Molecular Medicine Tri-Con

Feb 17th 2021

Translational and precision medicine development in immuno and gene therapies rely on biomarker data from assays including genomics, proteomics, IHC, Flow cytometry and cell phenotyping data. Biomarkers are not only generated from the patient Bio samples, but also from the biomanufacturing sites such as in adoptive immune cell biomanufacturing for novel immunotherapies. Extracting valuable insights from these disparate data sources and integrating it to clinical data to relate to patient outcome and/or discover and validate relevant biomarkers are met with challenges of ingestion, harmonization and integration of disparate data with the clinical data. Key decisions and ideas that impact study design of future clinical trials depend on gaining insights rapidly from such integrated data on patients or stratified cohorts. Systematic curation with self-validation for completeness and consistency is time consuming and difficult without technology. Xbiom, built on Machine Learning and Universal Data Modelling effectively solves these challenges of disparate, big and varied data sources. Xbiom’s Smart Transformation platform, can make ingestion, curation, and harmonization process automatic and is also capable of processing both streamed data as well as in batch mode.

Poster: A Universal Data Model for Longitudinal Integration of Disparate Biomarker and In-Life Patient Data Augmented by Machine Learning
Click here to View Abstract