Bayesian Optimization in Bioprocess Engineering—Where Do We Stand Today?

IF 3.5 2区生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Biotechnology and Bioengineering Pub Date : 2025-03-05 DOI:10.1002/bit.28960

Florian Gisperg, Robert Klausser, Mohamed Elshazly, Julian Kopp, Eva Přáda Brichtová, Oliver Spadiut

引用次数: 0

Abstract

Bayesian optimization is a stochastic, global black-box optimization algorithm. By combining Machine Learning with decision-making, the algorithm can optimally utilize information gained during experimentation to plan further experiments—while balancing exploration and exploitation. Although Design of Experiments has traditionally been the preferred method for optimizing bioprocesses, AI-driven tools have recently drawn increasing attention to Bayesian optimization within bioprocess engineering. This review presents the principles and methodologies of Bayesian optimization and focuses on its application to various stages of bioprocess engineering in upstream and downstream processing.

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来源期刊

Biotechnology and Bioengineering 工程技术-生物工程与应用微生物

CiteScore

7.90

自引率

5.30%

发文量

280

审稿时长

2.1 months

期刊介绍： Biotechnology & Bioengineering publishes Perspectives, Articles, Reviews, Mini-Reviews, and Communications to the Editor that embrace all aspects of biotechnology. These include: -Enzyme systems and their applications, including enzyme reactors, purification, and applied aspects of protein engineering -Animal-cell biotechnology, including media development -Applied aspects of cellular physiology, metabolism, and energetics -Biocatalysis and applied enzymology, including enzyme reactors, protein engineering, and nanobiotechnology -Biothermodynamics -Biofuels, including biomass and renewable resource engineering -Biomaterials, including delivery systems and materials for tissue engineering -Bioprocess engineering, including kinetics and modeling of biological systems, transport phenomena in bioreactors, bioreactor design, monitoring, and control -Biosensors and instrumentation -Computational and systems biology, including bioinformatics and genomic/proteomic studies -Environmental biotechnology, including biofilms, algal systems, and bioremediation -Metabolic and cellular engineering -Plant-cell biotechnology -Spectroscopic and other analytical techniques for biotechnological applications -Synthetic biology -Tissue engineering, stem-cell bioengineering, regenerative medicine, gene therapy and delivery systems The editors will consider papers for publication based on novelty, their immediate or future impact on biotechnological processes, and their contribution to the advancement of biochemical engineering science. Submission of papers dealing with routine aspects of bioprocessing, description of established equipment, and routine applications of established methodologies (e.g., control strategies, modeling, experimental methods) is discouraged. Theoretical papers will be judged based on the novelty of the approach and their potential impact, or on their novel capability to predict and elucidate experimental observations.