Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Human biomimetic liver microphysiology systems in drug development and precision medicine

Abstract

Microphysiology systems (MPS), also called organs-on-chips and tissue chips, are miniaturized functional units of organs constructed with multiple cell types under a variety of physical and biochemical environmental cues that complement animal models as part of a new paradigm of drug discovery and development. Biomimetic human liver MPS have evolved from simpler 2D cell models, spheroids and organoids to address the increasing need to understand patient-specific mechanisms of complex and rare diseases, the response to therapeutic treatments, and the absorption, distribution, metabolism, excretion and toxicity of potential therapeutics. The parallel development and application of transdisciplinary technologies, including microfluidic devices, bioprinting, engineered matrix materials, defined physiological and pathophysiological media, patient-derived primary cells, and pluripotent stem cells as well as synthetic biology to engineer cell genes and functions, have created the potential to produce patient-specific, biomimetic MPS for detailed mechanistic studies. It is projected that success in the development and maturation of patient-derived MPS with known genotypes and fully matured adult phenotypes will lead to advanced applications in precision medicine. In this Review, we examine human biomimetic liver MPS that are designed to recapitulate the liver acinus structure and functions to enhance our knowledge of the mechanisms of disease progression and of the absorption, distribution, metabolism, excretion and toxicity of therapeutic candidates and drugs as well as to evaluate their mechanisms of action and their application in precision medicine and preclinical trials.

Key points

  • Liver in vitro experimental models have a long history involving the use of 2D and 3D models that continue to have valuable roles in our understanding of liver physiology and pathophysiology.

  • Human microphysiology systems (MPS) have evolved from simple cell-based experimental models and have the potential to meet the need for human experimental models for basic biomedical research and the development of therapeutics.

  • Human biomimetic liver MPS (HBL-MPS) aim to improve the efficiency of developing biomarkers, repurposed drugs and novel therapeutics by maximally recapitulating the structure and functions of the liver acinus.

  • HBL-MPS are evolving based either on liver organoids derived from patient cells that self-assemble and differentiate or on the directed assembly or bioprinting of matrix materials and cells into microfluidic devices.

  • Organoid-derived MPS and structured MPS are next-generation HBL-MPS that are projected to enable applications of precision medicine, including preclinical trials, either as stand-alone liver models or as coupled, multi-organ MPS.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Human liver acinus structure and organization.
Fig. 2: Illustration of one design of a current HBL-MPS.
Fig. 3: Organoid-MPS and Structured-MPS are platforms for advancing precision medicine.

References

  1. 1.

    Alex, A., Harris, C. J., Keighley, W. W. & Smith, D. A. In Attrition in the Pharmaceutical Industry: Reasons, Implications, and Pathways Forward (eds Alex, A., Harris, C. J. & Smith, D. A.) 106–127 (Wiley, 2015).

  2. 2.

    Arrowsmith, J. & Miller, P. Trial watch: phase II and phase III attrition rates 2011-2012. Nat. Rev. Drug Discov. 12, 569 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M. & Sanyal, A. J. Mechanisms of NAFLD development and therapeutic strategies. Nat. Med. 24, 908–922 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. 4.

    Gribkoff, V. K. & Kaczmarek, L. K. The need for new approaches in CNS drug discovery: Why drugs have failed, and what can be done to improve outcomes. Neuropharmacology 120, 11–19 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  5. 5.

    Jardim, D. L., Groves, E. S., Breitfeld, P. P. & Kurzrock, R. Factors associated with failure of oncology drugs in late-stage clinical development: a systematic review. Cancer Treat. Rev. 52, 12–21 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  6. 6.

    Parasrampuria, D. A., Benet, L. Z. & Sharma, A. Why drugs fail in late stages of development: case study analyses from the last decade and recommendations. AAPS J. 20, 46 (2018).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  7. 7.

    Sanyal, A. J. Past, present and future perspectives in nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 16, 377–386 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    Taylor, D. L. et al. Harnessing human microphysiology systems as key experimental models for quantitative systems pharmacology. Handb. Exp. Pharmacol. 260, 327–367 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. 9.

    Eslam, M. & George, J. Genetic contributions to NAFLD: leveraging shared genetics to uncover systems biology. Nat. Rev. Gastroenterol. Hepatol. 17, 40–52 (2020).

    PubMed  Article  PubMed Central  Google Scholar 

  10. 10.

    Mullard, A. FDA rejects NASH drug. Nat. Rev. Drug Discov. 19, 501 (2020).

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Roussel, R., Steg, P. G., Mohammedi, K., Marre, M. & Potier, L. Prevention of cardiovascular disease through reduction of glycaemic exposure in type 2 diabetes: a perspective on glucose-lowering interventions. Diabetes Obes. Metab. 20, 238–244 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  12. 12.

    Menon, V. et al. Fasiglifam-induced liver injury in patients with type 2 diabetes: results of a randomized controlled cardiovascular outcomes safety trial. Diabetes Care 41, 2603–2609 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    Mosedale, M. & Watkins, P. B. Drug-induced liver injury: advances in mechanistic understanding that will inform risk management. Clin. Pharmacol. Ther. 101, 469–480 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Hartung, T. A toxicology for the 21st century - mapping the road ahead. Toxicol. Sci. 109, 18–23 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  15. 15.

    Sultana, J., Cutroneo, P. & Trifiro, G. Clinical and economic burden of adverse drug reactions. J. Pharmacol. Pharmacother. 4, S73–S77 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Bernal, W. Acute liver failure: review and update. Int. Anesthesiol. Clin. 55, 92–106 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Vernetti, L. et al. in Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools (eds Ekins, S. & Xu, J. J.) Ch. 3, 53–73 (Wiley & Sons, 2009).

  18. 18.

    Moore, T. J., Zhang, H., Anderson, G. & Alexander, G. C. Estimated costs of pivotal trials for novel therapeutic agents approved by the US Food and Drug Administration, 2015-2016. JAMA Intern. Med. 178, 1451–1457 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  19. 19.

    Wouters, O. J., McKee, M. & Luyten, J. Estimated research and development investment needed to bring a new medicine to market, 2009–2018. JAMA 323, 844–853 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  20. 20.

    Stern, A. M., Schurdak, M. E., Bahar, I., Berg, J. M. & Taylor, D. L. A perspective on implementing a quantitative systems pharmacology platform for drug discovery and the advancement of personalized medicine. J. Biomol. Screen. 21, 521–534 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Low, L. A. & Tagle, D. A. Tissue chips - innovative tools for drug development and disease modeling. Lab Chip 17, 3026–3036 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Watson, D. E., Hunziker, R. & Wikswo, J. P. Fitting tissue chips and microphysiological systems into the grand scheme of medicine, biology, pharmacology, and toxicology. Exp. Biol. Med. 242, 1559–1572 (2017).

