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Biomarker as a classifier in pharmacogenomics clinical trials: a tribute to 30th anniversary of PSI
Author(s) -
Wang SueJane
Publication year - 2007
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.316
Subject(s) - pharmacogenomics , clinical trial , pharmacogenetics , medicine , precision medicine , bioinformatics , computational biology , pharmacology , biology , genetics , pathology , genotype , gene
Pharmacogenetics is one of many evolving sciences that have come to the fore since the formation of the Statisticians in the Pharmaceutical Industry (PSI) 30 years ago. Following the completion of the human genome project and the HapMap in the early 21st century, pharmacogenetics has gradually focused on studies of whole‐genome single‐nucleotide‐polymorphisms screening associating disease pathophysiology with potential therapeutic interventions. Around this time, transcription profiling aiming at similar objectives has also been actively pursued, known as pharmacogenomics. It has become increasingly apparent that treatment effects between different genomic patient subsets can be dissimilar, and the value and need for genomic biomarkers to help predict effects, particularly in cancer clinical studies, have become issues of paramount importance. Pharmacogenomics/pharmaogenetics has thus become intensely focused on the search for genomic biomarkers for use as classifiers to select patients in randomized‐controlled trials. We highlight that the predictive utility of a genomic classifier has tremendous clinical appeal and that there will be growing examples in which use of a companion diagnostic will need to be considered and may become an integral part in the utilization of drugs in medical practice. The credible mechanism to test the clinical utility of a genomic classifier is to employ the study results from a prospective trial that recruits all patients. Such investigations, if well designed, will allow analysis of all relevant performance factors in the drug and diagnostic combination including the sensitivity, specificity, positive and negative predictive values of the diagnostic test and the efficacy of the drug. Published in 2007 by John Wiley & Sons, Ltd.