Novel quantitative tools for engineering analysis of hepatocyte cultures in bioartificial liver systems

Abstract

Extracorporeal bioartificial liver devices (BAL) are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to plasma from the patient, hepatocytes are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. Based on hepatic intermediary metabolism, we have utilized mathematical programming techniques to optimize the biochemical environment of hepatocyte cultures towards the desired effect of increased albumin and urea synthesis. To investigate the feasible range of optimal hepatic function, we have obtained a Pareto optimal set of solutions corresponding to liver-specific functions of urea and albumin secretion in the metabolic framework using multiobjective optimization. The importance of amino acids in the supplementation and the criticality of the metabolic pathways have been investigated using logic-based programming techniques. Since the metabolite measurements are bound to be patient specific, and hence subject to variability, uncertainty has to be integrated with system analysis to improve the prediction of hepatic function. We have used the concept of two stage stochastic programming to obtain robust solutions by considering extracellular variability. The proposed analysis represents a new systematic approach to analyze behavior of hepatocyte cultures and optimize different operating parameters for an extracorporeal device based on real-time conditions.

Control of hepatic differentiation via cellular aggregation in an alginate microenvironment

“…One specific application of ES cells is the derivation of a renewable hepatocyte cell source, needed for the development of bioartificial livers (Balis et al, 2002;Chan et al, 2004;Sharma et al, 2005;Shinoda et al, 2006;Shito et al, 2003;Yarmush et al, 1992), environmental biosensors (Otsuka et al, 2004;Sin et al, 2004), and in vitro drug screening systems (Dambach et al, 2005;LeCluyse, 2001). The successful development of these applications lies in expanding a large hepatocyte cell mass.…”

Stoichiometric Modeling of Oxygen Transportation through the Surface of Isolated Perfused Rat Liver

“…Поэтому для определения распределения субстратных потоков в печени необходимо поставить задачу многокритериального программирования с максимизацией синтеза мочевины и АТФ. Для решения данной задачи в работе использовали метод ε-ограничений [30], который максимизирует основную целевую функцию при ограничениях, накладываемых на дополнительную целевую функцию. Здесь в качестве основной целевой функции использовали скорость продукции АТФ, а в качестве дополнительной -синтез мочевины.…”

Multiobjective Optimization in Bioinformatics and Computational Biology

“…Other examples of the use of multiobjective optimization for process optimization are applications related to the beer fermentation process [122], the citric acid fermentation of Aspergillus niger [14], the production of gluconic acid [123], as well as investigations regarding optimal liver function [124] and the production of oil in the yeast Yarrowia lipolytica [125].…”