Microbial Technologies Enhanced by Artificial Intelligence for Healthcare Applications.

Journal: Microbial biotechnology
PMID:

Abstract

The combination of artificial intelligence (AI) with microbial technology marks the start of a major transformation, improving applications throughout biotechnology, especially in healthcare. With the capability of AI to process vast amounts of biological big data, advanced microbial technology allows for a comprehensive understanding of complex biological systems, advancing disease diagnosis, treatment and the development of microbial therapeutics. This mini review explores the impact of AI-integrated microbial technologies in healthcare, highlighting advancements in microbial biomarker-based diagnosis, the development of microbial therapeutics and the microbial production of therapeutic compounds. This exploration promises significant improvements in the design and implementation of health-related solutions, steering a new era in biotechnological applications.

Authors

  • Taeho Yu
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon, 34141, Republic of Korea.
  • Minjee Chae
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Ziling Wang
    School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China.
  • Gahyeon Ryu
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon, 34141, Republic of Korea.
  • Gi Bae Kim
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 four), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea; Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
  • Sang Yup Lee
    Department of Chemical and Biomolecular Engineering (BK21 Plus Program), KAIST, Daejeon 34141, Republic of Korea.