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Using artificial neural networks to accelerate flowsheet optimization for downstream process development.

Daphne Keulen¹, Erik van der Hagen¹, Geoffroy Geldhof²

¹Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.

Biotechnology and Bioengineering

|May 31, 2023

Summary

This summary is machine-generated.

Artificial neural networks (ANNs) accelerate biopharmaceutical purification process design by reducing the number of purification options evaluated. This method significantly cuts overall optimization time by 50%, ensuring safety and economic benefits.

Keywords:

artificial neural networks chromatography downstream process development flowsheet optimization mechanistic modeling model‐based process optimization

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Area of Science:

Biopharmaceutical purification
Process optimization
Computational modeling

Background:

Optimal purification processes are crucial for biopharmaceutical safety and economics.
Screening the design space is necessary for global optimization.
Chromatographic mechanistic modeling (MM) can be time-consuming for flowsheet optimization.

Purpose of the Study:

To accelerate the early design of biopharmaceutical purification processes.
To reduce the computational time for flowsheet optimization.
To integrate artificial neural networks (ANNs) into global optimization strategies.

Main Methods:

Utilizing artificial neural networks (ANNs) for global optimization of purification flowsheets.
Reducing the number of candidate flowsheets for subsequent local optimization.
Comparing ANN-guided optimization with traditional mechanistic modeling (MM).

Main Results:

ANNs reduced the number of flowsheets for final optimization from 15 to 3.
Local optimization starting from ANN or MM global outcomes yielded similar results.
Overall flowsheet optimization time was decreased by 50% using ANNs.

Conclusions:

ANNs effectively accelerate early-stage purification process design.
The proposed approach is generic, flexible, and material-independent.
Integrating ANNs offers significant time savings in biopharmaceutical process development.