Case Study: Cambridge-Based Oncology-Focused Company accelerates target identification by 75% with Elucidata

A Cutting edge Cancer using ML & Curated Biomolecular Data

Cambridge-Based Oncology-Focused Company partnered with Elucidata to accelerate its cancer drug discovery efforts, focused on differentiation therapy for AML, neuroblastoma, and melanoma. The company needed help finding relevant datasets, harmonizing heterogeneous public and in-house biomolecular data, creating a standard processing pipeline, and enabling ML-driven target identification and patient stratification.

Elucidata implemented an Enterprise OmixAtlas on its Polly platform, providing curated ML-ready datasets, cloud-based data management, collaboration tools, and flexible analysis via Python or GUI, along with a customized data-processing pipeline and an SVR-based patient classification model. As a result, the company fast-tracked target identification in 2–3 months instead of the typical 1–2 years, identified 2+ AML targets, and validated one of them, with Elucidata continuing to support ongoing research and clinical translation.