Generic placeholder image

Current Pharmaceutical Design


ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

Review Article

Brain-on-a-chip Devices for Drug Screening and Disease Modeling Applications

Author(s): Beatrice Miccoli, Dries Braeken* and Yi-Chen Ethan Li*

Volume 24, Issue 45, 2018

Page: [5419 - 5436] Pages: 18

DOI: 10.2174/1381612825666190220161254

Price: $65


Neurodegenerative disorders are related to the progressive functional loss of the brain, often connected to emotional and physical disability and, ultimately, to death. These disorders, strongly connected to the aging process, are becoming increasingly more relevant due to the increase of life expectancy. Current pharmaceutical treatments poorly tackle these diseases, mainly acting only on their symptomology. One of the main reasons of this is the current drug development process, which is not only expensive and time-consuming but, also, still strongly relies on animal models at the preclinical stage.

Organ-on-a-chip platforms have the potential to strongly impact and improve the drug screening process by recreating in vitro the functionality of human organs. Patient-derived neurons from different regions of the brain can be directly grown and differentiated on a brain-on-a-chip device where the disease development, progression and pharmacological treatments can be studied and monitored in real time. The model reliability is strongly improved by using human-derived cells, more relevant than animal models for pharmacological screening and disease monitoring. The selected cells will be then capable of proliferating and organizing themselves in the in vivo environment thanks to the device architecture, materials selection and bio-chemical functionalization.

In this review, we start by presenting the fundamental strategies adopted for brain-on-a-chip devices fabrication including e.g., photolithography, micromachining and 3D printing technology. Then, we discuss the state-of-theart of brain-on-a-chip platforms including their role in the study of the functional architecture of the brain e.g., blood-brain barrier, or of the most diffuse neurodegenerative diseases like Alzheimer’s and Parkinson’s. At last, the current limitations and future perspectives of this approach for the development of new drugs and neurodegenerative diseases modeling will be discussed.

Keywords: Brain-on-a-chip, drug screening, 3D brain model, brain cancer, blood-brain barrier, neurodegenerative disorders.

