Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets

Simone Pernice; Marco Beccuti; Pietro Do; Marzio Pennisi; Francesco Pappalardo

doi:10.1109/BIBM.2018.8621259

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets

Simone Pernice
, Marco Beccuti
, Pietro Do
, Marzio Pennisi
, Francesco Pappalardo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Editors	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1393-1400
Number of pages	8
ISBN (Electronic)	9781538654880
DOIs	https://doi.org/10.1109/BIBM.2018.8621259
Publication status	Published - 21 Jan 2019
Externally published	Yes
Event	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain Duration: 3 Dec 2018 → 6 Dec 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Country/Territory	Spain
City	Madrid
Period	3/12/18 → 6/12/18

Keywords

Computational modelling
Multiple sclerosis
Sensitivity Analysis
Uncertainty Analysis

Access to Document

10.1109/BIBM.2018.8621259

Cite this

Pernice, S., Beccuti, M., Do, P., Pennisi, M., & Pappalardo, F. (2019). Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 1393-1400). Article 8621259 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621259

Pernice, Simone ; Beccuti, Marco ; Do, Pietro et al. / Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1393-1400 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

@inproceedings{4c5a8462de2649e18c8c15d73c6892f9,

title = "Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets",

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.",

keywords = "Computational modelling, Multiple sclerosis, Sensitivity Analysis, Uncertainty Analysis",

author = "Simone Pernice and Marco Beccuti and Pietro Do and Marzio Pennisi and Francesco Pappalardo",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",

year = "2019",

month = jan,

day = "21",

doi = "10.1109/BIBM.2018.8621259",

language = "English",

series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1393--1400",

editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",

booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",

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Pernice, S, Beccuti, M, Do, P, Pennisi, M & Pappalardo, F 2019, Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018., 8621259, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1393-1400, 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Madrid, Spain, 3/12/18. https://doi.org/10.1109/BIBM.2018.8621259

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets. / Pernice, Simone; Beccuti, Marco; Do, Pietro et al.
Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1393-1400 8621259 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets

AU - Pernice, Simone

AU - Beccuti, Marco

AU - Do, Pietro

AU - Pennisi, Marzio

AU - Pappalardo, Francesco

PY - 2019/1/21

Y1 - 2019/1/21

N2 - 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.

AB - 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.

KW - Computational modelling

KW - Multiple sclerosis

KW - Sensitivity Analysis

KW - Uncertainty Analysis

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DO - 10.1109/BIBM.2018.8621259

M3 - Conference contribution

AN - SCOPUS:85062527310

T3 - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

SP - 1393

EP - 1400

BT - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

A2 - Schmidt, Harald

A2 - Griol, David

A2 - Wang, Haiying

A2 - Baumbach, Jan

A2 - Zheng, Huiru

A2 - Callejas, Zoraida

A2 - Hu, Xiaohua

A2 - Dickerson, Julie

A2 - Zhang, Le

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Y2 - 3 December 2018 through 6 December 2018

ER -

Pernice S, Beccuti M, Do P, Pennisi M, Pappalardo F. Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets. In Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editors, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1393-1400. 8621259. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). doi: 10.1109/BIBM.2018.8621259

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets

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