We generate biomarkers to select the patients who will respond favorably to your therapies - reducing the risk of efficacy failure and bringing personalized treatments to market faster
Gain key insights into disease mechanisms and factors driving patient response
Uncover patient stratification biomarkers for recruitment criteria informing clinical trial design
Create complementary diagnostics for treatments with responder stratification biomarkers
Add value to R&D programs with retrospective analysis to identify drug response biomarkers
Our prospective clinical trial analysis identifies the combinations of genetic and non-genetic features responsible for individual disease subtypes, enabling you to design smaller, faster to read out clinical trials targeted at your drug’s mechanism.
Our retrospective analysis of clinical trial datasets that have not returned clear enough efficacy signal identifies drug response biomarkers that clearly delineate responders from non-responders to inform strategy and enable future trial success.
We help you avoid the considerable costs associated with clinical trial failure while also reducing the costs of running successful programs with faster, more focused trials.
Our proprietary method for stratifying patients whose disease is mediated by the drug candidate’s mechanism of action identifies responders, decreasing cohort sizes and recruitment times necessary to obtain statistical validation of the efficacy of new treatments.
Recover sunk costs with our retrospective analysis of patient cohorts from trials that previously failed to demonstrate sufficient efficacy.
We generate patient stratification biomarkers from retrospective analysis of Phase III clinical trials to identify the features that differentiate patients who show a strong drug response. These insights maximize the opportunity for clinical trial success and avoid the primary causes of an original study’s failure in follow-up trials.
The benefits of using our approach do not end at regulatory approval. The same stratification biomarkers provide an easy means for clinicians to identify the people most likely to benefit from your approved treatment, ensuring that it’s adopted quickly and prescribed to the people who need it most.
We identified multiple patient subgroups with clearly distinguishable disease development and progression drivers, to reduce the risk of clinical trial failures.