    CAS  Article  Google Scholar 

  23. 23.

    Ewart, L. et al. Navigating tissue chips from development to dissemination: a pharmaceutical industry perspective. Exp. Biol. Med. 242, 1579–1585 (2017).

    CAS  Article  Google Scholar 

  24. 24.

    Bhatia, S. N. & Ingber, D. E. Microfluidic organs-on-chips. Nat. Biotechnol. 32, 760–772 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25.

    Ronaldson-Bouchard, K. & Vunjak-Novakovic, G. Organs-on-a-chip: a fast track for engineered human tissues in drug development. Cell Stem Cell 22, 310–324 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. https://doi.org/10.1038/s41573-020-0079-3 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Tagle, D. A. The NIH microphysiological systems program: developing in vitro tools for safety and efficacy in drug development. Curr. Opin. Pharmacol. 48, 146–154 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  28. 28.

    Sorger, P. K. et al. Quantitative and Systems Pharmacology in the Post-genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms (NIH, 2011).

  29. 29.

    Isoherranen, N., Madabushi, R. & Huang, S.-M. Emerging role of organ-on-a-chip technologies in quantitative clinical pharmacology evaluation. Clin. Transl. Sci. 12, 113–121 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

    European Medicines Agency. Meeting Report: First EMA workshop on non-animal approaches in support of medicinal product development – challenges and opportunities for use of micro-physiological systems (EMA/CHMP/SWP/250438/2018) (European Medicines Agency, 2018).

  31. 31.

    Fang, Y. & Eglen, R. M. Three-dimensional cell cultures in drug discovery and development. SLAS Discov. 22, 456–472 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Shamir, E. R. & Ewald, A. J. Three-dimensional organotypic culture: experimental models of mammalian biology and disease. Nat. Rev. Mol. Cell Biol. 15, 647–664 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Simian, M. & Bissell, M. J. Organoids: a historical perspective of thinking in three dimensions. J. Cell Biol. 216, 31–40 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Bhushan, A. et al. Towards a three-dimensional microfluidic liver platform for predicting drug efficacy and toxicity in humans. Stem Cell Res. Ther. 4 (Suppl. 1), S16 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  35. 35.

    Ma, L. D. et al. Design and fabrication of a liver-on-a-chip platform for convenient, highly efficient, and safe in situ perfusion culture of 3D hepatic spheroids. Lab Chip 18, 2547–2562 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Underhill, G. H. & Khetani, S. R. Advances in engineered human liver platforms for drug metabolism studies. Drug Metab. Dispos. 46, 1626–1637 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. 37.

    Foster, A. J. et al. Integrated in vitro models for hepatic safety and metabolism: evaluation of a human liver-chip and liver spheroid. Arch. Toxicol. https://doi.org/10.1007/s00204-019-02427-4 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Proctor, W. R. et al. Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury. Arch. Toxicol. 91, 2849–2863 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Wang, Y. et al. In situ differentiation and generation of functional liver organoids from human iPSCs in a 3D perfusable chip system. Lab Chip 18, 3606–3616 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Takebe, T. et al. Vascularized and functional human liver from an iPSC-derived organ bud transplant. Nature 499, 481–484 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    Guye, P. et al. Genetically engineering self-organization of human pluripotent stem cells into a liver bud-like tissue using Gata6. Nat. Commun. 7, 10243 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Takebe, T., Zhang, B. & Radisic, M. Synergistic engineering: organoids meet organs-on-a-chip. Cell Stem Cell 21, 297–300 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Ho, B. X., Pek, N. M. Q. & Soh, B. S. Disease modeling using 3D organoids derived from human induced pluripotent stem cells. Int. J. Mol. Sci. 19 https://doi.org/10.3390/ijms19040936 (2018).

  44. 44.

    Fatehullah, A., Tan, S. H. & Barker, N. Organoids as an in vitro model of human development and disease. Nat. Cell Biol. 18, 246–254 (2016).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  45. 45.

    May, S., Evans, S. & Parry, L. Organoids, organs-on-chips and other systems, and microbiota. Emerg. Top. Life Sci. 1, 385–400 (2017).

    CAS  PubMed Central  Article  Google Scholar 

  46. 46.

    Ouchi, R. et al. Modeling steatohepatitis in humans with pluripotent stem cell-derived organoids. Cell Metab. 30, 374–384.e6 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47.

    Lancaster, M. A. & Huch, M. Disease modelling in human organoids. Dis. Model. Mech. 12, dmm039347 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Prior, N., Inacio, P. & Huch, M. Liver organoids: from basic research to therapeutic applications. Gut 68, 2228–2237 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Prestigiacomo, V., Weston, A., Messner, S., Lampart, F. & Suter-Dick, L. Pro-fibrotic compounds induce stellate cell activation, ECM-remodelling and Nrf2 activation in a human 3D-multicellular model of liver fibrosis. PLoS ONE 12, e0179995 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  50. 50.

    Jang, M., Neuzil, P., Volk, T., Manz, A. & Kleber, A. On-chip three-dimensional cell culture in phaseguides improves hepatocyte functions in vitro. Biomicrofluidics 9, 034113 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  51. 51.

    Khetani, S. R. & Bhatia, S. N. Microscale culture of human liver cells for drug development. Nat. Biotechnol. 26, 120–126 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  52. 52.

    Davidson, M. D., Lehrer, M. & Khetani, S. R. Hormone and drug-mediated modulation of glucose metabolism in a microscale model of the human liver. Tissue Eng. Part C Methods 21, 716–725 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. 53.

    Davidson, M. D., Kukla, D. A. & Khetani, S. R. Microengineered cultures containing human hepatic stellate cells and hepatocytes for drug development. Integr. Biol. 9, 662–677 (2017).

    CAS  Article  Google Scholar 

  54. 54.

    Berger, D. R., Ware, B. R., Davidson, M. D., Allsup, S. R. & Khetani, S. R. Enhancing the functional maturity of induced pluripotent stem cell-derived human hepatocytes by controlled presentation of cell-cell interactions in vitro. Hepatology 61, 1370–1381 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Avila, A. M. et al. An FDA/CDER perspective on nonclinical testing strategies: classical toxicology approaches and new approach methodologies (NAMs). Regul. Toxicol. Pharmacol. 114, 104662 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  56. 56.

    Li, X., George, S. M., Vernetti, L., Gough, A. H. & Taylor, D. L. A glass-based, continuously zonated and vascularized human liver acinus microphysiological system (vLAMPS) designed for experimental modeling of diseases and ADME/TOX. Lab Chip 18, 2614–2631 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  57. 57.

