A pharmaceutical company with a targeted therapy for non-small cell lung cancer (NSCLC) was facing competitive pressures from market-leading alternatives. Despite strong clinical data, the company was losing patients to competitor therapies at key decision points along the patient journey.

A global pharmaceutical company with a targeted therapy for advanced breast cancer that demonstrated strong clinical efficacy sought to generate real-world evidence to support inclusion in NCCN clinical guidelines- a key driver for physician adoption and payer reimbursement.

A large regional health system sought to expand its precision medicine research by launching investigator-led clinical studies and collaborating with external research partners. However, they faced challenges in making their clinical, genomics, and imaging data readily unusable for research studies.

A mid-sized academic medical center (500-900 beds) with a growing research program had extensive clinical, genomic, and imaging datasets and wanted to leverage these assets for external collaborations, grant funding, and multi-site research studies.

By implementing datma.FED, the lab securely monetized its molecular and pathology data while keeping it securely within their own environment. datma.BASE, integrated into datma.FED, automated data readiness, handling everything from extracting unstructured pathology data to mapping source data into a common model. This ensured the lab’s data was ready for external queries with minimal internal effort.