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结核病疫苗H56+IC31的剂量反应曲线呈峰值而非饱和状态:为新的数学建模方法生成数据以指导疫苗剂量决策。

The TB vaccine H56+IC31 dose-response curve is peaked not saturating: Data generation for new mathematical modelling methods to inform vaccine dose decisions.

作者信息

Rhodes Sophie J, Zelmer Andrea, Knight Gwenan M, Prabowo Satria Arief, Stockdale Lisa, Evans Thomas G, Lindenstrøm Thomas, White Richard G, Fletcher Helen

机构信息

TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK.

Immunology and Infection Department, London School of Hygiene and Tropical Medicine, UK.

出版信息

Vaccine. 2016 Dec 7;34(50):6285-6291. doi: 10.1016/j.vaccine.2016.10.060. Epub 2016 Nov 2.

Abstract

INTRODUCTION

In vaccine development, dose-response curves are commonly assumed to be saturating. Evidence from tuberculosis (TB) vaccine, H56+IC31 shows this may be incorrect. Mathematical modelling techniques may be useful in efficiently identifying the most immunogenic dose, but model calibration requires longitudinal data across multiple doses and time points.

AIMS

We aimed to (i) generate longitudinal response data in mice for a wide range of H56+IC31 doses for use in future mathematical modelling and (ii) test whether a 'saturating' or 'peaked' dose-response curve, better fit the empirical data.

METHODS

We measured IFN-γ secretion using an ELISPOT assay in the splenocytes of mice who had received doses of 0, 0.1, 0.5, 1, 5 or 15μg H56+IC31. Mice were vaccinated twice (at day 0 and 15) and responses measured for each dose at 8 time points over a 56-day period following first vaccination. Summary measures Area Under the Curve (AUC), peak and day 56 responses were compared between dose groups. Corrected Akaike Information Criteria was used to test which dose-response curve best fitted empirical data, at different time ranges.

RESULTS

(i) All summary measures for dose groups 0.1 and 0.5μg were higher than the control group (p<0.05). The AUC was higher for 0.1 than 15μg dose. (ii) There was strong evidence that the dose-response curve was peaked for all time ranges, and the best dose is likely to be lower than previous empirical experiments have evaluated.

CONCLUSION

These results suggest that the highest, safe dose may not always optimal in terms of immunogenicity, as the dose-response curve may not saturate. Detailed longitudinal dose range data for TB vaccine H56+IC31 reveals response dynamics in mice that should now be used to identify optimal doses for humans using clinical data, using new data collection and mathematical modelling.

摘要

引言

在疫苗研发中,通常假定剂量反应曲线是饱和的。来自结核病(TB)疫苗H56+IC31的证据表明这可能是不正确的。数学建模技术可能有助于有效地识别最具免疫原性的剂量,但模型校准需要跨多个剂量和时间点的纵向数据。

目的

我们旨在(i)在小鼠中生成一系列H56+IC31剂量的纵向反应数据,以供未来的数学建模使用,以及(ii)测试“饱和”或“峰值”剂量反应曲线是否更符合实验数据。

方法

我们使用ELISPOT测定法测量接受0、0.1、0.5、1、5或15μg H56+IC31剂量的小鼠脾细胞中IFN-γ的分泌。小鼠接种两次(在第0天和第15天),并在首次接种后的56天内的8个时间点测量每个剂量的反应。比较剂量组之间的曲线下面积(AUC)、峰值和第56天反应的汇总指标。使用校正的赤池信息准则来测试在不同时间范围内哪种剂量反应曲线最符合实验数据。

结果

(i)0.1和0.5μg剂量组的所有汇总指标均高于对照组(p<0.05)。0.1μg剂量的AUC高于15μg剂量。(ii)有强有力的证据表明,在所有时间范围内剂量反应曲线都是峰值,并且最佳剂量可能低于先前的实验评估。

结论

这些结果表明,就免疫原性而言,最高的安全剂量可能并不总是最佳的,因为剂量反应曲线可能不会饱和。结核病疫苗H56+IC31的详细纵向剂量范围数据揭示了小鼠中的反应动态,现在应使用新的数据收集和数学建模,利用临床数据来确定人类的最佳剂量。

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