    Ahadian, S. et al. Organ-on-a-chip platforms: a convergence of advanced materials, cells, and microscale technologies. Adv. Healthc. Mater. https://doi.org/10.1002/adhm.201700506 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Soto-Gutierrez, A., Gough, A., Vernetti, L. A., Taylor, D. L. & Monga, S. P. Pre-clinical and clinical investigations of metabolic zonation in liver diseases: the potential of microphysiology systems. Exp. Biol. Med. 242, 1605–1616 (2017).

    CAS  Article  Google Scholar 

  59. 59.

    Lee-Montiel, F. T. et al. Control of oxygen tension recapitulates zone-specific functions in human liver microphysiology systems. Exp. Biol. Med. 242, 1617–1632 (2017).

    CAS  Article  Google Scholar 

  60. 60.

    Bin Ramli, M. N. et al. Human pluripotent stem cell-derived organoids as models of liver disease. Gastroenterology 159, 1471–1486.e12 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  61. 61.

    Sharma, A., Sances, S., Workman, M. J. & Svendsen, C. N. Multi-lineage human iPSC-derived platforms for disease modeling and drug discovery. Cell Stem Cell 26, 309–329 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  62. 62.

    Vernetti, L. A. et al. A human liver microphysiology platform for investigating physiology, drug safety, and disease models. Exp. Biol. Med. 241, 101–114 (2016).

    CAS  Article  Google Scholar 

  63. 63.

    McAleer, C. W. et al. On the potential of in vitro organ-chip models to define temporal pharmacokinetic-pharmacodynamic relationships. Sci. Rep. 9, 9619 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  64. 64.

    Kizawa, H., Nagao, E., Shimamura, M., Zhang, G. & Torii, H. Scaffold-free 3D bio-printed human liver tissue stably maintains metabolic functions useful for drug discovery. Biochem. Biophys. Rep. 10, 186–191 (2017).

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Feaver, R. E. et al. Development of an in vitro human liver system for interrogating nonalcoholic steatohepatitis. JCI Insight 1, e90954 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  66. 66.

    Kostrzewski, T. et al. A microphysiological system for studying nonalcoholic steatohepatitis. Hepatol. Commun. 4, 77–91 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  67. 67.

    Huch, M., Knoblich, J. A., Lutolf, M. P. & Martinez-Arias, A. The hope and the hype of organoid research. Development 144, 938–941 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68.

    Huch, M. et al. Long-term culture of genome-stable bipotent stem cells from adult human liver. Cell 160, 299–312 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  69. 69.

    Saito, Y. et al. Establishment of patient-derived organoids and drug screening for biliary tract carcinoma. Cell Rep. 27, 1265–1276.e1264 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  70. 70.

    Guan, Y. et al. Human hepatic organoids for the analysis of human genetic diseases. JCI Insight https://doi.org/10.1172/jci.insight.94954 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Broutier, L. et al. Human primary liver cancer-derived organoid cultures for disease modeling and drug screening. Nat. Med. 23, 1424–1435 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  72. 72.

    Velazquez, J. J. et al. Synthetic maturation of multilineage human liver organoids via genetically guided engineering. bioRxiv https://doi.org/10.1101/2020.05.10.087445 (2020).

    Article  Google Scholar 

  73. 73.

    Koike, H. et al. Modelling human hepato-biliary-pancreatic organogenesis from the foregut-midgut boundary. Nature 574, 112–116 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Kostrzewski, T. et al. Three-dimensional perfused human in vitro model of non-alcoholic fatty liver disease. World J. Gastroenterol. 23, 204–215 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  75. 75.

    Jang, K. J. et al. Reproducing human and cross-species drug toxicities using a Liver-Chip. Sci. Transl. Med. https://doi.org/10.1126/scitranslmed.aax5516 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  76. 76.

    Beckwitt, C. H. et al. Liver ‘organ on a chip’. Exp. Cell. Res. 363, 15–25 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  77. 77.

    Senutovitch, N. et al. Fluorescent protein biosensors applied to microphysiological systems. Exp. Biol. Med. 240, 795–808 (2015).

    CAS  Article  Google Scholar 

  78. 78.

    Auner, A. W., Tasneem, K. M., Markov, D. A., McCawley, L. J. & Hutson, M. S. Chemical-PDMS binding kinetics and implications for bioavailability in microfluidic devices. Lab Chip 19, 864–874 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  79. 79.

    Tan, K. et al. A high-throughput microfluidic microphysiological system (PREDICT-96) to recapitulate hepatocyte function in dynamic, re-circulating flow conditions. Lab Chip 19, 1556–1566 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  80. 80.

    Wikswo, J. P. et al. Engineering challenges for instrumenting and controlling integrated organ-on-chip systems. IEEE Trans. Biomed. Eng. 60, 682–690 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  81. 81.

    Bavli, D. et al. Real-time monitoring of metabolic function in liver-on-chip microdevices tracks the dynamics of mitochondrial dysfunction. Proc. Natl Acad. Sci. USA 113, E2231–E2240 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  82. 82.

    Esch, M. B., Ueno, H., Applegate, D. R. & Shuler, M. L. Modular, pumpless body-on-a-chip platform for the co-culture of GI tract epithelium and 3D primary liver tissue. Lab Chip 16, 2719–2729 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  83. 83.

    Miller, P. G. & Shuler, M. L. Design and demonstration of a pumpless 14 compartment microphysiological system. Biotechnol. Bioeng. 113, 2213–2227 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  84. 84.

    Oleaga, C. et al. Multi-organ toxicity demonstration in a functional human in vitro system composed of four organs. Sci. Rep. 6, 20030 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  85. 85.

    Wang, Y. I., Carmona, C., Hickman, J. J. & Shuler, M. L. Multiorgan microphysiological systems for drug development: strategies, advances, and challenges. Adv. Healthc. Mater. 7, https://doi.org/10.1002/adhm.201701000 (2018).

  86. 86.

    Wang, Y., Wang, L., Guo, Y., Zhu, Y. & Qin, J. Engineering stem cell-derived 3D brain organoids in a perfusable organ-on-a-chip system. RSC Adv. 8, 1677–1685 (2018).

    CAS  Article  Google Scholar 

  87. 87.

    Park, S. E., Georgescu, A. & Huh, D. Organoids-on-a-chip. Science 364, 960–965 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  88. 88.

    Zhang, Y. S. et al. Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors. Proc. Natl Acad. Sci. USA 114, E2293–E2302 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  89. 89.

    Ehrlich, A., Duche, D., Ouedraogo, G. & Nahmias, Y. Challenges and opportunities in the design of liver-on-chip microdevices. Annu. Rev. Biomed. Eng. 21, 219–239 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  90. 90.

    Ehrlich, A. et al. Microphysiological flux balance platform unravels the dynamics of drug induced steatosis. Lab Chip 18, 2510–2522 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  91. 91.

