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Development of a Microscale Cell Culture Analog To Probe Naphthalene Toxicity
Abstract
Prediction of human response to drugs or chemicals is difficult as a result of the complexity of living organisms. We describe an in vitro model that can realistically and inexpensively study the adsorption, distribution, metabolism, elimination, and potential toxicity (ADMET) of chemicals. A microscale cell culture analog (microCCA) is a physical replica of the physiologically based pharmacokinetics (PBPK) model. Such a microfabricated device consists of a fluidic network of channels to mimic the circulatory system and chambers containing cultured mammalian cells representing key functions of animal "organ" systems. This paper describes the application of a two-cell system, four-chamber microCCA ("lung"-"liver"-"other tissue"-"fat") device for proof-of-concept study using naphthalene as a model toxicant. Naphthalene is converted into reactive metabolites (i.e., 1,2-naphthalenediol and 1,2-naphthoquinone) in the "liver" compartment, which then circulate to the "lung" depleting glutathione (GSH) in lung cells. Such microfabricated in vitro devices are potential human surrogates for testing chemicals and pharmaceutics for toxicity and efficacy.
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Cites
Role of Quinones in Toxicology
Bolton, J. L., Trush, M. A., Penning, T. M., Dryhurst, G., & Monks, T. J. (2000) · Chemical Research in Toxicology · doi:10.1021/tx9902082 · Cited by 1,703
Cited by
El-Ali, J., Sorger, P. K., & Jensen, K. F. (2006) · Nature · doi:10.1038/nature05063 · Cited by 2,102
From 3D cell culture to organs-on-chips
Huh, D., Hamilton, G. A., & Ingber, D. E. (2011) · Trends in Cell Biology · doi:10.1016/j.tcb.2011.09.005 · Cited by 1,834
A guide to the organ-on-a-chip
Leung, C. M., de Haan, P., Ronaldson-Bouchard, K., Kim, G.-A., Ko, J., Rho, H. S., Chen, Z., Habibovic, P., Jeon, N. L., Takayama, S., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00118-6 · Cited by 1,116
Self-citationAdvances in organ-on-a-chip engineering
Zhang, B., Korolj, A., Lai, B. F. L., & Radisic, M. (2018) · Nature Reviews Materials · doi:10.1038/s41578-018-0034-7 · Cited by 1,017
Continuous perfusion microfluidic cell culture array for high‐throughput cell‐based assays
Hung, P. J., Lee, P. J., Sabounchi, P., Lin, R., & Lee, L. P. (2005) · Biotechnology and Bioengineering · doi:10.1002/bit.20289 · Cited by 522
Interconnected Microphysiological Systems for Quantitative Biology and Pharmacology Studies
Edington, C. D., Chen, W. L. K., Geishecker, E., Kassis, T., Soenksen, L. R., Bhushan, B. M., Freake, D., Kirschner, J., Maass, C., Tsamandouras, N., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-22749-0 · Cited by 487
Microfluidics technology for manipulation and analysis of biological cells
Yi, C., Li, C.-W., Ji, S., & Yang, M. (2006) · Analytica Chimica Acta · doi:10.1016/j.aca.2005.12.037 · Cited by 478
Organ-on-a-chip devices advance to market
Zhang, B., & Radisic, M. (2017) · Lab on a Chip · doi:10.1039/c6lc01554a · Cited by 437
Microfluidic cell culture systems for drug research
Wu, M.-H., Huang, S.-B., & Lee, G.-B. (2010) · Lab on a Chip · doi:10.1039/b921695b · Cited by 432
Differentiation-on-a-chip: A microfluidic platform for long-term cell culture studies
Tourovskaia, A., Figueroa-Masot, X., & Folch, A. (2005) · Lab on a Chip · doi:10.1039/b405719h · Cited by 363
Organ-on-a chip systems: microengineering to biomimic living systems
Zheng, F., Fu, F., Cheng, Y., Wang, C., Zhao, Y., & Gu, Z. (2016) · Small · doi:10.1002/smll.201503208 · Cited by 338
Zhang, C., Zhao, Z., Abdul Rahim, N. A., van Noort, D., & Yu, H. (2009) · Lab on a Chip · doi:10.1039/b915147h · Cited by 340
Marx, U. (2016) · ALTEX · doi:10.14573/altex.1603161 · Cited by 295
Recent Advances in Body-on-a-Chip Systems
Sung, J. H., Wang, Y. I., Narasimhan Sriram, N., Jackson, M., Long, C., Hickman, J. J., & Shuler, M. L. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b05293 · Cited by 268
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Vunjak-Novakovic, G., Ronaldson-Bouchard, K., & Radisic, M. (2021) · Cell · doi:10.1016/j.cell.2021.08.005 · Cited by 248
“For example, naphthalene was converted in the liver module into its reactive metabolites and transferred to the lung module, where it depleted cellular glutathione levels and caused the accumulation of hydrophobic compounds in the fat module (Viravaidya et al., 2004).”
