Financing
We offer unfair advantages to benefit from private and public financing opportunities
Open Innovation Calls
Benefit from our close collaboration with a network of private investors to support your growth.
Start-up mode®
Tap into our expertise to assist your team in creating new value propositions and product concepts.
Deal flow
Connect with leading organizations to activate collaboration and investment opportunities.
Private Financing
Benefit from our network of private investors with whom we work in close collaboration.
Open Innovation Calls
Benefit from our close collaboration with a network of private investors to support your growth.
How to accelerate the scalability and adoption of health innovations
Open discussion with INPHO Venture Summit
Click on one of the links below to discover their insights:
We are delighted to share with you a curated selection of podcasts and webinars highlighting the most impactful topics financing innovation in health.
This webinar will explores how health authorities define and address today’s major health challenges, from system sustainability to innovation adoption. Together, we’ll look at how AI, data management, and new collaboration models can support more resilient, preventive, and impactful healthcare across Europe.
Benhamou Global Ventures is a leading fund with + $2 BN raised, more than 50 companies in portfolio. Eric Benhamou, former CEO of 3Com and Palm Pilot, with 8 IPOs and 37 M&As under his belt, is looking for this discussion and will share his insights on the most promising deeptech investment opportunities in 2025 and beyond. Eric brings a unique perspective on emerging trends and strategic opportunities.
As a follow-up to the INPHO® Venture Summit discussions on What’s next to invest in DeepTech?, we have identified topics to be challenged.
The discussion was introduced by Géraldine Andrieux, who set the stage by providing context for the conversation and explaining its relevance. Both she and Eric Benhamou play active roles on the editorial committee of the INPHO Venture Summit, helping to shape crucial conversations about the future of deep tech investment. She acknowledged Eric’s presence and the pleasure of having him taking part to this conversation.
She also extended a warm welcome to all the participants, with a special mention of François Breniaux from Supernova Invest, Christian Claussel from Ventech VC, Emmanuel Daugeras from Karista VC, Marc Lambrechts from Capricorn Partners, Anne Lebreton-Wolf from ALW Finance & Innovation and Rémy de Tonnac from ETF Partners.
This conversation is the result of a discussion started during previous INPHO Venture Summit editions regarding the challenges of pinpointing ‘what’s next’ in deep tech investment. Just a few months ago, in October 2024, the last INPHO Venture Summit, focused on identifying the next big opportunities in deep tech. Since then, so much has unfolded. The objective of the discussion is not only to join INPHO participants but also key stakeholders from across the French and European innovation ecosystems, which promises a particularly exciting and diverse discussion.
Géraldine Andrieux: Eric, could you share your thoughts on what’s next for deep tech investment? Given our discussions at INPHO and the rapid evolution of AI and other technologies, what are the key trends shaping the landscape?
Eric Benhamou: Since our last discussion in Bordeaux, one of the most significant developments in AI has been the introduction of the DeepSeek-R1 model in January. This was a major milestone for several reasons.
First, it marks a breakthrough from a Chinese company, demonstrating deep innovation not just in software but also in hardware. It reinforces the idea that simply increasing computing power isn’t enough to drive AI forward; smart innovation in architecture plays an equally crucial role. DeepSeek has delivered a significant leap in performance while simultaneously reducing costs, proving that strategic advancements can be just as powerful as raw computational force.
Another key factor is DeepSeek’s commitment to open-source AI. By making its model open-weight, DeepSeek is accelerating AI deployment, particularly in enterprise applications. This isn’t an isolated case. In recent weeks, we’ve seen similar or even greater advancements from Chinese tech giants like Alibaba and Baidu.
This underscores the intensifying global competition in AI, with the U.S., China, and Europe all vying for leadership. China’s research ecosystem, despite restrictions on NVIDIA’s most sophisticated GPUs, has produced world-class advancements. Instead of using H100 GPUs, they have worked with H800 chips, which have lower chip-to-chip bandwidth but have compensated through algorithmic improvements such as quantization and reinforcement learning with reduced human input. Overall, these developments are significant and signal a positive trajectory for AI innovation worldwide.
Rémy de Tonnac: However, Europe, has yet to fully position itself. While companies like Mistral AI show promise, large-scale collective investments similar to an “Airbus of AI” have not materialized. This leaves Europe at a competitive disadvantage compared to the U.S. and China.
Rémy de Tonnac: A few weeks after the DeepSeek “tsunami,” have we started to understand if the DeepSeek architecture design is indeed significantly different from what has been done before? Does it inherently offer a huge advantage?
Eric Benhamou: There’s broad agreement that the innovations introduced by DeepSeek represent a high-quality breakthrough, reflecting the caliber of their scientists. The innovations fall into two categories: hardware and software.
On the hardware side, the key focus is finding ways around the limitations of not having access to the latest GPUs, particularly when it comes to chip-to-chip bandwidth. DeepSeek’s approach to reducing the amount of data traffic between chips is a key innovation. One such technique is quantization, which allows for faster matrix multiplications, core to AI processes, by reducing the precision of calculations. Essentially, you can drop off the last few digits in calculations, cutting down on computational cost and data movement without sacrificing significant accuracy. This drastically reduces the cost of compute and sidesteps the need for advanced chips.
On the software side, DeepSeek has made significant strides in training efficiency. Training with human feedback (like reinforcement learning) is expensive, so finding ways to reduce the need for extensive human input can save considerable costs. DeepSeek has excelled at this, and much of their software innovation has been published in research papers. The great thing is that these software techniques are available for anyone to use. The hardware innovations are proprietary, but the software advancements are open for the industry.
I think this is a step-function innovation for the AI field, and I believe it will benefit the industry overall. I haven’t looked deeply into the more recent Chinese models from Alibaba and Baidu, but I suspect their approaches are similar, given the competitive landscape.
Christian Claussel: There has been some controversy surrounding DeepSeek, with questions about whether it truly lives up to expectations. Some initial skepticism impacted stock markets, but the concerns seemed to fade over time.
Eric Benhamou: DeepSeek is definitely not a scam and should be taken very seriously. Their team consists of top-tier, highly reputable researchers, and their work has been peer-reviewed. However, there have been discussions about whether some of their training data was acquired under questionable circumstances. In China, where copyright laws are less strict, data access can be more flexible, which might give them an advantage in training efficiency.
