用血管激素转化酶抑制剂治疗的各种患者的药物基因组知识和意识
Hetanshi Naik1, Michelle Y O'Connor2, Saskia C Sanderson1
1Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
新的算法确定了血管激素转化酶抑制剂 (ACEi) 诱导的血管发病例. 患者希望进行药物基因组测试,以更好地遵守药物治疗,尽管医生对药物变异性的沟通有限.
科学领域:
- 药物基因组学 药物基因组学
- 生物信息学是一种生物信息学.
- 临床药理学 临床药理学
背景情况:
- 电子健康记录和生物库是药物遗传学研究的宝贵资源.
- 鉴定药物遗传学研究的特定患者队列可能具有挑战性.
- 患者对药物基因组学和药物反应变化的理解往往是有限的.
研究的目的:
- 在BioMe生物库中开发和验证电子表型算法,用于识别血管激素转化酶抑制剂 (ACEi) 诱导的血管的病例和控制.
- 评估患者对药物基因组学和药物反应变异性的认识.
- 测量患者对药物基因组测试的兴趣及其对药物服药的潜在影响.
主要方法:
- 使用BioMe生物银行数据开发新的电子表型算法.
- 对ACEi诱导的血管的病例对照鉴定.
- 一项调查分发给患者,以评估药物基因组测试的认识,兴趣和潜在影响.
主要成果:
- 使用开发的算法准确识别ACEi诱导的血管发病例和对照.
- 超过三分之一的受访患者报告说,与医生就药物反应变化或不良事件风险进行的讨论不足.
- 73%的患者不知道药物基因组学,但大多数人对测试表达了兴趣,67%的人认为这将改善药物服药.
结论:
- 新型电子表现型为药物基因组学研究的生物银行队列定义提供了一种创新的方法.
- 患者对药物基因组测试表现出显著的兴趣,这表明改善药物坚持的潜在途径.
- 需要加强患者教育和医生在药物基因组学方面的沟通.
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