Abstract
We present an improved version of an agent-based model developed to reproduce the typical oscillating behavior of relapsing remitting multiple sclerosis, a demyelinating autoimmune disease of the central nervous system. The model now includes the effects of vitamin D, a possible immune-modulator that can potentially influence the disease course, as well as the mechanisms of action of daclizumab, a monoclonal antibody that was previously reported as the unique third line treatment for MS, i.e., to be used only in patients who had an inadequate response to the other therapies, but then retired from market due to the arising of severe side effects. The use of this computational approach, capable of qualitatively reproducing the main effects of daclizumab, is used to grasp some useful insights to delineate the possible causes that led to the withdrawal of the drug. Furthermore, we explore the possibility to combine vitamin D administration with a reduced dosage of daclizumab, in order to qualitatively delineate if a combined treatment can lead to similar efficacy, thus entitling a reduced risk of adverse effects.
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Pennisi, M., Russo, G., Sgroi, G., Palumbo, G.A.P., Pappalardo, F. (2020). In Silico Evaluation of Daclizumab and Vitamin D Effects in Multiple Sclerosis Using Agent Based Models. In: Cazzaniga, P., Besozzi, D., Merelli, I., Manzoni, L. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019. Lecture Notes in Computer Science(), vol 12313. Springer, Cham. https://doi.org/10.1007/978-3-030-63061-4_25
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