Working in close collaboration with multiple VHIO research groups, the Data Engineering for Research Unit focuses on the standardization, integration, and digitization of biomedical data. In addition to actively contributing to several research projects, the Unit develops and maintains robust infrastructure and environments that support institutional data storage, accessibility, interoperability, and governance.
The Unit manages a wide range of data types, including clinical, omics, imaging, and other biomedical datasets, aiming to maximize their usability and research value while providing investigators with appropriate tools and support. The team also contributes to the definition and implementation of Data Management Plans (DMPs), ensuring compliance with institutional and regulatory data management requirements throughout the data lifecycle.
Through the design and implementation of ETL (Extract, Transform, Load) pipelines, the development of structured and interoperable databases, the integration of heterogeneous data sources, and the creation and maintenance of specialized software solutions, the Unit provides a reliable framework that enables researchers to efficiently generate, manage, and exploit research data.
The Unit is actively advancing Artificial Intelligence (AI)-driven initiatives, including the development of clinical trial matching tools to support patient recruitment and the implementation of large language model (LLM) approaches for the structuring and extraction of information from unstructured clinical notes. These efforts aim to enhance data usability, accelerate clinical research workflows, and contribute to precision oncology initiatives.
- Advance institutional clinical data standardization through expansion of the OMOP common data model and FAIR-aligned data governance practices.
- Consolidate and expand the VHIO Data Lake (VHIO-Lake) as a secure, interoperable environment integrating clinical, molecular, imaging, pharmacy, and clinical trial datasets.
- Strengthen data interoperability across institutional systems through scalable ETL pipelines, structured databases, and harmonized digital platforms.
- Enhance advanced data exploration and visualization through integrative tools (e.g., cBioPortal, OMERO) to support translational and precision oncology research.
- Expand AI-driven initiatives, including LLM-based structuring of clinical notes and intelligent tools for clinical trial patient matching.
- Develop tailored digital solutions to support research data capture, patient tracking, and project-specific institutional needs.
Group lead
Anna Pedrola
Biomedical Data Engineers
Marina Arias
Carlota Gozalbo
Mario Sánchez
Image Data Engineer
Cristina Villaseca
Data Steward
Clara Vallés
Most relevant scientific publications
- Pedrola A, Franch-Expósito S, Lahoz S, Esteban-Fabró R, Dienstmann R, Bassaganyas L, et al. PCIG: a web-based application to explore immune-genomics interactions across cancer types. Bioinformatics. 2022 Apr 15;38(8):2374–2376.
- Matos I, Villacampa G, Hierro C, Martin-Liberal J, Berché R, Pedrola A, et al. Phase I prognostic online (PIPO): A web tool to improve patient selection for oncology early phase clinical trials. Eur J Cancer. 2021 Sep;155:168–78.
- Cedres, S., Assaf, J. D., Iranzo, P., Callejo, A., Pardo, N., Navarro, A., Martinez-Marti, A., Marmolejo, D., Rezqallah, A., Carbonell, C., Frigola, J., Amat, R., Pedrola, A., Dienstmann, R., & Felip, E. (2021). Efficacy of chemotherapy for malignant pleural mesothelioma according to histology in a real-world cohort. Scientific reports, 11(1), 21357.
- Mirallas, O., Martin-Cullell, B., Navarro, V., Vega, K.S., Recuero-Borau, J., Gómez-Puerto, D., López-Valbuena, D., de Torres, C.S., Andurell, L., Pedrola, A. and Berché, R., 2024. Development of a prognostic model to predict 90-day mortality in hospitalised cancer patients (PROMISE tool): a prospective observational study. The Lancet Regional Health–Europe.
- SYNTHIA: Synthetic Data Generation Framework for Integrated Validation of Use Cases and AI Healthcare Applications. Funded by the European Commission. 01/09/2024-31/08/2029. PI: Rodrigo Dienstmann.
- Cancer Core Europe (CCE). Founded in 2014, this consortium comprises seven leading European comprehensive cancer centers, including VHIO, to accelerate the development of innovative cancer therapies through close collaboration in translational and clinical research.
- The EU-funded CCE Building Data Rich Clinical Trials (CCE_DART) is an innovative project dedicated to deliver novel methods for the design and implementation of newer, more efficient and effective clinical trials in oncology.
- Historia clínica Inteligente: Transformando Notas Clínicas en Datos Estructurado.
- EU-funded AI4Lungs project: AI-Based Personalised Care for Respiratory Disease using Multi-Modal Data in Patient Stratification.
- American Association for Cancer Research (AACR) Project GENIE® (Genomics Evidence Neoplasia Information Exchange).
- PROLoNg: Phase III randomized study evaluating Pembrolizumab combined with radiotherapy for oligometastatic squamous cell carcinoma of the head and neck.
- REDEcon: Strategic Advisory Network on Cancer Policies (Red ECON), aims to bridge the scientific-health ecosystem and Spanish authorities by developing national data frameworks, R&D&I strategies, and recommendations to optimize patient care and research integration.
- EUnetCCC: European Network of Cancer Centres (EUnetCCC), aiming to foster collaboration among leading cancer centers across Europe to harmonize data sharing, promote best practices, and support multicenter research initiatives in oncology.
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