{"id":9618,"date":"2023-04-30T15:30:00","date_gmt":"2023-04-30T12:30:00","guid":{"rendered":"https:\/\/kenes-exhibitions.com\/biomed\/?p=9618"},"modified":"2023-04-30T15:34:49","modified_gmt":"2023-04-30T12:34:49","slug":"ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22","status":"publish","type":"post","link":"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/","title":{"rendered":"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22)"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"9618\" class=\"elementor elementor-9618\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ea495d6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ea495d6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ae68a10\" data-id=\"ae68a10\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3d17452 elementor-widget elementor-widget-image\" data-id=\"3d17452\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.12.1 - 02-04-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img width=\"624\" height=\"346\" src=\"https:\/\/kenes-exhibitions.com\/biomed\/wp-content\/uploads\/2023\/04\/WhatsApp-Image-2023-04-30-at-15.32.48.jpeg\" class=\"attachment-large size-large wp-image-9621\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/kenes-exhibitions.com\/biomed\/wp-content\/uploads\/2023\/04\/WhatsApp-Image-2023-04-30-at-15.32.48.jpeg 624w, https:\/\/kenes-exhibitions.com\/biomed\/wp-content\/uploads\/2023\/04\/WhatsApp-Image-2023-04-30-at-15.32.48-300x166.jpeg 300w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7235dec elementor-widget elementor-widget-text-editor\" data-id=\"7235dec\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.12.1 - 02-04-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p class=\"paragraph\"><em>Ofer Sharon, M.D., CEO, OncoHost\/company courtesy\u00a0<\/em><\/p><p class=\"paragraph\">Artificial intelligence and machine learning could change the face of cancer diagnostics.<\/p><p>Today, physicians may run blood tests to find biomarkers specific to cancer, conduct imaging tests via MRI, CT or ultrasound to visualize a potential tumor or biopsy to analyze tissue up close.<\/p><p>But these methods have drawbacks, including the possibility of not catching the cancer at all.\u00a0<\/p><p>AI and ML can be given datasets to &#8220;learn&#8221; from, ultimately improving accuracy for detecting malignant cells.<\/p><p>Predictive models can use genetic information and other factors regarding a patient\u2019s lifestyle to determine their likelihood of developing a certain type of cancer. This same information can also be used to identify how the cancer will respond to different treatments.\u00a0<\/p><p>Some of the most difficult-to-treat cancers &#8211; including glioblastoma multiforme (GBM), ovarian cancer and non-small cell lung cancer (NSCLC) &#8211; could benefit from recent advances in AI\/ML.\u00a0\u00a0<\/p><p><strong>Helping to Predict Brain Tumor Progression\u00a0<\/strong><\/p><p>GBM remains one of the deadliest cancers, with a median survival time of\u00a0<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/books\/NBK558954\/#:~:text=Glioblastoma%20multiforme%20%28GBM%29%20is%20the%20most%20common%20primary,%25%20of%20patients%20survived%20five%20years%20post-diagnosis.%20\">15 months<\/a>\u00a0and a five-year survival rate of only 5.5%, according to the National Institutes of Health.\u00a0<\/p><p>Understanding the progression of GBM is challenging because the tumor must be treated quickly and aggressively for the best possible outcome. There is no time to wait and see how it will grow.\u00a0<\/p><figure class=\"image\"><img loading=\"lazy\" src=\"https:\/\/www.biospace.com\/getasset\/444f725f-6b28-4146-8f4f-3c7cd6f7d48a\/\" alt=\"Cameron Meaney_University of Waterloo2\" width=\"190\" height=\"201\" \/><figcaption>Cameron Meaney<\/figcaption><\/figure><p>This leaves researchers at a loss for creating precision therapeutics. Without a roadmap of the cancer\u2019s progression over time, it can be difficult to predict how a tumor might grow or the best time for surgery.<\/p><p>Researchers from the University of Waterloo and University of Toronto partnered with St. Michael\u2019s Hospital to analyze MRI data from GBM patients. A unique dataset of five patients who chose not to have their tumors treated provided data that demonstrated how untreated GBM tumors grow over time.\u00a0<\/p><p>The team developed a method that combined existing mathematical models with novel artificial intelligence approaches to predict patient-specific tumor progression.