An AI framework can identify targets for CAR-T cell therapy in weeks, streamlining a process that often takes months to years, according to a study published June 25 in Cell.
Here are three notes from the study:
- Researchers at Philadelphia-based Penn Medicine Abramson Cancer Center built the framework using single-cell RNA sequencing datasets and validated it in melanoma, leukemia, lung and colorectal cancers.
- The framework uses large language models to screen and rank thousands of potential CAR-T targets, then repeats simulations 1,000 times to reduce the risk of AI errors.
- Researchers said the framework can be applied to any cancer type or other conditions, using different datasets or future LLMs, according to a June 25 news release from Penn Medicine.
Read the full study here.
At the Becker's Perioperative Summit, taking place September 14–15 in Chicago, perioperative leaders and healthcare executives will focus on improving operating room efficiency, enhancing patient safety, optimizing staffing and driving innovation across surgical services. Apply for complimentary registration now.