    Kilic, T., Navaee, F., Stradolini, F., Renaud, P. & Carrara, S. Organs-on-chip monitoring: sensors and other strategies. Microphysiol. Syst. https://doi.org/10.21037/mps.2018.01.01 (2018).

    Article  Google Scholar 

  92. 92.

    Sung, J. H. Pharmacokinetic-based multi-organ chip for recapitulating organ interactions. Methods Cell. Biol. 146, 183–197 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  93. 93.

    Sung, J. H. et al. Using physiologically-based pharmacokinetic-guided “body-on-a-chip” systems to predict mammalian response to drug and chemical exposure. Exp. Biol. Med. 239, 1225–1239 (2014).

    Article  CAS  Google Scholar 

  94. 94.

    Vernetti, L. A., Vogt, A., Gough, A. & Taylor, D. L. Evolution of experimental models of the liver to predict human drug hepatotoxicity and efficacy. Clin. Liver Dis. 21, 197–214 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  95. 95.

    Ewart, L. et al. Application of microphysiological systems to enhance safety assessment in drug discovery. Annu. Rev. Pharmacol. Toxicol. 58, 65–82 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  96. 96.

    Wang, X., Cirit, M., Wishnok, J. S., Griffith, L. G. & Tannenbaum, S. R. Analysis of an integrated human multiorgan microphysiological system for combined tolcapone metabolism and brain metabolomics. Anal. Chem. 91, 8667–8675 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  97. 97.

    Herland, A. et al. Quantitative prediction of human pharmacokinetic responses to drugs via fluidically coupled vascularized organ chips. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-019-0498-9 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  98. 98.

    Vernetti, L. et al. Functional coupling of human microphysiology systems: intestine, liver, kidney proximal tubule, blood-brain barrier and skeletal muscle. Sci. Rep. 7, 42296 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  99. 99.

    Wikswo, J. P. et al. Scaling and systems biology for integrating multiple organs-on-a-chip. Lab Chip 13, 3496–3511 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  100. 100.

    Koui, Y. et al. An in vitro human liver model by iPSC-derived parenchymal and non-parenchymal cells. Stem Cell Rep. 9, 490–498 (2017).

    CAS  Article  Google Scholar 

  101. 101.

    Prendergast, M. E. et al. Microphysiological systems: automated fabrication via extrusion bioprinting. Microphysiol. Syst. https://doi.org/10.21037/MPS.2018.03.01 (2018).

    Article  Google Scholar 

  102. 102.

    Velazquez, J. J., Su, E., Cahan, P. & Ebrahimkhani, M. R. Programming morphogenesis through systems and synthetic biology. Trends Biotechnol. 36, 415–429 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  103. 103.

    Ebrahimkhani, M. R. & Ebisuya, M. Synthetic developmental biology: build and control multicellular systems. Curr. Opin. Chem. Biol. 52, 9–15 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  104. 104.

    Johnson, M. B., March, A. R. & Morsut, L. Engineering multicellular systems: using synthetic biology to control tissue self-organization. Curr. Opin. Biomed. Eng. 4, 163–173 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  105. 105.

    Colnot, S. & Perret, C. in Molecular Pathology of Liver Diseases (ed. Satdarshan, S. & Monga, P.) 7–16 (Springer, 2011).

  106. 106.

    Marx, U. et al. Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing. ALTEX 33, 272–321 (2016).

    PubMed  PubMed Central  Google Scholar 

  107. 107.

    Baudy, A. R. et al. Liver microphysiological systems development guidelines for safety risk assessment in the pharmaceutical industry. Lab Chip 20, 215–225 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  108. 108.

    Hughes, D. J., Kostrzewski, T. & Sceats, E. L. Opportunities and challenges in the wider adoption of liver and interconnected microphysiological systems. Exp. Biol. Med. 242, 1593–1604 (2017).

    CAS  Article  Google Scholar 

  109. 109.

    Wheeler, S. E. et al. Spontaneous dormancy of metastatic breast cancer cells in an all human liver microphysiologic system. Br. J. Cancer 111, 2342–2350 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  110. 110.

    Sundaram, V. & Björnsson, E. S. Drug-induced cholestasis. Hepatol. Commun. 1, 726–735 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  111. 111.

    Sampaziotis, F. et al. Directed differentiation of human induced pluripotent stem cells into functional cholangiocyte-like cells. Nat. Protoc. 12, 814–827 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  112. 112.

    Sampaziotis, F. et al. Reconstruction of the mouse extrahepatic biliary tree using primary human extrahepatic cholangiocyte organoids. Nat. Med. 23, 954–963 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  113. 113.

    Sampaziotis, F. Building better bile ducts. Science 359, 1113 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  114. 114.

    Du, Y. et al. A bile duct-on-a-chip with organ-level functions. Hepatology 71, 1350–1363 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  115. 115.

    Leclerc, E. et al. Comparison of the transcriptomic profile of hepatic human induced pluripotent stem like cells cultured in plates and in a 3D microscale dynamic environment. Genomics 109, 16–26 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  116. 116.

    Grant, M. H. et al. Human adult hepatocytes in primary monolayer culture. Maintenance of mixed function oxidase and conjugation pathways of drug metabolism. Biochem. Pharmacol. 36, 2311–2316 (1987).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  117. 117.

    Guzelian, P. S., Bissell, D. M. & Meyer, U. A. Drug metabolism in adult rat hepatocytes in primary monolayer culture. Gastroenterology 72, 1232–1239 (1977).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  118. 118.

    Long, T. J. et al. Modeling therapeutic antibody-small molecule drug-drug interactions using a three-dimensional perfusable human liver coculture platform. Drug Metab. Dispos. 44, 1940–1948 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  119. 119.

    Tsamandouras, N. et al. Quantitative assessment of population variability in hepatic drug metabolism using a perfused three-dimensional human liver microphysiological system. J. Pharmacol. Exp. Ther. 360, 95–105 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  120. 120.

    Cirit, M. & Stokes, C. L. Maximizing the impact of microphysiological systems with in vitro-in vivo translation. Lab Chip 18, 1831–1837 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  121. 121.

    Shen, J. X., Youhanna, S., Shafagh, R. Z., Kele, J. & Lauschke, V. M. Organotypic and microphysiological models of liver, gut and kidney for studies of drug metabolism, pharmacokinetics and toxicity. Chem. Res. Toxicol. 33, 38–60 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  122. 122.

    Truskey, G. A. Human microphysiological systems and organoids as in vitro models for toxicological studies. Front. Public. Health 6, 185–185 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  123. 123.

