Effectively-implemented optimisations of industrial bioprocesses can lead to massive improvements in process yields, productivity, and sustainability. These often lead to significant advances in the competitiveness and profitability of the companies that implement them. However, each bioprocess, feedstock and microorganism is unique, which presents challenges to be overcome and requires customised optimisation methods.  

Celignis have launched a new bioprocess optimisation service that reduces the time and financial costs compared with conventional optimisation approaches. This is done by combining theoretical modelling with experimental work and rapid analytical tools. The new Celignis Bioprocess Framework builds on the company's existing core strengths of biomass analysis, analytical method development, enzyme and microbial expertise, computational data, and data analysis.  

The Celignis Bioprocess Framework proposes a hybrid innovative modelling framework that utilises data-driven models and empiric data collection from Celignis’s labs for bioprocess monitoring, parameter estimation, and optimisation. Compared to traditional optimisation methods, data-driven models and machine learning enable highly accurate bioprocess control and bioprocess parameter optimisation. This enables us to rapidly characterise multiple process parameters, including mixing time, agitator types, temperature profile, pH profile, feed profile for fed-batch and continuous fermentation, and off-gas profile.  

How it Works 

Step 1 - Stakeholders from the bioprocessing industry or academic institutions reach Celignis via phone or e-mail to arrange a preliminary meeting. At the meeting, they are encouraged to share the process details and their desired outcomes (e.g. higher yields, lower energy costs etc.) with Celignis's bioprocess experts. 

Step 2 – Celignis presents a proposal and timeline outlining the planned work. This work can cover mathematical modelling utilising the client's existing data, experimental laboratory work (at various scales) at Celignis, or a combination of the two. 

Step 3 – Celignis undertakes the planned work, providing interim reports and video calls as the project progresses. 

Step 4 - Celignis finalises the work and represents a complete detailed report to the customer. 

Example Project  

ICISR is focusing on acetone, butanol, and ethanol production (using glucose and xylose from rice straw hydrolysate) via fermentation. The developer experienced low yields in overall ABE fermentation. Our investigation of the process parameters and fermentation yields revealed a key component causing metabolic shift in the system towards unwanted by-products. After a careful evaluation of the process, Celignis proposed a customised optimisation strategy. Celignis undertook kinetic modelling of the fermentation, substrate and product inhibition kinetics, followed by in-situ model development for fermentation optimisation. The prediction models were validated by performing experiments in Celignis’s laboratories at batch scale. Based on this work, an optimised continuous fermentation strategy was designed and submitted to the client.  The new fermentation protocol has allowed ICISR to achieve a 22% increase in the yield of the desired product (butanol).