ON.Multiomics delivers discovery‑ready, biomarker‑defined patient cohorts designed to hold up under real‑world translational study criteria. It links comprehensive molecular profiling from Caris Life Sciences with longitudinal clinical data from The US Oncology Network to support translational research analysis over time.
Make earlier, more confident assessments about targets, biomarkers and program feasibility using cohorts designed to remain usable under real‑world study criteria
Validate biological signals in clinically meaningful patient populations and assess prevalence, stratification and signal durability without losing cohort integrity
Work with discovery‑ready clinico‑molecular datasets that reduce time spent reconstructing cohorts and validating data before analysis
Understand how molecular signals translate into treatment sequencing, response and resistance beyond controlled trial settings
ON.Multiomics supports translational teams working through high‑stakes questions that require both molecular depth and real‑world clinical context.
Test whether molecular signals hold up in real‑world patient populations before programs advance
Define clinically meaningful patient populations that remain analyzable as biomarker, treatment and outcome criteria are applied
Assess treatment response, durability and resistance patterns across lines of therapy using longitudinal clinical context
Determine whether sufficient patient populations exist to support planned research and development efforts earlier in the lifecycle
Many multiomics datasets emphasize molecular depth or raw scale but lose analytical usability once real‑world study criteria are applied. ON.Multiomics is constructed to preserve analyzable patient cohorts after biomarker, treatment and outcome filters are applied.
ON.Multiomics is delivered as predefined, discovery‑ready datasets designed around common translational research needs. Cohorts are structured and linked in advance rather than built as one‑off custom services.
Cohort definition, data linkage and quality checks occur before delivery. Patients included have sufficient molecular and longitudinal clinical context to support real‑world analysis without extensive rework.
ON.Multiomics includes multi‑year clinical data that capture treatment sequencing and clinician‑assessed outcomes, enabling analysis of response and resistance over time in routine oncology care.
Yes. A consistent clinico‑molecular structure allows teams to reuse the dataset across multiple studies without rebuilding cohorts for each new question.
If you’re evaluating clinico‑molecular data for translational research, a focused conversation can help clarify whether ON.Multiomics is the right fit. Our team can walk through cohort characteristics, data coverage and how the dataset is designed to support real‑world translational questions.