From lab to ledger: a sequential policy framework for de-risking biotechnological investments in environmental sustainability

1 Introduction

The global shift toward a circular bioeconomy is no longer just a policy aspiration, it is increasingly a practical necessity. Across the world, governments, researchers, and industries are exploring biotechnological solutions to address urgent environmental challenges such as plastic pollution, land degradation, and rising carbon emissions (Saka et al., 2025). Innovations such as engineered microbes capable of breaking down waste and bio-based alternatives to fossil-derived materials highlight how far the science has progressed. Indeed, the broader “biotechnological potential,” driven by advances in tools like CRISPR-based genome editing and microbial fuel systems, is at an unprecedented level (D’Adamo et al., 2021; El-Chichakli et al., 2016; Venkata Mohan et al., 2022; Zilberman et al., 2018).

Despite these advances, a persistent gap remains between laboratory success and large-scale commercial deployment. Many promising innovations fail to progress beyond pilot phases, a phenomenon widely referred to as the “Valley of Death” (Zilberman et al., 2018). Importantly, this gap is not primarily due to scientific failure, but rather to economic and institutional constraints. Biotechnological innovation typically involves long development cycles, high capital intensity, and significant uncertainty. For instance, scaling a bio-based production process often requires specialized infrastructure, rigorous testing, and compliance with strict environmental and health regulations (Yusuf and Ojedokun, 2024).

This reality creates a structural mismatch with conventional financing models. Venture capital, which has driven rapid growth in digital sectors, tends to prioritize short-term returns and scalable, low-capital innovations. In contrast, environmental biotechnology projects demand patient capital and longer investment horizons, making them less attractive under traditional funding frameworks (Gentry and Keohane, 2021). Additionally, these technologies often compete against well-established, fossil-fuel-based industries that benefit from existing infrastructure and, in some cases, policy support, further complicating their market entry (Arguedas et al., 2025; Bansal et al., 2023; Kircher, 2023).

As a result, many technically viable and environmentally beneficial solutions fail to scale, not because they lack effectiveness, but because they lack access to appropriate, stage-specific financing. This financing gap is particularly critical at transitional phases, such as moving from prototype to demonstration or from demonstration to commercialization. Without targeted financial instruments to support these stages, innovation pipelines remain stalled.

In the current macroeconomic landscape, the urgency of addressing this gap has intensified. Governments are strengthening climate commitments, businesses are under increasing pressure to meet environmental, social, and governance (ESG) standards, and the economic costs of environmental degradation continue to rise. Bridging this divide therefore requires moving beyond a “one-size-fits-all” approach to funding. Instead, there is a need for a coordinated and sequential investment framework that aligns financial instruments with the specific risk profiles of each stage of biotechnological development (OECD, 2024).

This article examines how rethinking investment architecture can help transform promising biotechnological practices into scalable and sustainable prospects, ensuring that the growing biological revolution delivers tangible economic and environmental benefits beyond the laboratory.

2 The problem: risk assessment in biotech

The biggest obstacle to the widespread adoption of biotechnological solutions is not a lack of ideas or scientific capability, it is how risk is perceived, measured, and managed. Unlike traditional industrial systems or digital innovations, biotechnology carries a layered and often unfamiliar risk profile. In simple terms, investors and policymakers are dealing with two broad categories of risk: technical risk (will it work reliably?) and market risk (will it be profitable and adopted?). In biotechnology, both are amplified because the core of the technology is “living” systems, which are naturally more variable and less predictable (Scarlat et al., 2022).

One of the most difficult challenges lies in scaling. In the digital world, once a product works, it can often be replicated and distributed at almost no additional cost. Biotechnology does not work that way. It operates in what scientists sometimes call “wetware”, systems involving living organisms, enzymes, and biological processes. A solution that performs well in a controlled laboratory setting may behave very differently when moved to an industrial scale. Factors such as temperature fluctuations, contamination, or inconsistencies in raw materials can significantly affect outcomes. For example, engineered microbes designed to break down waste or capture carbon may lose efficiency when exposed to real-world conditions like impure feedstock or unstable environments (Brizga et al., 2022).

