Model created by Cedars-Sinai investigators could speed patient selection for clinical trials

Share on facebook
Share on twitter
Share on linkedin
Share on email
Share on print

A group of investigators led by Cedars-Sinai have developed and successfully tested a new artificial intelligence method to make launching cancer clinical trials easier and faster. The method uses patients’ pathology reports to automate the classification of patients by the severity of their cancers, potentially shortening the process of selecting candidates for clinical trials.

To access this subscriber-only content please log in or subscribe.

If your institution has a site license, log in with IP-login or register for a sponsored account.*
*Not all site licenses are enrolled in sponsored accounts.

Login Subscribe
Table of Contents

YOU MAY BE INTERESTED IN

Technological innovations are often hailed as transformative tools capable of revolutionizing healthcare. From gene editing for conditions like sickle cell disease to AI predicting hospital readmissions, to telemedicine expanding healthcare access, these advancements have the potential to change the way we treat diseases. 
Genmab A/S announced on March 17 updated data from cohort B1 of the phase I/II RAINFOL-01 study of rinatabart sesutecan, an investigational folate receptor-alpha-targeted, TOPO1 antibody-drug conjugate that showed Rina-S 120 mg/m2 every three weeks resulted in a confirmed objective response rate of 55.6% (95% CI: 30.8-78.5) in heavily pre-treated ovarian cancer patients regardless of FRα expression levels. 
The field of surgical oncology has undergone transformative advancements over the last decade. From refining minimally invasive techniques to leveraging immunotherapy and viral oncolytics, our collective goal remains the same: improving patient outcomes while reducing treatment burden. At City of Hope, we have prioritized accelerating the translation of laboratory discoveries into clinical applications, and nowhere is this more evident than in our work with oncolytic viruses, remote surgery, and the integration of AI in surgical decision-making.

Never miss an issue!

Get alerts for our award-winning coverage in your inbox.

Login