Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design.
Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design.
复制标题
DOI：
10.1371/journal.pcbi.1006505
复制
发表时间：
2018-10
影响因子：
4.3
通讯作者：
Antia R
中科院分区：
文献类型：
--
作者：
Handel A;Li Y;McKay B;Pawelek KA;Zarnitsyna V;Antia R
接种疫苗是预防传染病的有效方法。任何疫苗制剂中的一个重要考虑因素是接种物剂量，即，所用抗原或减毒活病原体的量。较高的水平通常会更好地刺激免疫反应，但可能会导致更严重的副作用，并在疫苗短缺的情况下减少人口覆盖面。确定最佳接种剂量是合理疫苗设计的重要组成部分。数学模型与实验数据的结合可以帮助确定接种剂量的影响。我们说明了使用数据和模型的概念，告知接种疫苗剂量的确定，wby拟合的数学模型，从甲型流感病毒（IAV）感染的小鼠和人副流感病毒（HPIV）感染的棉鼠在不同的接种剂量的数据。我们使用该模型来映射接种剂量的免疫保护和发病率的水平，并探讨如何使用这样的框架来确定最佳的接种剂量。我们展示了如何将数学模型与实验数据相结合的框架可用于研究接种剂量对免疫保护和发病率等重要结果的影响。我们的研究结果表明，接种剂量对免疫保护和发病率的影响可以取决于特定的病原体，保护和发病率不一定随着接种剂量的增加而单调增加。一旦疫苗设计目标指定所需的保护水平和可接受的发病率水平，我们提出的框架可以帮助合理设计疫苗和确定最佳接种量。疫苗的一个重要组成部分是包含在疫苗中的病原体接种物（死的或活的）的量。该接种物剂量，有时也称为抗原剂量，需要足够大以诱导良好的保护性免疫。然而，人们通常也希望保持低剂量以降低成本，最大限度地增加可用的疫苗剂量，并最大限度地减少潜在的疫苗副作用。目前根据临床试验的有限数据选择接种物剂量。在这项研究中，我们建立了一个框架，将数据与数学模型相结合，以说明这种组合如何能够更好，更有效地确定疫苗的最佳接种剂量。
Vaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose. We illustrate the concept of using data and models to inform inoculum dose determination for vaccines, wby fitting a mathematical model to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) infection of cotton rats at different inoculum doses. We use the model to map inoculum dose to the level of immune protection and morbidity and to explore how such a framework might be used to determine an optimal inoculum dose. We show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. Our findings illustrate that the impact of inoculum dose on immune protection and morbidity can depend on the specific pathogen and that both protection and morbidity do not necessarily increase monotonically with increasing inoculum dose. Once vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework can help in the rational design of vaccines and determination of the optimal amount of inoculum. An important component of vaccines is the amount of pathogen inoculum, dead or alive, that is included in the vaccine. This inoculum dose, sometimes also referred to as antigen dose, needs to be large enough to induce good protective immunity. However, one usually also wants to keep the dose low to reduce costs, maximize the number of vaccine doses available, and minimize potential vaccine side effects. The inoculum dose is currently chosen based on limited data from clinical trials. In this study, we set up a framework that combines data with mathematical models to illustrate how such a combination could lead to better and more efficient determination of an optimal inoculum dose for vaccines.
登录
查看更多内容
影响因子：
3.7
作者：
Dobrovolny HM;Reddy MB;Kamal MA;Rayner CR;Beauchemin CA
通讯作者：
Beauchemin CA
影响因子：
7.6
作者：
Amanna, Ian J.;Slifka, Mark K.
通讯作者：
Slifka, Mark K.
影响因子：
5.4
作者：
Canini, Laetitia;Carrat, Fabrice
通讯作者：
Carrat, Fabrice
影响因子：
3.9
作者：
Handel, Andreas;Longini, Ira M., Jr.;Antia, Rustom
通讯作者：
Antia, Rustom
影响因子：
15.3
作者：
GINSBERG, H S;HORSFALL, F L Jr
通讯作者：
HORSFALL, F L Jr