Literature DB >> 16096112

Pharmacogenetics in drug regulation: promise, potential and pitfalls.

Rashmi R Shah1.   

Abstract

Pharmacogenetic factors operate at pharmacokinetic as well as pharmacodynamic levels-the two components of the dose-response curve of a drug. Polymorphisms in drug metabolizing enzymes, transporters and/or pharmacological targets of drugs may profoundly influence the dose-response relationship between individuals. For some drugs, although retrospective data from case studies suggests that these polymorphisms are frequently associated with adverse drug reactions or failure of efficacy, the clinical utility of such data remains unproven. There is, therefore, an urgent need for prospective data to determine whether pre-treatment genotyping can improve therapy. Various regulatory guidelines already recommend exploration of the role of genetic factors when investigating a drug for its pharmacokinetics, pharmacodynamics, dose-response relationship and drug interaction potential. Arising from the global heterogeneity in the frequency of variant alleles, regulatory guidelines also require the sponsors to provide additional information, usually pharmacogenetic bridging data, to determine whether data from one ethnic population can be extrapolated to another. At present, sponsors explore pharmacogenetic influences in early clinical pharmacokinetic studies but rarely do they carry the findings forward when designing dose-response studies or pivotal studies. When appropriate, regulatory authorities include genotype-specific recommendations in the prescribing information. Sometimes, this may include the need to adjust a dose in some genotypes under specific circumstances. Detailed references to pharmacogenetics in prescribing information and pharmacogenetically based prescribing in routine therapeutics will require robust prospective data from well-designed studies. With greater integration of pharmacogenetics in drug development, regulatory authorities expect to receive more detailed genetic data. This is likely to complicate the drug evaluation process as well as result in complex prescribing information. Genotype-specific dosing regimens will have to be more precise and marketing strategies more prudent. However, not all variations in drug responses are related to pharmacogenetic polymorphisms. Drug response can be modulated by a number of non-genetic factors, especially co-medications and presence of concurrent diseases. Inappropriate prescribing frequently compounds the complexity introduced by these two important non-genetic factors. Unless prescribers adhere to the prescribing information, much of the benefits of pharmacogenetics will be squandered. Discovering highly predictive genotype-phenotype associations during drug development and demonstrating their clinical validity and utility in well-designed prospective clinical trials will no doubt better define the role of pharmacogenetics in future clinical practice. In the meantime, prescribing should comply with the information provided while pharmacogenetic research is deservedly supported by all concerned but without unrealistic expectations.

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Year:  2005        PMID: 16096112      PMCID: PMC1569525          DOI: 10.1098/rstb.2005.1693

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  162 in total

1.  Medical implications of HGP's sequence of chromosome 22.

Authors:  J R Idle; J Corchero; F J Gonzalez
Journal:  Lancet       Date:  2000-01-22       Impact factor: 79.321

2.  Bioinformatics research on inter-racial difference in drug metabolism I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19.

Authors:  Takako Shimizu; Hirohide Ochiai; Fredrik Asell; Hiroshi Shimizu; Ryuta Saitoh; Yoshimasa Hama; Jun Katada; Munehiro Hashimoto; Hitoshi Matsui; Katsuhiko Taki; Tsuguchika Kaminuma; Michiko Yamamoto; Yoshitaka Aida; Akira Ohashi; Naoki Ozawa
Journal:  Drug Metab Pharmacokinet       Date:  2003       Impact factor: 3.614

3.  Ethnic distribution of slow acetylator mutations in the polymorphic N-acetyltransferase (NAT2) gene.

Authors:  H J Lin; C Y Han; B K Lin; S Hardy
Journal:  Pharmacogenetics       Date:  1994-06

4.  Relationship of polymorphism in CYP2C9 to genetic susceptibility to diclofenac-induced hepatitis.

Authors:  G P Aithal; C P Day; J B Leathart; A K Daly
Journal:  Pharmacogenetics       Date:  2000-08

5.  Genetic polymorphism of cytochrome P450 2C9 in a Caucasian and a black African population.

Authors:  M G Scordo; E Aklillu; U Yasar; M L Dahl; E Spina; M Ingelman-Sundberg
Journal:  Br J Clin Pharmacol       Date:  2001-10       Impact factor: 4.335

6.  Beta-adrenoceptor genotype influences the response to carvedilol in patients with congestive heart failure.

Authors:  David M Kaye; Belinda Smirk; Carolyn Williams; Garry Jennings; Murray Esler; Dianne Holst
Journal:  Pharmacogenetics       Date:  2003-07

7.  Defective N-oxidation of sparteine in man: a new pharmacogenetic defect.

Authors:  M Eichelbaum; N Spannbrucker; B Steincke; H J Dengler
Journal:  Eur J Clin Pharmacol       Date:  1979-09       Impact factor: 2.953

8.  Impact of the ultrarapid metabolizer genotype of cytochrome P450 2D6 on metoprolol pharmacokinetics and pharmacodynamics.

