Publication details
Výzkumná platforma REDCap integrující klinická data a biologické tkáňové modely pro precizní medicínu pankreatického adenokarcinomu
| Title in English | Research REDCap platform integrating clinical data and biological tissue models for precision medicine in pancreatic adenocarcinoma |
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| Year of publication | 2026 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Pancreatic ductal adenocarcinoma (PDAC) represents one of the most serious types of solid tumors, with a low 5-year survival rate and still limited options for early diagnosis and treatment. Precision oncology and personalized medicine represent a promising direction that takes into account the genotype, mutational profile, and biological characteristics of an individual tumor. To investigate the individual characteristics of tumors and model them under laboratory in vitro conditions, we used the REDCap database system within a project conducted by the Faculty of Medicine of Masaryk University and Brno University Hospital. The system is used to manage demographic data, clinical and radiological characteristics, treatment course, molecular-genetic results, and survival data of patients with PDAC. This integrated clinical-biological ecosystem is linked to a pilot biobank that stores patient samples used to generate 3D tissue models (organoids and spheroids), while the parameterized data are structured in a format suitable for machine learning and artificial intelligence methods. To date, a database has been successfully established containing detailed longitudinal data from more than 160 patients with tumors of the pancreas and related histological and anatomical regions. The database records diagnostic and therapeutic procedures and their relationship to molecular-genetic profiling and treatment response. The resulting platform serves as a foundation for the development of predictive models and biomarker validation, thereby successfully demonstrating the feasibility of comprehensive data collection within a university hospital setting. Despite the logistical and capacity demands and the need to harmonize the input data, this infrastructure has the potential to be expanded into a national research network and is open to collaboration. The integration of clinical data and biological models thus provides a functional, real-world foundation for data- and biology-driven support of treatment and research, contributes to the advancement of personalized care, and offers a comprehensive platform for therapeutic planning in oncology. |
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