{"id":43400,"date":"2022-05-02T15:29:32","date_gmt":"2022-05-02T19:29:32","guid":{"rendered":"https:\/\/sciencebusiness.technewslit.com\/?p=43400"},"modified":"2022-05-02T15:29:32","modified_gmt":"2022-05-02T19:29:32","slug":"ai-aided-cancer-analytics-gain-21-5m-in-early-funds","status":"publish","type":"post","link":"https:\/\/technewslit.com\/sciencebusiness\/?p=43400","title":{"rendered":"AI-Aided Cancer Analytics Gain $21.5M in Early Funds"},"content":{"rendered":"
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(Gerd Altmann, Pixabay)<\/figcaption><\/figure>\n

2 May 2022. A start-up enterprise using artificial intelligence algorithms to analyze tumor biopsy images is raising $21.5 million in seed and first-round venture funding. Imagene AI is a two year-old company in Tel Aviv, Israel of cancer researchers and data scientists that aims to speed diagnostics for precision medicine.<\/p>\n

Imagene AI is developing a process to better understand the precise genetic composition of an individual’s cancer by analyzing images of biopsy tissue<\/a> samples. The company says its technology uses A.I. algorithms to seek out patterns in the visual evidence not normally revealed by human inspection. Imagene AI says its algorithms can return results in about two minutes, much faster than current processes often requiring weeks, and provide precise diagnostics of a patient’s cancer, down to specific genomics and proteomics.<\/p>\n

The company does not cite any studies that demonstrate the technology, but Nir Peled<\/a>, Imagene AI’s medical director and head of the Integrated Oncology Institute at Shaare Zedek Medical Center in Jerusalem, explains in a 2017 interview how visual evidence combined with biomarkers can provide better lung cancer diagnostics. In the interview with the journal Translational Lung Cancer Research<\/em><\/a>, Peled recommended first using imaging techniques such as CT scans to screen for lung cancer before analyzing molecular indicators in blood samples. “That would allow us to have a higher specificity of the diagnosis,” Peled tells the interviewer, “and to effectively reduce invasive procedures for patients with tiny nodules who have normal biomarkers. I think this is the next topic that we should focus on in terms of research and clinical implications.”<\/p>\n

Precision medicine available to only a few<\/h4>\n

Imagene AI says its visual analytics can help can aid cancer researchers<\/a> to more accurately identify new biomarker targets and predict responses to treatments, and recruit and stratify patients for clinical trials. For physicians, says the company, its technology can provide more precise companion diagnostics<\/a>, and because of the near real-time turnaround, initiate precision therapies much sooner.<\/p>\n

“Precision medicine is transforming cancer care, yet, still relevant and available to less than 15 percent of cancer patients,” says Dean Bitan<\/a>, Imagene AI’s co-founder and CEO in a company statement<\/a> released through Globe Newswire, citing a 2018 report in Science magazine<\/a>. “Our scalable technology strives to enable treatment opportunities for all cancer patients, driving precision medicine to be tailored per individual patient condition.”<\/p>\n

Imagene AI is raising $21.5 million in a combined seed and first venture funding rounds, $3 million and 18.5 million respectively. Leading the financing is early-stage technology investor Blumberg Capital<\/a> in San Francisco and Tel Aviv, with participation by individual investors Larry Ellison, David Agus, and Eyal Gura. Ellison is co-founder and chief technology officer of global technology company Oracle, who with David Agus, founded the Institute for Transformative Medicine<\/a> at University of Southern California in 2016. Gura is an Israeli entrepreneur and venture investor.<\/p>\n

“The ongoing digitization of health care,” says Yodfat Buchris<\/a>, managing director of Blumberg Capital, “will reward medical providers, payers, and patients with new ways of leveraging data to improve diagnoses, treatments and outcomes by improving accuracy, streamlining processes and reducing costs.”<\/p>\n

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