This unpredictability creates what many investors interpret as unreliability. From a financial standpoint, uncertainty translates into risk, and risk increases the cost of capital. As a result, projects that could deliver long-term environmental benefits, such as bio-based waste treatment or carbon capture, often struggle to attract funding because they are seen as too risky in the short term. This is not necessarily because they fail, but because their outcomes are harder to guarantee compared to more conventional technologies (Adejoh and Yusuf, 2025).

Another major issue is the dominance of existing “grey” infrastructure. Over decades, economies have been built around traditional chemical, mechanical, and fossil-fuel-based systems. These systems benefit from established supply chains, regulatory familiarity, and, in many cases, government subsidies. This creates what economists refer to as “path dependency”, a situation where past investments shape and limit present choices (Mazzucato and Books, 2021). Biotechnological alternatives, no matter how promising, must compete against these deeply entrenched systems.

This leads to what is often called the “green premium”, the extra cost associated with choosing environmentally friendly technologies over conventional ones. In biotechnology, this premium can be particularly high because many of its benefits, such as cleaner ecosystems or reduced emissions, are not fully reflected in market prices. In other words, society gains, but the investor does not always see immediate financial returns.

Compounding the problem is the lack of standardized ways to measure and communicate “bio-risk.” Unlike traditional engineering projects, where performance metrics are well established, biotechnology lacks universally accepted benchmarks for reliability and scalability. This makes it harder for institutional investors to carry out due diligence and compare opportunities confidently. As a result, capital tends to flow toward safer, more familiar sectors, leaving high-potential biotechnological innovations underfunded (Fritsche et al., 2021).

Taken together, these challenges explain why many promising biotechnological solutions struggle to move from concept to widespread use. Addressing them requires not just better science, but a more structured and sequential approach to managing risk, one that aligns financing, policy, and innovation at every stage of development.

3 A Sequential Gate Framework for biotechnological de-risking

For biotechnological innovations to move from promising laboratory “practices” to real-world “prospects,” the way we fund and support them must change. A one-size-fits-all or linear funding approach does not work because the risks involved in biotechnology are not constant—they evolve at each stage of development. What is needed instead is a more structured and step-by-step approach that responds to the specific challenges a technology faces as it grows. This is where the idea of a Sequential Gate Framework becomes useful, providing a roadmap that aligns financial tools and policy support with the changing risk profile of biotechnology across its lifecycle.

3.1 Stage 1: the R&D gate–addressing fundamental uncertainty

At the earliest stage of innovation, the biggest challenge is uncertainty. At this point, scientists and entrepreneurs are still trying to answer a basic question: Does this idea actually work? This is what is commonly referred to as “technical risk.” Many ideas fail at this stage, and even those that succeed may take years before showing any commercial promise. Because of this high level of uncertainty, private investors are usually reluctant to commit funds, seeing the chances of losing capital as prohibitively high.

Yet, this is exactly the stage where support is most needed; without early funding, many potentially transformative ideas never get off the ground. While classical literature highlights this early funding friction as a primary driver of the “Valley of Death” (Zilberman et al., 2018), broader venture capital and institutional studies show that institutional neglect at this phase is exacerbated by extreme capital intensity and the lack of secondary markets for highly specialized biological intellectual property (OECD, 2024).

This is where government intervention becomes critical. Direct R&D subsidies can help cover the cost of early experiments, equipment, and skilled personnel. In addition, policies such as “Patent Box” tax regimes, which reduce taxes on income generated from intellectual property, can make innovation more attractive by ensuring that successful ideas are rewarded. The goal at this stage is not immediate profit but learning and validation. To exit this gate, technologies must reach a clear laboratory proof-of-concept (equivalent to TRL 3–4), verifying basic biological efficacy under controlled parameters.

3.2 Stage 2: the demonstration gate–bridging the “Valley of Death”

The second stage is the point where a technology moves from small-scale laboratory success to larger, real-world testing. It is one thing for a process to work in a test tube; it is another for it to function reliably in a pilot plant or industrial setting. Here, the main challenge shifts from pure technical uncertainty to “scaling risk.” Biological systems can behave unpredictably when conditions change. For example, microbes that perform efficiently in controlled environments may react differently when exposed to variations in temperature, raw materials, or contamination at larger scales. These uncertainties make institutional investors cautious, as failures at this stage can be very costly.

