A research team led by Distinguished Professor Sang Yup Lee at KAIST has mapped out the key bottlenecks standing between laboratory breakthroughs in microbial cell factories and their commercial-scale deployment, offering a roadmap for closing the “valley of death” that strands so many promising biomanufacturing technologies.

Systems metabolic engineering – the discipline of designing and optimizing microbial cell factories to produce chemicals, materials, and fuels – has produced a wealth of impressive laboratory results over the past two decades. Yet translating those results into profitable, large-scale industrial production remains a persistent challenge, with many promising technologies failing to make the leap from bench to factory floor.

Case studies in the valley of death

To illustrate the scope of the problem, the researchers examined two case studies: succinic acid, a platform chemical with wide industrial applications, and polyhydroxyalkanoate (PHA), a biodegradable plastic seen as a promising alternative to petroleum-based plastics. Both have been produced successfully using engineered microbes in laboratory and pilot settings, but both have struggled to achieve the cost competitiveness needed to displace their petrochemical-derived counterparts at scale.

The analysis identified a recurring pattern: technologies that work in the lab often fail to account for the economic and logistical realities of industrial-scale production, including feedstock costs, downstream purification expenses, and the volatility of commodity chemical markets.

A phased strategy for commercialization

To address this gap, the research team proposed a phased commercialization strategy. Rather than attempting to compete immediately in low-margin, high-volume commodity chemical markets, the researchers suggest that biomanufacturers should first target high-value markets such as pharmaceuticals, cosmetics, and specialty food ingredients, where customers are willing to pay a premium for bio-based or sustainably produced ingredients. Revenue and expertise gained in these smaller, higher-margin markets can then help fund and refine the technology for eventual expansion into larger, more price-sensitive commodity markets.

The team also emphasized the growing role of artificial intelligence in accelerating this process. AI-driven tools can now assist with enzyme design, microbial strain optimization, and the creation of digital twins that simulate production processes before committing to costly physical scale-up. The researchers argue that techno-economic analysis and life cycle assessment should be incorporated as early-stage design criteria, rather than being considered only after a technology has already been developed, so that economic viability and environmental impact are built into the process from the very beginning.

Supply-chain resilience was also highlighted as an increasingly important design standard, given how global disruptions can upend the economics of feedstock-dependent biomanufacturing processes.

“By combining systems metabolic engineering with AI-driven design and economic analysis from the earliest stages, we believe the field can finally bridge the gap between laboratory success and industrial-scale impact,” the research team noted, pointing to the succinic acid and PHA case studies as evidence that the barriers, while significant, are not insurmountable.

The study was co-first authored by KAIST PhD candidates Ji Yeon Kim and Hye Eun Yu.

Journal: Nature Communications
DOI: 10.1038/s41467-026-73835-1
Article Title: Beyond petrochemicals: challenges and opportunities in industrial-scale biomanufacturing
Publication Date: 30-May-2026 (online)
Funding: National Research Foundation of Korea; Ministry of Science and ICT

Source: EurekAlert