Big data and machine learning driven bioprocessing - Recent trends and critical analysis.

Journal: Bioresource technology
Published Date: Jan 13, 2023

Abstract

Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) was employed to explore the direction of the research domain. All the papers from 2013 to 2022 with specific keywords of bioprocessing using AI were extracted from Scopus and grouped into two five-year periods of 2013-to-2017 and 2018-to-2022, where the past and recent research directions were compared. Based on this procedure, selected sample papers from recent five years were subjected to further review and analysis. The result shows that 50% of the publications in the past five-year focused on topics related to hybrid models, ANN, biopharmaceutical manufacturing, and biorefinery. The summarization and analysis of the outcome indicated that implementing AI could improve the design and process engineering strategies in bioprocessing fields.

Authors

  • Chao-Tung Yang
    Department of Computer Science, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Taichung City 407224, Taiwan.
  • Endah Kristiani
    Department of Computer Science, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Taichung City 407224, Taiwan.
  • Yoong Kit Leong
    Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung 407224, Taiwan; Department of Chemical and Materials Engineering, Tunghai University, Taichung 407224, Taiwan.
  • Jo-Shu Chang
    Department of Chemical and Materials Engineering, Tunghai University, Taichung 407, Taiwan; Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung 407, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan 701, Taiwan.

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