Literature DB >> 17005258

Can personalized drug therapy be achieved? A closer look at pharmaco-metabonomics.

Daniel W Nebert1, Elliot S Vesell.   

Abstract

Between 1930 and 1990, several dozen high-penetrance, predominantly monogenic disorders were identified and characterized, which led some investigators to speculate that individualized drug treatment was just around the corner. Informative DNA tests were sought to determine genetic predisposition to toxicity and cancer, thereby identifying individuals in which a drug was likely to be effective and those at increased risk of drug toxicity. These assays represent the leading edge of phenotype-genotype association studies, which are a major goal of clinical pharmacology and pharmacogenomics. Because of the complexity of the genome, however, the task is more challenging than anticipated originally. In the past decade we have come to appreciate how difficult it is to determine unequivocally either an exact phenotype or genotype. In the near future it seems unlikely that, by themselves, either transcriptomics or proteomics will be particularly helpful in achieving individualized drug therapy. However, recent advances in metabonomics are exciting and show promise. In the future, and perhaps in combination with proteomics, metabonomics might complement genomics in achieving personalized drug therapy.

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Year:  2006        PMID: 17005258     DOI: 10.1016/j.tips.2006.09.008

Source DB:  PubMed          Journal:  Trends Pharmacol Sci        ISSN: 0165-6147            Impact factor:   14.819


  8 in total

1.  Characterization of CYP1A2, CYP2C19, CYP3A4 and CYP3A5 polymorphisms in South Brazilians.

Authors:  Fabiana B Kohlrausch; Ángel Carracedo; Mara H Hutz
Journal:  Mol Biol Rep       Date:  2014-01-18       Impact factor: 2.316

2.  Analysis of metabolomic PCA data using tree diagrams.

Authors:  Mark T Werth; Steven Halouska; Matthew D Shortridge; Bo Zhang; Robert Powers
Journal:  Anal Biochem       Date:  2009-12-21       Impact factor: 3.365

3.  Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism.

Authors:  T Andrew Clayton; David Baker; John C Lindon; Jeremy R Everett; Jeremy K Nicholson
Journal:  Proc Natl Acad Sci U S A       Date:  2009-08-10       Impact factor: 11.205

4.  Incorporating genetics and genomics in risk assessment for inhaled manganese: from data to policy.

Authors:  Christine P Curran; Robert M Park; Shuk-mei Ho; Erin N Haynes
Journal:  Neurotoxicology       Date:  2009-07-29       Impact factor: 4.294

Review 5.  LC-MS-based metabolomics in drug metabolism.

Authors:  Chi Chen; Frank J Gonzalez; Jeffrey R Idle
Journal:  Drug Metab Rev       Date:  2007       Impact factor: 4.518

6.  Identification of differential responses to an oral glucose tolerance test in healthy adults.

Authors:  Ciara Morris; Colm O'Grada; Miriam Ryan; Helen M Roche; Michael J Gibney; Eileen R Gibney; Lorraine Brennan
Journal:  PLoS One       Date:  2013-08-22       Impact factor: 3.240

Review 7.  Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come?

Authors:  Luca Sala; Milena Bellin; Christine L Mummery
Journal:  Br J Pharmacol       Date:  2016-09-20       Impact factor: 8.739

8.  Given the complexity of the human genome, can 'personalised medicine' or 'individualised drug therapy' ever be achieved?

Authors:  Daniel W Nebert
Journal:  Hum Genomics       Date:  2009-07       Impact factor: 4.639

  8 in total

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