Translational systems biology understanding the limits of animal models as predictors of human biology

Carine Poussin, Leonidas Alexopoulos, Vincenzo Belcastro, Erhan Bilal, Carole Mathis, Pablo Meyer, Raquel Norel, Jeremy J Rice, Gustavo Stolovitzky, Julia Hoeng, Manuel Peitsch


Inferring how humans respond to external cues such as drugs, chemicals, viruses or hormones is an essential question in biomedicine. Very often, however, this question cannot be addressed due to the impossibility to perform experiments in humans. A reasonable alternative consists of generating responses in animal models and “translating” the results to humans. The limitations of such translation, however, are far from clear, and systematic assessments of its actual potential are badly needed. We have designed a series of challenges in the context of the ‘sbv IMPROVER’ project (Industrial Methodology for Process Verification in Research; to address the issue of translatability between humans and rodents. Our main aim is to understand the limits and opportunities of species to species translatability at different levels of biological organization: signalling, transcriptional, and release of secreted factors (such as cytokines, chemokines or growth factors) leveraging large scale omics datasets specially generated for this purpose. The sbv IMPROVER project are part of a collaborative project designed to enable scientists to learn about and contribute to the development of a new crowd sourcing method for verification of scientific data and results.


systems biology; crowd sourcing; challenge; species translatability

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