To address this, a different set of financial tools is required. Public-Private Partnerships (PPPs) are particularly useful because they allow risks to be shared between Government and private investors. In addition, mechanisms such as First-Loss Guarantees can play a crucial role. Under this arrangement, a public institution, such as a government agency or development bank, agrees to absorb the initial portion of any losses. This reduces the financial risk for private investors and makes them more willing to participate.

The goal at this stage is to achieve what can be called “technical bankability.” Progression past this gate requires proving that the technology works not just once, but consistently and at scale (TRL 6–7), minimizing biological variance to a margin acceptable to institutional underwriters. Once lenders and investors are convinced that the process is stable and repeatable, it becomes much easier to attract the larger amounts of capital needed for full commercialization.

3.3 Stage 3: the market gate–achieving competitive parity

Even after a technology has been proven to work at scale, another major challenge remains: market competition. Many biotechnological solutions struggle to compete with traditional, fossil-fuel-based alternatives that are often cheaper due to established infrastructure and historical subsidies. This creates what is known as “market risk.” At this stage, the problem is not whether the technology works, but whether it can survive and grow in a competitive marketplace. Without support, even the most effective innovations can fail simply because they are not economically viable in the short term.

To overcome this, policy tools must focus on creating a level playing field. One effective instrument is the Contracts for Difference (CfD) model. Under this system, the government guarantees a fixed price for the product. If the market price falls below this level, the government pays the difference; if it rises above, the producer may pay back the surplus. This provides revenue stability and reduces uncertainty for investors. Another important tool is Advanced Market Commitments (AMCs). These involve governments or large organizations committing in advance to purchase a certain quantity of a product once it is available. For example, a government could agree to buy a specified volume of bio-based materials or carbon capture services. This guaranteed demand encourages producers to invest in scaling up production.

The goal at this stage is to eliminate or significantly reduce the “green premium,” the extra cost of choosing environmentally friendly solutions. Progression to an un-subsidized, self-sustaining market architecture is achieved when the technology reaches commercial cost parity and integrates into existing industrial supply chains (TRL 8–9). By doing so, biotechnological innovations can compete fairly with conventional alternatives and eventually stand on their own as profitable, self-sustaining businesses.

3.4 Counterarguments and institutional risks: crowding-out and policy capture

While a sequential policy framework offers a structured pathway for de-risking, critics rightly point to significant institutional risks, notably the “crowding-out” effect and the vulnerability to policy capture. The crowding-out hypothesis suggests that aggressive public interventions, such as direct R&D subsidies or heavy public first-loss guarantees, may displace private venture capital that would otherwise have funded high-potential innovations. If public financing is too readily accessible, it risks distorting market signals, resulting in capital misallocation toward inefficient technologies while private underwriters retreat to less interventionist sectors. To mitigate this, public financial instruments must be strictly structured as co-investments, ensuring that state capital acts as a catalyst rather than a replacement for private equity.

Furthermore, long-term market support mechanisms like Contracts for Difference (CfD) and Advanced Market Commitments (AMCs) are highly susceptible to policy capture and rent-seeking behavior. Well-entrenched industrial actors or early-stage biotech monopolies can leverage political influence to lock in long-term government price guarantees, effectively insulating themselves from genuine market competition and shifting technological performance risks onto taxpayers. This risk underscores the necessity of designing policy gates with clear, time-bound “sunset clauses” and strict, performance-based metrics. Policy incentives must decay predictably as technologies mature, ensuring that state support functions as a temporary bridge to market viability rather than a permanent institutional subsidy.

3.4.1 Bringing it all together

What makes the Sequential Gate Framework effective is its recognition that different problems require different solutions at different times. Early-stage innovation needs protection and encouragement. Mid-stage development requires risk-sharing and validation. Late-stage commercialization depends on market support and demand creation.

When these stages are properly aligned, the entire innovation ecosystem becomes stronger. Instead of promising ideas getting stuck at one stage, they are gradually guided toward full market adoption. This not only benefits innovators and investors but also ensures that society can take full advantage of biotechnological solutions to address pressing environmental challenges.

