Genetic tests and genomic biomarkers: Regulation, qualification and validation (original) (raw)
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Biomarkers in Disease Diagnosis and Treatment
Philips Research
The concept of biomarkers is becoming more relevant in disease diagnosis and prognosis, as well as in pharmaceutical drug development. The particular role of these biomarkers is to improve the early diagnosis of human disorders, to give an individual prognosis of the stage and progression of a diagnosed disease, and to predict and monitor the effectiveness of an applied therapy. In medical compound development, their main impact will be on the prediction of adverse and toxic effects, and clinical efficacy of new chemical entities in man.
Genomic medicine: bringing biomarkers to clinical medicine
Current Opinion in Chemical Biology, 2005
An important by-product of sequencing the human genome has been the development of a novel 'toolbox' for biomarker discovery and development. Genomic medicine is an emerging discipline in the genome sciences that integrates these tools to interrogate genomic variation in well-defined populations in order to develop predictors of disease susceptibility, progression and drug response. Several important classes of biomarkers result from these analyses which, when translated to clinical medicine and drug development, will have an important impact on human health and disease. This review highlights both the opportunities and challenges in bringing biomarkers into clinical medicine.
Clinical Cancer Research, 2012
Molecular diagnostics are increasingly important in clinical research to stratify or identify molecularly profiled patient cohorts for targeted therapies, to modify the dose of a therapeutic, or to assess early response to therapy or monitor patients. Molecular diagnostics can also be used to identify pharmocogenetic risk of adverse drug reactions. The articles of this CCR Focus section on Molecular Diagnosis describe the development and use of markers for medical decision-making in the cancer patient. They define the sources of preanalytic variability to minimize as well as the regulatory and financial challenges in diagnostic development and integration into clinical practice. They also outline an NCI program to assist diagnostic development. Molecular diagnostic clinical tests require rigor in their development and clinical validation with sufficient sensitivity, specificity and validity that is comparable to that used for development of therapeutics. These diagnostics must be offered at a realistic cost that reflects both their clinical value and the costs associated with their development. When genome sequencing technologies move into the clinic, they must be integrated with and traceable to current technology because they may identify more efficient and accurate approaches to drug development. In addition, regulators may define progressive drug approval for companion diagnostics that requires further evidence regarding efficacy and safety before full approval. A way to accomplish this is to emphasize Phase IV postmarketing hypothesis driven clinical trials with biological characterization that permits accurate definition of the association of low prevalence gene alterations with toxicity or response in large cohorts.
New Advances on Disease Biomarkers and Molecular Targets in Biomedicine
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A measure of the performance of biomarkers for disease
Cancer biomarkers : section A of Disease markers, 2006
The statistical properties required for effective biomarkers for disease are examined. It is shown that an "effectiveness parameter" D can be calculated that summarises the performance of a given biomarker and can distinguish between effective and ineffective biomarkers. D can be readily calculated from published summaries of biomarker levels and provides a simpler alternative to the commonly used "Area under the Curve" statistic. The impact of within-individual and between-individual variation in biomarker levels is also evaluated. An approach to the choice of sample size for experiments to estimate D is described.
Predictive genetic testing -- new possibilities in determination of risk of complex diseases
Croatian medical journal, 2001
Predictive genetic testing offers the possibility to statistically determine the risk of inheriting a complex phenotype by establishing an individual s genotype for metabolic polymorphisms. Here we discuss the conditions under which a predictive test may be offered to a patient and the problems connected with it. Examples of predictive genetic testing for multifactorial diseases and drug responses are given. We describe in detail the association of the C677T polymorphism of methylentetrahydrofolate reductase gene with hyperhomocystinemia and folate levels, as an independent risk factor for cardiovascular disease, and the association of a polymorphism of the promoter of the 5-lipoxygenase gene and the response to leukotriene inhibitors in asthma. Prospective development of genomic medicine and its use in the study of complex traits will hopefully bring significant benefit to the population and enhance the prevention and therapy of common diseases.
Biomarkers in molecular epidemiology studies for health risk prediction
Mutation Research-reviews in Mutation Research - MUTAT RES-REV MUTAT RES, 2002
The field of molecular epidemiology is very promising, as sophisticated techniques are being developed to address etiology, genetic susceptibility and mechanisms for induction of disease. The use of biomarkers plays a key role in these investigations because the information can be used to predict the development of disease and to implement disease prevention programs. However, as emphasized by Frederica P. Perera, the field is strewn with studies either that failed to use validated biomarkers or whose designs did not adequately consider the biology of the endpoints, and the availability of validated biomarkers of health risk is still limited. In this review, we have briefly described the usefulness of certain biomarkers for the documentation of exposure and early biological effects, with special concern for the prediction of cancer. An emphasis is placed on understanding the biological and health significance of biomarkers. By building reliable biomarker databases, a promising futur...
The Fundamental Difficulty With Evaluating the Accuracy of Biomarkers for Guiding Treatment
Journal of the National Cancer Institute, 2015
Developing biomarkers that can predict whether patients are likely to benefit from an intervention is a pressing objective in many areas of medicine. Recent guidance documents have recommended that the accuracy of predictive biomarkers, ie, sensitivity, specificity, and positive and negative predictive values, should be assessed. We clarify the meanings of these entities for predictive markers and demonstrate that generally they cannot be estimated from data without making strong untestable assumptions. Language suggesting that predictive biomarkers can identify patients who benefit from an intervention is also widespread. We show that in general one cannot estimate the chance that a patient will benefit from treatment. We recommend instead that predictive biomarkers be evaluated with respect to their ability to predict clinical outcomes among patients treated and among patients receiving standard of care, and the population impact of treatment rules based on those predictions. Ideally these entities are estimated from a randomized trial comparing the experimental intervention with standard of care.