PUBLIC HIV DRUG RESISTANCE DATABASE

描述（由申请方提供）：全面、准确和公开的HIV-1抗逆转录病毒（ARV）耐药性数据对于在资源有限地区进行基于人群的获得性和传播性耐药性监测、指导资源充足地区的ARV补救治疗以及确定总体ARV发展需求至关重要。然而，构成HIV-1大流行的病毒的变异性和HIV-1的高突变率使得难以量化传播和获得的耐药性，难以最佳地解释HIV-1基因型耐药性测试，也难以识别与未来抗逆转录病毒药物开发最相关的抗逆转录病毒药物耐药性变体。斯坦福大学HIV耐药性数据库（HIV-1 Drug Resistance Database，HIV-1 Drug Resistance Database）是唯一一个公开的HIV-1耐药性相关性数据的来源：（1）抗逆转录病毒治疗的酶靶点- PR、RT和IN -的基因型数据与获得HIV-1分离株序列的人的抗逆转录病毒治疗之间的相关性;（2）基因型与体外药物敏感性之间的相关性;（3）基因型与抗逆转录病毒治疗方案病毒学应答的相关性。通过强调收集、注释、传播和分析三种主要类型的数据，艾滋病毒数据库促进了荟萃分析，其中可以有效地综合来自许多已发表研究和临床试验的数据。这一为HIV-1数据库提供资金的竞争性更新的具体目标是：（1）开发标准化的基因型方法，以监测传播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、注释和传播基因型-治疗、基因型-表型、和基因型-病毒学应答数据，其告知基因型抗性测试解释。结合这一目标，我们将创建一个 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;以及（3）识别和初步表征可能有助于指导未来抗逆转录病毒药物开发的代表性和新型抗逆转录病毒药物变体。该提案的创新方面包括：（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）开发和实施新的应用回归方法和相关网络分析;以及（3）使用从模式生物数据库中采用的数据招募和管理方法，为HIV数据库的延续和扩展创建可持续的模型。!

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 main data correlations underlying HIV-1 drug resistance knowledge: (1) Correlations between genotypic data for the enzymatic targets of ARV therapy - PR, RT, and IN - with the ARV treatments of persons from whom the sequenced HIV-1 isolates were 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 create an 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 novel applied regression methods and correlation network analyses; 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. !