Authors:  Julia Kirchheiner; Claudia Heesch; Steffen Bauer; Christian Meisel; Angela Seringer; Mark Goldammer; Mladen Tzvetkov; Ingolf Meineke; Ivar Roots; Jürgen Brockmöller
Journal:  Clin Pharmacol Ther       Date:  2004-10       Impact factor: 6.875

9.  Quinidine-enhanced beta-blockade during treatment with propafenone in extensive metabolizer human subjects.

Authors:  K E Mörike; D M Roden
Journal:  Clin Pharmacol Ther       Date:  1994-01       Impact factor: 6.875

10.  Interethnic difference in omeprazole's inhibition of diazepam metabolism.

Authors:  Y Caraco; T Tateishi; A J Wood
Journal:  Clin Pharmacol Ther       Date:  1995-07       Impact factor: 6.875

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  13 in total

1.  Introduction: genetic variation and human health.

Authors:  M P H Stumpf; D B Goldstein; N W Wood
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-08-29       Impact factor: 6.237

Review 2.  Genetics of congenital and drug-induced long QT syndromes: current evidence and future research perspectives.

Authors:  Saagar Mahida; Andrew J Hogarth; Campbell Cowan; Muzahir H Tayebjee; Lee N Graham; Christopher B Pepper
Journal:  J Interv Card Electrophysiol       Date:  2013-03-21       Impact factor: 1.900

Review 3.  Pathogenesis of thrombosis: cellular and pharmacogenetic contributions.

Authors:  Dileep D Monie; Emma P DeLoughery
Journal:  Cardiovasc Diagn Ther       Date:  2017-12

Review 4.  Do we need pharmacogenetics to personalize antidepressant therapy?

Authors:  Cristina Lanni; Marco Racchi; Stefano Govoni
Journal:  Cell Mol Life Sci       Date:  2012-12-28       Impact factor: 9.261

Review 5.  Pharmacogenetics and stroke.

Authors:  James F Meschia
Journal:  Stroke       Date:  2009-09-17       Impact factor: 7.914

6.  Distribution of CYP2D6 and CYP2C19 polymorphisms associated with poor metabolizer phenotype in five Amerindian groups and western Mestizos from Mexico.

Authors:  Joel Salazar-Flores; Luis A Torres-Reyes; Gabriela Martínez-Cortés; Rodrigo Rubi-Castellanos; Martha Sosa-Macías; José F Muñoz-Valle; César González-González; Angélica Ramírez; Raquel Román; José L Méndez; Andrés Barrera; Alfredo Torres; Rafael Medina; Héctor Rangel-Villalobos
Journal:  Genet Test Mol Biomarkers       Date:  2012-08-22

7.  The genetic architecture of fasting plasma triglyceride response to fenofibrate treatment.

Authors:  Jennifer A Smith; Donna K Arnett; Reagan J Kelly; Jose M Ordovas; Yan V Sun; Paul N Hopkins; James E Hixson; Robert J Straka; James M Peacock; Sharon L R Kardia
Journal:  Eur J Hum Genet       Date:  2008-01-23       Impact factor: 4.246

8.  Animal models and conserved processes.

Authors:  Ray Greek; Mark J Rice
Journal:  Theor Biol Med Model       Date:  2012-09-10       Impact factor: 2.432

Review 9.  Pharmacogenetics of Drug-Induced QT Interval Prolongation: An Update.

Authors:  Maartje N Niemeijer; Marten E van den Berg; Mark Eijgelsheim; Peter R Rijnbeek; Bruno H Stricker
Journal:  Drug Saf       Date:  2015-10       Impact factor: 5.606

10.  Development of a novel, fully-automated genotyping system: principle and applications.

Authors:  Shun-Ichi Suzuki; Mariko Komori; Mitsuharu Hirai; Norio Ureshino; Shinya Kimura
Journal:  Sensors (Basel)       Date:  2012-12-03       Impact factor: 3.576

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