mRNA-1273 的免疫刺激/免疫动力学模型用于指导儿科疫苗剂量选择。

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Vijay Ivaturi, Husain Attarwala, Weiping Deng, Baoyu Ding, Sabine Schnyder Ghamloush, Bethany Girard, Javid Iqbal, Saugandhika Minnikanti, Honghong Zhou, Jacqueline Miller, Rituparna Das
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引用次数: 0

摘要

包括 mRNA-1273 在内的 COVID-19 疫苗已被迅速开发和应用。确定最佳剂量对于开发安全有效的疫苗至关重要。建模和模拟有可能在指导疫苗剂量的选择和开发方面发挥关键作用。在此背景下,我们开发了一个免疫刺激/免疫动力学(IS/ID)模型,用于定量描述从三项临床研究中获得的 mRNA-1273 引起的中和抗体滴度。所开发的模型用于预测未来儿科试验的最佳疫苗剂量。据预测,在幼儿(2-5 岁)和婴儿(6-23 个月)中,25μg 的初级疫苗系列符合非劣效性标准。使用 IS/ID 模型预测的这一剂量水平的几何平均滴度和几何平均比率与儿科临床研究中观察到的结果相吻合。这些研究结果表明,IS/ID 模型是指导以数据为导向的疫苗临床剂量选择的一种新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Immunostimulatory/Immunodynamic model of mRNA-1273 to guide pediatric vaccine dose selection.

COVID-19 vaccines, including mRNA-1273, have been rapidly developed and deployed. Establishing the optimal dose is crucial for developing a safe and effective vaccine. Modeling and simulation have the potential to play a key role in guiding the selection and development of the vaccine dose. In this context, we have developed an immunostimulatory/immunodynamic (IS/ID) model to quantitatively characterize the neutralizing antibody titers elicited by mRNA-1273 obtained from three clinical studies. The developed model was used to predict the optimal vaccine dose for future pediatric trials. A 25-μg primary vaccine series was predicted to meet non-inferiority criteria in young children (aged 2-5 years) and infants (aged 6-23 months). The geometric mean titers and geometric mean ratios for this dose level predicted using the IS/ID model a priori matched those observed in the pediatric clinical study. These findings demonstrate that IS/ID models represent a novel approach to guide data-driven clinical dose selection of vaccines.

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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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