Image analyses for engineering advanced tissue biomanufacturing processes

被引:11
作者
Allenby, Mark C. [1 ,2 ]
Woodruff, Maria A. [2 ]
机构
[1] Univ Queensland, Sch Chem Engn, BioMimet Syst Engn BMSE Lab, Brisbane, Qld, Australia
[2] Queensland Univ Technol, Biofabricat & Tissue Morphol BTM Grp, Ctr Biomed Technol, Sch Med Mech & Proc Engn MMPE, Brisbane, Qld, Australia
基金
澳大利亚研究理事会;
关键词
Biomanufacturing; Bioreactors; Image analysis; Bioprocess engineering; Computational biology; HEMATOPOIETIC STEM-CELLS; PERFUSION-BIOREACTOR; NEOTISSUE GROWTH; MODEL; SCAFFOLDS; DESIGN; OPTIMIZATION; MICROSCOPY; DYNAMICS; BONE;
D O I
10.1016/j.biomaterials.2022.121514
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Industrial cell culture processes are inherently expensive, time-consuming, and variable. These limitations have become a critical bottleneck for the industrial translation of human cell and tissue biomanufacturing, as few human cell culture products deliver sufficient benefit, value, and consistency to offset their high manufacturing costs and produce useful clinical or biomedical solutions. Recent advances in biomedical image analysis and computational modelling can enhance the design and operation of high-efficiency tissue biomanufacturing platforms, as well as the high-content characterisation and monitoring of culture performance, to enable bioprocess control, optimisation, and automation. These computational technologies aim to maximize culture outcomes while minimizing variability and process development expense. In this review, we outline current resources and approaches which harness biomedical imaging and image-based computational models to design and operate efficient and robust human tissue biomanufacturing platforms.
引用
收藏
页数:15
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