Development of a Universal Influenza Vaccine

摘要 在所有传染病中，流感病毒（流感）的疾病负担最高， 生命年。季节性流行病每年在全世界造成200，000 - 500，000人死亡。总经济负担 据估计，美国每年季节性流感的直接费用约为260亿至870亿美元， 医疗费用和损失的工作和生产力。此外，至少有六种已知的流感大流行已成为 全球性的人类灾难，最著名的是1918年的西班牙流感大流行，造成世界上3-5%的人死亡。 人口任何降低流感感染率、传播和严重程度的措施都将大大减少 我们的医疗保健支出和改善生活质量的数百万人每年。当前 每年根据预测哪种流行的流感毒株可能在一个国家流行来配制疫苗。 给定的季节。这些疫苗的有效性每年都有变化， 意想不到的抗原变体和其他因素。流感病毒的多样性使疫苗设计变得复杂 菌株，每一个都具有快速进化的显性抗原表位（“诱饵”表位），其在很大程度上刺激菌株- 有限豁免权一种用于合理抗原设计的策略，称为免疫重聚焦技术（IRT）， 包括引入降低这些诱饵表位的免疫原性的突变， 靶向更广泛保守的亚显性表位的免疫应答。BMI之前已应用此IRT 在其他病毒抗原（例如HRV和RSV F蛋白）上取得了一些显著的成功，现在我们 以H1、H3和B疫苗株为亲本，重点研究主要流感表面抗原糖蛋白HA 抗原设计适当修饰的抗原的预期努力通常将涉及长期的研究。 对许多潜在候选人进行反复试验的过程。然而，我们最近开发了 ANATOPE自动化B细胞表位预测软件包，使用 人工智能的方法。我们的算法识别表位的成功率显著高于 以前的预测程序。这一突破使我们能够分配免疫原性“强度” 分数，以特定的抗原表面补丁，并将进一步指导和加速突变体的设计 将免疫应答重新聚焦于跨菌株保守表位的抗原。在本申请中，我们提出 为了工程化和测试合理设计的含有突变的HA抗原的免疫原性， 抑制显性菌株限制性诱饵表位的免疫原性和2）增强 与广泛中和抗体相关的保守亚显性表位的免疫原性。跟着- UP研究将在雪貂攻击研究中评估合理设计的抗原，并为 作为一种不需要每年重新配制的通用疫苗转化为人类。

ABSTRACT Influenza virus (flu) ranks highest in disease burden of all infectious diseases as measured in disability-adjusted life years. Seasonal epidemics cause 200,000-500,000 worldwide deaths annually. The total economic burden of seasonal flu is estimated to range from approximately $26B to $87B each year in the US in terms of direct medical expenses and lost work and productivity. Additionally, at least six known flu pandemics have become global human catastrophes, most notably the Spanish Flu pandemic of 1918, which killed 3-5% of the world’s population. Any reduction in the infection rate, transmission, and severity of flu infection would greatly reduce our healthcare expenditures and improve the quality of life for millions of people every year. The current vaccines are formulated annually based on predictions of which circulating flu strains may be prevalent in a given season. The effectiveness of these vaccines varies from year to year based on the circulation of unexpected antigenic variants and other factors. Vaccine design is complicated the by the multiplicity of flu strains, each with rapidly-evolving dominant antigen epitopes (“decoy” epitopes) that largely stimulate strain- restricted immunity. One strategy for rational antigen design, termed Immune Refocusing Technology (IRT), involves introducing mutations that reduce the immunogenicity of these decoy epitopes thus shifting the immune response to target more widely-conserved subdominant epitopes. BMI has previously applied this IRT approach with some notable successes to other viral antigens (e.g. HRV and the RSV F protein), and we now focus on the major flu surface antigen glycoprotein HA using H1, H3, and B vaccine strains as parental antigens. The anticipated effort to design a suitably modified antigen would ordinarily involve a protracted process of trial-and-error testing of many potential candidates. However, we have recently developed the ANATOPE automated B cell epitope prediction software package with algorithm parameters tuned using methods in artificial intelligence. Our algorithm identifies epitopes with a significantly higher success rate than previously available prediction programs. This breakthrough allows us to assign immunogenicity “strength” scores to particular antigen surface patches and will further guide and accelerate the design of mutant antigens that refocus the immune response to cross-strain conserved epitopes. In this application, we propose to engineer and test the immunogenicity of rationally-designed HA antigens containing mutations that both 1) dampen the immunogenicity of dominant strain-restricted decoy epitopes and 2) enhance the immunogenicity of conserved subdominant epitopes associated with broadly neutralizing antibodies. Follow- up studies will assess the rationally-designed antigens in a ferret challenge study and prepare the approach for translation into humans as a universal vaccine that does not require annual reformulation.