One of the first AI solutions to be deployed was developed by Imagene, an emerging leader in AI-based precision oncology, incorporating an algorithm to identify actionable biomarkers of non-small cell lung cancer. The algorithm is directly applied to a digitized image of a conventionally stained pathology slide and can then, within minutes, identify the presence of actionable biomarkers in the tumor, thus providing crucial information for diagnostic and therapeutic decisions. The solution essentially shortens diagnostic time from three weeks to minutes, enabling patients to begin treatment earlier.
“We have reached another significant milestone in digital pathology with this ability to detect biomarkers by AI. The use of deep learning algorithms is changing the world of diagnosis, and in certain cases can drastically shorten the cost and time to treatment. I am excited to hear about the growing number of patients who were able to receive rapid diagnoses and treatment using our new service” said Prof. Iris Barshack, Head of the Pathology Institute at Sheba Medical Center.
This latest advancement in cancer diagnostics builds on the significant progress Sheba’s Pathology Institute has made in recent years. In 2019, the pathology lab at the hospital went fully digital, using computer screens for diagnosis instead of microscopes. Once the Pathology lab turned fully digital, the team worked in collaboration with Imagene who developed a rapid AI-based molecular profiling algorithm to identify actionable biomarkers from the digital biopsy image alone.
“AI is already transforming the field of healthcare and oncology specifically. ARC is proud to be a part of this collaborative achievement in precision medicine that will have a significant impact in global health,” said Prof. Eyal Zimlichman, Chief Transformation Officer and Chief Innovation Officer at Sheba Medical Center and Director and Founder of ARC Innovation.