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Article Dans Une Revue Mathematical Modelling of Natural Phenomena Année : 2020

HYBRID DATA-BASED MODELLING IN ONCOLOGY: SUCCESSES, CHALLENGES AND HOPES

Résumé

In this opinion paper we make the statement that hybrid models in oncology are required 4 as a mean for enhanced data integration. In the context of systems oncology, experimental and clinical 5 data need to be at the heart of the models developments from conception to validation to ensure 6 a relevant use of the models in the clinical context. The main applications pursued are to improve 7 diagnosis and to optimize therapies.We first present the Successes achieved thanks to hybrid modelling 8 approaches to advance knowledge, treatments or drug discovery. Then we present the Challenges than 9 need to be addressed to allow for a better integration of the model parts and of the data into the 10 models. And finally, the Hopes with a focus towards making personalised medicine a reality. 11 Mathematics Subject Classification. 35Q92, 68U20, 68T05, 92-08, 92B05. 12
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Dates et versions

hal-02405782 , version 1 (11-12-2019)

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Angélique Stéphanou, Pascal Ballet, Gibin Powathil. HYBRID DATA-BASED MODELLING IN ONCOLOGY: SUCCESSES, CHALLENGES AND HOPES. Mathematical Modelling of Natural Phenomena, 2020, 15, ⟨10.1051/mmnp/2019026⟩. ⟨hal-02405782⟩
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