Identifying and Prioritizing AML Targets via Reconstructed Cell-Type Resolution from Bulk Transcriptomics Data
Key Highlights
A biotechnology company focused on oncology and inflammatory disease set out to build its AML program on a differentiation therapy thesis, that leukemic cells arrested at early states of the hematopoietic hierarchy drive the most aggressive disease.
The company faced significant challenges in finding transcriptomic data that carried both cell-type resolution and clinical annotation, which public AML repositories rarely provided together.
Elucidata reconstructed the missing resolution through deconvolution, harmonized it into a provenance-tracked atlas of hematopoiesis, and trained a classifier that positioned each patient sample along the hematopoietic hierarchy.
As a result, the program converged on one validated lead target, now in Phase 1 with FDA Fast Track designation, in 6 months against 12+ months for internal solutioning, with 10K+ datasets harmonized and 4x faster delivery from the pre-existing atlas.
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