TL;DR
Three themes emerged from the 19th Annual European Life Sciences CEO Forum: capital is selective (but still available) and rewards clearer differentiation and earlier proof. Innovation attention is concentrating in a few high-momentum areas (cardiometabolic and obesity, autoimmune and inflammation, radiopharmaceuticals), and partnering is trending toward more integrated, global innovation ecosystems rather than a single “biotech builds, pharma buys” path.
Lessons from the European Life Sciences CEO Forum
I spent the two interesting days at the 19th Annual European Life Sciences CEO Forum, and left with a familiar feeling: the biotech and biopharma environment is not “down,” but it is more disciplined. The conversations I heard, across investment, research and development (R&D) strategy, and partnership models, kept coming back to the same underlying question:
What does “quality” look like right now, and how early does a company need to prove it?
Below are the three themes that stood out most clearly to me. I’m sharing them in a practical way, with an eye toward what they mean for teams making real decisions such as building pipelines, designing evidence plans, and figuring out when to partner.
1. Capital is re selective, but quality science still gets funded
If there is one headline I would give the current financing environment, it is “selective, not frozen.”
The consensus in the room aligns with what everyone has been living through since the post-2021 correction: investors are still willing to fund, but the bar is higher: they are prioritizing capital efficiency, differentiated biology, and clearer development paths, especially for early-stage companies.
Here are the key trends that currently shape the industry:
- fewer but larger investments specifically in programs that have a strong mechanistic rationale.
- more interest in platforms that can generate multiple assets, not only single-asset stories
- small companies focus on risk sharing earlier in development by partnering with large pharmaceutical companies
What this means for early companies which was mentioned by a few senior BD executives from large pharma during a panel: seed and Series A companies are often being pushed to show translational evidence and a stronger clinical hypothesis earlier than they might have been asked for a few years ago.
My interpretation is that the “selectivity” trend is likely also driving more internal prioritization: companies appear to be trimming peripheral programs sooner and investing disproportionately in the 1–2 assets where they can credibly create a clear value inflection point.
2. Therapeutic innovation is converging around a few high-momentum areas
Another strong thread was that innovation is not evenly distributed. Certain therapeutic and modality areas are attracting a disproportionate share of attention, talent, and capital. In the sessions and side conversations, three areas kept coming up as especially “hot,” and for understandable reasons. Spoiler alert: none of these should come as a surprise:
- Cardiometabolic and obesity
Glucagon-like peptide-1 (GLP-1) and next-generation incretin biology continue to dominate the cardiometabolic conversation. The interesting part now is how quickly the work is evolving and branching to include:
- multi-agonists and combination approaches
- oral formulations
- strategies aimed at broader metabolic syndrome and cardiovascular risk, not weight loss alone
- Autoimmune and inflammation
Here, the trend is the increasing focus on precision immunology. Instead of broadly suppressing immune activity, there is more focus on pathway-specific modulation. In addition, we see continued expansion across biologics, cell therapies, and targeted small molecules.
- Radiopharmaceuticals in oncology
Radiopharmaceuticals is one of the fastest-growing areas of interest and pharmaceutical companies are investing heavily in targeted radio-ligand therapies and isotope supply chains. This suggests that radiopharmaceuticals are a new therapeutic pillar alongside biologics and small molecules.
Across these domains, the shared theme is mechanistic precision combined with better patient stratification.
In other words: fewer “broad bets,” more programs designed around a specific biological hypothesis and a clearer plan for identifying the patients most likely to benefit.
My take is that the convergence around a few high-momentum areas may increase competitive density. That usually raises the bar for differentiation and can accelerate partnering, particularly for smaller companies that want to move faster than otherwise possible for them.
3. Partnership models are shifting toward more integrated innovation ecosystems
The last theme is less about science and more about how science gets turned into a pipeline and ultimately products. The “traditional” pathway, biotech innovates, then pharma acquires, still exists, but it no longer is the only or even the default story.
Instead, there seems to be growing acceptance that innovation is globally distributed and that companies are building networks as deliberately as they build internal capabilities. The developments that stood out:
- external innovation and search and evaluation teams are playing a larger role in sourcing early science
- cross-border dealmaking is accelerating, including activity connected to Greater China biotech ecosystems
- more partnering with venture studios, incubators, and platform biotech firms
This shift reflects the reality that the innovation frontier is now globally distributed, and requires companies to build global networks rather than rely purely on internal R&D.
Another important note from the representatives of large pharma: several speakers pointed to what appears to be a growing strategic trend among U.S. biotechs: structuring partnerships around ex-US rights while retaining the United States as their core commercial market.
The discussion suggested that many emerging companies are increasingly building their entire development and financing strategy around the U.S., seeking large pharma partners primarily for the rest of the world to handle registration, commercialization, and distribution. What was particularly striking, and in my mind very controversial, almost worrisome, was the observation that in certain cases ROW access is becoming almost an afterthought, with some companies delaying global plans until very late in development or even deprioritizing them altogether.
Much of this dynamic appears to be driven by the ongoing debate around drug pricing and market economics, which makes the U.S. market disproportionately attractive. Several participants noted that while the model may make financial sense for small innovators, it can create significant delays in patient access outside the U.S. This raises the broader questions about how global access to new therapies will evolve if this trend continues.
The bottom line
The clearest through-line from the forum was that biotech is entering a phase defined by disciplined capital allocation, targeted therapeutic momentum, and deeper collaboration across the ecosystem.
Success increasingly seems to hinge on combining strong scientific hypotheses with high-quality data infrastructure and a partnering strategy that reflects a more networked and global innovation landscape.
The comment that many U.S. biotechs today are effectively building their strategy around the U.S. market first and figuring out the rest of the world later, if at all – stuck with me because it highlights how difficult some of these strategic decisions have become. When the external landscape is moving quickly—new assets emerging, valuations shifting, and regulatory paths evolving—it becomes harder to prioritize opportunities, calibrate development risk, and make decisions with a consistent baseline of evidence.
If you’re navigating questions like how to prioritize with confidence, assess risk with a transparent benchmark, and stay current on a rapidly evolving external landscape, I’m always happy to compare notes. At Intelligencia AI, much of our work centers on helping teams build that foundation—combining curated development data and explainable analytics so programs can be compared more objectively and critical decisions can be taken with greater clarity.
For more tailored, data-rich insights, let’s talk.
