From DNA research that unlocked the biotechnology sector to fibre optics and digital imaging that enabled today’s networked society, fundamental discoveries have shaped industry and society alike. Yet public research and development commitments have stalled globally for the first time in two decades.
How can we reinvigorate a growth model that treats science not as a cost but as a strategic engine for prosperity?
This session is in collaboration with the Geneva Science and Diplomacy Anticipator (GESDA)
At Davos 2026, leaders from government, industry, and IP debated why “science as a growth engine” is weakening just as discovery accelerates across AI, quantum, and biotech. Switzerland’s Martina Hirayama noted the state’s role remains central—“80% of the public funding goes for basic research”—but warned that looming budget pressures could mean “no growth,” and that over-directing funds narrows the diversity basic science needs. DSM-firmenich’s Sarah Reisinger argued breakthroughs require decades of patient capital: “An mRNA vaccine didn’t come in three months.” She urged leaders to treat R&D “not a spend” but “an investment in our shared future,” and to tell clearer public narratives about long timelines from curiosity to impact.
WIPO’s Daren Tang reframed intellectual property as a strategic tool to “create value, store value, and share value,” emphasizing ecosystem-building over legalism and cautioning that R&D is concentrating into too few sectors. Formation Bio’s Benjamine Liu highlighted a practical bottleneck: drug discovery is outpacing development, with approvals stuck near 50 per year; the constraint is clinical trials, regulatory throughput, and uncertain endpoints. The panel converged on three imperatives: sustain diverse basic research, modernize regulatory readiness, and build innovation ecosystems that translate lab insights into scalable societal and economic outcomes.
Good afternoon, and welcome to this conversation on science as a Growth Engine. My name is Marilyn Anderson. I'm the director general of the Gesta Foundation and professor at EPFL. And it's my great pleasure to invite you here and welcome you here to listen to our distinguished panelists, which includes Martina Hirayama, State Secretary for education, Research and Innovation of Switzerland. Darren Tang, director general of the World Intellectual Property Organization. Sara Risinger, chief science and research officer at DSM Firmenich. And Benjamin Liu, CEO and co-founder of Formation Bio. Welcome, everyone. Today, the pace of scientists scientific discovery is accelerating and this is happening in many different fields. Artificial intelligence, quantum computing, synthetic biology, neurotechnology. While institutions have a hard time keeping up with that pace. And yet these changes have a transformative impact on our society, especially as AI is now accelerating even further across these different fields. So these advances are not just transforming our economies. They are redefining what it means to be human, how we think, how we decide, how we relate to each other and to our planet. And as science advances become drivers of geopolitical tensions, as we can already see with AI, as well as generate existential questions on our common future, we need to anticipate what these changes are and prepare our institutions for them. This is, in fact, what Gesta, the organization I have the pleasure of leading, is doing, anticipating upcoming scientific breakthroughs that are emerging tomorrow by acting about them already today, when it is still time to do something about the transformations ahead and try to act and decide, acknowledging them in both the diplomacy and the business sector. Now, the key institutions in that regard are those that are funding fundamental research. But we are witnessing a paradox. While governments and societies tend to rely on these scientific breakthroughs and the discovery to enhance productivity, competitiveness and resilience, as well as offer responses to our main challenges on societal challenges or environmental challenges, we see public investment in fundamental science waning. The diminishing, which is a little bit of a surprise. And this happens in different economies. So the session today will explore what is at stake in this shift and assess how funding dynamics evolve, whether from a policy angle or from a business angle, how scientific breakthroughs go from labs to broader economic or societal value, and therefore use the next 40 minutes with by focusing on what is required to reestablish science as a strategic engine for long times prosperity, and more firmly place science in economic models by balancing risks with opportunities. We will also reflect why sustained and strengthened support to scientific research is critical to generate discovery underpinning future growth. So, to start the conversation, I would like to first address myself to State Secretary Hirayama. And so from your experience leading national science and innovation institutions, how have public funding priorities for fundamental research shifted in recent years? And what risks or tradeoffs do these shifts create for long term scientific capacity and economic resilience?
