PROJECT SCOPE AND OBJECTIVES
Bioeconomy is worth €2 trillion in EU with an annual turnover to account for approximately 9% of theworkforce (more than 22 million jobs). Biorefineries stand in the center of these developments largely depending on biochemical advances for processingtechnologies and innovations. Industrial Biotechnology, essentially a convergence of numerous scientific and engineering disciplines, provides biocatalysts and bioprocesses for a wide range of products. Empowered by modern biology, it is generating unprecedented amounts of tools and knowledge that can be funneled into bioprocess development pipelines.
Developments involve Design-Build-Test-Learn cycles (Fig.1) that include: (a) the generation of de novo biosynthetic pathways creating portfolios of (known and de novo) options to produce target compounds; (b) experimental work to build enzymes, (c) experimental work to test enzymes, and (d) design of process engineering units to produce chemicals at pilot and industrial scales.
To accelerate innovations by means of high throughput analysis, strong interactions are needed across development stages. To that purpose, IBISBA2 has been recently set up as an Industrial Biotechnology Innovation and Synthetic Biology Accelerator. IBISBA functions as an EU research (ESFRI) infrastructure (roadmap entry in 2018) to specifically support the DBTL process. Built on long-term collaborations between a large consortium of partners and through international projects (BIOCORE, NANO3BIO, RENESENG3,4), IBISBA is intended to mobilize €52.6 million capital to provide academics and private sectors with infrastructures to develop and test innovation pipelines for biochemistries. Research team has been extremely active in shaping up IBISBA (including coordination and participation in major research projects that built its research basis), now featuring a role to deliver systems work and to strengthen links with process engineering. Besides promises to revolutionise Industrial Biotechnology using advanced techniques (including genome engineering for the construction of biocatalysts, especially microbial cell factories), the DBTL concept is challenged by poor interactions between upstream research and process engineering.
That bears an impact on the industrial relevance of the research produced, also in capabilities to reverse-engineer decisions from engineering to science. Interactions are challenged by differences in context, practices, data, and objectives for each individual domain. Systems engineering could deliver a structured basis to unlock cross-disciplinary interactions with rigorous, generic, and systematic ways. The ambitious objective of research grant is to strengthen interactions between synthetic biology and process engineering using systems engineering to expedite and stimulate development stages of DBTL cycles. Systems engineering offers excellent technologies to explore lines that would integrate and accelerate developments by means of modelling, optimization, advanced analytics, and synthesis technologies: advanced analytics and ontology engineering to bridge knowledge gaps; modelling to set the background for analysis; optimization to screen pathways; synthesis to provide for discoveries and innovations. Meanwhile, IBISBA ESFRI makes an excellent and resourceful background to pull out expertise, data and knowledge, also means to validate and exploit research. Past and ongoing collaboration with international groups has already piloted several case studies and benchmark problems to test the research.
In contrast to Oil & Gas plants, the biorefinery concept is much richer in processing options, technologies, and feedstocks. Biorefinery production features value chains that diversify with regional supplies, technologies, and markets. There is a tremendous range of options to configure value chains with local economies, particularly in the context of Industrial Symbiosis and Circular Economy; the use of biowaste as biorefinery feedstock is a notable example. Industrial biotechnology and the development of biochemical paths can be instrumental to address the need to diversity and adapt the biorefinery concept. Synthetic biology offers an extremely promising knowledge basis producing substantial volumes of data and information including tools, models, and technologies to assist with the configuration of custom-made biochemistries (Fig.2).
The explosion of data masks poor interactions between upstream science and engineering. Unlike conventional industrial chemistries rich in theories and models, Industrial Biotechnology is hampered by knowledge gaps with synthetic biology and underlying principles; notwithstanding a tremendous scope to connect synthetic biology with process engineering, significant research is required to meet up the challenge. Industrial Biotechnology developments in systems engineering essentially remain at infant stages as even process modelling relies on unit operations rooted in Oil & Gas industry. Missing systems technology is apparently important to save costs and coordinate experimental work. Even more important, it would be to link up synthetic biology with real-life experiments, pull out knowledge from science to engineering, and infer guidelines for bioscience research to procure biocatalysts fully adapted to bioprocesses. To accelerate the development of biochemical processes, it would be necessary to build systems capabilities as well as methods to systematize and intensify data and knowledge transfer across the DBTL cycle (Fig.3).
Upstream science essentially accounts for the Design stage whose current interactions with Build, Test, Learning, also with process engineering and scale-up stages are currently weak and undeveloped. Design and Build stages combine computational and experimental research. While Design typically produces hundreds, thousands, or even millions of candidates, Build stages proceed with a few choices (often made by heuristics and/or intuition). Other than such choices hold no guarantees for quality, all inheritance and knowledge generated by the in-silico work is lost and unexplored. Kinetic models produced at Design and Test hold significant methodological differences that prevent validation of kinetics and knowledge gaps that restrict stage interactions. Rooted in thermodynamics rather than process dynamics, in-silico kinetics are produced as families of attainable models (by means of thermodynamically permissible permutations of the kinetic parameters involved). In contrast, kinetics at Test constitute conventional chemical engineering expressions regressed over experimental observables (concentration profiles, temperature, etc.); they remain disconnected from thermodynamically curated models and, subsequently, disconnected from the underlying reaction pathways associated with them. In comparison with others, Design and Learn, (including process engineering and scale-up) account for the weakest of all interactions in the DBTL cycle. As Design deploys over-simplified formulations for mass and balances, it neglects important aspects of process engineering and its promises are hardly realized; yields in pilot or industrial scale installations are dramatically inferior to initial promises. There is extensive and well-reported literature that process intensification could dramatically increase engineering yields; biochemistries can be conveniently manipulated to assist with intensification. Moreover, the manipulations can be used to build resistance in industrial environments once reverse-engineering are explored in the DBTL cycle. Systems analytics and systems engineering are hopeful lines to achieve such objectives.
