Computer-Aided Chemical Synthesis Planning (CASP) algorithms have the potential to help chemists predict how to make molecules, and decide which molecules to prioritize for synthesis and testing. Recently, several algorithms have been proposed to tackle this problem, reporting large performance improvements. In this work, we re-examine current and prior State-of-the-Art synthesis planning algorithms under controlled and identical conditions, providing a holistic view using several previously un-reported evaluation metrics which cover the common use-cases of these algorithms. In contrast to prior studies, we find that under strict control, differences between algorithms are smaller than previously assumed. Our findings can guide users to choose the appropriate algorithms for specific tasks, as well as stimulate new research in improved algorithms.<\/p>\n","protected":false},"excerpt":{"rendered":"
Computer-Aided Chemical Synthesis Planning (CASP) algorithms have the potential to help chemists predict how to make molecules, and decide which molecules to prioritize for synthesis and testing. Recently, several algorithms have been proposed to tackle this problem, reporting large performance improvements. In this work, we re-examine current and prior State-of-the-Art synthesis planning algorithms under controlled […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-921192","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2022-12-2","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/openreview.net\/forum?id=8VLeT8DFeD","label_id":"243109","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/openreview.net\/pdf?id=8VLeT8DFeD","label_id":"243132","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Austin Tripp","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Krzysztof Maziarz","user_id":38955,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Krzysztof Maziarz"},{"type":"user_nicename","value":"Sarah Lewis","user_id":41305,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sarah Lewis"},{"type":"user_nicename","value":"Guoqing Liu","user_id":40438,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Guoqing Liu"},{"type":"user_nicename","value":"Marwin Segler","user_id":40300,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Marwin Segler"}],"msr_impact_theme":[],"msr_research_lab":[851467],"msr_event":[873195],"msr_group":[],"msr_project":[689607],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":689607,"post_title":"Generative Chemistry","post_name":"generative-chemistry","post_type":"msr-project","post_date":"2022-03-01 04:07:12","post_modified":"2023-02-20 05:49:31","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/generative-chemistry\/","post_excerpt":"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. 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