Improving CAR-T Trial Success With Historical Trial Data Optimization

Recent breakthroughs in oncology have revolutionized patient care, offering novel treatment options when traditional methods have reached their limits. For example, adoptive cell therapies, such as Chimeric Antigen Receptor (CAR) T-cell and engineered T-cell Engager (TCE) therapies, utilize immune systems to combat diseases and have been reported to hold immense promise.

CAR-T cell therapy has been in clinical trials for over a decade and has emerged as a groundbreaking treatment for adults and children with specific blood cancers. To date, the FDA has approved six CAR-T cell therapies since 2017. However, the widespread use of CAR-T as a first-line treatment faces challenges, including associated side effects, limited accessibility, and hurdles in clinical development.

This white paper takes a look at treatment access, challenges faced in clinical development, and how data can be utilized to accelerate clinical development, specifically how Medidata’s AI CAR-T Data Cube can generate insights throughout the patient journey and leverage historical data and artificial intelligence to design better trials in the future.