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- W2913223553 abstract "Multiple Sclerosis (MS) is an immune-mediated inflammatory disease of the central nervous system which damages the myelin sheath enveloping nerve cells causing severe physical disability in patients. Relapsing Remitting Multiple Sclerosis (RRMS) is one of the most common form of MS and it is characterized by a series of attacks of new or increasing neurologic symptoms, followed by periods of remission. Recently, many treatments were proposed and studied to contrast the RRMS progression. Among these drugs Daclizumab, an antibody tailored against the interleukin -2 receptor of T cells, exhibited promising results. Unfortunately, more recent studies on Daclizumab highlight severe adverse effects, that led to its retirement from the EU marketing authorization process. Motivated by these recent studies, in this paper we describe how computational modelling can be efficiently exploited to improve our understanding on Daclizumab mechanism of action, and on how this mechanism leads towards the observed undesirable effects." @default.
- W2913223553 created "2019-02-21" @default.
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- W2913223553 date "2018-12-01" @default.
- W2913223553 modified "2023-10-16" @default.
- W2913223553 title "Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets" @default.
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- W2913223553 doi "https://doi.org/10.1109/bibm.2018.8621259" @default.
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