{"id":5591,"date":"2022-04-14T02:00:00","date_gmt":"2022-01-30T04:01:40","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&p=5591"},"modified":"2022-02-24T09:25:25","modified_gmt":"2022-02-24T00:25:25","slug":"2022-04-14-2","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-04-14-2\/","title":{"rendered":"A systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment"},"content":{"rendered":"

This talk will be presented online. Zoom link: 997 8258 4700<\/a> (pw: 1234)<\/p>\n

Abstract: Tuberculosis (TB) is one of the world\u2019s deadliest infectious diseases. Caused by the pathogen <\/span>Mycobacterium<\/span><\/i> tuberculosis <\/span><\/i>(Mtb), the standard regimen for treating TB consists of treatment with multiple antibiotics for at least six months. There are a number of complicating factors that contribute to the need for this long treatment duration and increase the risk of treatment failure. The structure of granulomas, lesions forming in lungs in response to Mtb infection, create heterogeneous antibiotic distributions that limit antibiotic exposure to Mtb. \u00a0 We can use a systems biology approach pairing experimental data from non-human primates with computational modeling to represent and predict how factors impact antibiotic regimen efficacy and granuloma bacterial sterilization. We utilize an agent-based, computational model that simulates granuloma formation, function and treatment, called <\/span>GranSim<\/span><\/i>.\u00a0 A goal in improving antibiotic treatment for TB is to find regimens that can shorten the time it takes to sterilize granulomas while minimizing the amount of antibiotic required. We also created a whole host model, called HOSTSIM, to study Mtb dynamics within a human host. <\/span>\u00a0Overall, we<\/span><\/i> use these models to help better understand TB treatment and strengthen our ability to predict regimens that can improve clinical treatment of TB.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: Tuberculosis (TB) is one of the world\u2019s deadliest infectious diseases. Caused by the pathogen Mycobacterium tuberculosis … <\/p>\n

Continue reading “A systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment”<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":5572,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[221],"class_list":["post-5591","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-biomedical-mathematics-colloquium","cat_biomedical-mathematics-colloquium","tribe-ext-events-control-list-event--live"],"yoast_head":"\nA systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment - Biomedical Mathematics Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-04-14-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"This talk will be presented online. 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