Six Months to Success: Accelerating AML Target-indication Assessment With Advanced Knowledge Graphs
Key Highlights
A Massachusetts-based therapeutics company sought to accelerate AML target-indication assessment using differentiation therapy, a novel approach that transforms malignant cells into healthy functional ones.
The company faced significant challenges in finding and harmonizing molecular and clinical data from public and in-house sources.
Elucidata’s Polly automated data ingestion, harmonization, and knowledge graph-driven analysis, delivering a 360-degree view of disease biology to support better decision-making.
As a result, the company assessed 10 AML differentiation targets in just 6 months, a process that traditionally takes 15-24 months. They also achieved a 3X reduction in report generation costs and improved the probability of early discovery success from 1:2000 to 1:5.
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