Literature DB >> 31395552

Toward Portable Artificial Kidneys: The Role of Advanced Microfluidics and Membrane Technologies in Implantable Systems.

Bac Van Dang, Robert A Taylor, Alexander J Charlton, Pierre Le-Clech, Tracie Jacqueline Barber.   

Abstract

Globally, around 2.6 million people receive renal replacement therapy (RRT), and a further 4.9-9.7 million people need, but do not have access to, RRT [1]. The next generation RRT devices will certainly be in demand due to the increasing occurrence of diabetes, atherosclerosis and the growing population of older citizens. This review provides a comprehensive, yet concise overview of the cleared and remaining hurdles in the development of artificial kidneys to move beyond traditional dialysis technology-the current baseline of renal failure treatment. It compares and contrasts the state-of-the-art in 'cell-based' and 'non-cell-based' approaches. Based on this study, a new engineering perspective on the future of artificial kidneys is described. This review suggests that stem-cell-based artificial kidneys represent a long-term, complete solution but it can take years of development due to the limitations of current cell seeding technology, viability and complicated behaviour control. Alternatively, there is much potential for near- and medium- term solutions with the development of non-cell-based wearable and implantable devices to support current therapies. Based on recent fundamental advances in microfluidics, membranes and related research, it may be possible to integrate these technologies to enable implantable artificial kidneys (iAK) in the near future.

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Year:  2019        PMID: 31395552     DOI: 10.1109/RBME.2019.2933339

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  2 in total

Review 1.  Membranes for the life sciences and their future roles in medicine.

Authors:  Xiaoyue Yao; Yu Liu; Zhenyu Chu; Wanqin Jin
Journal:  Chin J Chem Eng       Date:  2022-06-15       Impact factor: 3.898

2.  Intelligent Diagnostic Prediction and Classification Models for Detection of Kidney Disease.

Authors:  Ramesh Chandra Poonia; Mukesh Kumar Gupta; Ibrahim Abunadi; Amani Abdulrahman Albraikan; Fahd N Al-Wesabi; Manar Ahmed Hamza; Tulasi B
Journal:  Healthcare (Basel)       Date:  2022-02-14
  2 in total

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