Engineering liver

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 unprece...

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Bibliographic Details
Main Authors: Griffith, Linda G. (Contributor), Wells, Alan (Author), Stolz, Donna B. (Author)
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor)
Format: Article
Language:English
Published: Wiley Blackwell, 2015-10-21T12:00:45Z.
Subjects:
Online Access:Get fulltext
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001 99381
042 |a dc 
100 1 0 |a Griffith, Linda G.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Biological Engineering  |e contributor 
100 1 0 |a Griffith, Linda G.  |e contributor 
700 1 0 |a Wells, Alan  |e author 
700 1 0 |a Stolz, Donna B.  |e author 
245 0 0 |a Engineering liver 
260 |b Wiley Blackwell,   |c 2015-10-21T12:00:45Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/99381 
520 |a 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. 
520 |a National Institutes of Health (U.S.) (UH2TR000496) 
520 |a National Institutes of Health (U.S.) (R01-EB 010246) 
520 |a National Institutes of Health (U.S.) (R01-ES015241) 
520 |a National Institutes of Health (U.S.) (P30-ES002109) 
546 |a en_US 
655 7 |a Article 
773 |t Hepatology