{"id":689607,"date":"2022-03-01T04:07:12","date_gmt":"2022-03-01T12:07:12","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=689607"},"modified":"2023-02-20T05:49:31","modified_gmt":"2023-02-20T13:49:31","slug":"generative-chemistry","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/generative-chemistry\/","title":{"rendered":"Generative Chemistry"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background-grey card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1400\" height=\"788\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788.png\" class=\"attachment-full size-full\" alt=\"generative chemistry, drug discovery, molecules, stock image\" style=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788.png 1400w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-300x169.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-768x432.png 768w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-1024x576.png 1024w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-1066x600.png 1066w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-655x368.png 655w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/11\/NIPS_Minimizing-Trial-And-Error-In-The-Drug-Discovery-Process_DL_Site_11_2018_1400x788-343x193.png 343w\" sizes=\"(max-width: 1400px) 100vw, 1400px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 align-self-center\">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 class=\"h2 wp-block-heading\" id=\"generative-chemistry\">Generative Chemistry<\/h1>\n\n\n\n<p>Training machine learning to identify relevant project candidates<\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<p>The process for developing new drugs is incredibly complex, requiring the evaluation of hundreds of thousands of candidate compounds before a project reaches the clinical trial stage. This process is slow, costly, and requires immense amounts of expert time. In this project, we are trying to train machine learning systems to help chemists and pharmacists to more quickly find new relevant candidates for their projects.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>The process for developing new drugs is incredibly complex, requiring the evaluation of hundreds of thousands of candidate compounds before a project reaches the clinical trial stage. This process is slow, costly, and requires immense amounts of expert time. In this project, we are trying to train machine learning systems to help chemists and pharmacists to more quickly find new relevant candidates for their projects.<\/p>\n","protected":false},"featured_media":551418,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13556,13553],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-689607","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-medical-health-genomics","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2020-01-01","related-publications":[543570,803299,822850,921192],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"guest","display_name":"John Bronskill","user_id":774337,"people_section":"Section name 0","alias":""},{"type":"user_nicename","display_name":"Jose Jimenez-Luna","user_id":41515,"people_section":"Section name 0","alias":"jjimenezluna"},{"type":"user_nicename","display_name":"Sarah Lewis","user_id":41305,"people_section":"Section name 0","alias":"sarahlewis"},{"type":"user_nicename","display_name":"Krzysztof Maziarz","user_id":38955,"people_section":"Section name 0","alias":"krmaziar"},{"type":"user_nicename","display_name":"Marwin Segler","user_id":40300,"people_section":"Section name 0","alias":"marwinsegler"},{"type":"user_nicename","display_name":"Megan Stanley","user_id":41482,"people_section":"Section name 0","alias":"meganstanley"},{"type":"user_nicename","display_name":"Elise van der Pol","user_id":41749,"people_section":"Section name 0","alias":"evanderpol"}],"msr_research_lab":[199561,851467],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/689607"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":9,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/689607\/revisions"}],"predecessor-version":[{"id":982359,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/689607\/revisions\/982359"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/551418"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=689607"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=689607"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=689607"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=689607"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=689607"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}