A novel high-throughput scale-out fermentation array for isoprene bioprocess development
172,192
2024-02-01 to 2024-12-31
Collaborative R&D
Isoprene is a high-value, bulk commodity chemical, widely used in the production of industrial rubbers (~95% of all isoprene use). Additionally, isoprene can be converted downstream to a wide range of useful isoprenoid product molecules (e.g. limonene, retinol), commonly used in high-value sectors (e.g. flavourings, pharmaceuticals and beauty and fragrances). However, isoprene is currently primarily produced via petroleum cracking, which is both cost-intensive and highly detrimental to the environment. Furthermore, the dependence on fossil fuels for isoprene production leaves the isoprene market extremely susceptible to fluctuations in crude oil and gas prices. In recent times, this issue has become increasingly apparent owing to COVID supply chain issues and the Russia-Ukraine war severely impacting feedstock prices. The development of relatively cheap and sustainable isoprene production routes is of great interest.
Bio-based manufacturing using microorganisms offers a sustainable alternative for the production of isoprene. However, development of suitable host strains for industrial scale biomanufacturing is slow and expensive.
Twig are pioneering the development of a lab automation platform with machine learning to expedite the R&D process for strain development. This relies on increased automation using data driven insights applied to the strain development process, enabling the rapid development of highly productive commercially viable strains.
Building on advancements in miniature fermentation systems, we aim to advance our approach by incorporating data from high-throughput screening using pioreactor-arrays, to be developed in collaboration with UCL.
Successful outcomes will de-risk isoprene production and support post-project engagement with commercial partners for scale-up. Isoprene also unlocks pathways to other molecules of interest e.g. limonene, retinol, bakuchiol.
Machine learning accelerated pathway engineering for sustainable Palmitic Acid biomanufacture
224,889
2023-08-01 to 2024-10-31
Collaborative R&D
Palm oil production is reliant on intensive farming which is subject to price volatility and causes biodiversity loss. Global supply issues due to Covid and the war in Ukraine has also caused price inflation for manufacturers. In addition, the global population will grow to 10 billion by 2050, consuming more and more products - palmitic acid and palm oil derivatives are present in ~50% of packaged consumer products. There is an increasing need for a more sustainable and resilient process for palmitic acid production.
Bio-based manufacturing through the use of microorganisms offers exciting potential for the production of palmitic acid. However, development of suitable host strains for industrial scale biomanufacturing is slow and expensive.
Twig Bio are developing an automated, machine learning approach which will enable precision strain engineering and expedite development through rapid design-build-test cycles. The approach considers strain stabilisation from the outset ensuring strains are scalable and stable under continuous fermentation process conditions for use in industrial manufacturing.
In collaboration with the Centre for Process Innovation, the resulting strains will be evaluated for process scale up and commercial viability under process conditions to demonstrate the benefits of the approach in the development of sustainable bio-based manufacturing processes.
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