In essence, de-risking biotechnology is not about eliminating risk entirely, it is about managing it intelligently. By matching the right policies and financial tools to the right stage of development, governments and institutions can turn scientific breakthroughs into practical, scalable solutions that deliver both economic and environmental value.

4 Discussion and future prospects

The journey from small-scale biotechnological “practices” to widely adopted, sustainable “prospects” is fundamentally an institutional and structural challenge rather than a purely scientific one. By operationalizing the Sequential Gate Framework through explicit Technology Readiness Level (TRL) thresholds (Table 1) and tracing its mechanics via microbial plastic degradation (Section 4.1), this perspective demonstrates that biotechnology cannot evolve through isolated, linear funding leaps. Instead, success depends on a synchronized architecture where public de-risking instruments systematically decay as a technology achieves technical bankability. Consequently, contemporary green policy must pivot away from open-ended subsidies toward stage-specific interventions that actively bridge the information asymmetries separating biotechnologists from institutional underwriters.

TABLE 1. The Sequential Gate Framework for biotechnological de-risking across technology readiness levels (TRLs).

By 2026, the global economy is at a turning point. The growing impact of climate change, rising costs of environmental damage, and increasing adoption of carbon pricing mechanisms are forcing governments and businesses to rethink traditional industrial systems. Many long-standing “grey” assets, those tied to fossil fuels and conventional processes, are gradually losing their economic attractiveness as cleaner alternatives emerge. However, this transition is not automatic. For biotechnological solutions to truly replace or complement these systems, two important developments must play a central role: the integration of digital technologies with biotechnology, and the standardization of environmental and sustainability metrics across countries.

One of the major challenges in biotechnology, especially at the demonstration stage, is the unpredictability of scaling biological systems. What works in a controlled environment may behave differently when expanded to industrial levels. This is where digital innovation is beginning to make a real difference. The use of Digital Twins, virtual models that replicate real-life bioprocesses, offers a practical way to test and predict outcomes before committing large amounts of capital. By combining these models with Artificial Intelligence (AI), firms can analyze data from bioreactors in real time, monitor how biological systems respond to changes, and make adjustments quickly (Brizga et al., 2022).

This development has important economic implications. One of the reasons investors are cautious about biotechnology is the lack of clear, reliable information about performance at scale. Digital tools help reduce this uncertainty by making processes more transparent and predictable. In simple terms, they turn what once seemed like a “black box” into something closer to a “glass box,” where risks can be seen, measured, and managed. This reduces information gaps between innovators and investors, lowers perceived risk, and can make it easier to attract funding and speed up commercialization.

At the same time, progress at the global level remains uneven due to differences in regulations and standards. Today, a biotechnological product that is approved in one country may face entirely different requirements in another. This lack of harmonization creates what can be described as “compliance friction.” It increases costs, slows down expansion, and discourages cross-border investment. For a sector that depends on scale to become cost-effective, this fragmentation is a major obstacle (Patermann and Aguilar, 2023).

Looking ahead, one of the most important steps will be the development of a unified global framework for classifying and evaluating bio-based products. A Global Bioeconomy Taxonomy, similar in spirit to existing sustainable finance frameworks, could provide clear definitions and standards for what qualifies as a “green” or sustainable biotechnological activity. This would not only improve transparency but also build trust among investors.

Such standardization could unlock new financing opportunities. For instance, it would make it easier to group multiple biotechnological projects into financial instruments like green bonds, allowing them to attract funding from large institutional investors and sovereign wealth funds. These investors typically require clear benchmarks and low uncertainty before committing capital, and a standardized system would help meet those expectations.

In summary, the future of biotechnology will depend on more than just scientific breakthroughs. It will require better integration with digital tools, stronger alignment of global policies, and clearer standards for measuring impact. If these elements come together effectively, biotechnology can move beyond isolated successes and become a central pillar of a sustainable global economy.

4.1 Operationalizing the framework: a case study in microbial plastic degradation

To illustrate the practical mechanics of the Sequential Gate Framework, consider the commercialization of an engineered microbial system designed for the enzymatic degradation of Polyethylene Terephthalate (PET) plastic waste. At Stage 1 (The R&D Gate), the primary bottleneck is fundamental technical uncertainty: optimizing enzyme secretion and structural stability in laboratory strains. Direct public R&D grants fund the genetic sequencing and initial bioreactor assays. The technology exits this gate only when the engineered strains demonstrate a verifiable, repeatable rate of plastic depolymerization in laboratory settings (achieving TRL 3).

