Resource Library

biomarker discovery services partner

FFPE Multi-Omics for Precision Oncology Platforms

Extending molecular insights beyond DNA and RNA to realize new value in existing FFPE tissue biobanks.

The Bio Report: “Rewriting Drug Discovery with an AI-Multi-Omics Approach”

A look at how AI-driven, multi-omics platforms are advancing the discovery and development of precision medicines.

FFPE Multi-Omics for Clinical Oncology

Unlocking functional biology, new biomarker insights, and responder profiles from archived trial samples.

The Omics Brief | Proteomics at the Edge: Mapping the Cell Surface for Target Discovery

Using TAA profiling to identify differentially expressed, disease-modifying, tractable targets on the cell surface.

FFPE Multi-Omics for Translational Oncology

Delivering quantitative, reproducible protein measures for rapid proof-of-mechanism & target engagement insights.

Systematic Inflammatory Profiling Reveals Immune Modulation in Response to Weight Loss Intervention

Using multi-omics to characterize changes in inflammatory markers observed following GLP-1 therapy.

FFPE Multi-Omics for Discovery Oncology

Transforming archival tissue into a discovery-ready resource to move from target discovery to functional validation, in weeks.

Marker of the Month | Creatinine

We explore known & novel associations of creatinine using Sapient’s DynamiQ™ Insights Engine. See what we find.

Sapient Launches Next-Generation FFPE Proteomics Platform to Unlock New Functional Insights from Archived Tissue

Enabling measure of 10K+ proteins in FFPE tissue & tumors and multi-omic molecular mapping of tumor biology.

Next-Generation FFPE Proteomics

Unlocking functional tumor biology from FFPE tissue – quantitatively, reproducibly, and at scale.

Mind the Gaps: The Real Impact of Missing Data and Outliers in Biocomputational Analysis

Sharing analytical strategies to ensure omics datasets generate insights that are both truthful & actionable.

Sapient Bioanalytics awarded two U.S. patents for its novel machine learning-powered mass spectrometry (MS) methodologies

The innovations enhance how MS data is processed, filtered & interpreted across large-scale biological datasets.