    Zhou, Y., Shen, J. X. & Lauschke, V. M. Comprehensive evaluation of organotypic and microphysiological liver models for prediction of drug-induced liver injury. Front. Pharmacol. 10, 1093 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  124. 124.

    Terelius, Y. et al. Transcriptional profiling suggests that Nevirapine and Ritonavir cause drug induced liver injury through distinct mechanisms in primary human hepatocytes. Chem. Biol. Interact. 255, 31–44 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  125. 125.

    Schurdak, M. et al. Applications of the microphysiology systems database for experimental ADME-Tox and disease models. Lab Chip 20, 1472–1492 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  126. 126.

    Gough, A., Vernetti, L., Bergenthal, L., Shun, T. Y. & Taylor, D. L. The microphysiology systems database for analyzing and modeling compound interactions with human and animal organ models. Appl. In Vitro Toxicol. 2, 103–117 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  127. 127.

    Choudhury, Y. et al. Patient-specific hepatocyte-like cells derived from induced pluripotent stem cells model pazopanib-mediated hepatotoxicity. Sci. Rep. 7, 41238 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  128. 128.

    Koido, M. et al. Polygenic architecture informs potential vulnerability to drug-induced liver injury. Nat. Med. https://doi.org/10.1038/s41591-020-1023-0 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  129. 129.

    Adams, D. H., Ju, C., Ramaiah, S. K., Uetrecht, J. & Jaeschke, H. Mechanisms of immune-mediated liver injury. Toxicol. Sci. 115, 307–321 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  130. 130.

    Ahn, J. et al. Human three-dimensional in vitro model of hepatic zonation to predict zonal hepatotoxicity. J. Biol. Eng. 13, 22–22 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  131. 131.

    Tonon, F. et al. In vitro metabolic zonation through oxygen gradient on a chip. Sci. Rep. 9, 13557 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  132. 132.

    Halpern, K. B. et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 542, 352–356 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  133. 133.

    Prill, S. et al. Real-time monitoring of oxygen uptake in hepatic bioreactor shows CYP450-independent mitochondrial toxicity of acetaminophen and amiodarone. Arch. Toxicol. 90, 1181–1191 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  134. 134.

    Roden, M. & Shulman, G. I. The integrative biology of type 2 diabetes. Nature 576, 51–60 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  135. 135.

    Hardy, T., Oakley, F., Anstee, Q. M. & Day, C. P. Nonalcoholic fatty liver disease: pathogenesis and disease spectrum. Annu. Rev. Pathol. 11, 451–496 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  136. 136.

    Eslam, M., Sanyal, A.J., George, J. & International Consensus Panel. MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology, 158, 1999–2014 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  137. 137.

    Pennisi, G. et al. Pharmacological therapy of non-alcoholic fatty liver disease: what drugs are available now and future perspectives. Int. J. Environ. Res. Public Health 16, https://doi.org/10.3390/ijerph16224334 (2019).

  138. 138.

    Danford, C. J., Yao, Z.-M. & Jiang, Z. G. Non-alcoholic fatty liver disease: a narrative review of genetics. J. Biomed. Res. 32, 389–400 (2018).

    PubMed  PubMed Central  Google Scholar 

  139. 139.

    Sato, K. et al. Intercellular communication between hepatic cells in liver diseases. Int. J. Mol. Sci. 20 https://doi.org/10.3390/ijms20092180 (2019).

  140. 140.

    Boeckmans, J. et al. Human-based systems: mechanistic NASH modelling just around the corner? Pharmacol. Res. 134, 257–267 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  141. 141.

    Anstee, Q. M., Reeves, H. L., Kotsiliti, E., Govaere, O. & Heikenwalder, M. From NASH to HCC: current concepts and future challenges. Nat. Rev. Gastroenterol. Hepatol. 16, 411–428 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  142. 142.

    Mannaa, F. A. & Abdel-Wahhab, K. G. Physiological potential of cytokines and liver damages. Hepatoma Res. 2, 131–143 (2016).

    CAS  Article  Google Scholar 

  143. 143.

    Tacke, F. Targeting hepatic macrophages to treat liver diseases. J. Hepatol. 66, 1300–1312 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  144. 144.

    Musso, G., Cassader, M. & Gambino, R. Non-alcoholic steatohepatitis: emerging molecular targets and therapeutic strategies. Nat. Rev. Drug Discov. 15, 249–274 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  145. 145.

    Ezhilarasan, D., Sokal, E. & Najimi, M. Hepatic fibrosis: it is time to go with hepatic stellate cell-specific therapeutic targets. Hepatobiliary Pancreat. Dis. Int. 17, 192–197 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  146. 146.

    Higashi, T., Friedman, S. L. & Hoshida, Y. Hepatic stellate cells as key target in liver fibrosis. Adv. Drug Deliv. Rev. 121, 27–42 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  147. 147.

    Rao, S. S., Kondapaneni, R. V. & Narkhede, A. A. Bioengineered models to study tumor dormancy. J. Biol. Eng. 13, 3 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  148. 148.

    Lee, J. W. et al. Hepatocytes direct the formation of a pro-metastatic niche in the liver. Nature 567, 249–252 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  149. 149.

    Wells, A., Clark, A., Bradshaw, A., Ma, B. & Edington, H. The great escape: how metastases of melanoma, and other carcinomas, avoid elimination. Exp. Biol. Med. 243, 1245–1255 (2018).

    CAS  Article  Google Scholar 

  150. 150.

    Miedel, M. T. et al. Modeling the effect of the metastatic microenvironment on phenotypes conferred by estrogen receptor mutations using a human liver microphysiological system. Sci. Rep. 9, 8341 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  151. 151.

    Jia, S. et al. Clinically observed estrogen receptor alpha mutations within the ligand-binding domain confer distinguishable phenotypes. Oncology 94, 176–189 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  152. 152.

    Scherz-Shouval, R. et al. The reprogramming of tumor stroma by HSF1 is a potent enabler of malignancy. Cell 158, 564–578 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  153. 153.

    Clark, A. M. et al. A microphysiological system model of therapy for liver micrometastases. Exp. Biol. Med. 239, 1170–1179 (2014).

    Article  CAS  Google Scholar 

  154. 154.

    Clark, A. M. et al. A model of dormant-emergent metastatic breast cancer progression enabling exploration of biomarker signatures. Mol. Cell. Proteomics 17, 619–630 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  155. 155.

    Beckwitt, C. H. et al. Statins attenuate outgrowth of breast cancer metastases. Br. J. Cancer 119, 1094–1105 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  156. 156.

    Zhao, Y., Kankala, R. K., Wang, S. B. & Chen, A. Z. Multi-organs-on-chips: towards long-term biomedical investigations. Molecules https://doi.org/10.3390/molecules24040675 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  157. 157.

