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HIV Drug Resistance Database

HIV耐药数据库

基本信息

批准号：
10699882
负责人：
ROBERT William SHAFER
金额：
$ 71.45万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-05-01 至 2028-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10699882
关键词：
2019-nCoV Acquired Immunodeficiency Syndrome Address Anti-Retroviral Agents Antiviral Agents Antiviral Therapy Biological COVID-19 treatment Capsid Clinical Clinical Data Clinical Management Clinical Trials Cohort Studies Computer software Conduct Clinical Trials Data Data Collection Data Set Databases Development Drug resistance Ensure Epidemiologist Epidemiology Failure Fostering Foundations Funding Genbank Genotype Geographic Locations Goals Grant HIV HIV drug resistance HIV therapy In Vitro Individual Integrase Knowledge Laboratories Laboratory Research Literature Logic Meta-Analysis Metadata Modernization Molecular Target Monitor Mutation Outcome Patients Peptide Hydrolases Persons Pharmaceutical Preparations Play Positioning Attribute Predisposition Prevalence Prevention Public Health Publishing R24 RNA-Directed DNA Polymerase Recording of previous events Regimen Research Research Personnel Resistance Resources Role Scientist Sequence Analysis Sorting Testing Therapy Clinical Trials Update Virus Work antiretroviral therapy combat data sharing database query design drug development drug resistant virus experience fighting high risk improved knowledge base molecular sequence database novel novel strategies open source pandemic disease pathogenic virus population based predicting response programs public database public repository recruit resistance mutation response success systematic review targeted treatment transmission process

项目摘要

PROJECT SUMMARY HIV drug resistance (HIVDR) is a threat to the success of antiretroviral (ARV) therapy (ART) and a major barrier to the elimination of AIDS as a public health problem. Persons with HIV who develop virological failure (VF) during ART are at high risk of developing HIVDR and transmitting a drug-resistant virus to others while persons primarily infected with a drug-resistant virus are at high risk of developing VF and a further increase in HIVDR. Comprehensive, accurate, and publicly available HIVDR data are essential for population-based monitoring of acquired and transmitted HIVDR, for the management of HIV-infected patients, and for identifying overall drug-development needs. A public database that curates, annotates, synthesizes, and disseminates data from HIVDR studies will make it possible to identify and characterize the HIVDR mutations most relevant to surveillance, clinical management, and drug development, and will expedite research into the mechanisms of HIVDR and the predictors of response to the newest ARV regimens. The Stanford HIV Drug Resistance Database (HIVDB) provides a unique conceptual framework for addressing data-intensive questions about the main molecular targets of HIV therapy: reverse transcriptase, protease, integrase, and capsid. HIVDB’s sequence analysis programs have also become integrated into the workflows of many research laboratories worldwide. Accomplishing the Aims of this proposal will assist researchers engaged in HIVDR surveillance, ART clinical trials, and ARV development by enabling them to identify gaps in the published literature, incorporate contributions from HIVDB into novel analyses, and discover new knowledge. Our first Aim will involve expanding HIVDB as a resource that provides the scientific foundations of the clinical and epidemiological significance of HIVDR mutations and that address gaps in HIVDR knowledge including the correlates of resistance to recently approved ARVs, established ARVs used for new indications, and the long-acting ARVs that will be used for prevention and treatment. We will implement strategies to increase data sharing to help ensure the long-term sustainability of this project. Our second Aim will involve extending the logic of HIVDB’s genotypic resistance test interpretation program to predict the virological response to ARV combinations and common ART regimens. We will demonstrate and promote the use of our sequence analysis software for the analysis of other pathogenic viruses for which antiviral therapy is available. Our third Aim will involve converting HIVDB into a fully open source and transferable project. Accomplishing this aim will support researchers using HIVDB to advance their research by enabling them to seamlessly integrate HIVDR data into their research. Accomplishing this aim will also foster the long-term sustainability of the HIVDB project.

