PUBLIC HIV DRUG RESISTANCE DATABASE

公共艾滋病毒耐药数据库

基本信息

批准号：
9060859
负责人：
ROBERT William SHAFER
金额：
$ 76.29万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-05-01 至 2018-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9060859
关键词：
Acquired Immunodeficiency Syndrome Address Adopted Algorithms Anti-Retroviral Agents Antiretroviral drug resistance Antiretroviral resistance Applications Grants Clinical Clinical Trials Collection Country Coupled Data Data Correlations Databases Development Drug resistance Epidemiologist Funding Future Genetic Genotype Geographic Information Systems HIV HIV drug resistance HIV-1 HIV-1 drug resistance In Vitro Individual Knowledge Laboratories Licensing Meta-Analysis Methods Modeling Molecular Molecular Cloning Monitor Morbidity - disease rate Multi-Drug Resistance Mutation Nature Pattern Persons Pharmaceutical Preparations Phenotype Population Predisposition Publishing Reagent Recombinants Regimen Research Resistance Resources Risk Source South African Testing Treatment Protocols United States National Institutes of Health Variant Viral Virus Work acquired drug resistance antiretroviral therapy data sharing drug development evidence base experience improved innovation insight model organisms databases mortality non-nucleoside reverse transcriptase inhibitors novel pandemic disease population based prevent programs public health relevance research study resistance mechanism resistance mutation response success tool trend

项目摘要

DESCRIPTION (provided by applicant): Comprehensive, accurate, and publicly available HIV-1 antiretroviral (ARV) drug resistance data is essential for population-based monitoring of acquired and transmitted drug resistance in resource-limited regions, for guiding salvage ARV therapy in well-resourced regions, and for identifying overall ARV- development needs. However, the variability of viruses that comprise the HIV-1 pandemic and the high mutation rate of HIV-1 make it difficult to quantify transmitted and acquired drug resistance, to optimally interpret HIV-1 genotypic resistance tests, and to identify those ARV-resistant variants most relevant to the development of future ARVs. The Stanford HIV Drug Resistance Database (HIVDB) is the only publicly available source for three data correlations underlying HIV-1 drug resistance knowledge: (1) Correlations between the genetic sequences of the enzymatic targets of ARV therapy - PR, RT, and IN - with the ARV treatments of persons from whom sequenced HIV-1 variants are obtained; (2) Correlations between genotype and in vitro drug susceptibility; and (3) Correlations between genotype and the virological response to a new ARV treatment regimen. By emphasizing the collection, annotation, dissemination, and analysis of three main types of data, HIVDB facilitates meta-analyses in which data from many published studies and clinical trials can be effectively synthesized. The specific aims of this competing renewal for funding HIVDB are (1) To develop standardized genotypic methods to monitor the extent of transmitted and acquired drug resistance and to determine whether these methods can be applied across all HIV-1 subtypes; (2) To expand HIVDB by collecting, annotating, and disseminating the genotype-treatment, genotype-phenotype, and genotype-virological response data that inform genotypic resistance test interpretation. Coupled with this aim, we will improve the online framework for representing and describing the evidence basis associated with each genotypic resistance interpretation; and (3) To identify and preliminarily characterize representative and novel ARV-resistant variants that may help guide the development of future ARVs. Innovative aspects of this proposal include (1) the development of widely available and widely used online programs to facilitate data sharing and consistent analytic approaches across laboratories in many countries; (2) the development and implementation of regression methods and correlation network analyses to the study of HIV-1 drug resistance mutations; and (3) the use of data recruitment and curation methods adopted from model organism databases to create a sustainable model for the continuation and expansion of HIVDB.

描述（由申请人提供）：全面、准确且公开的 HIV-1 抗逆转录病毒 (ARV) 耐药性数据对于资源有限地区的获得性和传播性耐药性的人群监测、指导挽救性 ARV 治疗至关重要。 - 资源地区，并确定总体抗逆转录病毒药物开发需求。然而，构成 HIV-1 大流行的病毒的变异性和 HIV-1 的高突变率使得量化传播性和获得性耐药性、最佳解释 HIV-1 基因型耐药性测试以及识别那些抗逆转录病毒药物变得困难与未来抗逆转录病毒药物的开发最相关的变体。斯坦福 HIV 耐药数据库 (HIVDB) 是唯一可公开获取 HIV-1 耐药知识的三个数据相关性的来源：(1) ARV 治疗酶靶基因序列（PR、RT 和 IN）之间的相关性对获得 HIV-1 变异序列的人进行抗逆转录病毒治疗； (2)基因型与体外药敏的相关性； (3) 基因型与新抗逆转录病毒治疗方案的病毒学反应之间的相关性。通过强调三种主要数据类型的收集、注释、传播和分析，HIVDB 促进了荟萃分析，其中可以有效地综合许多已发表的研究和临床试验的数据。此次为 HIVDB 提供资金的竞争性更新的具体目标是 (1) 开发标准化基因型方法来监测传播性和获得性耐药性的程度，并确定这些方法是否可以应用于所有 HIV-1 亚型； (2) 通过收集、注释和传播为基因型耐药测试解释提供信息的基因型治疗、基因型-表型和基因型-病毒学反应数据来扩展 HIVDB。结合这一目标，我们将改进在线框架，用于表示和描述与每种基因型抗性解释相关的证据基础； (3) 识别并初步表征具有代表性和新颖的抗逆转录病毒药物变异体，这可能有助于指导未来抗逆转录病毒药物的开发。该提案的创新之处包括（1）开发广泛可用和广泛使用的在线程序，以促进许多国家实验室之间的数据共享和一致的分析方法； (2) HIV-1耐药突变研究回归方法和相关网络分析的开发和实施； (3) 利用模式生物数据库的数据招募和管理方法，为 HIVDB 的延续和扩展创建可持续的模式。