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Related Experiment Video

Updated: Dec 16, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Rapid process synthesis supported by a unified modular software framework.

Sebastian Herold¹, Dominik Krämer¹, Norman Violet²

¹Chair of Measurement and Control Technische Universität Berlin Berlin Germany.

Engineering in Life Sciences

|July 7, 2020

Summary

Model-based techniques for bioprocesses are difficult to implement. A new software tool integrates theoretical methods and IT to simplify model-based optimization, supervision, and control, enabling easier real-world testing.

Keywords:

Modeling Modeling software Process design State estimation Trajectory planning

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Area of Science:

Biotechnology
Process Engineering
Computational Biology

Background:

Widespread application of model-based techniques in bioprocesses is limited due to challenges in model creation and implementation of control methods.
Manual model crafting and error-prone coding of control strategies hinder efficient bioprocess development and optimization.
Lack of documented alternatives and viability studies for real-world implementation often leads to promising model-based approaches being overlooked.

Purpose of the Study:

To address the limitations in applying model-based techniques to bioprocesses.
To propose an integrated approach combining theoretical methods and information technology.
To demonstrate a software tool that facilitates model-based optimization, supervision, and control of bioprocesses.

Main Methods:

Development of a software architecture integrating theoretical methods and information technology for bioprocess modeling and control.
Implementation of an information strategy for managing bioprocess data and models.
Utilizing an exemplary software tool for testing and validating model-based approaches.

Main Results:

The developed software tool successfully promotes model-based optimization, supervision, and control of bioprocesses.
The environment allows for cost-effective testing of new ideas in real-life experiments.
Experimental results with a yeast strain demonstrated the efficacy of the proposed methods in synthesizing an industrially relevant product.

Conclusions:

The proposed combination of theoretical methods and IT, exemplified by the software tool, significantly enhances the application of model-based techniques in bioprocesses.
The approach facilitates rapid process development by enabling inexpensive testing and validation of model-based strategies.
This work provides a foundation for improved model-based optimization, supervision, and control in industrial biotechnology.