<\/p><p>\u201cGBM tumors are super resistant to a lot of treatments. They\u2019re super fast-growing and lead to a lot of recurrences after treatment,\u201d Cameron Meaney, leader of the study and Ph.D. candidate in applied mathematics at the University of Waterloo, told\u00a0<em>BioSpace<\/em>. \u201cProjections of tumor progression that are patient-specific can be more accurate for answering questions about timing of treatment.\u201d\u00a0<\/p><p>With more data collection, Meaney said it\u2019s possible physicians could utilize software that takes MRI images of a patient\u2019s tumor and uses those images to predict future tumor growth.\u00a0<\/p><p>Getting to this point will require collecting more data that shows how treatment affects tumor progression, Meaney said, and then using that data to make predictions specific to treatment.\u00a0<\/p><p>Meaney added that ML models could one day help determine the most effective way to attack the tumor or identify optimization schemes to make treatment more efficient.\u00a0<\/p><p><strong>A New Approach to Ovarian Cancer Detection<\/strong><\/p><p>Just as deadly, ovarian cancer is often labeled &#8220;the silent killer&#8221;.\u00a0<\/p><p>Israeli femtech company Gina Life takes a different approach to the detection of ovarian cancer. Three-quarters of patients are diagnosed with metastatic cancer, and survival rates vary between 5% and 20%, Inbal Zafir-Lavie, Ph.D., co-founder and CEO, told\u00a0<em>BioSpace<\/em>.<\/p><p>If detected early, however, she said survival rates are between 45 and 90%.<\/p><p>While most diagnostic approaches involve a blood test, Gina Life\u2019s test utilizes vaginal secretions, a biofluid in the vicinity of the tumor. The test leverages a panel of unique, proprietary biomarkers supported by AI.<\/p><figure class=\"image\"><img loading=\"lazy\" src=\"https:\/\/www.biospace.com\/getasset\/a38cca5b-74b2-4866-bf94-3b1d518ec382\/\" alt=\"Inbal Zafir-Lavie_Gina Life2\" width=\"180\" height=\"233\" \/><figcaption>Inbal Zafir-Lavie, Ph.D.<\/figcaption><\/figure><p>\u201cThe ovaries are small and they\u2019re white, so for an early-stage, small tumor, the signal in the blood is low,\u201d Zafir-Lavie said. \u201cBasically, trying to detect early-stage ovarian cancer in the blood is like taking a blue eye drop and dropping it into a pool. You can barely see the signal.\u201d\u00a0<\/p><p>Gina Life applies machine learning in a system that learns what a healthy woman looks like.<\/p><p>\u201cNow, we can add ovarian cancer patients and ask the system, where are the differences? With the human eye, this is really hard to do. I can see it, but I can&#8217;t see the complexities, and we&#8217;re looking for a fingerprint of biomarkers,\u201d Zafir-Lavie said.<\/p><p>She emphasized that the company does not allow the machine to run wild.<\/p><p>\u201cWe&#8217;re always applying our domain knowledge\u2026We\u2019re always verifying that [the results] make sense.\u201d\u00a0<\/p><p><strong>Optimizing the Power of Anti-PD 1\/PD-L1 Therapies<\/strong><\/p><p>AI\/ML can play a vital role in directing treatment as well.\u00a0<\/p><p>PD-1\/PD-L1 inhibitors like Keytruda (pembrolizumab) and Opdivo (nivolumab) have been instrumental in treating non-small cell lung cancer.\u00a0<\/p><p>These immunotherapies work by blocking the interaction between PD-L1, which is expressed on the cells of many tumors, and PD-1, which is highly expressed on many immune cells. They work for between 20 and 50% of patients. This poses a challenge for physicians.<\/p><figure class=\"image\"><img loading=\"lazy\" src=\"https:\/\/www.biospace.com\/getasset\/a0dc8846-da9c-4f2f-9f02-e408880e49c6\/\" alt=\"Ofer Sharon head shot_OncoHost\" width=\"200\" height=\"229\" \/><figcaption>Ofer Sharon, M.D.<\/figcaption><\/figure><p>\u201cWe don&#8217;t have good biomarkers for immunotherapy,\u201d Ofer Sharon, M.D., CEO of OncoHost and chair of the Precision Oncology session at the upcoming\u00a0<a href=\"https:\/\/kenes-exhibitions.com\/biomed\/agenda\/\">Biomed Israel conference<\/a>, told\u00a0<em>BioSpace<\/em>. \u201cA lot of the work by the clinician today is done based on clinical experience and sometimes trial and error.\u201d<\/p><p>In stage 4 NSCLC, up to 80% of patients will be treated with immunotherapy \u2013 either monotherapy or in combination with chemotherapy. Currently, if the tumor expresses less than 50% PD-L1, a combination is recommended, while tumors expressing more than 50% PD-L1 should be treated with monotherapy or a combination, Sharon said.\u00a0<\/p><p>There are currently hundreds of active trials involving various combinations with PD-1\/PD-L1 inhibitors.<\/p><p>In a few years, \u201cThe decision tree for first line therapy in lung cancer alone will involve numerous choices,\u201d Sharon said.