Case Study: Brigham & Women's Hospital achieves faster post-market drug efficacy analysis with Revolution Analytics

Improved Performance of Models Enables Innovation of New Methods for Analyzing Post - Market Drug Efficacy

Brigham & Womens Hospital needed a way to run very large simulation studies for post-market drug efficacy research, where real-world patient data is complex and non-randomized. The team used a solution from Revolution Analytics, alongside IBM Netezza, to analyze large, tangled datasets with enhanced R capabilities.

Revolution Analytics helped Brigham & Womens Hospital speed up large matrix operations and simulation runs that were difficult or impractical with standard R or SAS. The result was significantly faster turnaround for large-scale studies, improved productivity and efficiency, and the ability to complete work in a reasonable amount of time that previously would have been too slow to manage.

Brigham & Womens Hospital