The engine behind RESOLVE™

Harbinger HX focuses on biological programs that initiate cancer, rather than solely on features that characterize established disease. These programs create a shared biological framework across cancer types and stages that supports broad applicability.

The platform combines optimized laboratory workflows with high-resolution computational analysis designed to preserve subtle biological signal and minimize technical distortion. Sequencing and analytical infrastructure are tuned for low tumor fraction, heterogeneous samples, and large-scale deployment.

Data within Harbinger HX is generated under a shared biological and analytical framework. Biomarker discovery, assay design, and modeling are developed together, allowing datasets to remain coherent and comparable across time and use cases.

Algorithms within Harbinger HX are designed to extract meaning from ambiguity. Machine learning methods are applied within biologically informed constraints, linking statistical pattern recognition to plausible biological programs.

The platform supports core capabilities including cancer signal detection, tumor content estimation, and tissue-of-origin inference, using reproducible workflows designed for durability and scale.