Biomarkers have become key in personalized medicine, with applications in diagnosis, prognosis, and selection of targeted therapies. Personalized Medicine applications are broad, including the identification of the optimal drug and the optimal dosage for a subgroup of patients, or situations of withholding treatment, preventive interventions, or targeted treatment options for individual patients.
Personalized medicine is already used for some forms of hereditary cancer, in which individual genetic testing is the basis for deciding upon specific interventions such as preventive. For example, MammaPrint is a powerful prognostic indicator for disease outcome in breast cancer patients, with improved prediction of recurrence risk compared to currently used guidelines. MammaPrint is cleared by the FDA as an in vitro diagnostic test, and in Germany some health insurance companies cover the test expenses in particular circumstances. Another example is the IL28B gene, a strong indicator for response to standard treatment in patients with hepatitis C virus-1 (HCV-1) infection, or a test for epidermal growth factor receptor (EGFR) mutation in patients with advanced non-small cell lung cancer (NSCLC), which determines whether or not the first-line EGFR tyrosine kinase inhibitor therapy is indicated.
In July 2011, the FDA issued a draft guidance for industry on ‘‘in vitro companion diagnostic devices’’, which are predictive biomarkers essential for safe and effective use of a corresponding therapeutic product. The draft guidance anticipated three uses of companion diagnostics:
- Identification of patients most likely to benefit from a particular therapeutic product
- Identification of patients likely to be at increased risk for adverse reactions to a therapeutic product, and
- Monitoring treatment response to adjust treatment in order to improve efficacy and safety.
The FDA guideline suggests that because companion diagnostics provide critical information for the appropriate use of drugs, they require validation as part of the evaluation of efficacy of the experimental treatments, and information about the diagnostic is to be reflected in the drugs’ labeling.
The use of biobanks for prospective validation might play a role for already approved drugs, given the variation in individual responses to a specific treatment. Within the pharmaceutical industry, such research will become increasingly important to pharmacovigilance and postmarketing surveillance of drug use. Furthermore, companion tests will profoundly affect how clinical trials are performed. Although several options exist, the “interaction or biomarker-stratified” design, where patients are first tested for the biomarker, and then randomized to treatment or control with stratification by the companion biomarker’s test result, may well be considered the gold-standard design. It provides a sound basis for decision-making about the efficacy and risk-benefit of the experimental drug, and the ability of the companion diagnostic to identify the appropriate patient population to be treated.
Ziegler A. et al. Hum Genet (2012) 131:1627–1638
Hamburg M.A. et al. N Engl J Med 363;4
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