Computation (Nov 2017)

Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology

  • David Sadowsky,
  • Andrew Abboud,
  • Anthony Cyr,
  • Lena Vodovotz,
  • Paulo Fontes,
  • Ruben Zamora,
  • Yoram Vodovotz

DOI
https://doi.org/10.3390/computation5040046
Journal volume & issue
Vol. 5, no. 4
p. 46

Abstract

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Extracorporeal organ perfusion, in which organs are preserved in an isolated, ex vivo environment over an extended time-span, is a concept that has led to the development of numerous alternative preservation protocols designed to better maintain organ viability prior to transplantation. These protocols offer researchers a novel opportunity to obtain extensive sampling of isolated organs, free from systemic influences. Data-driven computational modeling is a primary means of integrating the extensive and multivariate data obtained in this fashion. In this review, we focus on the application of dynamic data-driven computational modeling to liver pathophysiology and transplantation based on data obtained from ex vivo organ perfusion.

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