<\/noscript><\/figure>\n<\/div>\nCurrently, as few as 28% of cancer patients receive a comprehensive analysis of all 9 actionable cancer biomarkers (based on NCCN guidelines) and up to 64% of lung cancer patients don\u2019t get the optimal treatment that\u2019s available. This can be attributed in large part to insufficient testing for biomarkers of the nature of the mutation. In many cases, including with NGS, there\u2019s a much lower sensitivity than expected. Moreover, interpretability can be poor because it requires well trained specialists that know what they\u2019re looking at. <\/p>\n
Imagene\u2019s technology takes a biopsy image and within a couple of minutes provides a report ready for a diagnosis of the biomarker, identifying the actual cancer mutation present in the biopsy. <\/p>\n
The time between biopsy and when the treatment is finally delivered, during which the nature of the cancer is being investigated, is measured in weeks right now, usually more than a month. Since this is too long for many patients, Imagene\u2019s technology promises to significantly shorten the waiting time till treatment initiation for many patients. Potentially, patients may know what the diagnosis is and what the treatment will be on the same day. <\/p>\n <\/noscript><\/figure>\nUnlike many other diagnostic modalities, Imagene\u2019s tech does not need any additional dedicated tissue. In fact, one digitized biopsy image, the diagnostic slide that was originally prepared for the initial pathology diagnosis, is all that is needed for an immediate gene alteration identification. It will not necessarily replace existing technologies, but Dean Bitan believes that his company\u2019s capabilities will improve the value of existing diagnostics by focusing them on where their value shines the most and improving how specific indications are arrived at.<\/p>\n <\/noscript><\/figure>\nArtificial intelligence, if thought of as a generalization of models, works quite well to detect cancer mutations in all kinds of patients and in all kinds of places because patterns of cancer repeat themselves. Imagene\u2019s merges self-supervised learning and other AI methods, where unlabeled data can be used to improve the results, as well as proprietary processing of prepared data to analyze images. Imagene is already working with 28 different biomarkers in eight different organs and is showing how their technology is standardized and providing the same level of results is accurate enough in order to assist in navigating clinical decision making. Currently the technology is still under clinical research, and soon it will be commercialized under the required regulatory requirements. Eventually the technology should be agnostic to any tissue type. Such work requires a lot of data points and they\u2019re working with medical centers, labs, pharma companies, and using public data to continue developing the technology.<\/p>\n
We hope to see Imagene showing off its technology at Biomed Israel, the leading international Life Science and HealthTech conference in Israel. This year it is scheduled for May 16-18, 2023 in Tel Aviv, and topics range from medical robotics, to bio-convergence, to the impact of AI on biopharma. Over 6,000 industry leaders, scientists, engineers, physicians, and investors will be attending for the 21st consecutive year of this conference. It is the largest event in Israel that brings together Israeli healthcare professionals and industry experts with international colleagues to work for three consecutive days on business opportunities, develop partnerships, and to seek new collaborations. Hundreds of Israeli life science firms will be showing off their products and technologies to attendees from all over the world. More info can be found at the Biomed Israel website. The conference is co-chaired by Ruti Alon, Founder and CEO of Medstrada, Ora Dar, PhD, Senior Expert, Medical Sciences and Health Innovation, and Nissim Darvish, MD, PhD, Managing Partner, Eliraz Ventures.<\/p>\n
Here\u2019s a video report from an Israeli news channel about Imagene\u2019s tech:<\/p>\n\n\n