Nations U. Nations U. World Population Prospects. The 2017 Revision. In: ed.^eds. 2017.
Parasuraman S. Toxicological screening. J Pharmacol Pharmacother 2011; 2(2): 74-9.
Varga OE, Hansen AK, Sandøe P, Olsson IA. Validating animal models for preclinical research: A scientific and ethical discussion. Altern Lab Anim 2010; 38(3): 245-8.
Van Dam D, De Deyn PP. Drug discovery in dementia: the role of rodent models. Nat Rev Drug Discov 2006; 5(11): 956-70.
van der Staay FJ. Animal models of behavioral dysfunctions: basic concepts and classifications, and an evaluation strategy. Brain Res Brain Res Rev 2006; 52(1): 131-59.
Esch EW, Bahinski A, Huh D. Organs-on-chips at the frontiers of drug discovery. Nat Rev Drug Discov 2015; 14(4): 248-60.
Volpatti LR, Yetisen AK. Commercialization of microfluidic devices. Trends Biotechnol 2014; 32(7): 347-50.
Pelvig DP, Pakkenberg H, Stark AK, Pakkenberg B. Neocortical glial cell numbers in human brains. Neurobiol Aging 2008; 29(11): 1754-62.
Pelham RJ Jr, Wang Yl. Cell locomotion and focal adhesions are regulated by substrate flexibility. Proc Natl Acad Sci USA 1997; 94(25): 13661-5.
Georges PC, Miller WJ, Meaney DF, Sawyer ES, Janmey PA. Matrices with compliance comparable to that of brain tissue select neuronal over glial growth in mixed cortical cultures. Biophys J 2006; 90(8): 3012-8.
Liddle JA, Gallatin GM. Lithography, metrology and nanomanufacturing. Nanoscale 2011; 3(7): 2679-88.
Okazaki S. High resolution optical lithography or high throughput electron beam lithography: The technical struggle from the micro to the nano-fabrication evolution. Microelectron Eng 2015; 133: 23-35.
Okazaki S. High resolution optical lithography or high throughput electron beam lithography: The technical struggle from the micro to the nano-fabrication evolution. Microelectron Eng 2015; 133: 23-35.
Xie S, Schurink B, Berenschot EJW, Tiggelaar RM, Gardeniers HJGE, Luttge R. Displacement Talbot lithography nanopatterned microsieve array for directional neuronal network formation in brain-on-chip Journal of Vacuum Science & Technology B, Nanotechnology and Microelectronics: Materials 2016; 34.
Tseng AA, Chen K, Chen CD, Ma KJ. Electron beam lithography in nanoscale fabrication: recent development. IEEE Trans Electron Packag Manuf 2003; 26: 141-9.
Salaita K, Wang Y, Mirkin CA. Applications of dip-pen nanolithography. Nat Nanotechnol 2007; 2(3): 145-55.
Curran JM, Stokes R, Irvine E, et al. Introducing dip pen nanolithography as a tool for controlling stem cell behaviour: unlocking the potential of the next generation of smart materials in regenerative medicine. Lab Chip 2010; 10(13): 1662-70.
Qin D, Xia Y, Whitesides GM. Soft lithography for micro- and nanoscale patterning. Nat Protoc 2010; 5(3): 491-502.
Recknor JB, Sakaguchi DS, Mallapragada SK. Directed growth and selective differentiation of neural progenitor cells on micropatterned polymer substrates. Biomaterials 2006; 27(22): 4098-108.
Bhatia SN, Ingber DE. Microfluidic organs-on-chips. Nat Biotechnol 2014; 32(8): 760-72.
Pennathur S, Meinhart CD, Soh HT. How to exploit the features of microfluidics technology. Lab Chip 2008; 8(1): 20-2.
Shields CW IV, Reyes CD, López GP. Microfluidic cell sorting: A review of the advances in the separation of cells from debulking to rare cell isolation. Lab Chip 2015; 15(5): 1230-49.
Kimura H, Sakai Y, Fujii T. Organ/body-on-a-chip based on microfluidic technology for drug discovery. Drug Metab Pharmacokinet 2018; 33(1): 43-8.
Chen X, Shen J. Review of membranes in microfluidics. J Chem Technol Biotechnol 2017; 92: 271-82.
Booth R, Kim H. Characterization of a microfluidic in vitro model of the blood-brain barrier (μBBB). Lab Chip 2012; 12(10): 1784-92.
Xiao RR, Zeng WJ, Li YT, et al. Simultaneous generation of gradients with gradually changed slope in a microfluidic device for quantifying axon response. Anal Chem 2013; 85(16): 7842-50.
Achyuta AKH, Conway AJ, Crouse RB, et al. A modular approach to create a neurovascular unit-on-a-chip. Lab Chip 2013; 13(4): 542-53.
