Implementation of a Product Lifecycle Management System for Biomedical Research

Part 2: Information Technology Models and Systems Implementations ; International audience ; Today’s biomedical research shows similar characteristics with manufacturing industry 20 years ago. Biomedical data are more and more complex and heterogeneous due to recent scientific discoveries and technological innovations. In a previous work, the Product Lifecycle Management (PLM) paradigm was applied to neuroimaging research to manage heterogeneous data and their provenance. A BMI-LM data model and an associated platform were proposed to enable data reuse and sharing in neuroimaging. Here, this application is extended to biomedical data related to Histology, Proteomics, and PET-CT modalities. Data originate from the IVIR laboratory in preclinical research of the Paris Cardiovascular Research Center (PARCC). We proposed a data and workflow integration method and applied them to the collected preclinical data. An extended version of the data model, that we called BMS-LM for BioMedical Study – Lifecycle Management, was developed. Three concepts were added to the data model: Agent, Sample and Intervention. As a proof of concept, samples of imported data from the three identified modalities are given. Results support the use of the BMS-LM data model and system to ameliorate trust of biomedical data and prospectively their reuse.