Background: In Silico Livers (ISLs) are works in progress. They are used to challenge multilevel, multi-attribute,\r\nmechanistic hypotheses about the hepatic disposition of xenobiotics coupled with hepatic responses. To enhance\r\nISL-to-liver mappings, we added discrete time metabolism, biliary elimination, and bolus dosing features to a\r\npreviously validated ISL and initiated re-validated experiments that required scaling experiments to use more\r\nsimulated lobules than previously, more than could be achieved using the local cluster technology. Rather than\r\ndramatically increasing the size of our local cluster we undertook the re-validation experiments using the Amazon\r\nEC2 cloud platform. So doing required demonstrating the efficacy of scaling a simulation to use more cluster\r\nnodes and assessing the scientific equivalence of local cluster validation experiments with those executed using\r\nthe cloud platform.\r\nResults: The local cluster technology was duplicated in the Amazon EC2 cloud platform. Synthetic modeling\r\nprotocols were followed to identify a successful parameterization. Experiment sample sizes (number of simulated\r\nlobules) on both platforms were 49, 70, 84, and 152 (cloud only). Experimental indistinguishability was\r\ndemonstrated for ISL outflow profiles of diltiazem using both platforms for experiments consisting of 84 or more\r\nsamples. The process was analogous to demonstration of results equivalency from two different wet-labs.\r\nConclusions: The results provide additional evidence that disposition simulations using ISLs can cover the\r\nbehavior space of liver experiments in distinct experimental contexts (there is in silico-to-wet-lab phenotype\r\nsimilarity). The scientific value of experimenting with multiscale biomedical models has been limited to research\r\ngroups with access to computer clusters. The availability of cloud technology coupled with the evidence of\r\nscientific equivalency has lowered the barrier and will greatly facilitate model sharing as well as provide\r\nstraightforward tools for scaling simulations to encompass greater detail with no extra investment in hardware.
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