Optimization and analisys of vaccination schedules using simulated annealing and agent based models

Marzio Pennisi; Giulia Russo; Juan A. Sánchez-Lantaron; Pedro A. Reche; Francesco Pappalardo

doi:10.1109/BIBM.2017.8217877

Optimization and analisys of vaccination schedules using simulated annealing and agent based models

Marzio Pennisi, Giulia Russo, Juan A. Sánchez-Lantaron, Pedro A. Reche, Francesco Pappalardo

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

Abstract

Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations of timing and dosage. We present here a computational approach based on the use of stochastic optimization techniques and validated "in silico" models to study and optimize vaccination protocols. We use Simulated Annealing in conjunction with a validated agent based model to suggest some interventions that may improve the efficacy of a candidate vaccine composed by influenza-A virosome and natural citrus-derived adjuvants to prevent influenza-A infection.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Editors	Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1455-1460
Number of pages	6
ISBN (Electronic)	9781509030491
DOIs	https://doi.org/10.1109/BIBM.2017.8217877
Publication status	Published - 15 Dec 2017
Externally published	Yes
Event	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States Duration: 13 Nov 2017 → 16 Nov 2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume	2017-January

Conference

Conference	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/Territory	United States
City	Kansas City
Period	13/11/17 → 16/11/17

Keywords

Artificial immune system
Immune system modeling
Immunotherapy
Simulated annealing
Stochastic optimization
Vaccine

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/BIBM.2017.8217877

Cite this

Pennisi, M., Russo, G., Sánchez-Lantaron, J. A., Reche, P. A., & Pappalardo, F. (2017). Optimization and analisys of vaccination schedules using simulated annealing and agent based models. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C.-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 1455-1460). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217877

Pennisi, Marzio ; Russo, Giulia ; Sánchez-Lantaron, Juan A. et al. / Optimization and analisys of vaccination schedules using simulated annealing and agent based models. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. editor / Illhoi Yoo ; Jane Huiru Zheng ; Yang Gong ; Xiaohua Tony Hu ; Chi-Ren Shyu ; Yana Bromberg ; Jean Gao ; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1455-1460 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017).

@inproceedings{a01c8b5eb2d1425a92ac84fcea1d0cf9,

title = "Optimization and analisys of vaccination schedules using simulated annealing and agent based models",

abstract = "Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations of timing and dosage. We present here a computational approach based on the use of stochastic optimization techniques and validated {"}in silico{"} models to study and optimize vaccination protocols. We use Simulated Annealing in conjunction with a validated agent based model to suggest some interventions that may improve the efficacy of a candidate vaccine composed by influenza-A virosome and natural citrus-derived adjuvants to prevent influenza-A infection.",

keywords = "Artificial immune system, Immune system modeling, Immunotherapy, Simulated annealing, Stochastic optimization, Vaccine",

author = "Marzio Pennisi and Giulia Russo and S{\'a}nchez-Lantaron, {Juan A.} and Reche, {Pedro A.} and Francesco Pappalardo",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",

year = "2017",

month = dec,

day = "15",

doi = "10.1109/BIBM.2017.8217877",

language = "English",

series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",

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

pages = "1455--1460",

editor = "Illhoi Yoo and Zheng, {Jane Huiru} and Yang Gong and Hu, {Xiaohua Tony} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",

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Pennisi, M, Russo, G, Sánchez-Lantaron, JA, Reche, PA & Pappalardo, F 2017, Optimization and analisys of vaccination schedules using simulated annealing and agent based models. in I Yoo, JH Zheng, Y Gong, XT Hu, C-R Shyu, Y Bromberg, J Gao & D Korkin (eds), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1455-1460, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, United States, 13/11/17. https://doi.org/10.1109/BIBM.2017.8217877

Optimization and analisys of vaccination schedules using simulated annealing and agent based models. / Pennisi, Marzio; Russo, Giulia; Sánchez-Lantaron, Juan A. et al.
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. ed. / Illhoi Yoo; Jane Huiru Zheng; Yang Gong; Xiaohua Tony Hu; Chi-Ren Shyu; Yana Bromberg; Jean Gao; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1455-1460 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January).

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

TY - GEN

T1 - Optimization and analisys of vaccination schedules using simulated annealing and agent based models

AU - Pennisi, Marzio

AU - Russo, Giulia

AU - Sánchez-Lantaron, Juan A.

AU - Reche, Pedro A.

AU - Pappalardo, Francesco

PY - 2017/12/15

Y1 - 2017/12/15

N2 - Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations of timing and dosage. We present here a computational approach based on the use of stochastic optimization techniques and validated "in silico" models to study and optimize vaccination protocols. We use Simulated Annealing in conjunction with a validated agent based model to suggest some interventions that may improve the efficacy of a candidate vaccine composed by influenza-A virosome and natural citrus-derived adjuvants to prevent influenza-A infection.

AB - Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations of timing and dosage. We present here a computational approach based on the use of stochastic optimization techniques and validated "in silico" models to study and optimize vaccination protocols. We use Simulated Annealing in conjunction with a validated agent based model to suggest some interventions that may improve the efficacy of a candidate vaccine composed by influenza-A virosome and natural citrus-derived adjuvants to prevent influenza-A infection.

KW - Artificial immune system

KW - Immune system modeling

KW - Immunotherapy

KW - Simulated annealing

KW - Stochastic optimization

KW - Vaccine

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DO - 10.1109/BIBM.2017.8217877

M3 - Conference contribution

AN - SCOPUS:85046016918

T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

SP - 1455

EP - 1460

BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

A2 - Yoo, Illhoi

A2 - Zheng, Jane Huiru

A2 - Gong, Yang

A2 - Hu, Xiaohua Tony

A2 - Shyu, Chi-Ren

A2 - Bromberg, Yana

A2 - Gao, Jean

A2 - Korkin, Dmitry

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

Y2 - 13 November 2017 through 16 November 2017

ER -

Pennisi M, Russo G, Sánchez-Lantaron JA, Reche PA, Pappalardo F. Optimization and analisys of vaccination schedules using simulated annealing and agent based models. In Yoo I, Zheng JH, Gong Y, Hu XT, Shyu CR, Bromberg Y, Gao J, Korkin D, editors, Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1455-1460. (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017). doi: 10.1109/BIBM.2017.8217877

Optimization and analisys of vaccination schedules using simulated annealing and agent based models

Abstract

Publication series

Conference

Keywords

UN SDGs

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