What’s also notable is how DeepSeek has been perceived as a real competitive threat. Companies like OpenAI have reportedly sought legal measures to limit its distribution, which is a strong indication that they see it as a viable rival. Rather than blocking access, it would be more constructive for OpenAI to highlight why their model is superior, but instead, we’re seeing restrictions on DeepSeek models entering the U.S. market. This underscores the global battle for AI dominance.
Anne Lebreton-Wolf: In today’s geopolitical landscape, Sovereignty in AI is a growing concern, more critical than ever. How do you see this shaping AI development?
Eric Benhamou: AI sovereignty is crucial. Training advanced models requires access to vast datasets. China enjoys a strategic advantage here, as its regulatory environment allows nearly unrestricted data access. Meanwhile, strict copyright laws in the West significantly increase training costs.
This naturally raises sovereignty concerns: If AI is truly a matter of national security and economic independence, as many believe, then placing such high costs on model training in the West could drive innovation elsewhere, potentially making us dependent on AI systems developed under entirely different values and biases.
Then there’s the question of regulation. In Europe, for example, the EU AI Act introduces strict compliance requirements for high-risk AI systems. While well-intentioned, some argue that these regulations stifle innovation and impose unnecessary costs too early, which could further disadvantage European AI players.
At the same time, the global AI landscape is becoming increasingly fragmented. Rising trade barriers and geopolitical tensions are leading to isolated AI ecosystems in the US, Europe, China, and other regions. As a result, companies may find it easier—or simply more cost-effective—to train their models in jurisdictions with fewer restrictions, which could influence the way AI develops worldwide.
Ultimately, while everyone agrees that AI is one of the most critical technological innovations of our generation, the landscape is far from even. Sovereignty in AI is about much more than just technological leadership—it’s about economic resilience, security, and control over the future of intelligence itself.
Géraldine Andrieux: AI is evolving rapidly, and we’re seeing the emergence of agentic AI. Eric, could you explain why this is significant?
Eric Benhamou: Agentic AI refers to models that can reason, set goals, break them down into manageable steps, and determine the best course of action through chain-of-thought reasoning. This evolution enables AI-driven agents to go beyond automation; they can interact with existing IT systems, access databases, and participate in process automation—not in a rigid, robotic manner, but with adaptive, reasoning-based intelligence.
This transformation was already underway, but the acceleration of AI models, now cheaper, more accessible, and increasingly capable, has made agentic AI even more viable. This creates a landscape where AI agents and human agents collaborate. AI agents will be auditable. We can track what they do, when they access data, and how they use it. This transparency is crucial for enterprise adoption.
Emmanuel Daugeras: Today, most large language models rely on statistical pattern recognition rather than true understanding of the physical world. There’s growing interest in “physically informed machine learning,” where AI derives differential equations from physical observations. Do you see this as the next big disruption in AI?
Eric Benhamou: Absolutely. Real-world models, those that reflect the physical environment—are key to advancing AI, particularly in robotics. The paradox is that while AI can now solve complex mathematical problems at a PhD level, it still struggles to manipulate objects as well as a toddler. A three-year-old can handle objects with greater dexterity than the most advanced robots today.
This capability gap needs to be closed. Integrating real-world models will be crucial for AI to navigate and interact with its environment more effectively. Back in the 1960s, people envisioned household robots capable of handling daily chores. Yet, even now, we lack robots that can load a dishwasher without breaking plates. This highlights the limitations of current AI and the need for more advanced real-world learning approaches.
Rémy de Tonnac: I completely agree. While the big infrastructure plays are largely dominated by tech giants, the real opportunity for VCs lies in applications leveraging agentic AI to drive productivity gains across industries.
Eric Benhamou: While AI remains a major focus, other deep-tech areas like space and defense are becoming increasingly important. In Europe, significant investments are being directed toward defense, particularly in drone warfare strategies and fleet coordination. Innovations in autonomous systems are shaping modern military tactics, making this a key area for technological advancement.
Space tech is another rapidly evolving field. From reusable rockets to space-based materials research and cyber defense for satellite payloads, there are countless opportunities. Companies working on Space Situational Awareness (SSA) are tackling challenges like collision detection using AI-driven pattern mapping rather than traditional computationally expensive methods.
Emmanuel Daugeras: We’re actively investing in dual-use space tech and defense infrastructure. The demand for AI-powered solutions in these areas is growing, and we’re seeing strong traction. The number of satellites is set to double within a few years, making space traffic management a critical challenge.
Christian Claussel: One of our portfolio companies is developing a Eurocontrol-like system for satellites, helping to manage space traffic. As payloads increase, AI-driven solutions for collision avoidance will become essential.
Rémy de Tonnac: From a VC perspective, we consider that quantum computing is probably the only area in deep tech where Europe has a real competitive edge. Google’s recent Willow announcement demonstrated a quantum leap—completing computations in five minutes that would take traditional supercomputers trillions of years.
Quantum will revolutionize fields like materials science, chemistry, and genetics. While direct investments in quantum infrastructure may be beyond the typical VC horizon, the real opportunity may be in developing the “picks and shovels”. In quantum computing, this could mean developing the tools and software that will accelerate its adoption.
What areas of deep tech hold the most promise for European competitiveness according to you?
Eric Benhamou: Quantum computing is indeed one such area where Europe has a competitive edge. While AI remains a major focus, other deep-tech areas like space and defense are becoming increasingly important. In Europe, significant investments are being directed toward defense, particularly in drone warfare strategies and fleet coordination. Innovations in autonomous systems are shaping modern military tactics, making this a key area for technological advancement.
Space tech is another rapidly evolving field. From reusable rockets to space-based materials research and cyber defense for satellite payloads, there are countless opportunities.
Emmanuel Daugeras: We’re actively investing in dual-use space tech and defense infrastructure. The demand for AI-powered solutions in these areas is growing, and we’re seeing strong traction. The number of satellites is set to double within a few years, making space traffic management a critical challenge. Companies working on Space Situational Awareness (SSA) for example are tackling challenges like collision detection using AI-driven pattern mapping rather than traditional computationally expensive methods.
