Abstract: A computer-implemented method of analyzing a dataset of pharmacovigilance data, includes determining a sample size-independent measure of association between two conditions of interest in the dataset of pharmacovigilance data; using a hypergeometric distribution to determine a measure of statistical unexpectedness between the conditions of interest in said dataset, wherein the distribution is based on an urn model under a hypothesis that the conditions are statistically independent; and displaying the measure of association with the measure of the statistical unexpectedness to identify a significant association between conditions of interest.

Abstract: A method, system, and software for providing clinical data for analysis. purposes, includes storing clinical data, received from one or more data source sites, in a data repository. On receiving a request for data from the data repository from a user at a data source site, a working set of data is created responsive to the request from the user, and the user is provided access to the working set for analysis purposes. The working set of data is created such that at least some of the data in the working set is unchanged while the analysis is performed even if the data repository is updated while the analysis is performed, and working set only includes restricted data from other data source sites other than the data source site of the user.

Abstract: An information processing method and system, for synchronization of disease progression data of individual patients, includes receiving disease progression data in an aperiodic form and representing the disease progression data as a set of functions having finite asymptotic values. The parameters of the set of functions are clustered and the step of representing the disease progression data as a set of functions includes transforming the functions into time invariant form and thereby synchronizing individual patient data that is clustered.