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Designing lab-on-a-chip systems with attribute dependency graphs

Published online by Cambridge University Press:  16 May 2024

Johannes Soika ,
Tobias Wanninger ,
Patrick Muschak ,
Sebastian Schwaminger ,
Sonja Berensmeier  and
Markus Zimmermann
Johannes Soika*
Affiliation:
Laboratory for Product Development and Lightweight Design, TUM School of Engineering and Design, Technical University of Munich, Germany
Tobias Wanninger
Affiliation:
Laboratory for Product Development and Lightweight Design, TUM School of Engineering and Design, Technical University of Munich, Germany
Patrick Muschak
Affiliation:
Chair of Bioseparation Engineering, TUM School of Engineering and Design, Technical University of Munich, Germany
Sebastian Schwaminger
Affiliation:
Chair of Bioseparation Engineering, TUM School of Engineering and Design, Technical University of Munich, Germany Division of Medicinal Chemistry, Otto Loewi Research Center, Medical University of Graz, Austria
Sonja Berensmeier
Affiliation:
Chair of Bioseparation Engineering, TUM School of Engineering and Design, Technical University of Munich, Germany Munich Institute for Integrated Materials, Energy and Process Engineering, Technical University of Munich, Germany
Markus Zimmermann
Affiliation:
Laboratory for Product Development and Lightweight Design, TUM School of Engineering and Design, Technical University of Munich, Germany
*
johannes.soika@tum.de

Abstract

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Lab-on-a-Chip (LOC) products for point-of-care diagnostics have gained significant attention. However, there is a lack of systematic approaches for LOC product development. To address this, we introduce an Attribute Dependency Graph exemplary for a magnetophoretic LOC system for pathogen detection. This model organizes dependencies between the design variables and crucial quantities of interest, such as detectability, cost per test, and test duration. The obtained model helps to manage design complexity and can be adapted to other LOC approaches.

Keywords

dependency modellingmethodical designproduct developmentcomplex systemslab-on-a-chip
Type
Design Methods and Tools
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 785 - 794
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

References

Armbruster, D.A. and Pry, T. (2008), “Limit of blank, limit of detection and limit of quantitation”, The Clinical Biochemist Reviews, 29 Suppl 1 No. Suppl 1, S49-52.Google ScholarPubMed
Bruus, H. (2008), Theoretical microfluidics, Oxford master series in physics Condensed matter physics, Vol. 18, Oxford Univ. Press, Oxford. https://doi.org/10.1093/oso/9780199235087.001.0001Google Scholar
Cha, H., Fallahi, H., Dai, Y., Yuan, D., An, H., Nguyen, N.-T. and Zhang, J. (2022), “Multiphysics microfluidics for cell manipulation and separation: a review”, Lab on a chip, Vol. 22 No. 3, pp. 423–444. https://doi.org/10.1039/d1lc00869bCrossRefGoogle ScholarPubMed
Chin, C.D., Linder, V. and Sia, S.K. (2012), “Commercialization of microfluidic point-of-care diagnostic devices”, Lab on a chip, Vol. 12 No. 12, pp. 2118–2134. https://doi.org/10.1039/c2lc21204hGoogle ScholarPubMed
Chong, P.H. et al. . (2021), “Continuous Flow Low Gradient Magnetophoresis of Magnetic Nanoparticles: Separation Kinetic Modelling and Simulation”, Journal of Superconductivity and Novel Magnetism, Vol. 34 No. 8, pp. 2151–2165. https://doi.org/10.1007/s10948-021-05893-zCrossRefGoogle Scholar
Diestel, R. (2017), Graph theory, Graduate texts in mathematics, Vol. 173, Fifth edition, Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53622-3Google Scholar
Ducrée, J. (2019), “Efficient Development of Integrated Lab-On-A-Chip Systems Featuring Operational Robustness and Manufacturability”, Micromachines, Vol. 10 No. 12. https://doi.org/10.3390/mi10120886CrossRefGoogle ScholarPubMed
Eiselt, T., Zickner, H., Schuldt, J., Gröger, S. and Weidlich, D. (2013), “Interdisciplinary Product Development - Virtual Reality Application in FMEA”, Industrial and Systems Engineering Review, Vol. 1 No. 1, pp. 59–67. https://doi.org/10.37266/ISER.2013v1i1.pp59-67CrossRefGoogle Scholar
Heintz, S., Mitic, A., Ringborg, R.H., Krühne, U., Woodley, J.M. and Gernaey, K.V. (2016), “A microfluidic toolbox for the development of in-situ product removal strategies in biocatalysis”, Journal of Flow Chemistry, Vol. 6 No. 1, pp. 18–26. https://doi.org/10.1556/1846.2015.00040CrossRefGoogle Scholar
Lim, Y.C., Kouzani, A.Z. and Duan, W. (2010), “Lab-on-a-chip: a component view”, Microsystem Technologies, Vol. 16 No. 12, pp. 1995–2015. https://doi.org/10.1007/s00542-010-1141-6CrossRefGoogle Scholar
Lindemann, U. (2009), Methodische Entwicklung technischer Produkte: Methoden flexibel und situationsgerecht anwenden, VDI-Buch, 3., korrigierte Aufl., Springer, Heidelberg. https://doi.org/10.1007/978-3-642-01423-9CrossRefGoogle Scholar
Munaz, A., Shiddiky, M.J.A. and Nguyen, N.-T. (2018), “Recent advances and current challenges in magnetophoresis based micro magnetofluidics”, Biomicrofluidics, Vol. 12 No. 3, p. 31501. https://doi.org/10.1063/1.5035388CrossRefGoogle Scholar
Pálovics, P. and Rencz, M. (2022), “Investigation of the motion of magnetic nanoparticles in microfluidics with a micro domain model”, Microsystem Technologies, Vol. 28 No. 6, pp. 1545–1559. https://doi.org/10.1007/s00542-020-05077-0CrossRefGoogle Scholar
Reiter, N., Auchter, J., Weber, M., Berensmeier, S. and Schwaminger, S.P. (2022), “Magnetophoretic Cell Sorting: Comparison of Different 3D-Printed Millifluidic Devices”, Magnetochemistry, Vol. 8 No. 10, p. 113. https://doi.org/10.3390/magnetochemistry8100113CrossRefGoogle Scholar
Reyes, D.R., van Heeren, H., Guha, S., Herbertson, L., Tzannis, A.P., Ducrée, J., Bissig, H. and Becker, H. (2021), “Accelerating innovation and commercialization through standardization of microfluidic-based medical devices”, Lab on a chip, Vol. 21 No. 1, pp. 9–21. https://doi.org/10.1039/d0lc00963fCrossRefGoogle ScholarPubMed
Rötzer, S., Schweigert-Recksiek, S., Thoma, D. and Zimmermann, M. (2022), “Attribute dependency graphs: modelling cause and effect in systems design”, Design Science, Vol. 8. https://doi.org/10.1017/dsj.2022.20CrossRefGoogle Scholar
Sajeesh, P. and Sen, A.K. (2014), “Particle separation and sorting in microfluidic devices: a review”, Microfluidics and Nanofluidics, Vol. 17 No. 1, pp. 1–52. https://doi.org/10.1007/s10404-013-1291-9CrossRefGoogle Scholar
Zimmermann, M. and Hoessle, J.E. von (2013), “Computing solution spaces for robust design”, International Journal for Numerical Methods in Engineering,Vol. 94 No. 3, pp. 290–307. https://doi.org/10.1002/nme.4450CrossRefGoogle Scholar