Clinical trial acceleration through risk stratification
Predict cardiovascular events with the SomaLogic CVD Secondary Risk Panel
If you could accurately predict the risk of a cardiovascular event at baseline, how would that information impact the design and execution of your trial?
- Validated for patients with stable coronary heart disease
- Enroll patients with high risk into efficacy trials
- Disqualify patients who are not likely to have an event
- Reduce the number of patients enrolled
- Accelerate time to endpoint
Biomarker discovery to clinical diagnostic panel1
- The SOMAscan® 1.1k Assay was used for hypothesis-free biomarker discovery
- 1,129 proteins measured simultaneously in 150 microliters of EDTA plasma
- 1,909 samples with outcomes and clinical metadata analyzed to build and validate the algorithm
- Machine learning was used to select biomarkers to predict myocardial infarction, congestive heart failure, stroke/transient ischemic attack or death.
- A multi-protein panel assay was developed.
Accelerate time to endpoint2
- Assumptions in the financial model
- Enrichment with five-year CVD Risk Score >40 percent
- Includes increased cost for risk screening
- 20 percent of potential subjects are enrolled
- Endpoint for the enriched trial is defined by the number of Events in the All Comers design
Let’s start a conversation about the SomaLogic CVD Secondary Risk Panel.
1- Ganz P et al. (2016). Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Disease. Journal of the American Medical Association. 351(23): 2532-2541.
2- Examination of Clinical Trial Costs and Barriers for Drug Development, HHS, July 2014