Christian Claussel: One of our portfolio companies is developing a Eurocontrol-like system for satellites, helping to manage space traffic. As payloads increase – the fleet estimated around 35,000 satellites today is expected to double in just three or four years – AI-driven solutions for collision avoidance will become essential.
Christian Claussel: At Ventech, rather than predicting the next big AI trend, we focus on what AI is already doing today. AI isn’t a sudden revolution—it’s been evolving for decades. I remember visiting a Fraunhofer Lab in 2001 where AI research was already well underway. What has changed is that computing power has finally caught up, allowing AI to reach its full potential. The key question for us is: where do we invest? In infrastructure, software, or new algorithms?
Eric Benhamou: As a VC, we don’t play in the massive infrastructure investment space, so we focus on high-value applications. For example, we wouldn’t make a $10 billion investment in a company like Mistral AI. It’s not that they aren’t competitive, but it’s simply not our swim lane.
Our strategy centers on young companies that leverage AI to drive productivity gains. Right now, the biggest opportunity lies in agentic AI—models that use reasoning-based intelligence rather than just automation. These systems dynamically solve business problems, interacting with IT systems, querying databases, and adapting decisions in real-time.
This creates a new landscape where AI and human agents collaborate. AI agents will be fully auditable, ensuring transparency in how they process data, making them viable for enterprise adoption.
That said, France has some of the world’s best mathematicians, but too many focus on algorithmic research rather than business applications. The real opportunity is in companies applying AI to solve concrete business challenges rather than just developing theoretical models. This is where the best returns will come from.
Emmanuel Daugeras: AI engines, to some extent, face the risk of becoming commoditized. AI engines consume massive amounts of energy and require huge capital expenditures. While they are transformative, how do you see real value being captured in AI?
Eric Benhamou: That’s a fundamental question. What’s the return on AI? While AI innovation is unquestionable, monetizing it remains a challenge.
In our view, the highest returns will come from AI-enabled applications and services. Infrastructure investments, though critical, are mainly reserved for well-funded firms. Companies like Mistral AI are exceptions—they are well-financed and have strong technology—but generally, infrastructure is a game for the tech giants.
AI-enabled services, however, span across industries. Software development, for instance, is already experiencing major transformation. AI-powered coding assistance tools are boosting developer productivity to the point where some Silicon Valley companies have reduced engineering headcount, not due to financial struggles, but because AI has made development more efficient.
Beyond software, customer-facing industries like financial services and insurance are seeing AI-driven automation in customer support and decision-making. These areas will yield the strongest AI-driven productivity gains and financial returns.
Géraldine Andrieux: Climate tech is a critical area. How do you see AI playing a role in energy management?
Eric Benhamou: I think there’s a crucial area of innovation here that many of us can agree on. We now need to harness a wide range of energy generation sources—solar, wind, nuclear (depending on the region), and others—into what we call virtual power plants. These virtual power plants are much more distributed and utilize various forms of energy generation and transportation.
To better manage energy, we need software constructs to pull all of these resources together. For instance, a small community could aggregate all of its solar power from rooftops into one unit, and manage that alongside a larger physical plant somewhere in the region. This requires holistic management in the form of virtual power plants.
AI is going to play a significant role here, improving utilization, balancing loads, and preventing energy waste. While there will certainly be innovations in physical energy generation and storage—areas we still know less about—what we understand more clearly is how to manage these systems efficiently.
This intersection of AI and climate tech is going to be extremely interesting, and it’s something we’ll certainly be paying attention to. In Europe, particularly with the ongoing Russia-Ukraine conflict and the subsequent shifts in energy sources, including the reevaluation of nuclear power, we’re seeing massive changes. This will result in a more diversified and distributed energy generation base.
The only way to manage this smartly is through virtual power plants. So, there are a lot of interesting problems to solve here, and I think this area is a fertile ground for startups.
Rémy de Tonnac: One of the companies I’ve invested in is already implementing multiple AI models to balance grid efficiency. Quantum computing is also being explored for energy optimization, further enhancing the potential of AI-driven energy management.
Marc Lambrechts: A key focus here is data, especially data quality. In health applications, reliable data sources are crucial for AI systems. I’m particularly interested in Voxel Sensors, one of our portfolio companies, which is developing a hardware solution combining depth sensing with eye scanning to gauge intent or attention. They’re focusing on both hardware and software, ensuring data quality for future visual language models. While major AI players focus on compute power and data volume, Voxel is innovating in data quality, adding unique value.
Eric Benhamou: I agree—data quality is essential for successful AI deployments. AI failures often stem from poor data curation, which hinders model training and insight generation. Improving data quality is critical for AI productivity gains.
Beyond data quality, data governance is vital—ensuring secure access and combating issues like fake news. As the world faces more conflicts and cyber threats, the demand for sophisticated cybersecurity tools will grow. Some threats may involve disinformation campaigns or AI agents posing as humans to disrupt systems.
The cybersecurity market will continue to expand, and while we may face competition in other sectors, its growth is assured. Additionally, space tech presents exciting opportunities, with France being a leader in space technology.
François Breniaux: AI is taking up a significant portion of venture funding. What does this mean for other sectors? Can you be a successful investor today without investing in AI?
Eric Benhamou: While AI dominates headlines, sectors like energy storage, materials science, and healthcare still offer strong investment opportunities.
The VC market is still recovering from the 2022 downturn. In 2021, overinvestment led to inflated valuations and wasteful spending, followed by a sharp correction.
Today, U.S. venture investment levels are similar to those of a decade ago, effectively wiping out years of growth. AI now takes the lion’s share of funding, leaving sectors like climate tech underfunded. However, I anticipate a surge in defense tech and cybersecurity investments in the coming years.
Géraldine expressed her gratitude to Eric for his strong statement, emphasizing the importance of not only considering the technology but also the current state of the VC market and the wealth available in the venture capital world. She thanked Eric for his time and insightful contributions, noting how much they were appreciated. Géraldine also extended her thanks to all the participants for joining the conversation, highlighting how valuable the discussion had been. She concluded by mentioning that the next INPHO Venture Summit will take place in Bordeaux in 2026, inviting everyone to join what promises to be an excellent opportunity to connect with both investors and industry professionals.
Dr. Iñaki Gutierrez Ibarluzea, Director of Health Research, Innovation and Evaluation at the Ministry for Health, shares insights on how the Basque Country is transforming its health system. In line with BLUMORPHO’s Financing Health Innovation program, and as an ambassador of this program, the Basque Country is happy to exchange on pioneering patient-centered care, sustainable financing models, and collaboration between ministries, insurers, innovators, and investors. In this discussion, Dr. Gutierrez Ibarluzea explores emerging needs, innovation priorities, and the conditions for successful adoption and financing of impactful health solutions. Using the Basque Country as a case study, he highlights how a regional health system can drive innovation, sustainability, and improved patient outcomes.
Géraldine Andrieux introduced the Financing Health Innovation (FHI) program as an initiative led by BLUMORPHO to accelerate the adoption and financing of impactful innovations. BLUMORPHO positions itself as a strategic innovation partner, supporting startups, corporates, and public organizations to access the right projects, financing, and innovation frameworks needed to scale what truly matters. Since 2016, the company has contributed to mobilizing over €1 billion to support innovation programs across sectors, with health as one of its key focus areas. The objective is not only to fund innovation but also to understand why and how to act effectively, ensuring alignment between technological solutions, societal needs, and sustainable health outcomes.
Géraldine then welcomed Dr. Iñaki Gutiérrez-Ibarluzea, Director of Health Research, Innovation, and Evaluation at the Basque Government’s Ministry of Health. Dr. Gutiérrez-Ibarluzea oversees strategic planning, R&D policy, and coordinates the Basque Health Research Institute, BIOef. He is also an active member of Health Technology Assessment International (HTAi) and participates in WHO initiatives. In addition, he currently serves as President of the EuroScan International Network, a consortium of more than 20 organizations worldwide dedicated to horizon scanning — the early identification and evaluation of emerging technologies likely to impact healthcare systems. With members across Europe and the Asia-Pacific region, EuroScan plays a key role in informing health authorities and supporting proactive decision-making.
Objectives and Structure of the Discussion
The conversation aimed to shed light on how health authorities define and prioritize innovation, the main health challenges they face, and the strategic directions they are taking to address them. The discussion is structured into three main parts:
Participants are invited to actively contribute questions throughout the session, ensuring an interactive and informative exchange.
Dr. Iñaki Gutiérrez-Ibarluzea:
I think this is a very relevant question in many respects. One of the main issues we’ve been discussing for years, and which remains a pressing concern is the sustainability of healthcare systems. Budget constraints are tightening everywhere, and this is now a central challenge, even for high-income countries. If we continue along the same path in terms of spending and investment, we will eventually reach a point where our systems become financially unsustainable. On one side, we face the technological pressure, the constant emergence of new and costly innovations. On the other, there’s a profound demographic shift affecting most countries. We’re dealing with the consequences of our modern lifestyles, such as rising obesity and declining physical activity. These, combined with an aging population, represent both a success story and a growing challenge for healthcare systems.
Another important aspect is that we can no longer think locally. For a long time, we assumed our populations were relatively stable and genetically homogenous. That’s no longer the case. The pandemic reminded us that we are now part of a global health ecosystem, with increasingly diverse populations and needs, even within high-income countries.
And then, of course, there’s climate change, which adds a completely new layer of complexity. We are already seeing its effects: the appearance of tropical diseases in regions where they were previously unknown, and extreme weather events, unprecedented floods, heatwaves, or freezing periods, all of which have direct impacts on mortality and morbidity.
So, if we look at all these factors together, technological pressure, demographic shifts, lifestyle-related diseases, globalization, and climate change, we can see that healthcare systems are entering a period of deep structural transformation. The challenge now is not just to adapt, but to ensure that these systems remain sustainable and resilient in the face of such rapid change.
Géraldine Andrieux:
The heatwaves we’ve been experiencing during recent summers are really striking. So, when you look at all these factors, would you say we’re facing more challenges than before, or is it more that different challenges are now combining and amplifying each other compared to the past?
Dr. Iñaki Gutiérrez-Ibarluzea:
No, I think one of the things we are missing is new approaches that could help us to address these challenges. Right now, we are still relying on old formulas, and they are no longer effective. They simply won’t succeed because they are not aligned with the realities we face today.
We need to explore all types of solutions and adopt different ways of approaching the problems confronting our health systems right now.
Géraldine Andrieux:
That’s why it’s good that we’re having this discussion and that we can launch an innovation program focused on this topic, which is something that is very much needed. This discussion will serve as a starting point for identifying and developing new solutions.
Dr. Iñaki Gutiérrez-Ibarluzea:
Indeed any crisis is an opportunity. I think this is a particularly good moment for several reasons. One of them is that the maturity of technology today is much higher than it was a decade ago. We were discussing this with service providers in the Basque Country, and it’s clear: we now have tools and capabilities that simply didn’t exist before. The challenge is that we need to be sufficiently clever in terms of using them for the sake of the systems.
Géraldine Andrieux:
Indeed, implementation, making sure these innovations are applied in practical, impactful ways is also a challenge.
When we prepared today’s discussion, and reflecting on our previous conversation, you highlighted this study from Imperial College London published in June this year. I think it would be very interesting if you could share a bit more about this analysis and explain the key points, especially this statement from Lord Darzi, the Director of the Institute of Global Health Innovation at the Imperial College in London: “By 2035, prevention and digital health could prevent millions of chronic diseases and save billions in treatment costs. However, only a fraction of investments currently targets community-based, data-driven models: hospital spending still accounts for over 60% of health budgets. “
Dr. Iñaki Gutiérrez-Ibarluzea:
Yes, I think it was a very honest analysis of the UK healthcare system, highlighting some of the key aspects related to investment over the years. One of the main issues is the lack of anticipation. Once again, old formulas were used without proactively preparing for what was coming.
On one hand, healthcare systems, especially in high-income countries, have been quite successful in keeping people alive. On the other hand, this focus has often neglected quality of life. People who might have died earlier are now living longer, which is a success, but it also creates new challenges for the system.