Bassoli E, Gatto A, Iuliano L, Violante MG. 3D printing technique applied to rapid casting. Rapid Prototyping J 2007; 13: 148-55.
Koechlin M, Poberaj G, Günter P. High-resolution laser lithography system based on two-dimensional acousto-optic deflection. Rev Sci Instrum 2009; 80(8): 085105.
Lantada AD, Romero AD, Schwentenwein M, Jellinek C, Homa J, Garcia-Ruiz JP. Monolithic 3D labs- and organs-on-chips obtained by lithography-based ceramic manufacture. Int J Adv Manuf Technol 2017; 93: 3371-81.
Tseng HY, Yin S, Subramanian V. Optimization of Inkjet-Based Process Modules for Printed Transistor Circuits Nip 25: Digital Fabrication 2009 2009; 603-6.
Adamski K, Kubicki W, Walczak R. 3D Printed electrophoretic lab-on-chip for DNA separation. Proceedings of the 30th Anniversary Eurosensors Conference - Eurosensors 2016, 2016; 168: 1454- 1457.
Kopplmayr T, Muhlberger M. Inkjet printing of polylactic acid on substrates prepared by fused deposition modeling and its potential for selective surface finishing. J Appl Polym Sci 2016; 133.
de Gans BJ, Schubert US. Inkjet printing of well-defined polymer dots and arrays. Langmuir 2004; 20(18): 7789-93.
Mujawar LH, van Amerongen A, Norde W. Influence of Pluronic F127 on the distribution and functionality of inkjet-printed biomolecules in porous nitrocellulose substrates. Talanta 2015; 131: 541-7.
Muth JT, Vogt DM, Truby RL, et al. Embedded 3D printing of strain sensors within highly stretchable elastomers. Adv Mater 2014; 26(36): 6307-12.
Wu W, DeConinck A, Lewis JA. Omnidirectional printing of 3D microvascular networks. Adv Mater 2011; 23(24): H178-83.
Kolesky DB, Homan KA, Skylar-Scott MA, Lewis JA. Three-dimensional bioprinting of thick vascularized tissues. Proc Natl Acad Sci USA 2016; 113(12): 3179-84.
Homan KA, Kolesky DB, Skylar-Scott MA, et al. Bioprinting of 3D Convoluted Renal Proximal Tubules on Perfusable Chips. Sci Rep 2016; 6: 34845.
Lee H, Cho DW. One-step fabrication of an organ-on-a-chip with spatial heterogeneity using a 3D bioprinting technology. Lab Chip 2016; 16(14): 2618-25.
Sohet F, Lin C, Munji RN, et al. LSR/angulin-1 is a tricellular tight junction protein involved in blood-brain barrier formation. J Cell Biol 2015; 208(6): 703-11.
Banerjee S, Bhat MA. Neuron-glial interactions in blood-brain barrier formation. Annu Rev Neurosci 2007; 30: 235-58.
Bernacki J, Dobrowolska A, Nierwińska K, Małecki A. Physiology and pharmacological role of the blood-brain barrier. Pharmacol Rep 2008; 60(5): 600-22.
Patabendige A, Skinner RA, Abbott NJ. Establishment of a simplified in vitro porcine blood-brain barrier model with high transendothelial electrical resistance. Brain Res 2013; 1521: 1-15.
Hatherell K, Couraud PO, Romero IA, Weksler B, Pilkington GJ. Development of a three-dimensional, all-human in vitro model of the blood-brain barrier using mono-, co-, and tri-cultivation Transwell models. J Neurosci Methods 2011; 199(2): 223-9.
van der Meer AD, Poot AA, Feijen J, Vermes I. Analyzing shear stress-induced alignment of actin filaments in endothelial cells with a microfluidic assay. Biomicrofluidics 2010; 4(1): 11103.
Cucullo L, Hossain M, Puvenna V, Marchi N, Janigro D. The role of shear stress in Blood-Brain Barrier endothelial physiology. BMC Neurosci 2011; 12: 40.
Galbraith CG, Skalak R, Chien S. Shear stress induces spatial reorganization of the endothelial cell cytoskeleton. Cell Motil Cytoskeleton 1998; 40(4): 317-30.
Griep LM, Wolbers F, de Wagenaar B, et al. BBB on chip: microfluidic platform to mechanically and biochemically modulate blood-brain barrier function. Biomed Microdevices 2013; 15(1): 145-50.
Brown JA, Pensabene V, Markov DA, et al. Recreating blood-brain barrier physiology and structure on chip: A novel neurovascular microfluidic bioreactor. Biomicrofluidics 2015; 9(5): 054124.
Alcendor DJ, Block FE III, Cliffel DE, et al. Neurovascular unit on a chip: implications for translational applications. Stem Cell Res Ther 2013; 4(Suppl. 1): S18.
de Robles P, Fiest KM, Frolkis AD, et al. The worldwide incidence and prevalence of primary brain tumors: A systematic review and meta-analysis. Neuro-oncol 2015; 17(6): 776-83.
