New analytic approaches and endpoints in human HIV vaccine correlate studies

人类艾滋病毒疫苗相关研究的新分析方法和终点

• 批准号: 10613609
• 负责人: Margaret E Ackerman
• 金额: $ 79.2万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-17 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10613609
• 关键词: Address; Algorithms; Antibodies; Antibody Response; Antibody Specificity; Antigens; Autologous; Benchmarking; Clinical Trials; Coupled; Data; Data Set; Effector Cell; Exclusion; Exposure to; Failure; Futility; Genetic; HIV vaccine; HIV-1; HIV-1 vaccine; Human; Immune response; Immunity; Individual; Infection; Investigation; Investments; Knowledge; Learning; Machine Learning; Measurement; Mediating; Methods; Nature; Outcome; Participant; Passive Transfer of Immunity; Phenotype; Population; Predisposition; Reagent; Risk; Role; Specificity; Supervision; Techniques; Technology; Testing; Vaccinated; Vaccine Research; Vaccinee; Vaccines; Viral; Virus; Work; base; data modeling; efficacy evaluation; efficacy study; efficacy trial; immunogenicity; immunoprophylaxis; improved; infection risk; innovation; insight; neutralizing antibody; next generation; novel; novel strategies; pandemic disease; pathogen; pathogen exposure; pre-clinical; research and development; response; supervised learning; vaccination strategy; vaccine efficacy; vaccine trial

SUMMARY HIV vaccine efficacy trials have been complicated by low rates of exposure and low levels of protection. Yet, despite these barriers, crucial correlates of infection risk (CoR) have been defined from trials that failed to meet overall efficacy criteria. Much has been learned about protective immune responses, host genetics, and viral susceptibility from analysis of ineffective and marginally effective trials. In particular, while neutralizing Ab breadth has long been considered key to vaccine-mediated protection, breadth of Fc-mediated effector functions has only more recently begun to be explored. Given the rich data from natural infection, passive Ab transfer studies probing mechanism of action, preclinical vaccine efficacy studies, and prior human HIV-1 vaccine efficacy trials that support the potential role of Ab effector functions to contribute to protection from infection, these activities represent an important avenue of investigation and optimization in vaccine research and development. To define these CoR, case-control analysis is typically conducted by comparing the response profiles of infected (case) and uninfected (control) subjects. However, the “control", or uninfected subject class is a mixture of individuals that lack the protective response and were simply not exposed to the pathogen, and those that possess the protective response and either were or were not exposed. For poorly effective vaccines, the majority of the control subjects are expected to show a response phenotype indistinguishable from the cases. Thus, traditional CoR analysis suffers from the dilution of the protected subjects with these unprotected but unexposed subjects. We propose to evaluate novel machine learning (ML) techniques that can robustly infer the protection status of vaccinated individuals on the basis of immunogenicity (or other) data in order to facilitate correlates discovery under these challenging circumstances. Accordingly, we propose tandem approaches to develop new insights into HIV vaccine efficacy · by developing new analytical approaches to correlates analysis relevant not only to this but other HIV vaccine trials and beyond, and · by collecting new humoral immune response data defining the breadth and potency of antibody effector function for the HVTN702 trial.

概括 由于接触率低和保护水平低，艾滋病毒疫苗功效试验变得复杂。 然而，尽管存在这些障碍，感染风险 (CoR) 的关键相关性已从未能成功的试验中定义出来。 满足总体功效标准。关于保护性免疫反应、宿主遗传学和 特别是在中和抗体时，通过分析无效和勉强有效的试验来确定病毒敏感性。 长期以来，广度一直被认为是疫苗介导的保护的关键，Fc 介导的效应子的广度 鉴于自然感染的丰富数据，被动抗体的功能最近才开始被探索。 探索作用机制的转移研究、临床前疫苗功效研究和先前的人类 HIV-1 疫苗功效试验支持抗体效应功能在预防感染方面的潜在作用 感染，这些活动代表了疫苗研究中调查和优化的重要途径 和发展。 为了定义这些 CoR，通常通过比较以下患者的反应概况来进行病例对照分析： 感染（病例）和未感染（对照）受试者但是，“对照”或未感染受试者类别是一个。 缺乏保护性反应并且根本没有暴露于病原体的个体的混合物，以及 那些具有保护性反应并且曾经或没有接触过效果不佳的疫苗的人， 大多数对照受试者预计会表现出与正常受试者无法区分的反应表型 因此，传统的 CoR 分析会受到受保护对象与未受保护对象的稀释的影响。 但我们建议评估新的机器学习（ML）技术，这些技术可以稳健地进行。 根据免疫原性（或其他）数据推断疫苗接种个体的保护状态，以便 有助于在这些充满挑战的情况下关联发现。 我们提出串联方法来开发艾滋病毒疫苗功效的新见解 · 通过开发新的分析方法来关联分析，不仅与此艾滋病毒相关，而且与其他艾滋病毒相关 疫苗试验及以后，以及 · 通过收集新的体液免疫反应数据来定义抗体效应物的广度和效力 HVTN702 试用版的功能。