Dynamical characterization of antiviral effects in COVID-19

被引：8

作者：

Abuin, Pablo ^{[1
]}

Anderson, Alejandro ^{[1
]}

Ferramosca, Antonio ^{[2
]}

Hernandez-Vargas, Esteban A. ^{[3
]}

Gonzalez, Alejandro H. ^{[1
]}

机构：

[1] CONICET UNL, Inst Technol Dev Chem Ind INTEC, Santa Fe, Argentina

[2] Univ Bergamo, Dept Management Informat & Prod Engn, Via Marconi 5, I-24044 Dalmine, BG, Italy

[3] UNAM, Unidad Juriquilla, Inst Matemat, Queretaro 76230, Mexico

来源：

ANNUAL REVIEWS IN CONTROL | 2021年 / 52卷

关键词：

SARS-CoV-2; In-host model; Dynamic characterization; Antiviral effectiveness; VIRUS-INFECTION; REMDESIVIR;

D O I：

10.1016/j.arcontrol.2021.05.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. In addition, the virus dynamic in the host - including the time-to-peak and the final monotonically decreasing behavior - is characterized as a function of the time to treatment initiation. Simulation results, based on nine patient data, show the potential clinical benefits of a treatment classification according to patient critical parameters. This study is aimed at paving the way for the different antivirals being developed to tackle SARS-CoV-2.

引用

页码：587 / 601

页数：15

共 55 条

[41]

Porter DP, 2020, NATURE, DOI DOI 10.1038/S41586-020-2423-5

[42] Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood [J].

Raue, A. ;

Kreutz, C. ;

Maiwald, T. ;

Bachmann, J. ;

Schilling, M. ;

Klingmueller, U. ;

Timmer, J. .

BIOINFORMATICS, 2009, 25 (15) :1923-1929

[43] Modeling HIV persistence, the latent reservoir, and viral blips [J].

Rong, Libin ;

Perelson, Alan S. .

JOURNAL OF THEORETICAL BIOLOGY, 2009, 260 (02) :308-331

[44] Pharmacologic Treatments for Coronavirus Disease 2019 (COVID-19) A Review [J].

Sanders, James M. ;

Monogue, Marguerite L. ;

Jodlowski, Tomasz Z. ;

Cutrell, James B. .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2020, 323 (18) :1824-1836

[45]

Storn R., 1995, International Computer Science Institute, V23, P341

[46] BIOAVAILABILITY OF HYDROXYCHLOROQUINE TABLETS IN HEALTHY-VOLUNTEERS [J].

TETT, SE ;

CUTLER, DJ ;

DAY, RO ;

BROWN, KF .

BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 1989, 27 (06) :771-779

[47]

Torres-Cerna CE, 2016, IEEE C EVOL COMPUTAT, P4662, DOI 10.1109/CEC.2016.7744385

[48] Ebola virus infection modeling and identifiability problems [J].

Van Kinh Nguyen ;

Binder, Sebastian C. ;

Boianelli, Alessandro ;

Meyer-Hermann, Michael ;

Hernandez-Vargas, Esteban A. .

FRONTIERS IN MICROBIOLOGY, 2015, 6

[49]

Vergnaud J.-M., 2005, ASSESSING BIOAVAILAB

[50] Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis [J].

Wang, Kai ;

Lu, Zhenzhen ;

Wang, Xiaomeng ;

Li, Hui ;

Li, Huling ;

Lin, Dandan ;

Cai, Yongli ;

Feng, Xing ;

Song, Yateng ;

Feng, Zhiwei ;

Ji, Weidong ;

Wang, Xiaoyan ;

Yin, Yi ;

Wang, Lei ;

Peng, Zhihang .

MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2020, 17 (04) :3052-3061

← 1 2 3 4 5 6 →