BackgroundTsamandouras, N., Chen, W. L. K., Edington, C. D., Stokes, C. L., Griffith, L. G., & Cirit, M. (2017) · The AAPS Journal · doi:10.1208/s12248-017-0122-4 · Cited by 222
Multi-cellular 3D human primary liver cell culture elevates metabolic activity under fluidic flow
Esch, M. B., Prot, J.-M., Wang, Y. I., Miller, P., Llamas-Vidales, J. R., Naughton, B. A., Applegate, D. R., & Shuler, M. L. (2015) · Lab on a Chip · doi:10.1039/c5lc00237k · Cited by 173
Self-citationIntegrated gut/liver microphysiological systems elucidates inflammatory inter‐tissue crosstalk
Chen, W. L. K., Edington, C., Suter, E., Yu, J., Velazquez, J. J., Velazquez, J. G., Shockley, M., Large, E. M., Venkataramanan, R., Hughes, D. J., et al. (2017) · Biotechnology and Bioengineering · doi:10.1002/bit.26370 · Cited by 172
Hepatic organoids for microfluidic drug screening
Au, S. H., Chamberlain, M. D., Mahesh, S., Sefton, M. V., & Wheeler, A. R. (2014) · Lab on a Chip · doi:10.1039/c4lc00531g · Cited by 162
On being the right size: scaling effects in designing a human-on-a-chip
Moraes, C., Labuz, J. M., Leung, B. M., Inoue, M., Chun, T.-H., & Takayama, S. (2013) · Integrative Biology · doi:10.1039/c3ib40040a · Cited by 134
Microengineered Liver Tissues for Drug Testing
Khetani, S. R., Berger, D. R., Ballinger, K. R., Davidson, M. D., Lin, C., & Ware, B. R. (2015) · SLAS Technology · doi:10.1177/2211068214566939 · Cited by 116
Microfluidic devices for in vitro studies on liver drug metabolism and toxicity
van Midwoud, P. M., Verpoorte, E., & Groothuis, G. M. M. (2011) · Integrative Biology · doi:10.1039/c0ib00119h · Cited by 115
Primary cells and stem cells in drug discovery: emerging tools for high-throughput screening
Eglen, R., & Reisine, T. (2011) · ASSAY and Drug Development Technologies · doi:10.1089/adt.2010.0305 · Cited by 100
Lee, J. B., & Sung, J. H. (2013) · Biotechnology Journal · doi:10.1002/biot.201300086 · Cited by 92
Engineered Liver Platforms for Different Phases of Drug Development
Ware, B. R., & Khetani, S. R. (2017) · Trends in Biotechnology · doi:10.1016/j.tibtech.2016.08.001 · Cited by 90
Organ-Tumor-on-a-Chip for Chemosensitivity Assay: A Critical Review
Kashaninejad, N., Nikmaneshi, M., Moghadas, H., Kiyoumarsi Oskouei, A., Rismanian, M., Barisam, M., Saidi, M., & Firoozabadi, B. (2016) · Micromachines · doi:10.3390/mi7080130 · Cited by 79
Ozkan, A., Ghousifam, N., Hoopes, P. J., Yankeelov, T. E., & Rylander, M. N. (2019) · Biotechnology and Bioengineering · doi:10.1002/bit.26919 · Cited by 73
Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction
Segovia-Zafra, A., Di Zeo-Sánchez, D. E., López-Gómez, C., Pérez-Valdés, Z., García-Fuentes, E., Andrade, R. J., Lucena, M. I., & Villanueva-Paz, M. (2021) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2021.11.013 · Cited by 70
Advances in Engineered Liver Models for Investigating Drug-Induced Liver Injury
Lin, C., & Khetani, S. R. (2016) · BioMed Research International · doi:10.1155/2016/1829148 · Cited by 66
Sung, J. H., Wang, Y., & Shuler, M. L. (2019) · APL Bioengineering · doi:10.1063/1.5097675 · Cited by 66
Self-citationIn vitro micro-physiological models for translational immunology
Ramadan, Q., & Gijs, M. A. M. (2015) · Lab on a Chip · doi:10.1039/c4lc01271b · Cited by 41
Metadata
- Authors
- Viravaidya, K., Sin, A., & Shuler, M. L.
- Venue
- Biotechnology Progress
- Publisher
- Wiley
- Published
- 2008-09-05
- Volume
- 20
- Issue
- 1
- Pages
- 316-323
- ISSN
- 1520-6033 (ISSN-L)
- 8756-7938
- OpenAlex
- W2139424714
- Cited by
- 305
- References
- 1
- FWCI
- 8.07
- Type
- journal article
- Language
- en
- Open access
- closed
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