch program that I mentioned earlier.

Ed, thanks for joining us.

Ed White: Thank you, Neville. Glad to be here.

Neville Hobson: So tell us about the Innovators to Watch program and indeed IMEC’s inclusion in this year’s report.

Ed White: Yeah, Innovators to Watch is actually quite a fun analysis piece that we put together, which what we’re doing is we’re delving much further into a wider Clarivate program called Top 100 Global Innovators. We started doing this around four years ago, around the same time that I took on the reins of that Top 100 program.

And actually the background to this is quite funny. It’s really because I got my hands on the data for the first time as an analyst. And my eyes straight away went to the organizations that were outside the top 100, who was hundred and first, who was coming, who’s rising up the ranks, the fastest, and hopefully on the not too arrogant basis that what I thought was interesting or what we thought was interesting, we thought would be interesting to other people as well.

So we created this new insight piece to really put a methodology around which organizations are on a pathway to top 100 status.

A little bit of background I think is needed on top 100 Global Innovators itself.

This is an enormous analysis of all global invention data. We are looking at patented ideas and we’re looking at which ones influence the most, which ones lead the field, which ones have the most reach geographically and have been most invested in, which ones are distinctive in their field and rare, and then mapping that to the entities which produce those strongest inventions at higher scale and do so most consistently.

For Innovators to Watch, we add a few steps. We then look for which organizations, which companies, which institutions have not been in the top 100 before, and therefore would be a new entrant, would be new to top 100.

We look at which ones are within a sort of set range of rank 100 and therefore kind of have a chance, if that makes sense. And then we also look at which ones on average have risen up the ranks in a way that is greater to their current gap to that position 100. And that produces, that gives us a list at each year of somewhere between 25 and 40 organizations. We don’t put a cap on that. There’s no quota on that. We just let that happen naturally.

And for 2023 and indeed 2022, brilliantly, that includes IMEC. When we think about, you know, the organizations that we see in there, what is an innovator to watch, what it really is, is an organization that is accelerating in its intellectual output versus not just its competitors or its peers or any other organisation in any other field, but against all human patented knowledge of the past five years. So the sheer scale of that, the enormity of that is really, really impressive.

And it’s there, Peter, that I’d love to ask you about your work at IMEC from a very specific angle, and it’s this angle around the… the cross-disciplinary nature of your work, which I find very fascinating.

One of the things that we’ve tracked in these large top-down datasets is the increasing nature of interdisciplinary innovation today in the 2020s. We’ve seen it lots of different ways, but probably the statistic that summarizes it for me is that we see more inventors on inventions today than we saw in the past.

And your and your team’s work seems to exemplify that cross-disciplinary approach and the wider difficulty and opportunity of tech convergence more generally. And in your area, I really see that overlap of semiconductors and computer science alongside biochemistry and genetics and microbiology and probably a whole load of other fields that I’m not mentioning, you know, they really come together.

I’d love to get your thoughts on of the importance of that to you. And also maybe whether you find you have to actively focus on it to create the circumstances for that to happen.

Peter Peumans: Yeah, absolutely. So as you point out, innovation happens per definition at the intersection of multiple domains and that implies automatically that you need to include folks from a multitude of backgrounds, perspectives, to come up with the best possible solution. This is, in my case, everyday crew that we need people who understand transistors and atoms, but also people who understand biology and cells and molecules.

So inclusion and making sure you’re building multidisciplinary teams is not just morally the right thing to do, a moral imperative, but it’s actually really, in a real sense, the best way to innovate and to make progress. And so this is something we worry about every day at IMEC.

Now, after having said that, I am also acutely aware that at most places, and this is definitely the case at IMEC, we still have some way to go in actually making sure that that’s true and making sure we do it the right way.

And I have a feeling that doing inclusion and making sure that we take all, we use all the possible different perspectives and ways to look at things is going to feel a little awkward at first as we expand teams to include perspectives. Because we’re doing things differently from the way that we’ve done before, but it’s the only way forward. And so if you want to get to the next level of innovation, so we’re working on that aspect every day at IMEC.

Neville Hobson: Anything you want to ask, anything else you want to add to that, Ed, that sounds a pretty good framework that Peter mentioned.

Ed White: It is, and one of the things that I find quite brilliant in your answer, Peter, is that you kind of treat it as air, which I think is telling in terms of the work that you’re doing.

Neville Hobson: So that’s actually brings us to a pretty good point where we can talk about what’s next, what things may look like a decade from now. Some are saying that the overall industry is anticipated to grow. I saw this figure recently to $1 trillion US dollars. I mean, that’s an impossible to think about number almost. It’s a lot of money in revenues by 2030. That’s doubling what it is in this decade.

So if the money is there, is the opportunity as well? That’s my question to it.

Peter, how does the landscape look to you looking ahead a decade? You mentioned earlier that some of the things that are happening in what you’re working with now in the cancer area, for instance, in healthcare, sets the scene for what’s possible.

I mean, some of the things you described that the costs are high, they’re falling. Sure. But as we look 10 years ahead, will some of these things be literally taken for granted, this is how we do stuff now? So what is it that we can expect to see in your areas of keen interest, such as genomics in 2023, let’s say? What do you see?

