– Life Image and Graticule announced the availability of GLIMPS (Graticule Life Image Machine Parsed Set) data licensing subscriptions in AWS Data Exchange.
– GLIMPS (Graticule Life Image Machine Parsed Set) is a de-identified patient-level data set including a summary of features generated from NLP processing on Life Image data.
– The goal of GLIMPS is to provide a cost-effective patient-level snapshot to biopharma data science teams to fuel the necessary discussions about these data, leading to sourcing broad curated sets or building artificial intelligence (AI) models to answer high value questions.
Life Image and its strategic partner Graticule, an advanced real-world data firm, today announced the availability of GLIMPS (Graticule Life Image Machine Parsed Set) data licensing subscriptions in Amazon Web Services (AWS) Data Exchange. By providing patient-level snapshots to biopharma data science teams, GLIMPS is fulfilling demands for RWE and allowing biopharma and AI companies to accelerate development, post-market safety, effectiveness, validation, and label expansion. This news capitalizes on Life Image’s strategic partnership with Graticule and the company’s unparalleled Real World Imaging™ database, launched in September.
What Is GLIMPS?
Graticule has published GLIMPS in the AWS Data Exchange. GLIMPS is a de-identified patient level data set including a summary of features generated from NLP processing from Life Image data, which has been de-identified using industry-leading tools with Life Image’s own expert determination service that uses a combination of human validators with a proprietary machine-learning algorithm specifically designed to catch personal health information (PHI) that can be hiding within the image pixels or meta tags.
The HIPAA-compliant repository of diagnostic images provides insights from a broad set of geographically-diverse providers in the U.S. that contain a rapidly growing cohort of 140,000 patients, 360,000 studies, and 92 million de-identified images. Because much of the important data in imaging is stored in unstructured reports or within images, it is difficult to construct queries to identify studies with features of interest to solve researcher questions. GLIMPS provides a safe, structured view of the patient-level medical information by providing coded values using open vocabularies such as ICD9 or SNOMED to execute feasibility analysis.
GLIMPS Data Model
The GLIMPS data model includes key fields from DICOM headers and a machine parsed mapping created using multiple medical Natural Language Processing (NLP) tools. Custom extraction approaches provide an additional deeper layer of clinical context using measurable values such as Ejection Fraction within echocardiograms. The data model was built to be compatible with the OHDSI (Observational Health Data Sciences and Informatics) Common Data Model to rapidly integrate into Real World Data tools used by Life Sciences companies and regulators.
This new partnership is fueled by Life Image’s ability to interpret and de-ID diagnostic images and radiology reports, combined with Graticule’s expertise in RWD. As a result, pharma and AI companies will be able to use this GLIMPS data to:
– Identify markers of disease prior to diagnosis and progression during treatment
– Supply machine learning teams with ‘control’ data from Life Image vs. ‘study’ data from a clinical trial or internal data source
– Study identification of novel imaging biomarkers for a rare or newly identified disease subtype
– Validate AI models on RWD that has been built on small or narrow data sets
– Support RWE teams with a novel source of data to support new approaches or techniques
“Diagnostic images and radiology reports contain interpretations and other information that provide rich diagnostic and outcomes data but have historically been extremely difficult to access and aggregate at scale,” said Dan Housman, CTO and Co-founder of Graticule. “AWS Data Exchange provides a sea change opportunity that allows us to distribute our data to provide a transparent view of available images and tools to deliver deeper data insights on demand.”