Abstract: Provided is a method, including obtaining data associated with clinical trials, storing the obtained data into a repository by preprocessing the data to standardize diverse input formats into unified data model and organizing the stored data into a schema designed to integrate data of diverse input formats, indexing the stored data and analyses performed on the stored data, selecting one or more visualizations responsive to the query by selecting one or more visualizations as being responsive to the query based on metadata associated with each of the one or more visualizations, determining whether the stored data is associated with a plurality of metadata requirements of each of the one or more visualizations, dynamically generating executable code configured to generate the one or more visualizations responsive to the query, executing the generated executable code, and providing a response to the query.

Abstract: Provided is a process including: accessing clinical trial data of an ongoing clinical trial that is not yet complete, the clinical trial having a plurality of treatment groups and a plurality of patients in the treatment groups; detecting, with an anomaly detection model, an anomaly in the clinical trial data for a first patient, the anomaly corresponding to a first patient among the plurality of patients; in response to detecting the anomaly classifying the first patient as anomalous in the trial; generating, with the computer system, by an artificial intelligence model, a candidate explanation for the detected anomaly by designating data in a record for the first patient as potentially correlated with the anomaly; and causing the anomaly and the candidate explanation to be presented to a data safety monitoring board (“DSMB”) of the clinical trial.

Abstract: Provided is a method, including obtaining data associated with clinical trials, storing the obtained data into a repository by preprocessing the data to standardize diverse input formats into unified data model and organizing the stored data into a schema designed to integrate data of diverse input formats, indexing the stored data and analyses performed on the stored data, selecting one or more visualizations responsive to the query by selecting one or more visualizations as being responsive to the query based on metadata associated with each of the one or more visualizations, determining whether the stored data is associated with a plurality of metadata requirements of each of the one or more visualizations, dynamically generating executable code configured to generate the one or more visualizations responsive to the query, executing the generated executable code, and providing a response to the query.

Abstract: Provided is a process, including: obtaining data assets characterizing a plurality of clinical studies, selecting a first subclass from a hierarchy of classes for the first data asset, selecting a second subclass from the hierarchy of classes for the second data asset, transforming the first data asset into the shared data format and data schema using the respective selected subclass storing transformation data including unique subject identifier mapping, the selected subclass, and the first format and first data schema of the first data asset, and saving resulting transformed first data asset in the shared data format and data schema in memory.

Abstract: A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

Abstract: A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.