Abstract: Described are techniques for determining one or more logical data objects for a storage location. The storage location indicating a location on a device of a data storage system is provided. A list of one or more logical data objects is received. For each of the one or more logical data objects, one or more related data storage system locations associated with each logical data object are determined. It is determined whether the storage location is included in any of the one or more logical data objects. It is also identified whether, for each of the one or more logical data objects, the storage location is one of the one or more related data storage system locations associated with each logical data object.

Abstract: The attached disclosure provides a systems approach based on mathematical modelling of the kinetics of essential biochemical pathways involved in organ homeostasis. When this in silico model is coupled with in-vitro and/or in-vivo measurements to quantify drug-induced perturbations, a powerful platform that allows accurate and mechanistic-level prediction of drug-induced organ injury can be generated. The method described in this disclosure demonstrates that several physiological situations can also be accurately modelled in addition to the effect of perturbations induced by drugs. It can also be used along with high-throughput “omics” data to generate testable hypotheses leading to informed decision-making in drug development.

Abstract: The present disclosure relates to a methodology that identifies the underlying mechanisms that lead to hepatotoxicity. This is done by using the alterations in cellular metabolite profiles obtained before and after therapy/drug treatment in combination with a model of liver metabolism. Subsequently, by using a covariance matrix adaptation followed by evolutionary selection, it compares the drug-induced metabolite profiles obtained experimentally with those generated using the in silico model, automatically shortlists potential parameters whose alterations could have produced the drug-treated metabolite profile. Values of these parameters are estimated by formulating an optimal control problem to minimize the differences between the model-generated metabolite values and experimentally observed data. The estimated parameters are given as an input to the homeostatic liver model and simulations are carried out, thereby the results providing a mechanistic explanation for the development of toxicity.

Abstract: The attached disclosure provides a systems approach based on mathematical modelling of the kinetics of essential biochemical pathways involved in organ homeostasis. When this in silico model is coupled with in-vitro and/or in-vivo measurements to quantify drug-induced perturbations, a powerful platform that allows accurate and mechanistic-level prediction of drug-induced organ injury can be generated. The method described in this disclosure demonstrates that several physiological situations can also be accurately modelled in addition to the effect of perturbations induced by drugs. It can also be used along with high-throughput “omics” data to generate testable hypotheses leading to informed decision-making in drug development.