Genetic Biomarker Stratification

Genetic biomarker stratification identifies patient populations with specific genetic features predicting treatment response. BRCA mutations predict chemotherapy sensitivity and immunotherapy response. KRAS mutations confer resistance to certain targeted agents. HLA typing predicts immune checkpoint inhibitor efficacy. Polygenic risk scores aggregate multiple genetic effects.

Companion diagnostic commercialisation with therapeutics streamlines biomarker testing. Regulatory submissions justify biomarker utility. Precision medicine restricts treatment to responsive populations. Clinical trial enrichment based on biomarkers improves efficacy signals. Post-approval monitoring confirms biomarker predictive value.