AccScience Publishing / IJAMD / Volume 1 / Issue 1 / DOI: 10.36922/ijamd.2279
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REVIEW

Application of machine learning in 3D bioprinting of cultivated meat

Wei Long Ng1* ,  Jian Song Tan1
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1 Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Republic of Singapore
IJAMD 2024, 1(1), 3–25; https://doi.org/10.36922/ijamd.2279
Submitted: 20 November 2023 | Accepted: 19 December 2023 | Published: 23 January 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Cultivated meat production, an innovative and sustainable alternative to conventional animal farming, has gained significant attention in recent years. As the demand for ethical and environmentally friendly protein sources continues to rise, the need for efficient and scalable production strategies becomes critical. Notably, the integration of advanced technology, such as machine learning (ML), can enhance the efficiency of the cultivated meat production process. The goal of this review paper is to highlight the advantages and limitations of various ML approaches and provide a balanced discussion on the integration of ML techniques for three-dimensional (3D)-bioprinted cultivated meat. This review paper explores the application of ML techniques in various facets of 3D-bioprinted cultivated meat and highlights the potential for ML to optimize various aspects of the process, from predicting printability and optimizing printing parameters to characterizing meat flavor and monitoring meat quality. ML plays a pivotal role in optimizing the material formulation to improve ink printability and identifying an optimal combination of printing parameters to achieve high printing resolution and accuracy. Furthermore, ML can aid in modeling sensory attributes, ensuring that the cultivated meat replicates the desired meat flavor. Finally, ML can be applied for meat quality control as it facilitates the automated detection of harmful pathogens, ensuring the safety and consistency of 3D-bioprinted cultivated meat.

Keywords
Cultivated meat
Machine learning
3D bioprinting
Biofabrication
Meat flavor
Quality control
Funding
NTU Presidential Postdoctoral Fellowship
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Conflict of interest
The authors declare that they have no competing interests.
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