Multi-Modal Medical Data Analysis Platform (3MDAP) for analysis and predictive modelling of cancer trial data

Abstract

This paper presents a user-friendly web-based collaborative environment for analyzing, assessing the quality of large multi-level clinical datasets and deriving predictive models. The Multi-Modal Medical Data Analysis Platform (3MDAP) follows two main objectives: a) to empower the user to analyze with ease clinic-genomic data in order to get simple statistics on selected parameters, perform survival analyses, compare regiments in selected cohort of patient and obtain genomic analysis results, and b) to perform heterogeneous clinical data modeling for deriving and cross-validating in multiple datasets predictive clinic-genomic models of patient response, and assessing the value of candidate biomarkers. 3MDAP's enhanced functionality is coupled with a security framework for enabling user authentication and authorization, a set of services that facilitate the process of loading and retrieving data from a data-warehouse (either locally based or in a cloud), and a widget-based front-end environment for assisting users in interacting with the platform's functionality in a user friendly manner. For each running analysis, 3MDAP supports an engine to create dynamically analysis reports. Last, the framework provides an internal database where a full analysis record of an executed analysis is stored, including metadata information (i.e. timestamp information, the examined data, any memory constraints, the dynamically generated reports in both .pdf and .html format, and etc.) in order to be used for future reference.