    Sung, J. H. et al. Recent advances in body-on-a-chip systems. Anal. Chem. 91, 330–351 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  158. 158.

    McAleer, C. W. et al. Multi-organ system for the evaluation of efficacy and off-target toxicity of anticancer therapeutics. Sci. Transl. Med. 11, eaav1386 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  159. 159.

    Vunjak-Novakovic, G., Bhatia, S., Chen, C. & Hirschi, K. HeLiVa platform: integrated heart-liver-vascular systems for drug testing in human health and disease. Stem Cell Res. Ther. 4 (Suppl. 1), S8 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  160. 160.

    Bricks, T. et al. Development of a new microfluidic platform integrating co-cultures of intestinal and liver cell lines. Toxicol. In Vitro 28, 885–895 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  161. 161.

    Bricks, T. et al. Investigation of omeprazole and phenacetin first-pass metabolism in humans using a microscale bioreactor and pharmacokinetic models. Biopharm. Drug Dispos. 36, 275–293 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  162. 162.

    Maschmeyer, I. et al. A four-organ-chip for interconnected long-term co-culture of human intestine, liver, skin and kidney equivalents. Lab Chip 15, 2688–2699 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  163. 163.

    Bauer, S. et al. Functional coupling of human pancreatic islets and liver spheroids on-a-chip: Towards a novel human ex vivo type 2 diabetes model. Sci. Rep. 7, 14620 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  164. 164.

    Tsamandouras, N. et al. Integrated gut and liver microphysiological systems for quantitative in vitro pharmacokinetic studies. AAPS J. https://doi.org/10.1208/s12248-017-0122-4 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  165. 165.

    Edington, C. D. et al. Interconnected microphysiological systems for quantitative biology and pharmacology studies. Sci. Rep. 8, 4530–4530 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  166. 166.

    Tilg, H., Moschen, A. R. & Roden, M. NAFLD and diabetes mellitus. Nat. Rev. Gastroenterol. Hepatol. 14, 32–42 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  167. 167.

    Ferreira, C. R., Cassiman, D. & Blau, N. Clinical and biochemical footprints of inherited metabolic diseases. II. Metabolic liver diseases. Mol. Genet. Metab. 127, 117–121 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  168. 168.

    Younossi, Z. M., Marchesini, G., Pinto-Cortez, H. & Petta, S. Epidemiology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis: implications for liver transplantation. Transplantation 103, 22–27 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  169. 169.

    Younossi, Z. M., Henry, L., Bush, H. & Mishra, A. Clinical and economic burden of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Clin. Liver Dis. 22, 1–10 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  170. 170.

    Goldberg, D. et al. Changes in the prevalence of hepatitis C virus infection, nonalcoholic steatohepatitis, and alcoholic liver disease among patients with cirrhosis or liver failure on the waitlist for liver transplantation. Gastroenterology 152, 1090–1099.e1 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  171. 171.

    Mikolasevic, I. et al. Nonalcoholic fatty liver disease and liver transplantation - where do we stand? World J. Gastroenterol. 24, 1491–1506 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  172. 172.

    Mittal, S. et al. Hepatocellular carcinoma in the absence of cirrhosis in United States veterans is associated with nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 14, 124–131.e1 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  173. 173.

    Singh, S. et al. Fibrosis progression in nonalcoholic fatty liver vs nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin. Gastroenterol. Hepatol. 13, 643–654.e1-9 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  174. 174.

    McPherson, S. et al. Evidence of NAFLD progression from steatosis to fibrosing-steatohepatitis using paired biopsies: implications for prognosis and clinical management. J. Hepatol. 62, 1148–1155 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  175. 175.

    Hoang, S. A. et al. Gene expression predicts histological severity and reveals distinct molecular profiles of nonalcoholic fatty liver disease. Sci. Rep. 9, 12541 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  176. 176.

    Younossi, Z. M. et al. Current and future therapeutic regimens for nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Hepatology 68, 361–371 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  177. 177.

    Sumida, Y. & Yoneda, M. Current and future pharmacological therapies for NAFLD/NASH. J. Gastroenterol. 53, 362–376 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  178. 178.

    Polyzos, S. A., Kountouras, J., Anastasiadis, S., Doulberis, M. & Katsinelos, P. Nonalcoholic fatty liver disease: Is it time for combination treatment and a diabetes-like approach? Hepatology 68, 389 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  179. 179.

    Dyson, J. et al. Hepatocellular cancer: the impact of obesity, type 2 diabetes and a multidisciplinary team. J. Hepatol. 60, 110–117 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  180. 180.

    Piscaglia, F. et al. Clinical patterns of hepatocellular carcinoma in nonalcoholic fatty liver disease: a multicenter prospective study. Hepatology 63, 827–838 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  181. 181.

    Wong, V. W., Adams, L. A., de Lédinghen, V., Wong, G. L. & Sookoian, S. Noninvasive biomarkers in NAFLD and NASH - current progress and future promise. Nat. Rev. Gastroenterol. Hepatol. 15, 461–478 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  182. 182.

    Greene, C. M. et al. α1-antitrypsin deficiency. Nat. Rev. Dis. Primers 2, 16051 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  183. 183.

    Hazari, Y. M. et al. Alpha-1-antitrypsin deficiency: genetic variations, clinical manifestations and therapeutic interventions. Mutat. Res. 773, 14–25 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  184. 184.

    Moat, S. J. et al. Performance of laboratory tests used to measure blood phenylalanine for the monitoring of patients with phenylketonuria. J. Inherit. Metab. Dis. 43, 179–188 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  185. 185.

    Blau, N. Genetics of phenylketonuria: then and now. Hum. Mutat. 37, 508–515 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  186. 186.

    Bergenthal, L. M., Shun, T. Y., Vernetti, L., Taylor, D. L. & Gough, A. H. The Microphysiology Systems Database http://mps.csb.pitt.edu (2018).

  187. 187.

    Shi, Y., Inoue, H., Wu, J. C. & Yamanaka, S. Induced pluripotent stem cell technology: a decade of progress. Nat. Rev. Drug Discov. 16, 115–130 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  188. 188.

    Takahashi, K. & Yamanaka, S. A decade of transcription factor-mediated reprogramming to pluripotency. Nat. Rev. Mol. Cell Biol. 17, 183–193 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  189. 189.

    Pei, F. et al. Connecting neuronal cell protective pathways and drug combinations in a Huntington’s disease model through the application of quantitative systems pharmacology. Sci. Rep. 7, 17803 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  190. 190.

    Chow, S. C. & Chang, M. Adaptive design methods in clinical trials - a review. Orphanet J. Rare Dis. 3, 11 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  191. 191.

    Fagiuoli, S., Daina, E., D’Antiga, L., Colledan, M. & Remuzzi, G. Monogenic diseases that can be cured by liver transplantation. J. Hepatol. 59, 595–612 (2013).