One of the main points raised in the analysis was about the type of investment. Most funding has been concentrated on healthcare delivery, rather than on health. Promotion and prevention have not been central priorities; systems have focused on treating disease rather than maintaining health. That focus, while successful in many ways, has also created limitations.
Lord Darzi and his team highlighted that only a small fraction of investment currently targets community-based, data-driven models. Hospital spending still accounts for over 60% of the health budget. But if you include drugs and other costs, the focus is even more heavily skewed toward reactive care. We’ve concentrated on solving immediate problems but not on addressing underlying ones.
Other factors driving costs include personnel expenses, rising demand for health professionals, and societal expectations. Citizens now expect care to be faster and closer to home, which increases demand exponentially. You can’t simply expand supply; the system needs different approaches.
The Darzi report proposed several solutions, including technological innovation. But technology alone isn’t enough. The key is first to understand the problems. Their approach emphasized moving from analog to digital, from hospital to community, and from pathology to prevention. However, this isn’t sufficient. More effort is needed in health promotion and early diagnosis, not just disease treatment.
Finally, one of the challenges is that health professionals are trained to identify and treat diseases, not to promote health. Medical and nursing schools focus on pathology, rehabilitation, and treatment, but not on maintaining well-being. We need to work with health professionals to strengthen health promotion, prevention, and the identification of healthy habits, building evidence for what works in practice.
Géraldine Andrieux
So, as you said, these are not health systems focused on keeping people healthy, but rather healthcare systems focused on treating illness and hospital care.
Dr. Iñaki Gutiérrez-Ibarluzea:
Yes, I think in many countries around the world, ministries changed their names from “Ministry of Health Care” to “Ministry of Health”, and that was the case for us about a decade ago. However, it seems we still haven’t fully embraced the concept of focusing on health rather than just healthcare.
This creates another challenge: we continue to repeat some of the same mistakes we made in the past. I believe this is part of the reason why we are where we are today, and why the near future may not look particularly optimistic unless we shift our approach.
Géraldine Andrieux
As you said, let’s turn these challenges into opportunities. Could you summarize, what are the most urgent needs today that we should focus on addressing, especially given the budgetary constraints and the investment required to shift the paradigm from healthcare to health? Technology could help, digital solutions might help, but what are the top priorities right now for you?
Dr. Iñaki Gutiérrez-Ibarluzea:
Probably, if we look directly at the issue, budget constraints are the main challenge, without a doubt. As I mentioned earlier, recent studies have pointed out that technological solutions are actually putting pressure on healthcare systems, because costs are increasing by around 6% a year. When we compare that to GDP growth in many countries, the numbers simply don’t align.
For example, in a high-income European country like Germany, GDP growth today is close to zero or just one percent a year, while in other well-performing economies it might be around 2.5%. So if technology adds cost instead of delivering savings or efficiencies, it clearly becomes a major pressure on the health budget.
Other factors relate to demographic success. Life expectancy is increasing globally though, as noted in the US, there are exceptions. Longer lifespans bring additional needs, particularly for older populations, and if we don’t address them, this creates further challenges.
Another critical issue is disparities. Even in high-income countries, there are inequalities in access to healthcare and socio-economic differences that strongly influence both quality of life and life expectancy. This remains a central concern: how to provide a healthcare system that is fair in terms of access and provision, while also addressing all the needs of the population.
Géraldine Andrieux:
How do you do that? What direction are you taking to address those challenges?
Dr. Iñaki Gutiérrez-Ibarluzea:
I was joking earlier when I said you have to choose between fear or death. And right now, I prefer fear. I’d rather be honest about the challenges we face. Fortunately, we are in a good position to act: technology is more mature, we have more data than ever, skilled professionals, and a society that is ready for solutions.
Some of these challenges can be addressed by the proposals outlined by NHS England for the next ten years, following Lord Darzi’s report. For example, moving from analog to digital and making decisions based on evidence rather than uncertainty. To do this, we need to ask the right questions and clearly define the current challenges.
We also need a paradigm shift. Most healthcare systems today are evaluated on surrogate outcomes, waiting lists, first visit access, or length of stay, rather than real patient outcomes. There is a growing movement toward value-based healthcare, which I strongly support. We need to focus on value and ensure that this perspective is communicated to society. Citizens should not only see metrics like waiting lists or hospital stays, but understand improvements in life expectancy, quality of life, and patient-centered outcomes. Healthcare performance should be measured based on these outcomes, not just structural or process metrics. Hospitals will always be needed for acute and complex care, but we must also invest in community care. This means understanding why patients transition from health to disease and designing solutions at the community level using data, preventive strategies, and targeted interventions. We need more than just more primary care physicians or community nurses; we need a deeper understanding of disease dynamics and effective tools to intervene early.
Prevention is essential, but I would go further: we need health promotion, anticipating problems before they occur. Just as with climate-related challenges, like fires in Spain, the goal is not only to respond but to understand why problems happen and how to minimize them. In healthcare, this means preventing patients from deteriorating and reducing costs before they arise.
Finally, a substantial portion of healthcare spending is wasted. Roughly 25 to 30% according to the New England Journal of Medicine and OECD reports. This includes inappropriate use of interventions, misaligned procurement, and inefficient practices. In the past, some of this was unavoidable due to lack of data, but now we have the information to analyze and make informed decisions. Addressing these inefficiencies is critical to creating a sustainable, high-performing healthcare system.
Géraldine Andrieux:
We’ll come back to the topic of data and AI shortly, but first we want to focus on a few questions about innovation priorities. Specifically, how is the Basque Health Ministry currently shaping its innovation agenda, and how does it collaborate with innovative companies and corporates to implement it?
Dr. Iñaki Gutiérrez-Ibarluzea:
What we are trying to create is an innovation ecosystem that fosters collaboration among all key actors. This was announced yesterday at BioSpain, the largest healthcare-focused event in Spain.
We need the participation of all stakeholders:
The goal is to combine public and private efforts. Most impactful solutions emerge from the interaction between healthcare systems and the innovation ecosystem, bringing together government, society, academia, and industry.
