The DACH life sciences ecosystem combines world-class academic research and multiple strong regional hubs, yet experts agree that converting scientific excellence into globally competitive, scalable companies remains the sector’s central challenge. Interviewed investors and industry leaders point to outstanding talent, Switzerland’s pharmaceutical capital, and growing Austrian start-up networks as strengths, while citing slow technology transfer, limited growth capital, regulatory inertia and constrained data access as barriers to commercialization.
DACH life sciences: strengths and gaps
DACH benefits from academic excellence and a large pool of young international talent across both top-tier institutions and numerous mid-tier universities, creating several strong hubs that compete with and complement one another (Dr Moritz Beissenhirtz, Brandenburg Kapital). Switzerland contributes pharmaceutical expertise and capital, Austria shows start-up growth, and Germany remains a source of groundbreaking basic-research technologies (Dr Martin Raditsch, Carma Fund).
However, multiple speakers flagged insufficient translational activity from academia into start-ups as a long-standing limitation that has constrained economic development (Beissenhirtz). Other recurring constraints are lower average growth capital, slower technology transfer processes, fewer serial entrepreneurs, and restricted access to data (Raditsch; Dr Angelika Vlachou, High-Tech Gründerfonds). Faster licensing, cross-border studies, institutional investors, speedier regulation and greater data access were all mentioned as practical levers to improve conversion of discoveries into world-class companies (Raditsch; Vlachou). Christoph Lengauer of Curie.Bio and Niels Sharman of shiftingbio both emphasised that the region’s scientific ideas are globally competitive but that translation into drug embodiments and large companies lags behind North America and China, often for reasons of capital, speed and early global thinking.
Where AI can make the biggest difference
Experts foresee AI having its greatest impact where complex or large datasets meet costly decisions. In diagnostics, AI can improve reliability and reduce workforce bottlenecks, particularly in complex imaging analysis (Beissenhirtz). Beyond diagnostics, AI has potential to enhance understanding of biological processes and molecular interactions when applied to large, fluctuating datasets such as proteomics (Beissenhirtz).
Several panelists expect AI to accelerate processes and generate enabling tools, with human scientists remaining essential in the loop to intercept, evaluate and guide AI at critical decision points (Lengauer). Lengauer singled out clinical trial design and conduct as an area where AI will be a game changer, while cautioning that generative drug design will attract large funding but is unlikely to meet broad expectations in the near term because of insufficient underlying experimental data.
Raditsch highlighted AI’s value in speeding and improving target validation, molecule design, clinical trials and diagnostics through iterative learn-and-test cycles—models suggest experiments, labs test them, and new data refines predictions—but he noted that ownership of proprietary data will be a decisive factor. Vlachou described a staged impact: short-term gains in drug discovery, clinical trials and diagnostics; medium-term advances in multimodal precision medicine and AI-enabled bioprocessing; and long-term developments toward autonomous labs and closed-loop design-build-test-learn systems. Sharman framed AI’s principal opportunity as reducing biological and clinical uncertainty—using large multimodal patient datasets to better predict treatment response, patient stratification and immunogenicity—and stressed that a material increase in clinical success rates enabled by AI still needs proof at scale.
Other attractive investment trends
Drug development continues to dominate investment interest, with growing attention beyond oncology to neurology and autoimmune diseases—areas seen as ripe for breakthroughs (Beissenhirtz). Medtech sentiment, after difficult years, appears to be improving.
Investors named a range of specific scientific and platform areas they view as attractive: RNA-based therapeutics; gene editing and transfer; protein degradation; radiopharmaceuticals; antibody-drug conjugates; multispecific antibodies; cell therapy; precision diagnostics; and biomanufacturing (Raditsch). Success in these areas, Raditsch warned, depends on deep biological understanding, manufacturing feasibility, reimbursement prospects and an effective capital strategy to reach clinical proof of concept.
Vlachou recommended prioritising technologies that make entire fields practical, scalable and affordable—solutions that resolve critical bottlenecks and have multiple applications. Sharman highlighted radiopharmaceuticals and targeted protein degradation as fields where DACH retains scientific strengths and urged taking more technological risk and adopting an early global mindset; he also suggested that combining strengths across ecosystems could help European biotech become more competitive.
The interviewed investors converge on a clear prescription: leverage DACH’s research excellence and industrial capabilities while accelerating translational pathways through more growth capital, faster regulation, broader data access and stronger cross-border and institutional support to turn discoveries into globally successful companies.