项目摘要 HIV耐药性（HIV drug resistance，HIV DR）是抗逆转录病毒（antiretroviral，ARV）疗法（antiretroviral therapy，ART）成功的一个威胁，也是HIV耐药性的主要原因。阻碍消除艾滋病这一公共卫生问题。病毒学失败的艾滋病毒感染者 (VF)在抗逆转录病毒治疗期间，主要感染耐药病毒的人患VF的风险很高，并且进一步增加 in HIVDR.全面、准确和公开的艾滋病毒/艾滋病数据对于基于人口的监测获得性和传播的HIV感染者，管理HIV感染者，确定总体药物开发需求。一个公共数据库，用于管理、注释、综合和传播来自HIV研究的数据将使识别和描述HIV突变成为可能最相关的监测，临床管理和药物开发，并将加快研究，艾滋病的机制和对最新抗逆转录病毒治疗方案反应的预测因素。斯坦福大学艾滋病毒耐药性数据库（HIV DB）提供了一个独特的概念框架，解决有关HIV治疗的主要分子靶点的数据密集型问题：逆转录酶，蛋白酶、整合酶和衣壳。HIV数据库的序列分析程序也已整合到全球许多研究实验室的工作流程。实现本建议的目标将有助于从事艾滋病监测、ART临床试验和ARV开发的研究人员，使他们能够确定已发表文献中的差距，将艾滋病毒/艾滋病数据库的贡献纳入新的分析，发现新知识。我们的第一个目标将涉及扩大艾滋病毒数据库作为一种资源，为临床治疗提供科学基础。和流行病学意义，并解决艾滋病知识的差距，包括对最近批准的抗逆转录病毒药物、用于新适应症的已确立的抗逆转录病毒药物以及将用于预防和治疗的长效ARV。我们将实施战略，数据共享有助于确保该项目的长期可持续性。我们的第二个目标将涉及扩展HIV数据库基因型耐药测试解释程序的逻辑预测抗逆转录病毒药物联合治疗和普通抗逆转录病毒疗法的病毒学应答。我们将演示并推广使用我们的序列分析软件来分析其他致病病毒，抗病毒治疗是可行的。我们的第三个目标是将HIV数据库转化为一个完全开源和可转让的项目。完成这一目标将支持研究人员利用艾滋病毒数据库，通过使他们能够无缝地将艾滋病毒/艾滋病数据纳入其研究。实现这一目标也将促进长期可持续性艾滋病病毒数据库项目。

项目成果

期刊论文数量（32）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Selection analyses of paired HIV-1 gag and gp41 sequences obtained before and after antiretroviral therapy.

对抗逆转录病毒治疗前后获得的配对 HIV-1 gag 和 gp41 序列进行选择分析。

DOI：
10.1038/sdata.2018.147
发表时间：
2018
期刊：
Scientific data
影响因子：
9.8
作者：
Tzou,PhilipL;Rhee,Soo-Yon;Pond,SergeiLKosakovsky;Manasa,Justen;Shafer,RobertW
通讯作者：
Shafer,RobertW

Potential role of doravirine for the treatment of HIV-1-infected persons with transmitted drug resistance.

DOI：
10.1186/s12981-023-00503-5
发表时间：
2023-02-07
期刊：
AIDS RESEARCH AND THERAPY
影响因子：
2.2
作者：
Rhee, Soo-Yon;Schapiro, Jonathan M. M.;Saladini, Francesco;Zazzi, Maurizio;Khoo, Saye;Shafer, Robert W. W.
通讯作者：
Shafer, Robert W. W.

Susceptibility of SARS-CoV-2 Omicron Variants to Therapeutic Monoclonal Antibodies: Systematic Review and Meta-analysis.

DOI：
10.1128/spectrum.00926-22
发表时间：
2022-08-31
期刊：
MICROBIOLOGY SPECTRUM
影响因子：
3.7
作者：
Tao, Kaiming;Tzou, Philip L.;Pond, Sergei L. Kosakovsky;Ioannidis, John P. A.;Shafer, Robert W.
通讯作者：
Shafer, Robert W.

A SARS-CoV-2 antiviral therapy score card.