Table 1.
Biomarker development paradigm
| Phase 1 | Biomarker discovery | |
| Major considerations | Dynamic range of biomarker expression | |
| Absolute expression level of the biomarker | ||
| Phase 2 | Biomarker Validation | |
| Major considerations | Reproducibility of biomarker utility in independent cohorts | |
| Development of a robust, easy assay for measurement of the biomarker | ||
| Cost of the assay | ||
| Phase 3 | Retrospective analyses of clinical datasets | |
| Major considerations | Does the biomarker improve stratification of cancer and normal samples? | |
| Reproducibility of clinical results in independent cohorts | ||
| Demographic composition of cohorts, reflecting the target population | ||
| Define the clinical endpoints distinguished by the biomarker | ||
| Phase 4 | Prospective screening | |
| Major considerations | Enrollment of the proper target population for the biomarker | |
| Matching control and experimental cohorts appropriately | ||
| Evaluating the proper clinical endpoints | ||
| Feasibility of biomarker measurement (cost, ease of assay) | ||
| Efficacy in improving stratification of cancer samples | ||
| Phase 5 | Large-scale population studies | |
| Major considerations | Validation of biomarker efficacy in a broad setting | |
| Biomarker reproducibility across multiple patient cohorts | ||
| Efficacy for the biomarker to improve patient management | ||
| Financial feasibility of biomarker introduction into clinical practice | ||