Disease processes as hybrid dynamical systems

Pietro Liò
(Computer Laboratory - University of Cambridge)
Emanuela Merelli
(School of Science and Technology - University of Camerino)
Nicola Paoletti
(School of Science and Technology - University of Camerino)

We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

In Ezio Bartocci and Luca Bortolussi: Proceedings First International Workshop on Hybrid Systems and Biology (HSB 2012), Newcastle Upon Tyne, 3rd September 2012, Electronic Proceedings in Theoretical Computer Science 92, pp. 152–166.
Published: 15th August 2012.

ArXived at: http://dx.doi.org/10.4204/EPTCS.92.11 bibtex PDF
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