We provide regulatory-grade Real-World Evidence
by combining datasets of imaging & clinical data, biology & genomics
with strong analytics capabilities.
"The value of imaging data is beginning to be recognized for its high clinical utility and value
in the end-to-end evidence management process.
The really hard part comes next:
how to access, deidentify, aggregate, govern, normalize and combine these complex data sets with other forms of data
so it can be put to work to improve research and help patients receive better care."
Matthew Michela, President and CEO, Life Image & Dan Housman, Co-founder and CTO, Graticule
This is where Medexprim intervenes.
Advances in artificial intelligence and image analytics allow the extraction of quantitative features characterizing functional and molecular information, known as radiomic features. This information is revealed by post-processing the images, and is correlated to the characteristics of the disease or treatment response. When reproducibility can be achieved, the quantitative features become imaging biomarkers.
Imaging biomarkers include biomarkers for detection (identification of disease), prediction (of risk of disease or therapeutic outcome), prognostication (prediction of outcome), and response assessment (evaluation of change with therapy). Imaging biomarkers are an ideal method to draw evidence from retrospective data: as new image processing pipelines are developed, they can be applied retrospectively to extract imaging biomarkers from anterior imaging scans.
Imaging biomarkers can be used both as inclusion criteria — to select relevant cohorts of patients, and output data — to quantify responses to treatments.
With the integration of imaging biomarkers to our service, we aim to improve the nature of the Real-World Imaging Evidence we provide.