Rapid process synthesis supported by a unified modular software framework

Abstract

Rapid process synthesis supported by a unified modular software frameworkAlthough known to be very powerful, the widespread application of model-based techniques is still significantly hampered in the area of bio-processes. Reasons for this situation can be found along the whole chain to set up and implement such approaches. In a time-consuming step, models are typically hand-crafted. Whether alternatives of better models exist to actually fulfill the final goals is undocumented, most often even unknown. In a next step, model-based process control methods are hand-coded in an error-prone procedure. For many of these methods given in the literature, only simulation studies are shown, leaving the interested reader with the unanswered question whether the implementation of a specific method in a real process is viable. As the potentially time-consuming implementation of such a method presents a risk for a rapid process development, promising candidates may be overlooked. To remediate this unsatisfactory situation, a combination of theoretical methods and information technology is proposed here. By an exemplarily realized software tool, it is shown how such an environment helps to promote model-based optimization, supervision, and control of bio-processes and allows for an inexpensive test of new ideas as well in real-life experiments. The contribution concentrates on an overview of a possible software architecture with respect to necessary methods and a meaningful information strategy, highlighting some of the more crucial building blocks. Experimental results exploiting parts of the proposed methods are given for a yeast strain synthesizing a product of industrial interest.

Model-Based Process Optimization for the Production of Macrolactin D by Paenibacillus polymyxa

“…The feeding rates of the fed-batch cultivations were realized by proportional-integral-controlled pump-scale systems and can be altered online via a custom-made process control system based on a central mySQL database [33]. A gas analyzer (BlueInOne Cell, BlueSens gas sensor GmbH, Germany) was used to determine the off-gas fraction of CO 2 .…”

“…After interpolation of all the measured quantities in a cultivation, their change over time is merged in a few distinctive phenomena that are then compared to assign probabilities to model components for example limiting behavior of a substrate. As a result, a family of process models with a descending probability can be created in the form of differential equations in MATLAB code, and their respective model parameters can be estimated using automated code generation [33].…”

Editorial: Bioprocess Development in the era of digitalization

“…Tailored software solutions for the integration of model‐based techniques are presented in the article by Wellenbeck et al. . One of the key elements of the efficient use of automation in biotechnology is the organised storage of all data in a database, as described in this issue by Schmidt et al.…”

“…With this strategy, the time frame for process development was reduced to 3 months [2]. Tailored software solutions for the integration of model-based techniques are presented in the article by Wellenbeck et al [3]. One of the key elements of the efficient use of automation in biotechnology is the organised storage of all data in a database, as described in this issue by Schmidt et al [4] in a way that these data are immediately accessible for e.g.…”