How to solve the biotech bottleneck by funding ideas, not data

In biotech, the innovation pipeline often stalls at its very beginning: the first dollar. Unlike AI and climate tech, where a brilliant idea backed by a strong vision can unlock millions in seed funding and rapid iteration towards market-ready products. In the case of biotech, bold ideas without extensive, pre-existing experimental data are frequently shown the door. This systemic bottleneck is holding back breakthroughs to pressing global challenges, from pandemics to climate-driven food insecurity, breakthroughs that we need much sooner. 

The Catch-22 

Biotech’s early-stage innovation is trapped in a classic vicious cycle: you need data to get funding, but you need funding to generate that data. This forces most nascent biotech ideas onto a slow, precarious academic path. Most early ideas emerge in academia, funded by grants from national agencies like the NIH in the US, the BBSRC or the MRC in the UK, and Horizon in the EU. These grants typically prioritise novel findings and academic publications. Government funding trickles into university labs, often with fixed requirements, and only a small percentage then finds its way to startups. Startups are the vehicles that transform inventions into real-world impact and commercial realities. But what exactly is an invention? At Deep Science Ventures, we define it as an idea driven by a clear objective and an open-minded approach to the knowledge needed for a solution. This process inherently generates both novelty and utility. 

This systemic bottleneck, rooted in a singular reliance on government and philanthropically funded academic research, costs us life-saving solutions. It’s a fundamental cultural mismatch. Academia rightly prizes discovery, pushing the boundaries of knowledge. However, building a therapy or a sustainable biomaterial requires an invention mindset where progress is combinatorial – combining technologies into products, products into companies, and companies into ecosystems. 

What makes biotech development truly unique is the irreversible nature of its iteration cycles, which can span a decade or more. Given the inherent complexities of scientific research, stringent regulations, manufacturing hurdles, and other requirements for effective treatments, invention needs to be at the forefront of biotech innovation. 

This engineering approach, key for successful product development, is consistently undervalued and underfunded in traditional academic settings. As a result, billions flow into discovery research, but the applied engineering that translates these discoveries into real-world impact is starved. This conflation of discovery with invention chokes the sector and injects unnecessary scientific risk into early ventures. Crucially, it also closes doors for talented individuals outside of academia because normally you can only access labs for experiments if you’re an academic. Those seeking to make a real-world impact often end up leaving academia because their drive isn’t based on discovering novelty. 

How Deep Science Ventures is reimagining the biotech lab

What if we approached biotech with the same urgency and diversified support we give to sectors like software and energy?  

Imagine combining non-proprietary solutions, often built on extensive scientific data (even more than typical university spinouts), to solve specific problems. At Deep Science Ventures, we call this “Zero-Data Biotech.” Here, we intentionally back ideas based on strong scientific rationale, first principles, and the team’s expertise, rather than demanding extensive experimental proof upfront. Post-investment, we then support teams in methodically invent solutions using the underlying science of the individual components.  

By treating biology as an engineering problem and assembling ‘proven’ knowledge components to create novel solutions, our failure rate to proof of concept is less than 1 in 10, with no company deaths due to scientific risk whatsoever. 

This radical shift in mindset allows for incredible speed. Companies like Genentech built recombinant insulin in under two years; Moderna went from concept to human trials in just a few years. Speed comes from informed conviction in the underlying components, not from waiting for years of academic validation. 

So, what’s the solution? 

To scale biotech invention, we need to do things differently. This challenge presents an enormous, untapped opportunity for investors and policymakers. 

Traditional venture capital often chases the same handful of academic spinouts, leading to competitive, inflated valuations.

Failure rate is not a good measure of ambition, but rather a measure of bad design. We can and should be targeting an 80% success rate. Backing inventions with battle-hardened components and rigorous engineering design, can paradoxically be less risky than a discovery with a decade of academic research behind it if that research hasn’t systematically de-risked the product pathway. 

Tying early innovation primarily to academic grants creates a single, vulnerable pathway. Diversifying the funding landscape by supporting “innovation grants” accessible to independent teams, creating dedicated research spaces outside academia, and streamlining regulatory pathways for low-risk biological materials can unlock a surge of new solutions. 

It’s time for a culture shift. Investors must dare to do “zero-data” deals, structuring investments around experimental milestones. Philanthropy can adopt a venture mindset, seeding engineering-led approaches to unmet needs. Universities must evolve, fostering entrepreneurship and celebrating the creation of products that save lives on par with published papers. 

Zero-Data Biotech doesn’t mean ignoring rigorous science; it means taking an engineering approach to idea generation, combining proven components into novel solutions, and generating critical data after initial investment, not before. The early risk should be financial, not scientific. We need to empower biotech’s builders as much as its discoverers. By removing the narrow funnel vision, we can create an era of commercialised breakthroughs. 

The question isn’t whether we can do this; it’s how we do it.