Upon entering Stage 2 (The Demonstration Gate), the innovation confronts the “Valley of Death.” The challenge shifts to scaling up the bioreactors from 1-L laboratory flasks to 10,000-L pilot facilities, where temperature fluctuations, shear stress, and unrefined municipal plastic feedstock present severe operational risks. Private venture capital is typically paralyzed by this scaling risk. By utilizing a Public-Private Partnership (PPP) backed by a public first-loss guarantee, the state absorbs the initial financial hit if the pilot bioreactor crashes due to feedstock contamination. Once the pilot plant demonstrates steady, high-yield enzymatic throughput over a continuous operational cycle, it achieves “technical bankability” and exits Gate 2.

Finally, at Stage 3 (The Market Gate), the bio-recycled monomer must compete against cheap, virgin fossil-fuel-derived PET. The premium cost of the bio-based alternative creates an immediate market entry barrier. By implementing a Contract for Difference (CfD), the government establishes a guaranteed strike price for bio-recycled PET. If the market price of virgin PET plummets, the government compensates the biotech firm for the price differential, providing the revenue stability required to secure long-term commercial loans and achieve true industrial scale.

4.2 Applicability and structural imperatives in emerging economies

Applying this sequential framework within emerging economies, particularly within Sub-Saharan Africa and nations like Nigeria presents unique institutional dynamics. In developing economic contexts, traditional deep-tech venture capital markets are virtually non-existent, and public fiscal space is heavily constrained by macroeconomic vulnerabilities and competing infrastructural needs. Consequently, relying strictly on direct state-funded R&D subsidies (Stage 1) or expansive sovereign price guarantees (Stage 3) is structurally unfeasible. Instead, the framework must be operationalized through alternative institutional channels.

For emerging markets, the financial architecture of the gates must pivot toward international climate finance, multilateral development banks (MDBs), and blended finance structures (International Finance Corporation, 2024). In Nigeria, for example, rather than utilizing domestic tax revenues, First-Loss Guarantees at the Demonstration Gate can be financed through sovereign green bonds or international financing facilities like the Green Climate Fund (GCF). Furthermore, Stage 3 market deployment can be driven by regional policy integration, such as leveraging the African Continental Free Trade Area (AfCFTA) to aggregate cross-border demand for bio-based products, thereby mitigating market risk without exhausting domestic fiscal reserves.

5 Conclusion

This study concludes that, while the challenges of environmental sustainability are deeply rooted in biological systems, the pathway to lasting solutions is largely structural and institutional. Scientific breakthroughs alone are not enough. What determines whether these innovations succeed or fail is the environment in which they are developed, financed, and scaled. As this paper has argued, the gap between promising biotechnological “practices” and viable large-scale “prospects” is mainly a function of how risk is managed across different stages of development.

Adopting a sequential de-risking framework provides a practical way forward. By aligning financial instruments, policy support, and market incentives with the specific needs of each stage, research, demonstration, and commercialization, stakeholders can create a smoother and more predictable pathway for innovation. This approach reduces uncertainty, attracts investment, and ensures that viable technologies are not abandoned midway due to avoidable financial or institutional barriers.

More importantly, such a framework transforms biotechnology from a collection of isolated laboratory achievements into a coordinated engine of industrial and environmental progress. It allows innovations to move beyond proof of concept and become embedded in real economic systems where they can deliver tangible value.

The transition to a circular bioeconomy, therefore, is not just an environmental ambition; it represents a fundamental shift in how economies function. It signals a move away from the traditional model of resource extraction and waste toward one based on regeneration, efficiency, and sustainability. If properly supported, this transition could define the next phase of global economic development, one where growth and environmental responsibility are no longer in conflict but are mutually reinforcing.

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Footnotes

Edited by: Dominika Dąbrowska, University of Silesia in Katowice, Poland

Reviewed by: Abhishek Tiwary, De Montfort University, United Kingdom

Rahbaar Yeassin, Ahsanullah University of Science and Technology, Bangladesh