The role of basic research in deep tech. A policy-oriented scoping review of the literature.

Deep tech is viewed as central to addressing Europe’s competitiveness, innovation, and security challenges. This report synthesises insights from a scoping review of academic and policy literature on the role of basic science in enabling deep tech development and the conditions that sustain its translation into innovation.

The term “deep technologies” refers to early-stage, science- and engineering-based innovations grounded in fundamental advances in areas such as materials, biotech, quantum, and fusion. They are typically hardware-centric, long-cycle, and high-risk, requiring strong ecosystems that connect discovery to market. Because most deep tech originates from research, universities form important seedbeds of deep tech innovation, providing the knowledge, talent, and infrastructure from which new solutions and ventures emerge.

This review focuses on the role of basic science in deep tech. What we understand by “basic science” has changed over time, alongside evolving research and innovation policy paradigms. For this report, “basic science” is defined by three characteristics: (i) it investigates phenomena at a fundamental level; (ii) it generates broadly applicable, foundational knowledge that supports multiple uses and sectors; and (iii) it expands the scientific frontier. The current emphasis on deep tech has renewed and elevated the importance of basic science as the foundation from which deep tech ultimately emerges. Expanding our fundamental understanding, pursuing discoveries, and enriching the shared knowledge base through basic science are here seen as essential preconditions for the development of transformative deep technologies.
The review identifies three conditions for basic science to flourish and be translated into deep tech innovation:

1. Sustained investment and protected spaces. Because the benefits of basic science are uncertain and often unfold over long time periods, basic science needs predictable, long-horizon funding and “protected space” – i.e. institutional, financial, and intellectual autonomy insulated from short-term political and market pressures – to pursue uncertain, fundamental lines of inquiry. This is ensured by e.g. tenure systems, block grants, and long-horizon research funding programmes that allow for the slow accumulation of knowledge that ultimately seeds deep tech breakthroughs. Overprogramming or oversteering of research, especially when coupled with short-term KPIs, risk crowding out the exploratory, curiosity-driven search that is an important element of basic science and thus of deep tech innovation.

2. Institutional diversity and balanced research portfolios. Evidence shows that national research strength correlates with the breadth of scientific fields rather than the concentration of funding. In other words, scientifically leading nations are highly diversified across a broad range of scientific fields. Moreover, diverse institutional arrangements and a heterogeneous set of funding instruments – including e.g. investigator-led grants, centres of excellence, and mission-oriented grants – sustain resilience and renewal in the scientific base. Excessive focus on narrow priorities or “picking winners”-strategies can increase vulnerability to hypedriven cycles and erode the exploratory capacity on which transformative innovation depends.

3. Effective translation and diffusion mechanisms. Scientific excellence and commercialisation are complementary, not competing. Studies show that entrepreneurial activities and industry engagement can in fact enhance research novelty and impact. Universities play a pivotal role in supporting the translation of science through mechanisms such as joint R&D, consultancy, contract research, and researcher mobility, as well as through the innovation ecosystems in which they nurture deep tech startups.

In summary, basic science is both the foundation and the flywheel of deep tech innovation. Its vitality depends on long-term investment, plurality in research institutions and agendas, and effective translational interfaces that connect scientific discovery to deep tech innovation and, ultimately, societal impact.