With regards to developing a platform for manufacture of chips, we have shown that 3D printed polymer tooling can be used to manufacture many identical devices in a pseudo-industrial process. The use of a 3D printed inlay permits masters to be produced without the expertise and time required for CNC milled tooling or those produced through traditional semiconductor methods. A critical part of the manufacturing process is creating sealed devices. Here, two methods have been explored: ultrasonic welding and lamination – both used industrially. The combination of using a 3D printed inlay and the described sealing methods has shortened the time required to produce a device to one working day, a feat that had not been realized previously. Examples of chip designs are shown in figure 1 with 1A showing the chips used for organoid experiments and 1B showing a typical fat-on-a-chip design.
The functionality of these first generation chips has also been achieved. For this work, Neil Convery (PhD student at University of Glasgow) spent 3 months at the Hybrid Technology Hub in Oslo to integrate the chips with organoids. During this visit, methods were developed to both load the organoids into the devices and maintain them for up to seven days in the chips. Viability test indicated that the organoids were successfully maintained in the chips. An image of this set up and results can be seen in figure 2A and 2B respectively. This work was then reproduced at the labs in Glasgow, highlighting the robustness of the methodology. During Neil’s visit at the Centre, a 3D printing facility was established to allow the Hub to design and prototype their own devices in polydimethylsiloxane (PDMS). Training on the equipment was also provided. The digital nature of 3D printing means that chips designed and prototyped in Norway can easily be shared electronically with the lab in Glasgow and, once a final design is decided upon, chips can be manufactured in bulk to facilitate further, impactful research.
Selected publications:
- Rostam, H. M., Reynolds, P. M., Alexander, M. R., Gadegaard, N. & Ghaemmaghami, A. M. Image based Machine Learning for identification of macrophage subsets. Scientific Reports 7, doi:10.1038/s41598-017-03780-z (2017).
- Jack, C. et al. Spatial control of chemical processes on nanostructures through nano-localized water heating. Nat. Commun. 7, 8, doi:10.1038/ncomms10946 (2016).
- McMurray, R. J. et al. Nanoscale surfaces for the long-term maintenance of mesenchymal stem cell phenotype and multipotency. Nature Materials 10, 637-644, doi:10.1038/nmat3058 (2011).
- Hendry, E. et al. Ultrasensitive detection and characterization of biomolecules using superchiral fields. Nature Nanotechnology 5, 783-787, doi:10.1038/nnano.2010.209 (2010).
- Dalby, M. J. et al. The control of human mesenchymal cell differentiation using nanoscale symmetry and disorder. Nature Materials 6, 997-1003, doi:10.1038/nmat2013 (2007).
Web profile:
https://www.gla.ac.uk/schools/engineering/staff/nikolajgadegaard/
