3 results
Now showing1 - 3 of 3
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Model-assisted DoE applied to microalgae processes(Elsevier, 2022-02-02); ; ; ; This study assesses the performance of the model-assisted Design of Experiment (mDoE) software toolbox for the design of two microalgae bioprocesses. The mDoE-toolbox was applied to maximize biomass growth for Desmodesmus pseudocommunis in a photobioreactor by varying the light intensity and pH and for Chlorella vulgaris in shake flasks, by varying the light intensity and duration. For both case studies, a mathematical mechanistic model was applied. In the first study only one experiment was necessary to adapt the mathematical model and identify a combination of light intensity and pH that improved biomass yield, as confirmed experimentally. In the second study, no well-established model was available for the specific experimental arrangement. On the basis of the literature, a mathematical model was constructed and a first cycle of mDoE was performed, thus identifying the desired factor combinations. Experiments confirmed the high biomass yield but revealed shortcomings of the model. The model was improved and a second cycle of mDoE was performed. The recommended factor combinations from both cycles were comparable. The mDoE was found to be a time-saving, cost-effective and useful method enabling the identification of factor combinations leading to high biomass production for the design of two different microalgae bioprocesses with low experimental effort.Publicationtype: Journal ArticleScopus© Citations 1 91 506 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses(Springer, 2021-01-20); ; ; ; Bioprocess development and optimization are still cost- and time-intensive due to the enormous number of experiments involved. In this study, the recently introduced model-assisted Design of Experiments (mDoE) concept (Möller et al. in Bioproc Biosyst Eng 42(5):867, https://doi.org/10.1007/s00449-019-02089-7, 2019) was extended and implemented into a software (“mDoE-toolbox”) to significantly reduce the number of required cultivations. The application of the toolbox is exemplary shown in two case studies with Saccharomyces cerevisiae. In the first case study, a fed-batch process was optimized with respect to the pH value and linearly rising feeding rates of glucose and nitrogen source. Using the mDoE-toolbox, the biomass concentration was increased by 30% compared to previously performed experiments. The second case study was the whole-cell biocatalysis of ethyl acetoacetate (EAA) to (S)-ethyl-3-hydroxybutyrate (E3HB), for which the feeding rates of glucose, nitrogen source, and EAA were optimized. An increase of 80% compared to a previously performed experiment with similar initial conditions was achieved for the E3HB concentration.Publicationtype: Journal ArticleScopus© Citations 10 113 320 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Estimation of process model parameters(Humana Press, 2020); ; ; ; Cell culture technology has become a substantial domain of modern biotechnology, particularly in the pharmaceutical market. Today, products manufactured from cells itself dominate the biopharmaceutical industry. In addition, a limited number of products made of in vitro cultivated cells for regenerative medicine were launched to the market. Modeling of such processes is an important task since these systems are usually nonlinear and complex. In this chapter, a framework for the estimation of process model parameters and its implementation is shown. It is aimed to support the parameter estimation task, which increases the potential of implementation and improvement of mathematical process models into the novel and existing bioprocesses. Apart from the parameter estimation, evaluation of the estimated parameters plays an essential role in order to verify these parameters and subsequently the selected model. The workflow is outlined and shown specifically on the basis of a mathematical process model describing a mammalian cell culture batch process.Publicationtype: Book Part150