ThoughtSphere’s integrated Modeling and Analysis Programming (MAP) interface allows data scientists and biostatisticians to seamlessly develop data models using SAS, R, and Python, with no data transfers or exports required. Find patterns in complex data, identify unusual data correlations, set benchmarks, or predict study outcomes using historical data; the possibilities are endless. MAP is fully integrated with ThoughtSphere’s ClinHUB and full line of solutions, but it can also be paired with ClinHUB as a standalone solution.
Real-Time Modeling & Data Exploration
Models can be developed using real-time data curated in ClinHub as well as imported external historical and RWE data sets to support translational medicine and therapeutic level research.
Library of Pre-built Models
MAP’s library provides pre-built models to surface correlation trends, digit preferences, and even duplicate patients. Developers can use these models out-of-the-box or customize them to meet the unique needs of any trial.
Automated process workflows and notebook capabilities allow developers across the globe to work in tandem to author, revise, validate, and execute data models in real-time across a single study or program of studies.