{"id":39029,"date":"2020-09-07T10:39:06","date_gmt":"2020-09-07T10:39:06","guid":{"rendered":"https:\/\/www.healthbenefitstimes.com\/glossary\/?p=39029"},"modified":"2020-09-07T10:39:06","modified_gmt":"2020-09-07T10:39:06","slug":"quantitative-structure-activity-relationship-qsar","status":"publish","type":"post","link":"https:\/\/www.healthbenefitstimes.com\/glossary\/quantitative-structure-activity-relationship-qsar\/","title":{"rendered":"Quantitative structure-activity relationship (QSAR)"},"content":{"rendered":"<p>A computer modeling technique that enables researchers (e.g., drug development chemists) to predict the likely activity (e.g., effect on tissue) of a new compound before that compound is actually created. QSAR is based on decades of research investigating the impact on &#8220;activity&#8221; of the chemical structures of thousands of thoroughly studied molecules.<\/p>\n<hr \/>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A computer modeling technique that enables researchers (e.g., drug development chemists) to predict the likely activity (e.g., effect on tissue) of a new compound before that compound is actually created. QSAR is based on decades of research investigating the impact on &#8220;activity&#8221; of the chemical structures of thousands of thoroughly studied molecules. &nbsp;<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[],"class_list":["post-39029","post","type-post","status-publish","format-standard","hentry","category-q"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Quantitative structure-activity relationship (QSAR) - Definition of Quantitative structure-activity relationship (QSAR)<\/title>\n<meta name=\"description\" content=\"A computer modeling technique that enables researchers (e.g., drug development chemists) to predict the likely activity (e.g., effect on tissue) of a new compound before that compound is actually created. 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