Thank you very much. So if I look at Switzerland going back to the early 2000, Switzerland tripled the funds for basic research in these years. So we had a good growth and a strong focus on basic research. Switzerland still has a strong focus on funding basic research with public funding. We have two funding agencies in Switzerland, the Swiss National Science Foundation, mainly funding basic research and careers, and Swiss mainly funding technology transfer to SMEs startups. So in Switzerland, 80% to the public. Funding goes for basic research because we believe there the role of the state is an important one. And in general, Switzerland has a strong commitment for research and development support. So we have about 3.2% of the GDP being invested in research and innovation. About 70% of it comes from private funds. So we need to go for good framework conditions to really have private funding in research and innovation. And a lot of it is also going in basic research, especially if you look at pharma, for example, a lot of this is used in this direction. And for us it's important to have the focus on competitive funding because we believe that this is crucial for excellence. You need, of course, a good basic funding of the university system. But in addition, the competition, when it is about funding, we need international cooperation, which is crucial for excellence. Therefore, for Switzerland, it's important to be part of the European programs. And this, if I look at the funding, is then the second largest funding in Switzerland and there in the European funding, of course, we have funds for basic research and for innovation, but the balance is different. So it's more for innovation and, and less for basic research than it is in Switzerland. Of course, the next years to come in Switzerland, 2829 we will have, a reduction of funding not only for basic research in general for research, innovation and education activities. Because of other needs for defense, for example. But if you look at the whole period, it means it's no growth. And it's a difference if there is no growth or if you really have cuts and reduction. But like you mentioned, we have important trends. We need, basic research. If you look at our future, I think, maybe we will talk about this later on. Bottom up, top down activities is an important question for the future. You know, Switzerland has a very strong bottom up focus. Long term short term activities. Basic research is always focused on long term, success. If we live in the age of AI, it's more about short term success. What does it mean? So a lot of questions.
Thank you very much. And if I may now transition to you, Sarah Riesinger, as you are in charge of scientific and research strategy in industry leading innovation, you are also well aware that public investment played a critical role in advancing mRNA research long before its rapid deployment in in vaccines. So from your perspective, what lessons does the amini r Amare m-rna the French is coming in here? Yeah. Experience offer for how governments think about funding fundamental research today, particularly in terms of time horizons, risk tolerance and readiness for future societal challenges.
Yeah, that's a great question. And when the first mRNA vaccines came out, people thought that technology came so fast. But really it was decades of research. And the story of that funding was not an easy one, which at times was very difficult to get that funding. But that's just one example, like quantum mechanics. That is something that really is the reason you have an iPhone. It's the reason we have semiconductors. You know, if you look at, Crispr, CAS and gene editing, that is so important for medicine and for new agriculture. That came about because someone was studying bacteria and identified these interesting repeats in DNA and said, what's going on? So that curiosity of these initial scientists that then took decades to then transform and have profound impact on human health and society and even just how we live our lives. And so what we have to realize is, when you're doing these basic science, when you're learning about mRNA, how life works, you maybe don't know yet in that moment how it's going to impact the world. And that's where we have to ring fence R&D money, both in academia but also in industry. Because in industry, it's easy to say I'm only wanting to fund the next quarter of R&D, but we have to, as a community, think about these huge leaps of breakthrough technology only happens with sustained investment. You can't invest and then take it away. That's why, as you said, you have to at least sustain what you have to continue to be able to do that. So for me, that's the profound importance of government as well as industry, looking at investing in the long term and then in industry, we also have to prepare ourselves to say, as these new technologies are coming out and as the convergence of all these sciences are coming together, how can we prepare to then deploy these into the world so they can have such an impact?
Great. Can I just follow up on this? Maybe, Sarah. So pressure increases now to demonstrate the actual impact of of research investments. So how can institutions and companies protect the longer term horizons that are required for fundamental science while still responding to expectations around productivity, competitiveness and return on investment?