<\/p><p>So, OncoHost developed the PROphet platform, which can help physicians understand the interplay between the tumor, the patient and the therapy. With a single blood test, PROphet analyzes proteomic patterns with AI algorithms to predict an individual patient\u2019s response to anti-PD-1\/PD-L1 therapies \u2013 so far, very\u00a0<a href=\"https:\/\/www.biospace.com\/article\/releases\/jitc-publishes-oncohost-study-identifying-predictive-proteomic-signature-to-analyze-treatment-resistance-in-nsclc-patients\/?keywords=OncoHost\">accurately<\/a>.<\/p><p>PROphet attempts to answer the following questions:<\/p><p>1. What is the optimal first-line therapy?<\/p><p>2. What drives the tumor\u2019s resistance?<\/p><p>3. What are the next steps?<\/p><p>A study published in the<em>\u00a0Journal for Immunotherapy of Cancer<\/em>\u00a0in June 2022 highlighted a predictive proteomic signature revealed by the PROphet platform for analyzing treatment resistance in NSCLC.\u00a0OncoHost launched the PROphet NSCLC test in the U.S. in February.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Ofer Sharon, M.D., CEO, OncoHost\/company courtesy\u00a0 Artificial intelligence and machine learning could change the face of cancer diagnostics. Today, physicians may run blood tests to find biomarkers specific to cancer, conduct imaging tests via MRI, CT or ultrasound to visualize a potential tumor or biopsy to analyze tissue up close. But these methods have drawbacks, [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":9621,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[14],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.6.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22) - Biomed 2026<\/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:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22) - Biomed 2026\" \/>\n<meta property=\"og:description\" content=\"Ofer Sharon, M.D., CEO, OncoHost\/company courtesy\u00a0 Artificial intelligence and machine learning could change the face of cancer diagnostics. Today, physicians may run blood tests to find biomarkers specific to cancer, conduct imaging tests via MRI, CT or ultrasound to visualize a potential tumor or biopsy to analyze tissue up close. But these methods have drawbacks, [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/\" \/>\n<meta property=\"og:site_name\" content=\"Biomed 2026\" \/>\n<meta property=\"article:published_time\" content=\"2023-04-30T12:30:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-04-30T12:34:49+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/kenes-exhibitions.com\/biomed\/wp-content\/uploads\/2023\/04\/WhatsApp-Image-2023-04-30-at-15.32.48.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"624\" \/>\n\t<meta property=\"og:image:height\" content=\"346\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"chantal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"chantal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/\",\"url\":\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/\",\"name\":\"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22) - Biomed 2026\",\"isPartOf\":{\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/#website\"},\"datePublished\":\"2023-04-30T12:30:00+00:00\",\"dateModified\":\"2023-04-30T12:34:49+00:00\",\"author\":{\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/#\/schema\/person\/bcbdb493d695d393e0f7c5f45999f642\"},\"breadcrumb\":{\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/kenes-exhibitions.com\/biomed\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/#website\",\"url\":\"https:\/\/kenes-exhibitions.com\/biomed\/\",\"name\":\"Biomed 2026\",\"description\":\"Biomed 2026 is the largest convention in Israel for Life Sciences and Technology\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/kenes-exhibitions.com\/biomed\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/#\/schema\/person\/bcbdb493d695d393e0f7c5f45999f642\",\"name\":\"chantal\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/kenes-exhibitions.com\/biomed\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/700eefc5df785131a5e93d5e7e21202d?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/700eefc5df785131a5e93d5e7e21202d?s=96&d=mm&r=g\",\"caption\":\"chantal\"},\"url\":\"https:\/\/kenes-exhibitions.com\/biomed\/author\/chantal\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22) - Biomed 2026","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/kenes-exhibitions.com\/biomed\/ai-ml-enables-earlier-cancer-detection-guided-treatment-feb-22\/","og_locale":"en_US","og_type":"article","og_title":"AI\/ML Enables Earlier Cancer Detection, Guided Treatment Feb 22) - Biomed 2026","og_description":"Ofer Sharon, M.D., CEO, OncoHost\/company courtesy\u00a0 Artificial intelligence and machine learning could change the face of cancer diagnostics. 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