Literature DB >> 18923406

The medical and economic roles of pipeline pharmacogenetics: Alzheimer's disease as a model of efficacy and HLA-B(*)5701 as a model of safety.

Allen D Roses1.   

Abstract

Pharmacogenetics (PGX) is the study of drug response as a function of an individual's DNA. PGX is often viewed as an extension of disease association genetics, and although this information may be related, it is not the study of drug response. Although medicines are used to treat diseases, the value of strategies that identify and incorporate DNA biomarkers associated with clinical efficacy, or DNA biomarkers for untoward clinical responses, can be applied directly to pharmaceutical pipelines. The growth of adverse event PGX studies involving marketed medicines generally uses relatively large numbers of affected patients, but has been productive. However, the two critical strategies for pipeline genetics must make use of fewer patients: (1) the early identification of efficacy signals so that they can be applied early in development for targeted therapies and (2) identification of safety signals that can subsequently be validated prospectively during development using the least number of patients with adverse responses. Assumptions are often made that large numbers of patients are necessary to recognize PGX hypotheses and to validate DNA biomarkers. In some ways, pipeline pharmacogenetics may be viewed as the opposite of current genome-wide scanning designs. The goal is to obtain PGX signals in as few patients as possible, and then validate PGX hypotheses for specificity and sensitivity as development trials go forward--not using hundreds of thousand of markers to detect strong linkage disequilibrium signals in thousands of patients and their controls. Drug development takes 5-7 years for a drug candidate to traverse to registration--and this is similar to the timeframe for validating genetic biomarkers using sequential clinical trials. Two important examples are discussed, the association of APOE genotypes to the demonstration of actionable efficacy signals for the use of rosiglitazone for Alzheimer's disease; and the identification of HLA-B(*)5701 as a highly sensitive and specific predictive marker for abacavir treated patients who will develop hypersensitivity syndrome (HSS). The rosiglitazone study prevented pipeline attrition by changing the interpretation of a critical Phase IIB proof of concept study (2005) from a failed study, to a positive efficacy response in a genetically predictable proportion of patients. Now, three years later, a Phase III program of clinical trials using pharmacogenetic designs is months away from completion (late08). If successfully registered (early09), millions of patients could benefit, and efficacy PGX would have achieved its first prospective block-buster. The use of safety candidate gene association genetics in patients who received abacavir therapy and developed HSS starting in 1998 culminated in a double blind clinical trial that determined sensitivity > 97% and specificity >99% in 2007. Clinical consensus panels rapidly recommended abacavir as the preferred therapy along with HLA-B(*)5701 pre-testing, immediately increasing the market share of abacavir with respect to other reverse transcriptases that are associated with there own adverse events. Targeting of medicines during drug development is now possible, practical, and profitable.

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Year:  2008        PMID: 18923406     DOI: 10.1038/npp.2008.153

Source DB:  PubMed          Journal:  Neuropsychopharmacology        ISSN: 0893-133X            Impact factor:   7.853


  16 in total

Review 1.  Some evolutionary perspectives on Alzheimer's disease pathogenesis and pathology.

Authors:  Daniel J Glass; Steven E Arnold
Journal:  Alzheimers Dement       Date:  2011-12-03       Impact factor: 21.566

2.  A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease.

Authors:  A D Roses; M W Lutz; H Amrine-Madsen; A M Saunders; D G Crenshaw; S S Sundseth; M J Huentelman; K A Welsh-Bohmer; E M Reiman
Journal:  Pharmacogenomics J       Date:  2009-12-22       Impact factor: 3.550

3.  Effect of Alzheimer disease genetic risk disclosure on dietary supplement use.

Authors:  Jacqueline A Vernarelli; J Scott Roberts; Susan Hiraki; Clara A Chen; L Adrienne Cupples; Robert C Green
Journal:  Am J Clin Nutr       Date:  2010-03-10       Impact factor: 7.045

Review 4.  Bioenergetic origins of complexity and disease.

Authors:  D C Wallace
Journal:  Cold Spring Harb Symp Quant Biol       Date:  2011-12-22

Review 5.  A mitochondrial etiology of Alzheimer and Parkinson disease.

Authors:  Pinar Coskun; Joanne Wyrembak; Samual E Schriner; Hsiao-Wen Chen; Christine Marciniack; Frank Laferla; Douglas C Wallace
Journal:  Biochim Biophys Acta       Date:  2011-08-16

6.  Estimating and disclosing the risk of developing Alzheimer's disease: challenges, controversies and future directions.

Authors:  J Scott Roberts; Sarah M Tersegno
Journal:  Future Neurol       Date:  2010-07-01

7.  Genomics of Dementia: APOE- and CYP2D6-Related Pharmacogenetics.

Authors:  Ramón Cacabelos; Rocío Martínez; Lucía Fernández-Novoa; Juan C Carril; Valter Lombardi; Iván Carrera; Lola Corzo; Iván Tellado; Jerzy Leszek; Adam McKay; Masatoshi Takeda
Journal:  Int J Alzheimers Dis       Date:  2012-03-14

Review 8.  Genomics and pharmacogenomics of dementia.

Authors:  Ramón Cacabelos; Rocío Martínez-Bouza
Journal:  CNS Neurosci Ther       Date:  2010-08-16       Impact factor: 5.243

Review 9.  Genetic susceptibility testing for neurodegenerative diseases: ethical and practice issues.

Authors:  J Scott Roberts; Wendy R Uhlmann
Journal:  Prog Neurobiol       Date:  2013-04-09       Impact factor: 11.685

10.  Alzheimer's disease: diagnostics, prognostics and the road to prevention.

Authors:  Iris Grossman; Michael W Lutz; Donna G Crenshaw; Ann M Saunders; Daniel K Burns; Allen D Roses
Journal:  EPMA J       Date:  2010-06-29       Impact factor: 6.543

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