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Virtual Liver: Assessing for Risks
Virtual Liver Navigation
Introduction
The liver plays a key role in removing chemicals from the body and frequently shows the earliest signs of their harmful effects. Animal testing gives useful information about the effects of environmental chemicals, however, the relevance of these findings to humans is not always clear. To address this challenge scientists at The National Center for Computational Toxicology are leading the development of a "Virtual Liver", which is a large-scale biologically-based computer model of the organ. The long-term objective of the Virtual Liver is to simulate the effect of chemicals accurately, efficiently and more humanely.
There are many steps involved in understanding the risk of chemicals in the environment to human health. Estimating this risk is necessary for the EPA to regulate safe levels of a chemical in the environment. Animal testing is the standard approach for understanding toxic effects of chemicals but there are rising concerns about the relevance of these studies to humans. In addition, ethical and economic concerns are demanding alternative toxicity testing approaches. The Virtual Liver project aims to address some of these issues. As the key metabolic organ for degrading harmful substances that enter the body through food or water, the liver frequently shows the earliest signs of injury due to chemicals. The liver also plays a central role in the synthesis and metabolism of hormones and other chemicals that the body uses to maintain appropriate function. So understanding whether and/or how a chemical could damage the liver will facilitate estimation of safe levels for humans. When using the currently available methods, it takes up to two years, hundreds of animals and millions of dollars to find out if a chemical is toxic. Human risk assessment will be more effective, efficient and humane if the biological phenomena involved in the fate chemicals through the body and the liver could be predicted accurately. The Virtual Liver aims to simulate these phenomena using large-scale computational models.