University of Minnesota researchers are challenging standard cancer research models to dramatically improve treatment success rates. Currently, clinical trials often rely on rigid dosage schedules, resulting in a success rate of only about five percent for new therapies. To address this, the University's Cancer Bioengineering Initiative, co-directed by biomedical engineering professors Paolo Provenzano and David Odde, is integrating mathematical and engineering principles into cancer therapy. Their goal is to double clinical trial success rates to 10 percent by moving away from static treatment models and toward dynamic, data-driven strategies.
The initiative brings together experts from across the University, including the Medical School and the College of Science and Engineering, to push beyond traditional limits. Highlights of this interdisciplinary work include David Largaespada’s use of the "Sleeping Beauty" transposon system to identify cancer-fighting genes like BACH2, and Jasmine Foo’s mathematical modeling to determine precise drug timing and dosages without relying on guesswork. Additionally, researchers Beau Webber, Branden Moriarity, and Emil Lou have successfully used CRISPR technology to deactivate the CISH gene in immune cells, a breakthrough that recently led to the complete remission of a patient's terminal cancer.