Utilization of proteomic surrogates for early detection of unexpected drug benefits
Detection of benefits and adverse effects of therapies in early clinical trial phases could improve the safety, efficiency, and cost of clinical trials. For example, while SGLT2i and GLP-1 RA drugs are recognized success stories, earlier identification of their benefits beyond improved diabetic control may have had the potential to save loss of pa%ents’ lives and years of sales.
CV risk and kidney prognosis SomaSignal tests (each derived from ~5000 plasma proteins measurements using SomaScan® assay) were applied to paired plasma samples at baseline and 9-months (SUGAR-DMHF) or 1-year (EXSCEL) in intervention (EXSCEL n=1840; SUGAR-DM-HF n=45) and control (EXSCEL n=1833; SUGAR-DM-HF n=52) participants. Power calculations were performed to determine the minimum number of samples needed to detect a significant change within the treatment period with alpha = 0.05, 80% power using a t-test comparing two-sample means.
We demonstrated that the cardiovascular benefits of exenatide were detectable with a proteomic surrogate within 1-year (p=0.002), with power analysis indicating a significant 1-year change is observable with group sizes of n=1368 compared with >7000 participants for up to 6.8 years follow-up. Additionally, kidney protection (p=0.037) and CV protection (p=0.06) impacts of empagliflozin within 36 weeks were detectable using proteomic surrogates in small sample sizes (n ~ 50) compared to published outcomes studies requiring thousands of participants followed for >2 years.
SomaSignal tests were able to predict cardiometabolic benefits of GLP-1 RA and SGLT2i drugs within a significantly shortened interval and fewer participants than in the outcome trials. Proteomics may provide a powerful tool for improving the efficacy, and cost of drug development by predicting effects of novel therapeutics in smaller, shorter studies.
SomaLogic Operating Co., Inc., Boulder, CO, USA
PosterComparison of Proteomic CV Risk to Established ASCVD 10-Year Risk Decision Points
The ASCVD pooled cohort equation (PCE) is well-established for CV risk assessment. Decision points for determining treatment plans are low, intermediate and high risk over 10 years, however this approach over and underestimates risk in certain subgroups. The validated CV Risk SomaSignal® Test (SST) provides 4-year risk probability of MACE allowing for timely assessment of risk, but the shorter timescale makes comparison to 10-year PCE risk less intuitive.
PosterStatin signature: using proteomics to detect pharmacological fingerprints
Using a previously described metacohort (n=5,575) of patients with increased CV risk, we hypothesized that PCE would stratify patients differently than the CV Risk SST, and that CV Risk score scaled to 10 years would yield an improved net reclassification index (NRI).
PosterUsing a proteomics-based cardiovascular risk test to identify systemic changes in a clinical trial of nonalcoholic fatty liver disease
Improvement in hepaKc inflammaKon, NAFLD acKvity score and fibrosis were associated with improved proteomic CV risk scores regardless of treatment provided.