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:10.3390/computation5040046

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^*

^*Corresponding author for this work

Surgery

Research output: Contribution to journal › Review article › peer-review

2 Scopus citations

Abstract

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.

Original language	English
Article number	46
Journal	Computation
Volume	5
Issue number	4
DOIs	https://doi.org/10.3390/computation5040046
State	Published - 1 Dec 2017

Keywords

Computational modeling
Extracorporeal organ perfusion
Transplantation

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title = "Dynamic data-driven modeling for ex vivo data analysis: Insights into liver transplantation and pathobiology",

abstract = "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.",

keywords = "Computational modeling, Extracorporeal organ perfusion, Transplantation",

author = "David Sadowsky and Andrew Abboud and Anthony Cyr and Lena Vodovotz and Paulo Fontes and Ruben Zamora and Yoram Vodovotz",

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AU - Sadowsky, David

AU - Abboud, Andrew

AU - Cyr, Anthony

AU - Vodovotz, Lena

AU - Fontes, Paulo

AU - Zamora, Ruben

AU - Vodovotz, Yoram

PY - 2017/12/1

Y1 - 2017/12/1

N2 - 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.

AB - 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.

KW - Computational modeling

KW - Extracorporeal organ perfusion

KW - Transplantation

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JO - Computation

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ER -

Dynamic data-driven modeling for ex vivo data analysis: Insights into liver transplantation and pathobiology

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Keywords

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