Strata Oncology develops predictive biomarkers for antibody-drug conjugates (ADCs) and immunotherapy, utilizing a proprietary algorithm that combines tumor mutation burden and protein expression metrics. This technology enables oncologists to identify the most effective treatment options for patients, improving therapeutic outcomes in precision oncology.
Funding
$139.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
WMFounders
Product
Problem
Selecting the optimal cancer treatment, particularly antibody-drug conjugates (ADCs) and immunotherapies, is challenging due to the heterogeneous nature of tumors and varying patient responses. Traditional methods often lack the precision needed to predict individual patient benefit from specific therapies, leading to suboptimal treatment decisions.
Solution
Strata Oncology offers a suite of predictive biomarker tests designed to optimize treatment selection for cancer patients. Their approach leverages proprietary algorithms that integrate tumor mutation burden, protein expression, and ADC target expression to predict patient response to specific ADC and immunotherapy treatments. The Immunotherapy Response Score, a pan-solid tumor diagnostic tool, combines tumor mutation burden with quantitative expression of PD-L1, PD-1, ADAM12, and TOP2A to predict benefit from anti-PD-1/PD-L1 monotherapy. Similarly, their ADC treatment response scores utilize a calculation method incorporating ADC target expression to predict benefit from various approved and investigational ADCs. By providing clinicians with data-driven insights, Strata Oncology aims to ensure that each patient receives the most effective therapy based on their unique tumor biology.
Target Audience
The primary target audience includes oncologists and other healthcare professionals involved in cancer treatment decisions, as well as pharmaceutical companies developing ADCs and immunotherapies.
Features
- Proprietary algorithms combining tumor mutation burden, protein expression, and ADC target expression for predictive biomarker analysis.
- Immunotherapy Response Score (IRS) for predicting response to anti-PD-1/PD-L1 monotherapy across solid tumors.
- ADC Treatment Response Scores for predicting benefit from approved and investigational antibody-drug conjugates.
- Multivariate analysis capturing the biology of the tumor and its microenvironment.
- Quantitative expression analysis of key biomarkers, including PD-L1, PD-1, ADAM12, and TOP2A.