3D‐Printed Soft Lithography for Complex Compartmentalized Microfluidic Neural Devices. Issue 16 (15th June 2020)

• Record Type: Journal Article
• Authors: Kajtez, Janko; Buchmann, Sebastian; Vasudevan, Shashank; Birtele, Marcella; Rocchetti, Stefano; Pless, Christian Jonathan; Heiskanen, Arto; Barker, Roger A.; Martínez‐Serrano, Alberto; Parmar, Malin; Lind, Johan Ulrik; Emnéus, Jenny
• Is Part Of: Advanced science. Volume 7:Issue 16(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-15
• Subjects: 3D printing -- compartmentalized devices -- fast prototyping -- human neural stem cells -- neurite guidance -- nigrostriatal pathway -- soft lithography; Science -- Periodicals; 505
• DOI: 10.1002/advs.202001150
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Compartmentalized microfluidic platforms are an invaluable tool in neuroscience research. However, harnessing the full potential of this technology remains hindered by the lack of a simple fabrication approach for the creation of intricate device architectures with high‐aspect ratio features. Here, a hybrid additive manufacturing approach is presented for the fabrication of open‐well compartmentalized neural devices that provides larger freedom of device design, removes the need for manual postprocessing, and allows an increase in the biocompatibility of the system. Suitability of the method for multimaterial integration allows to tailor the device architecture for the long‐term maintenance of healthy human stem‐cell derived neurons and astrocytes, spanning at least 40 days. Leveraging fast‐prototyping capabilities at both micro and macroscale, a proof‐of‐principle human in vitro model of the nigrostriatal pathway is created. By presenting a route for novel materials and unique architectures in microfluidic systems, the method provides new possibilities in biological research beyond neuroscience applications. Abstract : In this study, a hybrid additive manufacturing approach to soft lithography is developed for the fabrication of open‐well compartmentalized microfluidic devices used to engineer human stem‐cell derived neural networks in vitro. The approach provides larger freedom of design, removes the need for manual postprocessing, increases the biocompatibility of the system, and enables fast prototyping at the micro and macroscale.