TrialMap
Bringing Clinical Trial Inference to the 21st Century
Learn from each data point
Adapt to make trials more efficient
Personalized care for every patient
At the core of our advanced analytics, lies TrialMap. TrialMap is a proprietary platform based on academic research spun out of the Cardiovascular Data Science Laboratory at the Yale School of Medicine. It is built around an automated machine learning algorithm that can learn unique representations of each clinical trial and provide personalized insights and explainable predictions on the interaction between each patient's unique phenotype and the efficacy and safety of a given intervention. TrialMap has already been tested in several clinical trials of both diagnostic and therapeutic interventions. The findings have been published in leading peer-reviewed journals (Eur Heart J), presented in major academic conferences (American Heart Association Scientific Sessions), and received several academic awards.
AI-Driven Personalized Clinical Care
Therapeutics: Find out which patients
benefit most from each drug.
Prevention: Find unique treatment
goals for each individual.
Diagnostics: Choose the right test for
each patient, every time.
