Observation: Biological tissue collections are valuable resources for studying diseases. Creating new biobanks is complex and costly. Developing historic pathology tissue collections might be a more effective alternative.
Hypothesis: Turning historic collections into usable biobanks requires the following: (1) being able to analyse histopathological biomarkers in historic specimens; (2) developing an AI-assisted model for exploiting historic big data; and (3) offering an historical exposomic understanding of the categories on which these collections were established.
Objective: To use genomic, histopathological and exposomic methods to turn two historic twentieth-century tissue collections offering extraordinary chronological depth (>100 years) into biobanks that can be used for current translational research.
Approach: Combining tools borrowed from data science, artificial intelligence (AI), molecular biology, histopathology, clinical medicine, history and the medical humanities.
Data: a) Geneva Brain Bank (GBB, 1901-2013); b) Strasbourg Pathology Tissue Collection (SPTC, 1872-2003). The paper medical records (pathology and clinical reports) accompanying these tissue collections will be used to develop contextualised, historical epidemiological and archaeoexposomic understanding of the biomarker data.
