Our Platform

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.

Chronic Lymphocytic Leukaemia applications

Next Generation Sequencing (NGS) and Immunogenetics Data

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.

 

Main Benefits:

 

  • The AEGLE platform offers all standard analytics for human genome, exome and transcriptome data: moreover, the ability to concurrently analyse NGS immunogenetics data makes the platform truly unique.
  • The AEGLE platform can be used by researchers with advanced programming experience but also by researchers whom are less computer literature.
  • The user interacts with the platform through an accessible, user friendly interface and de novo visualization tools allowing users to easily visualize their results after analysis.
  • The AEGLE platform will support bioinformaticians in building their own pipelines or implementing existing pipelines (i.e. from the literature) on the platform.
  • Data is initially collected by clinicians, sequenced and converted (in an automated way) to the appropriate format using available tools.
  • The AEGLE platform enables the pseudo-anonymization of data conforming to EU regulations and its upload on AEGLE’s private cloud.
  • The AEGLE platform offers a solid access control mechanism ensuring security of data whilst enabling a workspace where users can share analytics, workflows and datasets with collaborators whom have been granted access.
  • The AEGLE platform can be purchased independently from existing NGS analytics and adopts a flexible, scalable model where users only pay for the storage and run-time they use.
 

Watch below the video recording of the AEGLE Demonstration Webinar for (Clinical) Researchers on the Chronic Lymphocytic Leukaemia use case:

 

 

Intensive Care Unit (ICU) applications

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.

 

Main benefits of the R&D-UI:

 

  • Several existing solutions offer local data storage and management whilst AEGLE platform offers scalable, fast cloud-based storage and data management.
  • With AEGLE platform, the patient data is pseudo-anonymized conforming to EU regulations prior to uploading.
  • The data of individual patients can be updated regularly, and this data can be used to improve and customize existing algorithms.
  • The R&D-UI offers an extensive package of analytics both descriptive and predictive.
  • Researchers have the ability to further improve and customize predictive analytics and present results using customized visualization tools.
  • All analyses can be accelerated which can result in faster results than current practice.
  • The analytics and visualisation tools can be used both for research purposes but also for generating quality metrics and gaining insight into the characteristics of the ICU population.
  • Other Platforms only include analytics for catheter-related bloodstream infection (CRBSI) and deterioration, however, the AEGLE platform also includes analyses of clusters of ineffective efforts (IEEVs), high driving pressure and nutrition optimisation.
 
 

Main benefits of the CDS-UI:

 

  • The AEGLE platform supports data from multichannel ICU monitors and ventilators.
  • The platform can provide real-time clinical decision support for identifying suboptimal nutrition, CRBSI, deterioration, and ineffective efforts. These results are then visualized on the local dashboard enabling the clinician to intervene.
  • The AEGLE analytics in the CDS-UI trigger a warning when IEEVs occur enabling the clinician to intervene.
  • Analytics in the CDS-UI aim to improve nutrition monitoring for ICU patients which may increase the percentage for whom the nutrition target is achieved with 0.34.
  • Using the electronic health record data, the CDS-UI can provide a risk score that a patient will develop catheter-related bloodstream infection (CRBSI). When the score of the patient is high, a clinician can replace the catheter and start treatment.
  • Combined, the analytics for IEEVs, nutrition and CRBSI hold the potential to save hospitals €2,557 and increase quality adjusted life years with 0.12 on average per patient.
 

Watch below the video recordings of the AEGLE Demonstration Webinar for (Clinical) Research and for Clinical Practice on the ICU use case:

 

 

Non-Malignant Chronic Diseases applications

Diabetes Mellitus Type 2

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.

 

Main benefits:

 

  • The scalability of AEGLE platform ensures it can handle any future changes to the data, such as the addition of monitoring data, collected for diabetes mellitus type 2 care.
  • The platform facilitates easier data management and analysis for researchers interested to access these databases.
  • The AEGLE platform demonstrates the ability to merge diverse databases at the cloud level to create a large dataset given the underlying data structures are identical, thereby harnessing and releasing the full potential of big data analysis for the diabetic patient group.
  • AEGLE platform offers a cloud-based solution. Prior to uploading data, the data is pseudo-anonymized conforming to EU regulations.
  • AEGLE platform offers users the ability to use, develop and improve predictive analytics and stratification of their patients with chronic diseases. These analytics can be used to personalize patient care.
  • The platform enables users to visualize the data, generate quality metrics and explore differences between providers using for instance population pyramids and heat maps.
  • The solutions offered by AEGLE platform are scalable and can handle large amounts of complex data.
  • AEGLE platform possesses a feature to collect data in the future by offering an app for diabetes patients to track their health.
 

Watch below the video recordings of the AEGLE Demonstration Webinar for (Clinical) Research on the Non-Malignant Chronic Diseases use case:

 

 

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