    PubMed  Article  PubMed Central  Google Scholar 

  192. 192.

    Isabella, V. M. et al. Development of a synthetic live bacterial therapeutic for the human metabolic disease phenylketonuria. Nat. Biotechnol. 36, 857–864 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  193. 193.

    Ghouse, R., Chu, A., Wang, Y. & Perlmutter, D. H. Mysteries of alpha1-antitrypsin deficiency: emerging therapeutic strategies for a challenging disease. Dis. Model. Mech. 7, 411–419 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  194. 194.

    Turner, A. M. et al. Hepatic-targeted RNA interference provides robust and persistent knockdown of alpha-1 antitrypsin levels in ZZ patients. J. Hepatol. 69, 378–384 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  195. 195.

    Hidvegi, T. et al. An autophagy-enhancing drug promotes degradation of mutant alpha1-antitrypsin Z and reduces hepatic fibrosis. Science 329, 229–232 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  196. 196.

    Bouchecareilh, M., Conkright, J. J. & Balch, W. E. Proteostasis strategies for restoring alpha1-antitrypsin deficiency. Proc. Am. Thorac. Soc. 7, 415–422 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  197. 197.

    Tafaleng, E. N. et al. Induced pluripotent stem cells model personalized variations in liver disease resulting from α1-antitrypsin deficiency. Hepatology 62, 147–157 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  198. 198.

    Low, L. A. & Tagle, D. A. Microphysiological systems (tissue chips) and their utility for rare disease research. Adv. Exp. Med. Biol. 1031, 405–415 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  199. 199.

    Blumenrath, S. H., Lee, B. Y., Low, L., Prithviraj, R. & Tagle, D. Tackling rare diseases: clinical trials on chips. Exp. Biol. Med. 245, 1155–1162 (2020).

    CAS  Article  Google Scholar 

  200. 200.

    Pan, G. Roles of hepatic drug transporters in drug disposition and liver toxicity. Adv. Exp. Med. Biol. 1141, 293–340 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  201. 201.

    Nguyen, D. G. et al. Bioprinted 3D primary liver tissues allow assessment of organ-level response to clinical drug induced toxicity in vitro. PLoS ONE 11, e0158674 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  202. 202.

    Norona, L. M., Nguyen, D. G., Gerber, D. A., Presnell, S. C. & LeCluyse, E. L. Editor’s highlight: modeling compound-induced fibrogenesis in vitro using three-dimensional bioprinted human liver tissues. Toxicol. Sci. 154, 354–367 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  203. 203.

    Norona, L. M. et al. Bioprinted liver provides early insight into the role of Kupffer cells in TGF-β1 and methotrexate-induced fibrogenesis. PLoS ONE 14, e0208958 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  204. 204.

    Trietsch, S. J., Israels, G. D., Joore, J., Hankemeier, T. & Vulto, P. Microfluidic titer plate for stratified 3D cell culture. Lab Chip 13, 3548–3554 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  205. 205.

    Domansky, K. et al. Perfused multiwell plate for 3D liver tissue engineering. Lab Chip 10, 51–58 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  206. 206.

    Novik, E., Maguire, T. J., Chao, P., Cheng, K. C. & Yarmush, M. L. A microfluidic hepatic coculture platform for cell-based drug metabolism studies. Biochem. Pharmacol. 79, 1036–1044 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  207. 207.

    Chao, P., Maguire, T., Novik, E., Cheng, K. C. & Yarmush, M. L. Evaluation of a microfluidic based cell culture platform with primary human hepatocytes for the prediction of hepatic clearance in human. Biochem. Pharmacol. 78, 625–632 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  208. 208.

    Dash, A. et al. Hemodynamic flow improves rat hepatocyte morphology, function, and metabolic activity in vitro. Am. J. Physiol. Cell Physiol. 304, C1053–C1063 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  209. 209.

    Boeri, L. et al. Advanced organ-on-a-chip devices to investigate liver multi-organ communication: focus on gut, microbiota and brain. Bioengineering 6, 91 (2019).

    CAS  PubMed Central  Article  Google Scholar 

  210. 210.

    Natarajan, V., Berglund, E. J., Chen, D. X. & Kidambi, S. Substrate stiffness regulates primary hepatocyte functions. RSC Adv. 5, 80956–80966 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  211. 211.

    Newman, R. H. & Zhang, J. The design and application of genetically encodable biosensors based on fluorescent proteins. Methods Mol. Biol. 1071, 1–16 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  212. 212.

    Collin de l’Hortet, A. et al. Generation of human fatty livers using custom-engineered induced pluripotent stem cells with modifiable SIRT1 metabolism. Cell Metab. 30, 385–401.e9 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  213. 213.

    Toepke, M. W. & Beebe, D. J. PDMS absorption of small molecules and consequences in microfluidic applications. Lab Chip 6, 1484–1486 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  214. 214.

    Regehr, K. J. et al. Biological implications of polydimethylsiloxane-based microfluidic cell culture. Lab Chip 9, 2132–2139 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  215. 215.

    Donato, M. T. & Tolosa, L. Stem-cell derived hepatocyte-like cells for the assessment of drug-induced liver injury. Differentiation 106, 15–22 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  216. 216.

    Rezvani, M., Grimm, A. A. & Willenbring, H. Assessing the therapeutic potential of lab-made hepatocytes. Hepatology 64, 287–294 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  217. 217.

    Tasnim, F. et al. Generation of mature kupffer cells from human induced pluripotent stem cells. Biomaterials 192, 377–391 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  218. 218.

    Coll, M. et al. Generation of hepatic stellate cells from human pluripotent stem cells enables in vitro modeling of liver fibrosis. Cell Stem Cell 23, 101–113.e7 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  219. 219.

    Parent, R. et al. An immortalized human liver endothelial sinusoidal cell line for the study of the pathobiology of the liver endothelium. Biochem. Biophys. Res. Commun. 450, 7–12 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  220. 220.

    Matsumura, T. et al. Establishment of an immortalized human-liver endothelial cell line with SV40T and hTERT. Transplantation 77, 1357–1365 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  221. 221.

    Maruyama, M. et al. Establishment of a highly differentiated immortalized human cholangiocyte cell line with SV40T and hTERT. Transplantation 77, 446–451 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  222. 222.

    Tabibian, J. H. et al. Characterization of cultured cholangiocytes isolated from livers of patients with primary sclerosing cholangitis. Lab. Invest. 94, 1126–1133 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  223. 223.

    Sampaziotis, F. et al. Cholangiocytes derived from human induced pluripotent stem cells for disease modeling and drug validation. Nat. Biotechnol. 33, 845–852 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  224. 224.

