Sapient’s biomarker discovery services enable rapid, high‑throughput profiling of proteins, metabolites, and lipids that capture biological states as they change over time. These dynamic biomarkers provide a functional readout of disease mechanisms and therapeutic effects, supporting informed decision‑making across the drug development lifecycle.
These approaches enable discovery of dynamic biomarkers that reflect real‑time disease biology, environmental influence, and therapeutic response.
Our data generation capabilities are paired with an advanced biocomputational framework and Sapient’s DynamiQ™ Insights Engine, a large-scale molecular-clinical database of multi-omics measures we can use to contextualize biomarkers observed in clients studies. Using these independent cohorts, we can confirm disease and clinical association and build human evidence for translation of early findings. The DynamiQ database includes:
Build confidence in observed
biomarkers by contextualizing their disease & clinical links in independent cohorts.
Cross-validate preclinical discoveries in real-world cohorts, building human evidence for translation.
Reveal correlated biomarker patterns within and across diseases to unlock disease subtypes and/or indication expansion opportunities.
See the exciting findings uncovered in this multi-omics study using discovery metabolomics, proteomics, and NULISA cytokine profiling a DynamiQ virtual cohort to characterize changes in inflammatory markers observed following GLP-1 therapy.
We tailor our biomarker discovery services around your context of use, ensuring that data generation and analysis align with your development stage and scientific objectives. This could include identification and analysis of biomarkers that inform:
Identify differentially expressed, disease-modifying, and tractable therapeutic targets that can be acted upon by your drug.
Confirm a target’s role in disease process and/or the effects of pharmacological modulation of the target.
Demonstrate the drug reaches its intended target with measurable binding effect.
Evaluate the biological activity of a drug.
Identify genetic and/or environmental factors that predispose to disease and/or cause disease progression.
Monitor disease status, the occurrence of new disease effects, and/or change in disease severity.
Select patients according to disease-based or drug-based biomarker signatures.
Select patients most likely to respond to a treatment to increase study power while reducing study size.
Assess the presence or extent of toxicity related to an intervention or drug exposure.
Identify predictive biomarkers that identify suitable patients for a treatment.
