Scalable solution for big data analysis in Healthcare
The AEGLE platform offers a scalable solution for analysing big healthcare data, which includes the ability for users to pseudo-anonymize data conforming to EU regulations and the security measures, ensuring data analysis and storage on a secure cloud platform accessible only to users with the necessary access requirements.
The platform can be offered with two user interfaces (UI). A research-oriented UI (R&D-UI) and a clinical decision support UI (CDS-UI). Both can be customized to the user’s needs. The platform has been developed for three scenarios, namely analysing next generation sequencing (NGS) and immunogenetics data, analysing monitoring data for Intensive Care Units (ICU) and analysing electronic health records (EHR) data for non-malignant chronic diseases such as diabetes.
The platform for analysing next generation sequencing (NGS) and immunogenetics data has been developed for researchers with an affiliation with chronic lymphocytic leukaemia. However, the platform can also be used by researchers in academic institutes, commercial labs and industry who aim to study NGS and immunogenetics data from other disease areas.
For whole exome/genome and RNA-sequencing data, the platform offers acceleration services when aligning reads prior to variant calling, annotation and interpretation and transcript assembly and expression analysis. Moreover, with the AEGLE platform, immunogenetics data can be filtered and analysed, enabling categorization of stereotyped subsets, mutation analysis and computation of public and exclusive clonotypes in samples. The visualization tools offer an integrated presentation of results from multiple data types for faster interpretation. The analyses of immunogenetics data is a feature where AEGLE can distinguish itself from competitors such as DNANexus and SevenBridges.
Watch below the video recording of the AEGLE Demonstration Webinar for (Clinical) Researchers on the Chronic Lymphocytic Leukaemia use case:
For the ICU, a platform can be offered with a CDS-UI and an R&D-UI. The platform is developed using data from ventilation and biosignal monitors (i.e. heart rate variability) and offers accelerated (predictive) analytics for nutrition optimization, catheter related bloodstream infection (CRBSI), deterioration, ineffective efforts and high driving pressure.
Watch below the video recordings of the AEGLE Demonstration Webinar for (Clinical) Research and for Clinical Practice on the ICU use case:
For non-malignant chronic diseases, like diabetes mellitus type 2, AEGLE offers a research platform that allows clinical researchers, hospitals management and pharmaceutical organisations to analyse their own EHR data. The platform and analytics available in AEGLE platform offer users much more flexibility in deciding what to analyse and for which patient populations in the hospital to develop/use predictive analytics. The analytics included can facilitate research into pharmacovigilance, treatment response, and complications whilst the visualization tools such as heatmaps and population pyramids can be used for hypothesis generation, but also presentation of quality metrics.
Watch below the video recordings of the AEGLE Demonstration Webinar for (Clinical) Research on the Non-Malignant Chronic Diseases use case: