This study is structured around the following key objectives:
- Integration of big data into clinical practice as part of a regional initiative.
This study is also embedded within a regional program focused on applying big data analytics to improve patient care (SUPER computing big data – Clust-ER Health). The core concept is that the integration of multi-omics data can facilitate the identification of more effective, personalized therapeutic strategies. This initiative, based in the Emilia-Romagna region, is supported by the European Horizon 2020 program.
- Assessment of anti-tumor response profiles to synthetic molecules and derivatives.
We aim to test both FDA/EMA-approved drugs and experimental compounds in laboratory settings, using pathological cells isolated from bone marrow, peripheral blood, or other tissues collected during routine clinical procedures from patients diagnosed with hematologic malignancies. Assays will be conducted to evaluate cell viability following treatment, induction of differentiation, and cellular metabolism.
- Identification of molecular biomarkers predictive of response to novel targeted therapies.
By leveraging cutting-edge technologies to characterize DNA and detect genetic mutations within malignant cells, we will investigate novel genetic and molecular alterations that confer sensitivity to compounds identified through laboratory screening. The goal is to uncover new actionable targets for therapy.
- Correlation of drug response with international classification criteria for hematologic malignancies.
The drug response data will be integrated with established diagnostic frameworks such as the WHO classification, cytogenetic/molecular profiling, and emerging omics-based technologies—including next-generation sequencing, single-cell analysis, and radiomics. This comprehensive approach aims to link clinical, molecular, and prognostic features with pharmacologic response.
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