Alieva M, van Rheenen J, Broekman MLD. Potential impact of invasive surgical procedures on primary tumor growth and metastasis. Clin Exp Metastasis 2018; 35(4): 319-31.
Tagliabue E, Agresti R, Carcangiu ML, et al. Role of HER2 in wound-induced breast carcinoma proliferation. Lancet 2003; 362(9383): 527-33.
Du X, Li W, Du G, et al. Droplet Array-Based 3D Coculture System for High-Throughput Tumor Angiogenesis Assay. Anal Chem 2018; 90(5): 3253-61.
Kim S, Lee H, Chung M, Jeon NL. Engineering of functional, perfusable 3D microvascular networks on a chip. Lab Chip 2013; 13(8): 1489-500.
Torisawa YS, Mosadegh B, Bersano-Begey T, et al. Microfluidic platform for chemotaxis in gradients formed by CXCL12 source-sink cells. Integr Biol 2010; 2(11-12): 680-6.
Ayuso JM, Monge R, Martínez-González A, et al. Glioblastoma on a microfluidic chip: Generating pseudopalisades and enhancing aggressiveness through blood vessel obstruction events. Neuro-oncol 2017; 19(4): 503-13.
Zhang Q, Liu T, Qin J. A microfluidic-based device for study of transendothelial invasion of tumor aggregates in realtime. Lab Chip 2012; 12(16): 2837-42.
Lee DW, Lee SY, Doh I, Ryu GH, Nam DH. High-Dose Compound Heat Map for 3D-Cultured Glioblastoma Multiforme Cells in a Micropillar and Microwell Chip Platform. BioMed Res Int 2017; 2017: 7218707.
Fan Y, Nguyen DT, Akay Y, Xu F, Akay M. Engineering a Brain Cancer Chip for High-throughput Drug Screening. Sci Rep 2016; 6: 25062.
Fan Y, Nguyen DT, Akay Y, Xu F, Akay M. Engineering a Brain Cancer Chip for High-throughput Drug Screening. Sci Rep 2016; 6: 25062.
Park J, Lee BK, Jeong GS, Hyun JK, Lee CJ, Lee SH. Three-dimensional brain-on-a-chip with an interstitial level of flow and its application as an in vitro model of Alzheimer’s disease. Lab Chip 2015; 15(1): 141-50.
Ren Y, Kunze A, Renaud P. Microfluidic and Compartmentalized Platforms for Neurobiological Research 2015.
Osaki T, Shin Y, Sivathanu V, Campisi M, Kamm RD. In Vitro Microfluidic Models for Neurodegenerative Disorders. 2018; p. 7.
Fernandes JT, Chutna O, Chu V, Conde JP, Outeiro TF. A Novel Microfluidic Cell Co-culture Platform for the Study of the Molecular Mechanisms of Parkinson’s Disease and Other Synucleinopathies. Front Neurosci 2016; 10: 511.
Seidi A, Kaji H, Annabi N, Ostrovidov S, Ramalingam M, Khademhosseini A. A microfluidic-based neurotoxin concentration gradient for the generation of an in vitro model of Parkinson’s disease. Biomicrofluidics 2011; 5(2): 22214.
Freundt EC, Maynard N, Clancy EK, et al. Neuron-to-neuron transmission of α-synuclein fibrils through axonal transport. Ann Neurol 2012; 72(4): 517-24.
Rosas-Hernandez H, Cuevas E, Lantz SM, et al. Neurovascular unit components on a chip as a model to study traumatic brain injury. Toxicol Lett 2016; 259: S86-6.
Prins M, Greco T, Alexander D, Giza CC. The pathophysiology of traumatic brain injury at a glance. Dis Model Mech 2013; 6(6): 1307-15.
Namjoshi DR, Good C, Cheng WH, et al. Towards clinical management of traumatic brain injury: A review of models and mechanisms from a biomechanical perspective. Dis Model Mech 2013; 6(6): 1325-38.
Dollé JP, Morrison B III, Schloss RS, Yarmush ML. Brain-on-a-chip microsystem for investigating traumatic brain injury: Axon diameter and mitochondrial membrane changes play a significant role in axonal response to strain injuries. Technology (SingapWorld Sci) 2014; 2(2): 106. [Singap World Sci].
Stein RA, Strickland TL. A review of the neuropsychological effects of commonly used prescription medications. Arch Clin Neuropsychol 1998; 13(3): 259-84.
Zhan L, Liang L, Shu Q, Yang S, Zhang Y. Distinct proteins in cortex of rats with closed traumatic brain injury detected by a WCX-2 protein chip. Neural Regen Res 2007; 2: 339-43.
Dauth S, Maoz BM, Sheehy SP, et al. Neurons derived from different brain regions are inherently different in vitro: A novel multiregional brain-on-a-chip. J Neurophysiol 2017; 117(3): 1320-41.
Bazarian JJ, Zhong J, Blyth B, Zhu T, Kavcic V, Peterson D. Diffusion tensor imaging detects clinically important axonal damage after mild traumatic brain injury: A pilot study. J Neurotrauma 2007; 24(9): 1447-59.