Yeah, so this is where I always like to say it's about investment. R&D is not a spend. It's an investment in our shared future. And this is where in companies especially you have a balanced portfolio. So yes we need to look at leveraging already existing technology. And how do we bring that to market quickly, but also with an eye towards how can we long term maintain competitiveness and bring completely new solutions to you? I also think both the the entire community of scientists, industry, academics and government, we need to do a better job telling these stories. We need to do a better job of telling the story or, you know, or the quantum mechanics story. And iPhone didn't just happen, right? An mRNA vaccine didn't come in three months. And so if we can, people connect with those stories so they see what's in the store or what's in their doctor's office, and realize that that's why some really basic funding or things like experiments happening on the moon actually do play a part years later in what you're doing in your day to day life.
Great. What if this might lead us to a Darren Tang as director of Ypo? So you have a very direct view of how funding demand dynamics for basic research evolve globally. But what role can the intellectual property system play in reinforcing science as a long term strategic asset, rather than the short term cost, while balancing incentives for innovation with public interest outcomes?
Well, first of all, Marilyn, very proud that Ypo was one of the founding stakeholders in. We are very excited about that. And I think a lot of what Sarah mentioned about, how do we make sure that the value that we put into R&D goes back to society? Right. And IP has a role to play in that. But in order for that to happen, right, we need to stop looking at IP from a legal compliance angle, which leads to very, uni dimensional conversations around whether to patent or not to looking at IP right, as a way to create value, as a way to store value, and as a way to share value. And I think that that mindset. Right. And that we're looking IP in a very different way, it's present in all the good ecosystems that we see, in universities that do this very well in terms of tech transfer, they're able to balance between the needs of society as well as the return on investment, as well as in countries that are, that are, that are good at that. Switzerland, by the way, congratulations. Top in global Innovation index for 14 years in a row. Because the Swiss system has that balance built in because of your checks and balances and that unique Swiss system. So if you look at IP as a way to create, store and to share value, right, then you have a very different mindset because people always have this stereotype that IP is just a way to grab and to hold on to value. But in fact, IP is a is a property, right? And like any property right, you can share it, you can lease it out, you can lease it on conditions. You can decide that I'm going to lease it for this very interesting public purpose. No royalties to be paid, but then maybe another in that same IP when someone wants to come and make a profit out of that, you can decide that. I want them to share a bit of the royalty. So IP can be a very flexible tool for you to use it to be able to get value in different ways. And I think part of that also is how do we help our member states, and how do we help those within member States to now to know how to balance between open innovation systems and closed innovation systems, open innovation systems being things where because it's a platform technology like the internet, for example, people say that if CERN and Tim Berners-Lee, if he had patented and monetized the internet, the world would be very different because he did not do that right. But at the same time, IP can be valuable even in these conversations, because you can have open innovation systems and strong IP systems at the same time. In fact, our research shows that, the the growth of patenting in the last 40 years with the Bayh-dole act in America has not reduced the amount of of open systems and amount of scientific collaboration as well. So I think we need to move away from a black and white stereotype views about IP, where it's seen as only relevant to advanced economies and advanced players, and not relevant to to others, to others, or to or to open systems. Right. And have a much more subtle view of that. So what we're trying to do at Ypo is how do we help member states and actors to have a much more nuanced, subtle, sophisticated use of IP, right, so that they can make use of it, for value, whether it's long term value back to society or whether it's a slightly more short term perspective where there's pressure to give returns back within the corporate setting or whether in, in, in, in a, you know, public private partnership. So it can be your very flexible tool to make that happen. If you look at it in the correct way.
With the right lens. Yes. So let's look at the lens from, Benjamin Liu. So you're taking the standpoint of a company built around accelerating drug discovery with AI. So that means you bring AI to expand the pipeline of potential drug candidates. But discovery isn't necessarily delivery. So what changes in research infrastructure or public private collaboration do you think are most critical to ensure that foundational science translates into scalable economic and health outcomes?
Great. You know, we're living you know, as you mentioned, one of the most exciting times for biotech and healthcare. You know, I actually trained as a computational biologist. I think, like many, was excited about how AI and all the genomic, proteomic transcriptomic data at scale could transform drug discovery. And when I was a graduate student, we discovered a few candidate drugs for Alzheimer's and Parkinson's and naively went to a number of pharma execs and said, hey, we discovered these drugs. Aren't you guys excited? They actually shared something quite surprising. They said, sorry to burst your bubble, but we often already have more good drugs discovered than we can afford to finance in drug development. A single clinical trial. Drug development across phase one, phase two, phase three could be hundreds of millions of dollars. And, you know, even though we're cash rich, you know, we have, ROI metrics that we need to kind of overcome. And so we kind of took a step back and we said, well, if we live in a world where drug discovery is only getting more efficient, but no one truly knows what's going to work until you run a clinical trial. And the past ten years, there's been A2X increase in number of drug candidates discovered. But the number of approved drugs has kept constant at 50 per year. And so the bottleneck, ironically, isn't actually in discovery. It's actually in that translation of those discoveries into new medicines and in this case, in the drug development kind of process. So as a company, we've thought a lot about this kind of bottleneck. And, you know, one of the biggest bottlenecks is how do you run clinical trials more efficiently. And the role of AI to transform things like medical writing, protocol development, biostats all the nuts and bolts of what's needed to do the process of clinical trials. You know, that's kind of a huge opportunity. Beyond just running trials more efficiently, though, like there are a number of things that I think would transform this bottleneck. And one is on the regulatory side, it takes a really long time currently for most regulators to ingest, you know, you know, an application for a new drug. And if you are trying to underwrite the upside, talking about ROI every month really matters, right? Every month is one year or every year. Every month is like that percentage of the patent life. So there's a lot of things, I think, that can be done with leveraging AI to transform the speed in reviewing applications. The other kind of thing is just to be very clear around what our approvable metrics. One of the biggest challenges as a biotech is understanding what you need to hit before, you get a drug approved. And as a scientist, I think we all came from like this hypothesis driven culture. So like basically you would like to say, if I hit this exact endpoint, I should get an approval, right? But we actually generally don't know. Or we get these feedback sessions. I'll talk about the FDA maybe once every like, you know, 3 to 6 months, sometimes not not even as frequent. And so that uncertainty makes it harder to underwrite. And as an industry actually, and this is where there's a really interesting, opportunity, but also disconnect between the basic science and between what is actually being financed in the for profit or kind of a commercial world. And so a lot of the scientists, I think, focus on these amazing basic research, kind of projects to understand what is truly disease modifying. Right. So do I understand the progression of disease? How can I target disease to modify the disease? In our industry, if something prevents maybe a longer term outcome, like we acquired a drug that that grows cartilage and knees. And it's been in three separate studies, including a five year study, two year treatment period, three year follow up, about 549 patients. And we found that it not only grew cartilage, but, everyone who took the highest dose didn't get a knee replacement within a five year period. That is a really hard situation for pharma to underwrite, because if something delays to prevent something five years later. Right. And arguably you want to take drugs that prevent longer term outcomes, be it Alzheimer's or osteoarthritis, knee replacements, you kind of have to run longer than a five to 10 to 20 year kind of trial. And so as a consequence, if you kind of think about every drug that's developed, it's not prevention based therapeutics. It tends to be symptomatic. And going to kind of Sara's point around the ROI or the underwriting of that. Most trials have to be 1 to 2 years, you know, long because it's a few hundred million dollars for even a 1 to 2 year study, let alone a 5 to 10 year study. And this is where I think, private public partnerships can play a huge role specifically identifying endpoints. So if you have maybe an AI predictor that predicts who gets a total knee replacement from an MRI image of the knee, and you can show that your drug reduces that risk, or in the case of Alzheimer's, if there's something that tracks with the progression of disease rather than waiting for the conversion, and you can then begin to go after these longer term kind of outcomes. But that's an interesting I always find a distinction between amazing basic science research, looking at the root cause of disease, challenging to underwrite those programs kind of in today's world without that public, private kind of partnership.
Thank you very much for enlightening us on the sort of the inner workings of this transition from the lab to society. And maybe I would like to go back to the role of government in, in this, in this transition. So what role can governments play in strengthening the pathways between publicly funded fundamental research and broader societal and economic value, while preserving. It's always a back and forth, preserving the independence and long time horizons that basic science of course, requires. By definition.
It was mentioned before that it's very important, that we can show to society, that you have added value through basic research activity. And this does not mean that every research you do has to result in a product or whatsoever. So it must be about curiosity, about new knowledge. And some of it can be very useful for society. So I think an important part is with the researchers themselves communicating about their their work, what they want to learn to to know what could be done if the research would be successful, and then if they are successful transfers, of technology, for example, to show this and explain what was necessary. Like you mentioned before, RNA was not there. Just in a few months. A lot of research had been done before. So to explain this, to really take the society serious, because in the end, it's a taxpayer who has to be committed to fund basic research. So what on on a government level, what can you do? You can try to find framework conditions to enable technology transfer. In Switzerland. Of course, one important activity is done by Swiss to bring universities and companies together to find out where possibilities for technology transfer are or to bring new, knowledge to startups to bring some disruptive, new ideas to the market. And this is where the government can play a role. And also, of course, defending basic research. But but the researcher has a very, very important part. And I think for a long time the researcher was focused on publishing in important papers, which is, of course, also an important part of research activity to share with your peers your thoughts, your results. But another important part is to share in another, language what you did, what you achieved, what you want to achieve with the society.
And so if we now go to the perspective of IP, you made a great case for IP being a right. And then you just mentioned tech transfer. So if we look at current IP frameworks that both support and constrain, as you said, the translation from fundamental scientific research into more broad economic and societal value. So what is your position in the context of a slowing public investment?
I think, there is, of course, a agree with Sarah and with, Martina that, in this day and age, where public finances are under a lot of pressures, a dollar spent on R&D is a dollar not spent on something else, whether it's infrastructure or trying to build a digital economy or restructuring or defense, as is the case. So I think the communication around this becomes very important. So I just want to start by saying that. And I think one of the things we try to do at Ypo is that we try to help people understand that in order to translate research into value for society and economy, you need to not look at IP again, just as passing laws and regulations and having the right IP, you know, legislation, but building innovation ecosystems. So a lot of wipo's work now. And I think you started saying that the world is transforming. So even we as a UN agency, we have to transform our work. Ypo historically has focused on IP enforcement, IP registration. Now a lot of our work is focused on helping IP be used to build innovation ecosystems. It goes beyond patenting. It looks at to things like, how do we help the research ecosystem connect with the enterprise ecosystem. It looks we look at things like how do we help develop tech transfer capabilities? We've set up 1800 tech transfer offices around the world in the last few years. We're helping the Baltic States Tech Transfer Network to be networked with Southeast Asia, which is where I come from, from Singapore. So really trying to do things that go beyond the traditional work, that of IP laws and passing IP laws. But how do we build innovation ecosystem? Because how do we help that great idea in the laboratory become something that helps people, you know, and sometimes the pathway is 20, 30 years. I mean, semiconductors, right? I think it was the initial research was done through material science at University of Göttingen as well as Tokyo. Then it got taken up by Bell Labs, and then from Bell Labs it became, you know, but that was like a 30, 40 year journey. And I think if we if we build innovation ecosystems that allow people to partner, to collaborate, to talk, that is really where we can see some of the value. Of course, then we have to tell the stories of these things. So I think, I think building ecosystems rather than just fixating on IP laws. Right. It's really the way to go. And we see more and more countries embrace that. And our job is to help to make sure that we are able to bring the skills, the policies, the practices, the strategies, right, very much in a practical way, to to allow them to make that happen.
And so when we connect this to funding and timeline, because time is also a big factor. When I would like to go back to you. So how do you see these constraints. So both funding and timeline across, research and clinical trials dictate which scientific discoveries ultimately do reach the patient. So going back to the delivery question.
I think timeline is one of the biggest drivers in our industry. And so, you know, if something just takes a lot longer, that's not just, patent life lost, but also, you know, I think most companies think about an IRR, so an internal rate of return and there's hurdles, right. And so we actually see this manifest a lot because, you know, there's been an explosion of drug discovery and discovered drugs are seen not worth much now until post phase two. But the issue is most biotechs are started, you know, and maybe it takes them 3 to 5 years to get into the clinic. And this is actually after the translation, medicine and all the great work that is funded through kind of governments and non-for-profits, but the average biotech kind of life cycles, that takes 3 to 5 years to get to the clinic, and then it takes 1 to 2 years to run the phase one, and then maybe two years or so to run at the phase two. And you actually don't get credit today until post phase two. Because if the if the world already has more good discover drugs, at the inflection actually doesn't happen until post phase two readout. So it actually influences a lot of where we see the gaps are. And it specifically has been in this early phase one to phase two translation where you have a maybe AI discovery company or platform company, they can discover five, ten, 20 drugs, but they only have enough capital for that lead asset. And if you know, for those that have been tracking the public markets, a biotech was very dislocated when the interest rates kind of went high because there's just so many assets and not enough capital to take that risk post phase two. So so we actually put together a pool of capital and kind of our models. We licensed drugs pre phase two. And then we're able to develop the drugs a lot faster using AI systems to do drug development process and to pick the right drug for the right indication, develop it post phase two and then we partner back it to pharma. Or sometimes we'll commercialize ourselves. But there's kind of some of these key bottlenecks. And I think you alluded to a lot of them. One is like just when the basic science discovery is made, we kind of took a look at in our industry, like every fundamental platform where modality, be it like mRNA or antibodies or small molecules, on average, it's 20 to 40 years for the time of the first published paper to when the first approved drug in that modality is. And so that actually frankly, without like funding from governments would be untenable for industry. And so our industry does not exist without funding from, kind of, governments and nonprofits. Even after that, as we discussed, because of this impedance mismatch where discoveries and we make the argument discoveries probably only getting more efficient as AI transforms drug discovery, the rise of China, new biotechnology kind of progress that this fundamental bottleneck will be this drug development post phase two kind of process. And I think if there are, kind of groups thinking about where to park capital to create these public private partnerships, it is around the space to kind of transition point, because it's also where you can make a return. And, you know, I think a lot of folks have talked about, maybe some of the institutions that fund the research should get a royalty or some percentage and kind of feed that back into the system that helps us communicate to societies. Some of the upside, you know, just maybe kind of one last point. You know, I was with a number of my, my friends in AI and tech and, you know, there are companies that are committing to trillions of dollars in data centers. And we're kind of sharing if you just spent a fraction of that, you know, you think about the UK Biobank cost maybe in the like 1 to £3 billion range for everything that has produced so much returns for our industry and these kind of projects would be something that I think could transform some of these bottlenecks and maybe, you know, agree with Sarah around that communication kind of gap. We should talk about how these projects actually yielded, you know, so many, so many more drugs. So super exciting times.
Exciting times indeed, where we are looking for actual impact of, of these research developments. So maybe one more question to you, Sarah. So we are living in a in a period of rapid technological disruption and of growing global volatility. So interesting times. But so how should companies actually best approach investment in innovation to secure their future competitiveness?
Yeah, I it's a great question. And if we think about everything's moving faster these days. Right. You know, when I was growing up in the Midwest, if you think about news, you had four TV channels that were on maybe a few hours a day, not even 12 hours a day. You had a daily newspaper and that was it, right? Maybe the radio. And now you have constant 24, seven news, many different types of way to do it on your phone anywhere. The same is with science. And so you can't do it all alone. So there's so much more information and technology breakthroughs every day. And it's hard to keep up. At DSM Firmenich we have 2000 people in R&D, but that's not enough. And so to take the point that you know of, how do you go faster, but also how do you use an ecosystem? And that's where I really believe that, you know, governments often are going to fund locally. But science is global. And so industry has an opportunity, especially in multinationals, to cross the borders and to be able to leverage all of the great innovation throughout the world in a unique way. And so that's where I really believe in. We invest in academic research in many different countries, and whoever's doing really cutting edge basic science that we think we can work and improve on the world in our products later. We also work with a lot of startups. And so to me, that ecosystem is the essential way to go faster and to have more impact. Because yes, you think about science and medicine, but you probably don't think about all of the science that's in your laundry detergent or in your deodorant. That is the reason that you can feel confident because your clothes smell good and and you can hug someone and not be a little nervous about it. And there's a lot of science in that, you know, it's fun. It's fun and funny because there's a lot of science in these everyday things that you do actually have to have basic science research of the receptors that in your nose and how you smell, and having understanding of that basic receptor knowledge that then decades later, can help you understand. How can we then make fragrances that delight you and do important things like malodor? And so I think that ecosystem and to bring those things even for everyday items is incredibly important.
So this is a very nice, positive note to maybe get to a more general questions. So we see accelerating discovery with transformative impact. So we can all acknowledge that of course AI, but also in other fields or AI impacting other fields. So if we think positively, not just others, but beyond, and look at what we want to be a desirable future, what we want as our future. So whether this is from an economic or societal or an environmental perspective, how should we prepare from each of your lenses? What would you say? So whoever can start first, I don't know. And Sarah. Yes, Darren.
I think one of the things that we are quite concerned about is that we're seeing a very a much higher concentration of R&D dollars in the private sector, right, in fewer and fewer sectors. It's it's an AI, it's in crypto. And as Sarah and, and all of you explained, the breakthroughs in science, right. Come may come from left our field. And we believe that a good innovation ecosystem has a varied diet. You know, it comes from. So if we are if we are spending more research dollars but in fewer areas. Right. That's something which I think is worrisome. So I would just say that it's something which the private sector can play a part because as you say, you cross borders. But I think there's something which governments, especially the governments that are doing a lot of funding in basic research the big players need to be aware of as well. That's something we see. So one of the things we're going to we're going to release a report in just a few days time talking about innovation complexity. I invite you to read the report. We're looking at the breadth and the depth of of different countries innovation ecosystem. And from there, we hope to at least put a bit of a spotlight on this issue, on for policymakers.
To oriented.
To to to yeah, to. Yeah, yeah.
And if I may add, I completely agree. The breadth of investment is incredibly important because we need to have many different types of solutions. And that's where then you can have breakthrough in the the borders between science. But I also think and it's something we haven't yet talked about that much about is regulatory preparedness. Because as we bring in new technologies, I mean, again, people think a lot about regulatory for for medicine, but regulatory is in everything we do in the foods you eat, in any types of products you use. And as we bring in new technologies, having the regulatory agencies throughout the globe be prepared and anticipate so that that timeline doesn't get increasingly longer, which is what we're seeing in all of our innovations. And that can also then decrease the industry's wanting to invest. If the hurdle of an extra 3 or 5 years of regulatory and the costs of that continue to add up, it could actually have a negative impact on further investment in innovation. So I think regulatory preparedness is incredibly important along with ensuring that breath great.
So maybe if I can pick up on that and then we can you can each have an opinion about that. Specific question you just talked about preparedness anticipation regulatory frameworks. So if we look ahead with all these transformations, coming up very soon, what would you see is the biggest risk of not anticipating, of not doing what you just said? And to not see which are these transformational impacts of future scientific advances when it comes notably to economic and societal prosperity. So each of you can have maybe been.
You know, I think in our industry, in order to almost, like, bear the fruit of AI, all these biotech progress where you're discovering way more, drugs, it's to kind of address the bottlenecks and we won't actually bear the fruits of all these new discoveries that we can't fix the bottlenecks. There's there's three core things. One is, transforming drug development, clinical trials. Second, it's on the regulatory side. So the regulatory bodies find out faster, more efficient ways of going through that process. And the third is like, if you can change the throughput, you also want to change the probability of success. Only one out of ten drugs that enter the clinic today actually are successfully approved. Our predictive models actually in biology are not great in the humans. We don't know what Alzheimer's getting better looks like. So we kind of need like a UK biobank but a bit on steroids. So like more like 5 million patients or 10 million patients. Genomic, proteomic, transcriptomic, behavior, lifestyle kind of kind of measures, human based perturbations. So what drugs are they taking? And if you can begin to understand what for every disease, what are markers that associate with good and negative progression, you begin to predict what might work so that if you're discovering now two, five, ten x more drugs, you're not logjammed around this translational kind of part because probability of success is greater. But also you can get more bang for your buck.
Thank you. I'm going to go.
Maybe coming to your question, what are the risks if you do not anticipate new developments and also regulation which might be needed. So one risk for sure is if you are too late. There might be fear around what could happen with the new technology and new development, which could lead to strong regulations which are not useful. So in Switzerland we have a quite liberal regulation approach. But this needs trust, of course, trust in science and and anticipation to see what's, what's coming. And you mentioned also, we have less money for basic research. You, argued in a little different way. I would, go to your direction. I don't think we have less money for basic research, but it's much more directed to certain fields. And what is the risk if basic research is heavily directed? We need diversity in basic research because we do not know in advance which will be the really great development. And I think there is also, a role of governments. And it's not so easy nowadays to stay open in funding. If you see the trends in the world, going to AI research, quantum research, who's interested in, I don't know what other topics which might be niche today, but very important for the future. And I think there is a risk if we are not open, in funding basic research.
Absolutely. Yes. Sarah.
Yeah, I think I agree with everything that's said, especially that the the narrowness that could happen and then industry could potentially make up some of that. But in maybe more short term thinking, it could be a, could be a bad story. And so again this is how do we help so that we don't have the institutional lag so that we can start seeing more and more success stories so that then it kind of becomes a virtuous cycle. Then you want to invest more. Because I think really what I would like to say is people need to view fundamental research as key infrastructure for the world, for, for countries, for companies. Just like you need roads, just like you need water and pipes and electricity. Science is what runs like progress, and it really helps this world. And we have to change the mindset there.
And I hope, yeah, go away from the mistrust in science because this is the foundation. Exactly. Darren. You want to.
Yeah I think innovation and science and research has become too important to the world to leave it to chance and leave it to coincidences. Right. And I think the progress in the world for the last 200 years has been because we have we have had the good fortune of, of of having, an ecosystem that developed organically. I think it's too important now to just leave it to organic growth. I think, of course, organic growth is important, but we need to make sure that we sit down and with deliberation, with, with, with thoughtfulness, right, to understand the ecosystem and to help to support it in different ways. The answer will be different in different countries, different maturity levels, but I think just simply too important for science, R&D and technology to leave it. And so I think, anticipation is one way of disciplining ourselves, right, to engage with it systematically, to, to, to connect with it, to get data, to get insights, to exchange and communicate. Right, so that we, we, we can work collaboratively, deliberately to, to continue having a strong R&D ecosystem, a strong innovation ecosystem. So I think it's just too important to to leave it to pure chance and to just say that magic will still happen because it's happened for the last 200 years. True. Yeah.
Great words. Collaboration, trust, anticipation. I think these are all wonderful key words to keep in mind, for to close this session. So I think the conversation has highlighted the long term value of fundamental research and the risks of continuing weakening of its foundations, or an alignment of the actual needs of our evolving scientific landscape. And so these dynamic funding, movements, show that there is a challenge to sustain investment and ensure that science remains embedded in approaches to growth, to competitiveness and to long term resilience. So I hope the discussion today has been able to inform how fundamental research is, and should be positioned within future policy and economic choices, and that the future is not something that we inherit, but something that we shape together. Thank you very much for your attention.
And.