Accelerate and de-risk clinical trials with evidence-based covariate adjustment

Data-driven design of clinical trials to improve cancer research

Oncology drugs are expensive and difficult to develop; 80% fail to meet their phase III endpoints.

Access this informative whitepaper from Owkin, to discover how evidence-based covariate adjustment can reduce the risk of trial failure by increasing the power and allowing broader eligibility criteria without sacrificing power in phase III oncology trials.

Key topics include:

• Leveraging machine learning and real-world data to complement randomized controlled trials.

• Identifying novel covariates via deep learning analysis of routine imaging data.

• Applying deep learning covariates to increase the power and accuracy of clinical trials.

• Evidence-based covariates provide compelling evidence for regulators.