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Big Data Platform

 

From data to the next generation of care

The HARMONY BigData Platform is a secure, innovative research data ecosystem providing a large data lake and state-of-the-art analytic services. The anonymous patient data sets at the Big Data Platform are collected securely following all legal and ethical requirements, harmonized and then analyzed. The data sets are provided by HARMONY Alliance Partners and Associated Members.


HARMONY Data Exploration and Outcome Prediction Tools

Over 165,000 blood cancer patient datasets have been identified and 115,000 records are currently available for analysis on the HARMONY Big Data Platform. We developed Data Exploration Tools where you can now explore data. This new tool is now available for ALL and AML cohorts and will soon be a reality for more Hematological Malignancies. The AML Outcomes Prediction Calculator is a machine-learning model. Click on the links below to gain access and start exploring! 



The HARMONY Data Exploration tool has been developed to facilitate the visualization of baseline data to foster the generation of new research ideas. You can select the characteristics of the cohort that are interesting for your research idea and see the number of cases that are currently available within the HARMONY Big Data Platform. 

The HARMONY Outcomes Prediction Calculator provides data-driven predictions to help clinicians decide if AML patients should be considered for allogeneic transplantation, especially in countries where targeted therapies are not available. 

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BigData Platform

The HARMONY BigData Platform is a governed data lake powered by advanced Big Data analytics created to speed up hematology research. It is a best-practice-based data platform where data submitted from various sources – once harmonized and anonymized – create a cohesive data lake ready for scientific research. Beyond a robust technical infrastructure, the Platform offers a secure and trusted research environment compliant with data processing regulations and ethical guidelines. So that researchers can focus on research instead of administrative issues of working on data. By the end of 2023, approximately 165,000 patient datasets had been identified, fortifying algorithms in their quest for new knowledge. Check our Databarometer >.


Converting data into insights

The HARMONY Alliance data processing pipeline consists of multiple steps:

Machine learning (ML) takes data analytics to a deeper level. ML algorithms operate without explicit instructions, relying on discovered patterns to make independent decisions and predictions – the system itself searches for links in the data without instructions on what it should look for. The new correlations identified by ML continue to be carefully evaluated and validated to ensure their accuracy and reliability.



Data security features 

Data protection and patient privacy are top priorities for HARMONY. A two-step data anonymization approach, known as the HARMONY Anonymization Concept, has been developed in collaboration with legal experts. It adheres to ethical guidelines and EU data protection regulations, including the General Data Protection Regulation (GDPR). The Platform enforces strict rules to prevent unauthorized data access. Scientists involved in the project are granted access only to data aligned with their expertise and legitimate research inquiries. This robust combination of ethical practices, modern technical safeguards, and data security ensures the research is innovative and well-secured. 


The Big Data Platform includes tools enabling research teams to analyze data at scale. The data scientists curating the Harmony BigData Platform developed ready-to-use models to promptly answer research questions. Interactive dashboards offer easy data analysis by applying statistical templates and pre-defined visualization tools. On the dashboard, the user can customize the variables to start modelling data to get searched results or understand trends, patterns, and insights within the data. On the HARMONY BigData Platform, researchers and data scientists can test their scientific hypotheses or explore the patterns in data. They gain new capabilities to characterize the molecular landscape of blood cancers, understand their pathophysiology, unlock the understanding of disease progression, and identify novel drug targets. 


Healthcare professionals can benefit from new insights, paving the way for precision medicine.

A better understanding of the course of blood cancers enables physicians to tailor therapies, moving from a "one-fits-all" to a "one-fits-one" approach. This is how the healthcare of the future – personalized, predictive, preventive, and participatory – is becoming within reach today.