Abstract: A method comprising retrieving a plurality of clinical trial records from a clinical trial database; mapping each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records; merging each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries; estimating imputed enrollees for each of the merged data entries; determining a ranking for each of the one or more ranking factors for each of the merged data entries; determining a score for each of the merged data entries based on the rankings; and generating a visualizer based on at least the score for each of the merged data entries.

Abstract: A computer-implemented method for clinical trial results endpoint-based analysis and dynamic aggregation, comprising the steps of receiving one or more selected clinical trials, wherein the one or more selected clinical trials match a specification; obtaining clinical trial results for the one or more selected clinical trials from at least one external data source; and interpreting, via a machine learning model, the obtained clinical trial results; importing the obtained clinical trial results as structured data. The method further comprising the steps of matching, based on a similarity analysis, via a processor, clinical trial endpoints identified in the obtained clinical trial results to corresponding normalized endpoint options; aggregating, based on the matched corresponding normalized endpoint options, the obtained clinical trial results to determine aggregated results; and providing the aggregated results.