BackgroundThe Design of Experiments (DoE) approach is a systematic, rigorous procedure used to understand the influence of various factors affecting a process and their interactive effects. It is a statistical tool that aims to optimise processes by not only focusing on the relationship between input parameters and output response but also considering the interdependencies between input variables. The statistical methodology underlying DoE allows for the more efficient and effective exploration of the design space and helps in developing empirical models for process understanding and optimisation.
MethodologyThe implementation of DoE in bioprocess optimisation at the lab-scale involves a sequence of steps. First, the process parameters (factors) and their potential ranges are identified. Then, an experimental design is chosen. This can be a full-factorial design, where all possible combinations of factors are tested, or a fractional factorial design, where only a subset of the possible combinations is tested. After performing the experiments, the data is analysed, often using regression analysis, to develop an empirical model of the process.
1. Understanding Your Requirements
2. Detailed Feedstock Analysis
3. Formulation of DoE
4. Undertake Experiments
5. Validation at Higher TRLs
6. Technoeconomic Analysis (TEA)
Has a deep understanding of all biological and chemical aspects of bioproceses. Has developed Celignis into a renowned provider of bioprocess development services to a global network of clients.
A dynamic, purpose-driven chemical engineer with expertise in bioprocess development, process design, simulation and techno-economic analysis over several years in the bioeconomy sector.
PhD (Analytical Chemistry)
Dreamer and achiever. Took Celignis from a concept in a research project to being the bioeconomy's premier provider of analytical and bioprocessing expertise.