Tang-Schomer MD, White JD, Tien LW, et al. Bioengineered functional brain-like cortical tissue. Proc Natl Acad Sci USA 2014; 111(38): 13811-6.
Faden AI, Demediuk P, Panter SS, Vink R. The role of excitatory amino acids and NMDA receptors in traumatic brain injury. Science 1989; 244(4906): 798-800.
Katayama Y, Becker DP, Tamura T, Hovda DA. Massive increases in extracellular potassium and the indiscriminate release of glutamate following concussive brain injury. J Neurosurg 1990; 73(6): 889-900.
Hinzman JM, Thomas TC, Burmeister JJ, et al. Diffuse brain injury elevates tonic glutamate levels and potassium-evoked glutamate release in discrete brain regions at two days post-injury: An enzyme-based microelectrode array study. J Neurotrauma 2010; 27(5): 889-99.
Menorca RM, Fussell TS, Elfar JC. Nerve physiology: mechanisms of injury and recovery. Hand Clin 2013; 29(3): 317-30.
Sunderland S. A classification of peripheral nerve injuries producing loss of function. Brain 1951; 74(4): 491-516.
Ko PY, Yang CC, Kuo YL, et al. Schwann-Cell Autophagy, Functional Recovery, and Scar Reduction After Peripheral Nerve Repair. J Mol Neurosci 2018; 64(4): 601-10.
Martin M, Benzina O, Szabo V, et al. Morphology and nanomechanics of sensory neurons growth cones following peripheral nerve injury. PLoS One 2013; 8(2): e56286.
Patel NP, Lyon KA, Huang JH. An update-tissue engineered nerve grafts for the repair of peripheral nerve injuries. Neural Regen Res 2018; 13(5): 764-74.
Schmidt CE, Leach JB. Neural tissue engineering: strategies for repair and regeneration. Annu Rev Biomed Eng 2003; 5: 293-347.
Bellamkonda RV. Peripheral nerve regeneration: An opinion on channels, scaffolds and anisotropy. Biomaterials 2006; 27(19): 3515-8.
Huval RM, Miller OH, Curley JL, Fan Y, Hall BJ, Moore MJ. Microengineered peripheral nerve-on-a-chip for preclinical physiological testing. Lab Chip 2015; 15(10): 2221-32.
Park J, Kim S, Park SI, Choe Y, Li J, Han A. A microchip for quantitative analysis of CNS axon growth under localized biomolecular treatments. J Neurosci Methods 2014; 221: 166-74.
Kim YT, Karthikeyan K, Chirvi S, Davé DP. Neuro-optical microfluidic platform to study injury and regeneration of single axons. Lab Chip 2009; 9(17): 2576-81.
Tong Z, Segura-Feliu M, Seira O, Homs-Corbera A, Río JAD, Samitier J. A microfluidic neuronal platform for neuron axotomy and controlled regenerative studies. RSC Advances 2015; 5: 73457-66.
Johnson BN, Lancaster KZ, Hogue IB, et al. 3D printed nervous system on a chip. Lab Chip 2016; 16(8): 1393-400.
Stiles J, Jernigan TL. The basics of brain development. Neuropsychol Rev 2010; 20(4): 327-48.
McTigue DM, Tripathi RB. The life, death, and replacement of oligodendrocytes in the adult CNS. J Neurochem 2008; 107(1): 1-19.
Pandey UB, Nichols CD. Human disease models in Drosophila melanogaster and the role of the fly in therapeutic drug discovery. Pharmacol Rev 2011; 63(2): 411-36.
Kalueff AV, Stewart AM, Gerlai R. Zebrafish as an emerging model for studying complex brain disorders. Trends Pharmacol Sci 2014; 35(2): 63-75.
Vaz RL, Outeiro TF, Ferreira JJ. Zebrafish as an Animal Model for Drug Discovery in Parkinson’s Disease and Other Movement Disorders: A Systematic Review. Front Neurol 2018; 9: 347.
Kilic O, Pamies D, Lavell E, et al. Brain-on-a-chip model enables analysis of human neuronal differentiation and chemotaxis. Lab Chip 2016; 16(21): 4152-62.
Lancaster MA, Renner M, Martin CA, et al. Cerebral organoids model human brain development and microcephaly. Nature 2013; 501(7467): 373-9.
Paşca AM, Sloan SA, Clarke LE, et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat Methods 2015; 12(7): 671-8.
Wang Y, Wang L, Zhu Y, Qin J. Human brain organoid-on-a-chip to model prenatal nicotine exposure. Lab Chip 2018; 18(6): 851-60.
Karzbrun E, Kshirsagar A, Cohen SR, Hanna JH, Reiner O. Human Brain Organoids on a Chip Reveal the Physics of Folding. Nat Phys 2018; 14(5): 515-22.

Rights & Permissions Print Export Cite as
© 2023 Bentham Science Publishers | Privacy Policy