WP5 will work on providing the means for analyzing complex data sets comprised of different layers of information. This will enable molecular and clinical data to be linked to predicting outcomes. Its activity will be centered on the description, analysis, and modeling of the data collected, which will then be generated into a personalized medicine framework. Tools and models will be implemented to answer the most important disease-specific questions and will be applicable to cross-disease analyses.
- Harmonizing data according to their heterogeneity and complexity, with a special emphasis on statistical data cleaning (which identifies and corrects any abnormalities in the data) and statistical harmonization (normalization);
- Characterizing any variables that impact the data collected;
- Describing and modeling outcomes, particularly those related to disease progression, responder/non-responder factors, quality of life, healthcare resource use, and cost;
- Using economic analysis tools to identify and compare the value of HM care;
- Integrating data to create a holistic approach in a personalized medicine framework;
- Reporting on the cost-effectiveness of therapies and their societal value (including information on the quality of life).
AEMPS, Amgen, AP-HP, Barts Health, Bayer, BFArM, EBMT, ELN, EORTC, Erasmus MC, ERIC, FISM Onlus, GFM, GMV, Goethe University, GPOH, GRAALL, GRL-SANGER, HHU, HULAFE, IECSCYL-IBSAL, IJC, Janssen, LeukaNET, LMU, LYSA, MediSapiens, MenarinI, MLL, MU, Newcastle University, NICE, Novartis, OPBG, Takeda, Ulm University, UNIBO, UNITO, University of Cambridge, University of Helsinki, University of Navarra, University of Rome Tor Vergata, University of York, VHIO, VIB, Vumc.
Considerable progress has been made in terms of establishing the Big Data platform and the methodology for analyzing data:
- In relation to service access and implementation of security standard ISO27001, all the services have been improved; all services can be accessed from a secure shell cryptographic network (SSH) or from a virtual private network (VPN); and all the processes related to security standard ISO27001 are in operation.
- Coordination with WP3-4 to define the workflow for data intake and research question formulation. Test access to platform; contact with the first relevant data owners to define terms for collaboration in data analysis
- HARMONY's Big Data platform has been established;
- A common data model that adheres to the FAIR (findable, accessible, interoperable, and reusable) data-sharing principles has been created;
- HARMONY has begun developing and testing models based on available data on AML (TCGA public data, UNIBO internal data and Sanger Institute data);
- HARMONY has started analyzing the description of datasets;
- Methods working on methods for gene network analyses are beginning to be developed.
WP5 will focus on demonstrating the value of harmonizing heterogeneous HM patient data sources: developing novel analytical algorithms to identify molecular predictors of clinical outcomes and efficacious therapies, trends in economic and social impacts and improve patient quality of life.
- Take steps to create small subgroups for each research project.
- Review and formulation of research questions.
- Given that real data is being utilized by outside users, further requirements/tools need to be created.