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Engineering brain-on-a-chip platforms

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From Nature Reviews Bioengineering

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Abstract

The increasing prevalence of neurological and psychiatric diseases, such as Alzheimer disease and schizophrenia, necessitates the development of new research tools to investigate these diseases and develop effective treatments. Thus, in vitro brain models, such as brain-on-a-chip devices, have been developed to mimic in vivo biochemical and mechanobiological interactions and to monitor their electrochemical activity. In this Review, we discuss the technologies to build complex brain models. We discuss progress in microfluidic and semiconductor-based technologies that facilitate in vitro modelling of the blood–brain barrier and neuronal circuits to study pathophysiological processes. We further discuss advances in 3D tissue engineering, electrode strategies and materials that, when combined, could allow simulation of the native complexity of brain regions and the interrogation of their activity at cellular length scales. Furthermore, we explore the engineering challenges and opportunities for complex physiologically relevant brain-on-a-chip devices and their future progress.

Key points

  • Brain-on-a-chip devices allow culturing and monitoring of highly complex models of the blood–brain barrier and brain parenchyma.

  • A wide range of approaches for in vitro brain modelling, such as bioprinting and microfluidics, have been commercialized.

  • Careful consideration is required to tailor the complexity of the brain model according to the specific research question.

  • As many technologies are developed independently, challenges remain to ensure that workflows are compatible with each other to unblock the full potential of brain-on-a-chip devices.

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Fig. 1: Methods for probing neural activity across different scales in brain physiology.
Fig. 2: BBB and neuronal in vitro models.
Fig. 3: A technological roadmap towards increasingly integrated brain-on-a-chip device components and assemblies.

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Acknowledgements

D.C. is the recipient of funding from the National Health and Medical Research Council (Ideas, APP2003446). N.M. is supported by an Australian Government Research Training Program (AGRTP) Scholarship. D.R.N. is supported by an Australian Research Council Future Fellowship (FT230100220) and a discovery project (DP220102549). V.G. acknowledges funding from the Australian Research Council and the Yulgilbar foundation.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, Victoria, Australia

    Bram Servais, Negar Mahmoudi, Vini Gautam, Michael R. Ibbotson, David R. Nisbet & David Collins

  2. The Graeme Clark Institute, The University of Melbourne, Melbourne, Victoria, Australia

    Bram Servais, Negar Mahmoudi, David R. Nisbet & David Collins

  3. Centre for Nanoscience and Engineering, Indian Institute of Science, Bangalore, India

    Vini Gautam

  4. School of Physics, The University of Melbourne, Parkville, Victoria, Australia

    Wei Tong

  5. Melbourne Medical School, Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Melbourne, Victoria, Australia

    David R. Nisbet

  6. BioFab3D, Aikenhead Centre for Medical Discovery, St Vincent’s Hospital Melbourne, Fitzroy, Victoria, Australia

    David R. Nisbet

  7. Laboratory of Advanced Biomaterials, John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia

    David R. Nisbet

  8. ANU College of Engineering & Computer Science, Canberra, Australian Capital Territory, Australia

    David R. Nisbet

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  1. Bram Servais
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Contributions

B.S. researched the first outline of the review and wrote the sections on microfluidic models and biosensor integration. B.S., V.G, W.T. and M.R.I. co-wrote the section on electrophysiological read-out. B.S. and N.M. co-wrote the section on 3D tissue construction and material diversification. D.R.N. and D.C. supervised the work. All authors contributed to final edits to the manuscript.

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Correspondence to David R. Nisbet or David Collins.

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Servais, B., Mahmoudi, N., Gautam, V. et al. Engineering brain-on-a-chip platforms. Nat Rev Bioeng 2, 691–709 (2024). https://doi.org/10.1038/s44222-024-00184-3

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