Peter Peumans: So I think the big thing that is happening right now, and we’ll see the fruits of it in 10 years time, is that increasingly it’s not just about reading genomes to understand them, it’s now also about actually using the knowledge and it’s about actually creating a toolbox so we can actually manipulate biology.

And that’s really important because some of the very powerful modalities, therapeutic modalities that we have, it’s actually all about manipulating genomes. So it’s about creating cell therapies that can actually fix a problem, whether it’s a tumor or neurodegeneration or some other pathology in somebody’s body. Or you might actually be interested in creating organisms that actually are really good at synthesizing a fuel or a food or a plastic that we need in a much cleaner, more sustainable way.

So for me, the next decade release is going to be the decade of synthetic biology where we use our genomic toolboxes and other toolboxes that are being worked on to actually manipulate biology to our advantage, either to cure people or to do things in a much more sustainable way.

Neville Hobson: That’s very interesting. Ed, what are your thoughts? What does 10 years ahead look like to you in this context?

Ed White: Well, I’d maybe broaden the context a little bit and talk about it in terms of the macro view that our sort of global research shows in innovation ecosystems. The first thing that comes is just the sheer scale of the challenge that humanity faces across so many different technology and innovation research fronts.

So the topics, they’re all familiar to us by now, but the topics that are going to be the drivers of technology development, they’re going to even more revolve around energy transition in every industry, we’re going to be talking more about resource management and reuse.

And of course, actually, in Peter’s world, I’m sure that the changing demographics that are the drivers for new solutions in healthcare, that all of that tells us that there’s going to be more, volumes will behigher, more work is going to be done.

We’ve been talking a little bit about convergence, and I would broaden that topic in terms of a trend into even more complexity and even more competition if we’re talking about it from that perspective. So we see those complexity drivers in terms of a very large-scale diversification in geographic sources of innovation, in particular the volume, the quality, and quite frankly, the importance of, for example, mainland Chinese research is going to change the way that innovation markets work.

And then another one that I think is really interesting is that convergence slash collaboration dynamic is we’re seeing that change the size of innovating organizations. We’re seeing more of current ideation coming from smaller and more specialist organizations.

And I can foresee a trend that we’ve seen in particular in the pharmaceutical industry. And I’m sure there’s something that Peter’s seen as well, where you get more technology licensing, more collaborative research, what I’d maybe call distributed research across a number of organizations feeding a pipeline, I can see that becoming more and more common in other areas as well.

And then lastly, data, data everywhere, data and connectivity changing the possibilities, you know, they’re changing the possibilities of why Peter’s field even exists in the first place. It’s clearly important in the medtech field, but it’s absolutely not limited to it.

So you take all of that together, a lot more challenge but a lot more opportunity. That makes it quite exciting. It’s gonna be more collaborative, more complex, more data, more AI driven, riskier probably for individual players. And because of that requiring even more knowledge and diligence and skill than ever before to succeed.

Neville Hobson: Terrific. Peter, final word from you to what Ed said, anything you want to add to that?

Peter Peumans: Well, I actually agree with all of what Ed said. Maybe a final word could be that, in a sense, it’s when I talk to people about the impact of technology on health and our lives, that a lot of people are worried about, you know, two aspects really.

One is, hey, that’s going to cost a lot of money. So is that even sustainable? And two is, yeah, but hey, what’s going to happen to my data? And, but I’m on the positive side of those two aspects. I think technology really has potential to make state-of-the-art healthcare, therapeutic options, just much more accessible, affordable for anyone. I mean, that’s, you know, we’ll see that happening.

And two is, I think, on the data side and the concerns about, you know, how you might even implement AI in a way that is acceptable in a healthcare context. I think there’s plenty of technical solutions to make that possible.

And so I’m on the glass half full side and I’ll continue to advocate for that.

Neville Hobson: Excellent. Now, the optimistic perspective is terrific. So I’d like to thank you both for sharing your knowledge and insights on a topic we’ve only scratched the surface on, but it’s been very, very interesting this conversation. It’s been a pleasure to discuss this with you both that presents such outstanding examples of thinking forward in the real world.

So Peter and Ed, thank you both very much.

Peter Peumans: Thank you, Neville.

Ed White: Thank you, Neville.

Neville Hobson: You’ve been listening to a conversation about innovation in semiconductors, genomics, and the future for health care with our guests, Peter Peumans, the CTO of Health Technologies at IMEC, and Ed White, Vice President and Principal Analyst for IP and Innovation Research at Clarivate.

For information about the Innovators to Watch program, visit clarivate dot com and search ‘Innovators to Watch’. For information about IMEC and its semiconductor technology, visit imec-int dot com and search ‘semiconductor’.

In a few weeks, we’ll release our next episode. Visit clarivate dot com slash podcasts for information about Ideas to Innovation. And for this episode, please consider sharing it with your friends and colleagues, rating us on your favorite podcast app, or leaving a review.

Until next time, thanks for listening.

Outro: Ideas to Innovation. From Clarivate.