    Ghanekar, A. & Kamath, B. M. Cholangiocytes derived from induced pluripotent stem cells for disease modeling. Curr. Opin. Gastroenterol. 32, 210–215 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  225. 225.

    Poisson, J. et al. Liver sinusoidal endothelial cells: physiology and role in liver diseases. J. Hepatol. 66, 212–227 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  226. 226.

    Hammoutene, A. & Rautou, P. E. Role of liver sinusoidal endothelial cells in non-alcoholic fatty liver disease. J. Hepatol. 70, 1278–1291 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  227. 227.

    DeLeve, L. D. & Maretti-Mira, A. C. Liver sinusoidal endothelial cell: an update. Semin. Liver Dis. 37, 377–387 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  228. 228.

    Jang, S., Collin de l’Hortet, A. & Soto-Gutierrez, A. Induced pluripotent stem cell-derived endothelial cells: overview, current advances, applications, and future directions. Am. J. Pathol. 189, 502–512 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  229. 229.

    Li, J., Zhao, Y. R. & Tian, Z. Roles of hepatic stellate cells in acute liver failure: From the perspective of inflammation and fibrosis. World J. Hepatol. 11, 412–420 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  230. 230.

    Grunhut, J. et al. Macrophages in nonalcoholic steatohepatitis: friend or foe? Eur. Med. J. Hepatol. 6, 100–109 (2018).

    PubMed  PubMed Central  Google Scholar 

  231. 231.

    Nishimura, T. & Nakauchi, H. Generation of antigen-specific T cells from human induced pluripotent stem cells. Methods Mol. Biol. 1899, 25–40 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  232. 232.

    Wang, G. et al. Modeling the mitochondrial cardiomyopathy of Barth syndrome with induced pluripotent stem cell and heart-on-chip technologies. Nat. Med. 20, 616–623 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  233. 233.

    Brown, J. A. et al. Metabolic consequences of inflammatory disruption of the blood-brain barrier in an organ-on-chip model of the human neurovascular unit. J. Neuroinflammation 13, 306 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  234. 234.

    Jenkins, R. W. et al. Ex vivo profiling of PD-1 blockade using organotypic tumor spheroids. Cancer Discov. 8, 196–215 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  235. 235.

    Peck, R. W., Hinojosa, C. D. & Hamilton, G. A. Organs-on-chips in clinical pharmacology: putting the patient into the center of treatment selection and drug development. Clin. Pharmacol. Ther. 107, 181–185 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  236. 236.

    Yi, H. G. et al. A bioprinted human-glioblastoma-on-a-chip for the identification of patient-specific responses to chemoradiotherapy. Nat. Biomed. Eng. 3, 509–519 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  237. 237.

    Aref, A. R. et al. 3D microfluidic ex vivo culture of organotypic tumor spheroids to model immune checkpoint blockade. Lab Chip 18, 3129–3143 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  238. 238.

    Shirure, V. S. et al. Tumor-on-a-chip platform to investigate progression and drug sensitivity in cell lines and patient-derived organoids. Lab Chip 18, 3687–3702 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  239. 239.

    Miller, C. P., Shin, W., Ahn, E. H., Kim, H. J. & Kim, D. H. Engineering microphysiological immune system responses on chips. Trends Biotechnol. 38, 857–872 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  240. 240.

    Chen, W. L. K. et al. Integrated gut/liver microphysiological systems elucidates inflammatory inter-tissue crosstalk. Biotechnol. Bioeng. 114, 2648–2659 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  241. 241.

    Li, G., Huang, K., Nikolic, D. & van Breemen, R. B. High-throughput cytochrome P450 cocktail inhibition assay for assessing drug-drug and drug-botanical interactions. Drug Metab. Dispos. 43, 1670–1678 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  242. 242.

    Siramshetty, V. B. et al. WITHDRAWN–a resource for withdrawn and discontinued drugs. Nucleic Acids Res. 44, D1080–D1086 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  243. 243.

    Wikswo, J. P. et al. Integrated human organ-on-chip microphysiolocal systems. US patent US 2015/0004077 A1 (2015).

Download references

Author information

Affiliations

Authors

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to D. Lansing Taylor.

Ethics declarations

Competing interests

A.S.-G. is co-founder and D.L.T. is an adviser for Von Baer Wolff Inc., a company focused on biofabrication of autologous human hepatocytes using stem cell technology and genetic reprogramming to overcome liver failure. Their interests are managed by the Conflict of Interest Office at the University of Pittsburgh, USA, in accordance with their policies. The other authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Gastroenterology & Hepatology thanks J. Hickman, Y. Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

U.S. National Library of Medicine Clinical Trials.gov: https://clinicaltrials.gov/

Supplementary information

Glossary

Absorption, distribution, metabolism, excretion and toxicity

(ADMET). Studies conducted during the drug discovery, lead optimization and preclinical development phases to provide information for characterization and ranking of compounds based on their properties and to predict their fate after administration into the human body.

Micropatterned cell arrays

Methodologies, often based on nanofabrication, to fix one or more cell types on a substrate with precisely controlled spatial distributions.

Spheroids

In vitro 3D spherical aggregates of cells of either a single cell type or a combination of cells generated by a variety of 3D culturing methods.

Organoids

3D multicellular systems produced primarily from patient-specific stem cells and their progenies via in situ differentiation, cell sorting and self-organization processes.

Plate-based platforms

Platforms designed around microplate standards from the Society of Biomolecular Sciences, available in 6–1,536-well formats.

Fit-for-purpose

A drug development tool that has been accepted for use in a specific application based on thorough evaluation of the information provided.

Synthetic biology

An interdisciplinary area of science focused on the (re)design and construction of biological systems in a bottom-up fashion, often through the engineering of well-characterized genetic components, modules and devices to attain new functions or to correct dysregulated ones.

Secretome

A set of proteins expressed by cells (organs) and secreted into the extracellular space, including cytokines, growth factors, extracellular matrix proteins mediating autocrine, paracrine, endocrine (via circulation) and/or exocrine (via ducts) physiological regulation or pathophysiological dysregulation.

Clearance

The collection of processes by which the body removes a drug, generally categorized as metabolism or elimination.

Pharmacokinetic models

Quantitative models that predict how an organism influences the absorption, distribution, metabolism and excretion of a drug.

Pharmacodynamic models

A quantitative integration of pharmacokinetics, pharmacological systems and (patho-) physiological processes to understand the intensity and time course of drug effects on the body.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gough, A., Soto-Gutierrez, A., Vernetti, L. et al. Human biomimetic liver microphysiology systems in drug development and precision medicine. Nat Rev Gastroenterol Hepatol (2020). https://doi.org/10.1038/s41575-020-00386-1

Download citation

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing