{"id":7988,"date":"2026-07-06T11:59:40","date_gmt":"2026-07-06T15:59:40","guid":{"rendered":"https:\/\/cqdm.org\/?post_type=project&#038;p=7988"},"modified":"2026-07-06T12:54:34","modified_gmt":"2026-07-06T16:54:34","slug":"development-of-a-predictive-ai-system-in-oncology-powered-by-phenotypic-data-capturing-the-evolution-of-the-tumor-microenvironment","status":"publish","type":"project","link":"https:\/\/cqdm.org\/en\/achievement\/funded-projects\/development-of-a-predictive-ai-system-in-oncology-powered-by-phenotypic-data-capturing-the-evolution-of-the-tumor-microenvironment\/","title":{"rendered":"Development of a predictive AI system in oncology powered by phenotypic data capturing the evolution of the tumor microenvironment\u00a0\u00a0"},"content":{"rendered":"\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">Project of $2,202,780 over 2 years<\/h2>\n\n\n\n<ul class=\"wp-block-list is-style-checkmark\">\n<li><strong><strong>Supported by CQDM through:<\/strong><\/strong><br>Minist\u00e8re de l\u2019\u00c9conomie, de l\u2019Innovation et de l\u2019\u00c9nergie du Qu\u00e9bec (MEIE)<\/li>\n\n\n\n<li><strong><strong><strong>By co-funding partners:<\/strong><\/strong><\/strong><br>&#8211; Simmunome inc.<br>&#8211; MISO Chip<\/li>\n\n\n\n<li><strong><strong><strong>And by project partner:<\/strong><\/strong><\/strong><br>&#8211; IVADO<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>The project in detail:<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Recent advances in artificial intelligence (AI) have improved the success rates of Phase I clinical trials, but have yet to achieve similar gains in Phase II, a critical stage for demonstrating therapeutic efficacy in humans. In oncology, treatment effectiveness is strongly influenced by the tumor microenvironment (TME), the molecular profile of tumors, and their evolution over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To accelerate the discovery of therapies that effectively target the TME, several key challenges must be addressed: the availability of standardized and structured molecular data, the development of AI systems capable of predicting clinical efficacy, and access to preclinical models that preserve the human TME and generate high-value phenotypic data with strong translational relevance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To meet these challenges, Simmunome and MISO Chip are developing TME Predict, an artificial intelligence system designed to predict treatment effects on the TME. This tool leverages a unique dataset, Functional TME Insights, integrating multi-omics and phenotypic data to capture the dynamic evolution of the human TME.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Targeted at the pharmaceutical industry, these integrated approaches have the potential to improve therapeutic candidate selection and significantly advance precision medicine.<\/p>\n","protected":false},"featured_media":3821,"template":"","project-category":[95],"class_list":["post-7988","project","type-project","status-publish","has-post-thumbnail","hentry","project-category-bioinformatics-and-artificial-intelligence"],"acf":[],"_links":{"self":[{"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/project\/7988","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/project"}],"about":[{"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/types\/project"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/media\/3821"}],"wp:attachment":[{"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/media?parent=7988"}],"wp:term":[{"taxonomy":"project-category","embeddable":true,"href":"https:\/\/cqdm.org\/en\/wp-json\/wp\/v2\/project-category?post=7988"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}