Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict.
Biomarkers, Tumor ; genetics ; metabolism ; Clinical Trials as Topic ; methods ; Decision Support Techniques ; Evidence-Based Medicine ; Humans ; Neoplasms ; diagnosis ; genetics ; metabolism ; Predictive Value of Tests ; Program Development ; methods