ERC Einstein Rockefeller CUNY Center for AIDS Research

ERC 爱因斯坦洛克菲勒纽约市立大学艾滋病研究中心

• 批准号: 10605278
• 负责人: Kathryn M. Anastos
• 金额: $ 78.74万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10605278
• 关键词: AIDS prevention; Acquired Immunodeficiency Syndrome; African American; Area; Behavioral; Biometry; COVID-19; Caring; Characteristics; Cities; Clinical; Clinical Research; Clinical Sciences; Clinical Services; Clinical Trials; Clinical and Translational Science Awards; Clinical effectiveness; Cohort Studies; Collaborations; Color; Community Health; Conduct Clinical Trials; Consent; Consultations; Creativeness; Data; Data Analyses; Databases; Development; Discipline; Electronic Health Record; Enrollment; Epidemic; Epidemiology; Explosion; Fertilization; Fostering; Funding; Genetic; Goals; HIV; HIV Infections; HIV Seronegativity; Health; Health Services; Health Services Accessibility; Health system; Heterosexuals; Hispanic; Human; Immunologics; Individual; Informatics; Information Systems; Infrastructure; Institution; Institutional Review Boards; International; Intervention; Investigation; Latinx; Leukapheresis; Link; Logistics; Machine Learning; Mental Health; Methods; Migrant; Mission; Natural Language Processing; New York; New York City; Outcome; Participant; Patient Recruitments; Patients; Persons; Phenotype; Policies; Population; Population Heterogeneity; Pregnancy; Pregnant Women; Prevention; Primary Prevention; Procedures; Prospective Studies; Protocols documentation; Provider; Public Health; Research; Research Activity; Research Design; Research Personnel; Research Support; Resources; Retrospective Studies; Science; Scientist; Services; Shipping; Source; Specific qualifier value; Specimen; Support System; System; Translational Research; Underrepresented Populations; United States National Institutes of Health; Universities; Update; Vision; Woman; Work; biobank; brain magnetic resonance imaging; cardiac magnetic resonance imaging; clinical database; clinical infrastructure; cohort; contextual factors; data infrastructure; experience; health care service utilization; health data; high risk; implementation science; improved; innovation; longitudinal database; men who have sex with men; novel; operation; participant enrollment; patient population; pre-exposure prophylaxis; prevent; prevention service; programs; prospective; recruit; repository; research study; sample collection; substance user; transgender; translational scientist; working group

PROJECT SUMMARY ERC-CFAR: CLINICAL AND TRANSLATIONAL SCIENCE CORE (CTSC) To help meet the vision of Ending the HIV Epidemic (EHE), the Einstein-Rockefeller-CUNY Center for AIDS Research (ERC-CFAR) has formed strong collaborations both within and beyond our partner institutions, including the New York City Department of Health and Mental Hygiene, to catalyze and support research that best serves the public’s health: to eradicate HIV infection, prevent new HIV infections, and improve the health of people living with HIV (PWH). The overarching goal of the ERC-CFAR and the Clinical and Translational Science Core (CTSC) is to support the EHE mission by creating a broad and robust resource available to researchers within our walls as well as nationally and globally. Our synergistic partnership provides a broad range of support for clinical, translational, health services, and implementation science investigations. By leveraging the resources of the Einstein CTSA-funded Institute for Clinical and Translational Research, the CTSC provides access to a robust clinical database and multiple biorepositories. The Clinical Cohort Database (CCDB), derived from the Montefiore/Einstein clinical services, has ~20,000 PWH and 475,000 HIV-negative patients; >6200 PWH are in active care; 43% are women, 48% Hispanic/Latinx and 41% African American. This comprehensive, longitudinal database accesses Montefiore’s extensive clinical infrastructure and has fostered an explosion of clinical prevention and treatment, epidemiologic, translational, health services and implementation science research. We facilitate enrollment of well-characterized patients (including HIV-negative controls) into new research protocols. Through CTSC resources the clinical population at Montefiore/Einstein enables research at Rockefeller, which lacks access to defined cohorts of PWH, recruiting new participants for Rockefeller’s cutting-edge research in HIV eradication. The City University of New York (CUNY) is a leader in implementation science assessing the factors that influence our ability to impact favorably on the public’s health with interventions of proven efficacy. The CTSC is integrated into the Scientific Working Group, a driver of the ERC-CFAR’s scientific direction, to provide optimal support to the emerging research activities, and foster cross- fertilization among cores and the SWG. We will leverage Einstein’s Center for Health Data Innovations and use of state-of-the-art informatics methods, including natural language processing and machine learning, to catalyze and facilitate new research in primary prevention of HIV infection, while maintaining our extensive support of well-established research areas.

项目摘要 ERC-CFAR：临床和翻译科学核心（CTSC） 为了帮助实现结束艾滋病毒流行病（EHE）的愿景，爱因斯坦-洛克菲勒-纽约市立大学艾滋病中心 研究（ERC-CFAR）在我们的合作机构内外都形成了强有力的合作， 包括纽约市卫生和心理卫生部，以促进和支持研究， 最好的服务于公众的健康：消除艾滋病毒感染，预防新的艾滋病毒感染，并改善健康 艾滋病毒携带者（PWH）ERC-CFAR的总体目标以及临床和转化 科学核心（CTSC）是通过创建广泛而强大的资源来支持EHE使命， 研究人员在我们的墙壁以及国家和全球。我们的协同合作伙伴关系提供了广泛的 为临床、转化、卫生服务和实施科学研究提供一系列支持。通过 利用爱因斯坦CTSA资助的临床和转化研究所的资源， CTSC提供对强大的临床数据库和多个生物储存库的访问。临床队列数据库 （CCDB），来自Montefiore/Einstein临床服务，有约20，000名PWH和475，000名HIV阴性 患者; >6200名PWH正在接受积极治疗; 43%为女性，48%为西班牙裔/拉丁裔，41%为非洲裔美国人。这 一个全面的纵向数据库访问Montefiore广泛的临床基础设施，并促进了 临床预防和治疗、流行病学、转化、卫生服务和 实施科学研究。我们促进了特征良好的患者（包括HIV阴性患者）的入组 控制）到新的研究方案。通过CTSC资源，Montefiore/Einstein的临床人群 使洛克菲勒的研究能够进行，该研究无法进入PWH的定义队列，招募新的参与者， 洛克菲勒在根除艾滋病方面的前沿研究纽约城市大学（CUNY）是 实施科学评估影响我们对公众健康产生有利影响的能力的因素 有效的干预措施。气候技术服务中心被纳入科学工作组， ERC-CFAR的科学方向，为新兴的研究活动提供最佳支持，并促进跨学科研究。 核心和SWG之间的施肥。我们将利用爱因斯坦的健康数据创新中心， 最先进的信息学方法，包括自然语言处理和机器学习， 促进艾滋病毒感染初级预防方面的新研究，同时继续广泛支持 完善的研究领域。