Analyzing biomedical Neuropathological data from subjects of clinical studies is complicated by the diverse data types due to the variety of spatiotemporal scales at which data is collected. MG is built on an integrated graph database platform which allows its users to ingest, organize, and correlate data from clinical trials, public databases, and proprietary multi-omics data. A graph representation of the multimodal data enables the users to explore structure-function relationships across different scales (from molecular to behavioral), and to model the response of the system to pharmacologic manipulations. It also incorporates gene expression data obtained from brain samples of a representative subject and simulated pharmacokinetic data in the cerebrospinal fluid. MG provides the framework for curation, visualization, and annotation of graph-based data, enabling the analysis of relationships between different types of biomedical data to derive novel hypotheses to accelerate drug development. In this session, Mr. Chandrashekar Dixith will talk about how graph database platform allows its users to ingest, organize, and correlate data from clinical trials and FEM Simulations of Pharmacodynamics and visualization. Chandrashekar Dixith has more than fifteen years of experience in mathematical modeling and simulation and last three. years he has been working on Neuro pathology involving ‘data modelling of brain graph’, ‘development of schema for visualization of disease progression in anatomical regions of brain’, and ‘supporting study data analysis and management’.

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21:30 - 22:00 hs GMT+1

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Umesh Hodeghatta
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