Engineering liver

Authors

  • Linda G. Griffith,

    Corresponding author
    1. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA
    • Address reprint requests to: Linda G. Griffith, Ph.D., Department of Biological Engineering, Massachusetts Institute of Technology, Room 16-429, 77 Massachusetts Avenue, Cambridge, MA 02139. E-mail: griff@mit.edu; fax: 617-253-2400.

    Search for more papers by this author
  • Alan Wells,

    1. Department of Pathology, University of Pittsburgh Medical School, Pittsburgh, PA
    Search for more papers by this author
  • Donna B. Stolz

    1. Department of Cell Biology and Center for Biological Imaging, University of Pittsburgh Medical School, Pittsburgh, PA
    Search for more papers by this author

  • Potential conflict of interest: Nothing to report.

  • This work was supported by supported by the National Institutes of Health (UH2TR000496, R01-EB 010246, R01-ES015241, and P30-ES002109).

Abstract

Interest in “engineering liver” arises from multiple communities: therapeutic replacement; mechanistic models of human processes; and drug safety and efficacy studies. An explosion of micro- and nanofabrication, biomaterials, microfluidic, and other technologies potentially affords unprecedented opportunity to create microphysiological models of the human liver, but engineering design principles for how to deploy these tools effectively toward specific applications, including how to define the essential constraints of any given application (available sources of cells, acceptable cost, and user-friendliness), are still emerging. Arguably less appreciated is the parallel growth in computational systems biology approaches toward these same problems—particularly in parsing complex disease processes from clinical material, building models of response networks, and in how to interpret the growing compendium of data on drug efficacy and toxicology in patient populations. Here, we provide insight into how the complementary paths of engineering liver—experimental and computational—are beginning to interplay toward greater illumination of human disease states and technologies for drug development. (Hepatology 2014;60:1426–1434)

Ancillary