Dr. Iñaki Gutiérrez-Ibarluzea:
In the past, collaboration was a need; today, it is a must. There is knowledge missing on both sides, within the healthcare system and among innovators. To effectively address the challenges we face, we need to work together to provide solutions. The first step is simply creating that collaboration.
Dr. Iñaki Gutiérrez-Ibarluzea:
As I was saying, this needs to be addressed on a global scale. Otherwise, we might try to impose local solutions on a system that is far too vast. We are not just dealing with local problems — these are global challenges that affect us in many ways.
Géraldine Andrieux:
What you’re saying is music to my ears. This ecosystem approach is exactly what we are working on. It’s part of the rules and DNA of Blumorpho. You’re calling for a paradigm shift, and this is truly the best way to achieve it. Very interesting. I’m excited to continue this discussion.
Dr. Iñaki Gutiérrez-Ibarluzea:
We also need to challenge innovators. Until now, they’ve been primarily focused on market-driven needs, often emphasizing prevention and early identification, which is important. But we need them to also focus on health promotion, helping to shift the system from being reactive to disease toward actively supporting overall health.
Géraldine Andrieux:
And this is something we need to do together.
Géraldine Andrieux:
What is needed to operate your vision? Do you already have a list of solutions you are looking for?
We’ve received a question about point-of-care diagnostics. Is this the type of solution you need to support the paradigm shift and advance the evolution of the health system?
Dr. Iñaki Gutiérrez-Ibarluzea:
Ultimately, what we need are tools that help us understand the dynamics of health and disease. When I talk about the dynamics of health and disease, I mean that many systems are still relying on static analyses. In epidemiology, for example, we used cross-sectional studies, a snapshot of the situation, and planned based on that.
But today, with the solutions available in healthcare systems, we have the tools to take a more sophisticated, dynamic approach. Understanding these dynamics allows us to plan more effectively and transform the way we organize care.
This includes early identification, biomarkers, and combining different types of data, not just from healthcare systems, but also environmental exposures, lifestyles, and socio-economic conditions. By analyzing how these factors interact, we can anticipate changes and intervene earlier, rather than just reacting. Otherwise, we end up putting bandages on problems.
Géraldine Andrieux:
A One Health approach and breaking down silos, as you mentioned, is essential to truly address the challenges.
From this perspective, is it possible for you to collaborate with innovative companies? And would you also need to work with large private companies?
I think you already started answering, because you mentioned the need for an ecosystem approach.
Dr. Iñaki Gutiérrez-Ibarluzea:
In the past, collaboration with innovative companies was a need, because the health system couldn’t solve all problems on its own. There were challenges we couldn’t address internally, so we looked to innovators for solutions. Today, collaboration is no longer optional, it is a must.
From the start, pre-commercial procurement initiatives, including those launched by the European Commission, were limited in impact, partly because systems weren’t yet mature enough to clearly communicate their needs to innovators. The traditional approach, “come to us with your offer and we’ll see if it fits” is no longer sufficient. Instead, we need to define our challenges clearly and work together with innovators to find solutions. Prioritizing these challenges allows for focused, practical collaboration.
Communication is crucial. Innovators and healthcare systems represent two different worlds that must connect. Big companies also play a vital role: they can scale innovations globally. Local testing and solution development is essential, but scaling requires the infrastructure and capacity that only larger companies can provide.
At the same time, we need a healthy ecosystem of innovators, often small companies or startups, that work alongside large companies and healthcare systems. The system’s role is to identify realistic needs, not just accept solutions pushed externally. Together, this creates a dynamic where the pull from the health system drives innovation, supported by a mix of small innovators and global companies, ensuring solutions are both practical and scalable.
Géraldine Andrieux:
You mentioned the need to shift the paradigm: moving from healthcare to health, from treatment to prevention. This requires budget and financing. Have you already started thinking about specific business models to support this approach, or do you see the process of challenging innovators and co-creating solutions as the way to define the right business model?
Dr. Iñaki Gutiérrez-Ibarluzea:
One of the key challenges is who pays for these changes. Who funds the shift from treatment to prevention and the running costs of such programs? If we look at traditional healthcare systems, they are not structured to cover these costs, so we need other actors to contribute. This was evident during the pandemic: we realized that without health, there is no wealth. If lockdowns had continued unchecked, economies would have collapsed.
Currently, the paradigm mostly compares different solutions in terms of investment versus immediate results, but that is no longer sufficient. New metrics are emerging, such as productivity-adjusted life years, but this raises the question: who pays for productivity? Health systems fund healthcare, quality of life, and life expectancy, but productivity benefits the economy, so companies and other government sectors, for instance, Ministries of Economy, also have a role.
This suggests the need to rethink how health systems are financed, beyond traditional healthcare budgets. It’s about creating new funding models that support a shift from healthcare to health, linking investment in prevention to societal and economic benefits. Society needs to understand and embrace this paradigm shift. It’s a key element for sustainable, impactful health systems.
Géraldine Andrieux:
Yes, financing is definitely a key issue. To enable the shift in business models from healthcare to health, we need approaches that provide both health impact and economic return.
Dr. Iñaki Gutiérrez-Ibarluzea:
Yes indeed. Financing is critical, but we should also consider that investors in health may not necessarily be traditional healthcare funders. Other actors could play a role. Importantly, financing becomes less of a constraint if we develop new solutions that generate a return on investment. In other words, effective innovations can create a self-sustaining cycle, where health improvements and economic benefits reinforce each other.
Géraldine Andrieux:
This ties into what we discussed earlier: public-private partnerships, blended finance, and similar approaches could all be very interesting. As health authorities, would these be options you are considering to enable the shift toward a health-focused system?
Dr. Iñaki Gutiérrez-Ibarluzea
We need to find funding wherever possible. Combining public and private funds is key. There’s an important distinction here: it’s not about privatizing healthcare provision, but about public-private partnerships for investing in solutions. In this context, data generated by public service providers should be shared with private companies to develop solutions. This approach reduces the cost of creating and validating solutions and improves the potential return on investment.
Géraldine Andrieux:
That’s very clear, and it opens the discussion for the weeks and months ahead regarding the actions we are implementing.
Géraldine Andrieux:
I also wanted to briefly touch on AI. You mentioned several times the need to be more proactive, to anticipate better, and to shift from siloed approaches to a more ecosystem-based approach. Could AI be the breakthrough innovation for these challenges? Is it something you are currently assessing?
Dr. Iñaki Gutiérrez-Ibarluzea
Yes, we are testing AI solutions, I would say in a sandbox environment, so it’s a safe space for experimentation. This is very interesting.
I was recently at the International Health Data Forum in Cardiff, and even major companies providing AI solutions highlighted that while AI is promising, the key is having good data. Systems need to provide well-curated, high-quality data. Without that, even the best AI solutions won’t succeed. For example, Microsoft’s Dr. Watson project struggled, and one of the main reasons for its limited success was precisely the lack of sufficiently curated data.
The main limitation for AI so far has been the lack of sufficient, accurate data, which is why collaboration is essential. Where we currently have good access to reliable data, for example, in diagnostics with objective biomarkers and imaging data. We see great potential. This reduces fear in the system because rather than replacing humans, AI is being used for intelligence augmentation. It allows us to process information faster than humans can, and in some cases, AI itself can help generate high-quality data. There is definitely space for AI, but we need to align expectations and focus on areas where it can operate safely and effectively. European healthcare systems tend to be conservative because we require guarantees and want to avoid errors. Some AI solutions introduced in the past actually increased mistakes rather than solving problems, highlighting the importance of careful implementation.
So, the challenge is twofold: we need to provide AI with high-quality data, and we need to ask the right questions. Only then can AI truly support healthcare systems. Interestingly, the Health Data Forum concluded with the principle: first data, then artificial intelligence. I would add: first questions, then data. We need to define the questions that require data, ensure we have high-quality data, and then test and enhance our capabilities to analyze that data and develop solutions using the tools available, artificial intelligence being one of the key ones.
Géraldine Andrieux:
One of the main challenges remains access to data and how to use it effectively, as data ownership is often a significant barrier. We’ve already been discussing some potential solutions together, but is data management a key concern for you? Would you be open to engaging in data-sharing or data-exploitation initiatives to address it?
Dr. Iñaki Gutiérrez-Ibarluzea
Well, it’s part of my nightmares, though I would say they are good nightmares. It’s true that managing data is a major challenge right now. In our country and region, we are closely monitoring the new European regulations on the secondary use of health data. By 2029, all public health data should be available for use, but we believe we can act much earlier with the technology we already have.
To do this, we need human intelligence to guide the process. There’s a paradigm shift: previously, European regulation treated data as owned by citizens, requiring informed consent for any use. Now, with the new rules, data can be used unless citizens opt out, but we still need to define concrete use cases.
We are working on this actively, proposing examples rather than pilots, because calling something a pilot implies a lack of trust in what we are doing. We call them use cases. We select specific use cases and explore them in depth, with the goal of scaling them in various contexts.
Géraldine Andrieux:
Let’s explore these use cases, because it’s useful to explore specific challenges and illustrate what we just discussed. At the start of our session, you highlighted the impact of the pandemic. Given its major effects, is the pandemic still considered a risk, and how are you factoring it into your planning? Are you also considering AI-based solutions to address this? Let’s cover this briefly so we can understand the current situation and the main threats related to it.
Dr. Iñaki Gutiérrez-Ibarluzea
Definitely, some people may say COVID is no longer an issue, and perhaps they are right. With the evolution of coronaviruses, future outbreaks may not even reach epidemic levels. But pandemics will continue to be a major risk. As I mentioned earlier, we can no longer think locally. We are global. Diseases that were once confined to tropical countries, like malaria or dengue, are now appearing elsewhere. For example, tiger mosquitoes (Aedes albopictus) are present in central Europe. We are also seeing new strains of flu, some originating from animals, which could become problematic. H1N1 in birds is one such example nearby. There will come a time when these viruses cross species barriers, so we need to be prepared.
This is why anticipation is key. We cannot wait until a pandemic strike to produce PPE or other emergency responses. If we plan ahead, such measures may not even be needed. Technology is certainly part of the solution, but only if we use it wisely. We can no longer claim ignorance. To anticipate effectively, we need access to real and relevant data, collaboration with other players, and a global perspective. Governments and healthcare systems cannot address these challenges alone. We need global investment, human expertise, and AI-driven solutions to support public health. Anticipation will be the critical factor in managing future risks.
Géraldine Andrieux:
Very good. Thank you very much for all the insights and sharing today. I think you’ve covered the topics we are focusing on at Financing Health Innovation very well.
To give a bit more context, these sessions are dedicated to the co-construction of solutions that truly fit the needs of health players. We start from the identified needs and work on fostering strategic collaboration among all key stakeholders, structuring a value chain with measurable impacts and coordinated actions. By doing so, we can potentially shift the paradigm, from simply checking boxes to truly measuring outcomes and impact. These models are also designed to be economically sustainable, engaging financial players with the right funding mechanisms.
Meanwhile, I also want to highlight that when we talk about the Basque Country and its Ministry of Health, many people agree that you are truly paving the way for innovation. So thank you again Iñaki for your time and contribution today. You’ve highlighted that while we face many challenges, there are also tremendous opportunities. This is exactly why we are very pleased to start working on this program together.
Christian Reitberger highlights two distinct aspects of France: its strong emphasis on nuclear energy and its successful collaboration between major defense players and the startup ecosystem. Christian Reitberger discusses the significance of nuclear energy in France, contrasting it with the preferences of other European countries like Germany. He suggests a lively debate on the necessity of nuclear energy, including Small Modular Reactors (SMRs), to meet energy demands, particularly for industries and data centers. Christian Reitberger also praises France’s model of collaboration between defense corporations and startups, noting its resemblance to successful practices in the United States. He emphasizes the uniqueness of these dynamics and suggests showcasing them at a French conference to provide valuable insights uncommon elsewhere.
CHRISTIAN REITBERGER
I think there are two special traits of France, that are less represented in other eastern European countries, if we think about, one of our key European challenges, it is the very high energy costs that we have across the continent.
We all would agree that we bet on renewable energies on energy conversion storage, et cetera, et cetera, but in France, there is still this enormously strong lobby on nuclear and the Germans, for example, don’t understand the French at all, and why they like it so much.
So, to give some spice to the discussion, one question could be for a dependable baseload energy supply, with the still rapidly ramping electricity needs of reshored industry, and all those data centers all filled with NVIDIA GPUs. Is nuclear required and, do SMRs play a role.
I’m seeing that because you could invite ORANO or EDF. One could invite a couple of the SMR players to have a very lively discussion that you would not have anywhere else, nuclear is part of the energy mix of the future.
Just what food for thought. And the other one is different. Where we’re France, again, France has built a very, very close and tight relationship between the 5-6 major defense players that you have, SAFRAN, THALES, et cetera. And your startup in VC community. The rest of Europe is only catching up to that. I know continuously being invited by defense organizations, contractors that want to talk about dual use technologies and investing in dual use technologies.
France, as I learned a couple of weeks ago with an organization, with, one of the defense players is advanced here. You have seemingly you have found the model how to establish these collaborations between this open innovation platform, between your Big Defense Corporates and the startup community. Something that the US has done in the last 30 years and trained it extremely well. And we probably should learn.
And that is something that I think you could definitely demonstrate at the French conference; I’d be hard pressed to find more than three German participants who could talk with credibility about this topic. Yeah This would be special. You would not find this anywhere else.
Francois Tison challenges Nvidia’s viewpoint, advocating for less compute power to sustain the planet. He sees a global shift towards frugal computing and believes Europe’s engineering strengths position it well for reindustrialization.
Dieter Kraft highlights the trend towards more efficient computing, particularly on the edge, and its potential to reshape architectures. Both identify these topics as key for discussion at the INPHO event, emphasizing collaboration to address challenges and seize opportunities.
FRANCOIS TISON
I think the comment of the Nvidia guys is extremely arrogant and goes. You always complete, completely contrary to where, where we’re going. I mean, there’s no way in Hell, you know.
The more you increase the level of abstraction, the more compute you need to achieve simple tasks, and we don’t need more compute to achieve simple tasks. We need less compute to achieve simple tasks, because the, you know, our planet cannot sustain more compute. So, I think I do think that, know, as I said in the beginning, we did a lot of CLEAN TECHS a lot.
In 2005, 2010, it was really, it was not the right time. I think now, we’re in an environment where both the public and the public at both ends, so, the consumers and the politicians that represent the consumers, are now extremely aware, and are pushing us and are pushing everyone to move into more frugal, way of consuming, and more frugal, ways of computing, cleaner, electricity, recycling, et cetera, et cetera.
Net zero, but beyond net zero or just a more frugal economy. Generally speaking, and we’re talking about the reindustrialization of Europe. I think those two subjects are linked, because in order to be more frugal to recycle more, we’re going to need to promote with smarter, smarter solutions, more engineering precision, engineering, stuff that mixes, engine, mechanic, precision mechanics, and Chemistry to produce, energy. Store energy, etcetera, etcetera.
And this is one of the traditional strengths of Europe. There are two places in the world where, where these technologies are really strong. It’s Europe, around the Alps, Austria, Switzerland, Germany, Italy, France, that area, and Japan.
But, but, Europe is one of the strong areas in the world in terms of Engineering on these, on these topics, so, I do think that reindustrilaisation and going towards smarter, more efficient solutions and a more frugal economy, those are things that play to Europe strengths, and they go together, and I think these would be certainly, one of the interesting topics to cover. AT INPHO
DIETER KRAFT
But think it’s, it’s indeed interlinked between, let’s say, more computing but also more efficient computing.
which leads to a trend I tend to observe, not really sure if it’s already a trend, but what we see is, in different European countries. Netherlands and Christian knows about that or Dresden, efficiency on the edge, AI with components.
Also, hardware investments, which are more or less enabling on the edge, computing with much more efficiency, than in the past.
And that totally changes the architecture, or might change the architecture, And might also, let us think about what can we do in order to lower down the power consumption of distributed computing?
That is something where we have a deeper look. And I think it’s potentially a point for discussion in the INPHO event because that is, for me, something, what is really differentiating, and where we need syndicates. Which can go together that way, might be capital intensive, but it might be huge in the impact.
Mathieu Costes highlights the evolving computing landscape, emphasizing Quantum Computing and emerging hardware technologies. He discusses the importance of these advancements for Venture Capital investments, particularly in early-stage ventures. Costes also underscores the need for software orchestration in hybrid architectures and the urgency for sustainability in data center operations.
MATHIEU COSTES
One thing, one theme that I think, resonates with what we discussed over the last few minutes, is the world of compute because, obviously Quantum Computing and the world of hardware is evolving. Who will win the race between ion trap, neutral Atom, and others? I don’t know, but things are progressing heavily.
If you think compute, we’ll go to the known world of CPUs that measure low consumption CPUs of tomorrow, GPUs with the Nvidia story that could enable AI and other stuff, QPU is quantum, The world of Neuromorphic chips may come in, and finally mature.
Then we see the world of photonics, that may be much faster to move a photon, to save time when latency and speed is critical and Think about a DNA based storage and chemistry-based computing that could offer unprecedented, paralyzed tasks. So, the world of compute, starting with the hardware, to me, is the key element that is relevant for Venture Capital, especially in early stage.
And on that one, you could even see the world of software to orchestrate between Solver, and the world of workload scheduler in this new hybrid architecture, will have a key role to play. This is a this is a global problem. Because obviously we know the world of AI, which generate a huge volume of workload. between that one, weather forecasts, scientific computing and whatever computing to be needed tomorrow. I think we’ve got a very promising field to share news and hopefully, too, deploy more capital into in the coming years.
I would even mentioned, sustainability, how to have datacenters, CPU, GPUs, QPUs, that will not absorb the full volume of green electricity produced. You see what happened in Ireland a couple of months ago, they stopped the growth and expansion of the datacenters. Say, they are consuming 18% of the electricity generated into the country, which is exactly the same level of the energy electricity consumed by the citizens. So things will have to change.
Blumorpho works accross the whole heath innovation ecosystem. We are happy to have you involved in more actions.