Anchored in Patient Biology
We start with proteomic profiling of real patient samples, capturing 8,000–11,000 proteins per sample to reflect disease complexity and heterogeneity at the functional level. This deep, unbiased view of protein expression gives us a real-time snapshot of cellular activity, enabling therapeutic decisions to be guided by the proper biological drivers of disease
Empirical, Testable Cell Models
Using patient-derived samples, we generate ProteoModels™, a unique library of ex vivo cellular systems that capture disease heterogeneity and represent clinically relevant patient subtypes and treatment phenotypes. Built directly from patient biology, these living models preserve molecular complexity and enable drug testing in systems that more accurately reflect real-world response, bridging patient biology to therapeutic decision-making
Machine Learning That Maps Biology to Response
Our proprietary deep learning architecture maps drug sensitivity across patient cohorts, predicting responders and identifying resistance patterns before trial initiation. By training on matched proteomic and drug response data, our deep learning framework reveals non-obvious patterns across diverse patient subtypes, bringing precision to trial design and increasing the likelihood of clinical success Biomarker Discovery and Validation
Biomarker Discovery and Validation
Using our ProteoCharts™ platform, we extract robust therapeutic signatures and companion biomarkers that are clinically actionable. These signatures drive more precise patient selection and enable more intelligent therapeutic positioning, bringing clarity to complex biology and improving translational success.