Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/BIBM.2018.8621259 | PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) |
Keywords | Field | DocType |
Multiple sclerosis, Computational modelling, Uncertainty Analysis, Sensitivity Analysis | Central nervous system,Disease,Interleukin,Computer science,Multiple sclerosis,Nerve cells,Adverse effect,Daclizumab,Bioinformatics,Myelin | Conference |
ISSN | Citations | PageRank |
2156-1125 | 1 | 0.38 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pernice Simone | 1 | 1 | 0.38 |
| Marco Beccuti | 2 | 195 | 26.04 |
| Do' Pietro | 3 | 1 | 0.38 |
| Marzio Pennisi | 4 | 109 | 23.03 |
| F. Pappalardo | 5 | 76 | 20.14 |