K A Phillips1, D L Veenstra, E Oren, J K Lee, W Sadee. 1. School of Pharmacy, Institute for Health Policy Studies, and Center for AIDS Prevention Studies, University of California, San Francisco, 3333 California St, Room 420, Box 0613, San Francisco, CA 94143, USA. kathryn@itsa.ucsf.edu
Abstract
CONTEXT: Adverse drug reactions are a significant cause of morbidity and mortality. Although many adverse drug reactions are considered nonpreventable, recent developments suggest these reactions may be avoided through individualization of drug therapies based on genetic information, an application known as pharmacogenomics. OBJECTIVE: To evaluate the potential role of pharmacogenomics in reducing the incidence of adverse drug reactions. DATA SOURCES: MEDLINE English-language only searches for adverse drug reaction studies published between January 1995 and June 2000 and review articles of variant alleles of drug-metabolizing enzymes published between January 1997 and August 2000. We also used online resources, texts, and expert opinion. STUDY SELECTION: Detailed inclusion criteria were used to select studies. We included 18 of 333 adverse drug reaction studies and 22 of 61 variant allele review articles. DATA EXTRACTION: All the investigators reviewed and coded articles using standardized abstracting forms. DATA SYNTHESIS: We identified 27 drugs frequently cited in adverse drug reaction studies. Among these drugs, 59% are metabolized by at least 1 enzyme with a variant allele known to cause poor metabolism. Conversely, only 7% to 22% of randomly selected drugs are known to be metabolized by enzymes with this genetic variability (range, P =.006-P<.001). CONCLUSIONS: Our results suggest that drug therapy based on individuals' genetic makeups may result in a clinically important reduction in adverse outcomes. Our findings serve as a foundation for further research on how pharmacogenomics can reduce the incidence of adverse reactions and on the resulting clinical, societal, and economic implications.
CONTEXT: Adverse drug reactions are a significant cause of morbidity and mortality. Although many adverse drug reactions are considered nonpreventable, recent developments suggest these reactions may be avoided through individualization of drug therapies based on genetic information, an application known as pharmacogenomics. OBJECTIVE: To evaluate the potential role of pharmacogenomics in reducing the incidence of adverse drug reactions. DATA SOURCES: MEDLINE English-language only searches for adverse drug reaction studies published between January 1995 and June 2000 and review articles of variant alleles of drug-metabolizing enzymes published between January 1997 and August 2000. We also used online resources, texts, and expert opinion. STUDY SELECTION: Detailed inclusion criteria were used to select studies. We included 18 of 333 adverse drug reaction studies and 22 of 61 variant allele review articles. DATA EXTRACTION: All the investigators reviewed and coded articles using standardized abstracting forms. DATA SYNTHESIS: We identified 27 drugs frequently cited in adverse drug reaction studies. Among these drugs, 59% are metabolized by at least 1 enzyme with a variant allele known to cause poor metabolism. Conversely, only 7% to 22% of randomly selected drugs are known to be metabolized by enzymes with this genetic variability (range, P =.006-P<.001). CONCLUSIONS: Our results suggest that drug therapy based on individuals' genetic makeups may result in a clinically important reduction in adverse outcomes. Our findings serve as a foundation for further research on how pharmacogenomics can reduce the incidence of adverse reactions and on the resulting clinical, societal, and economic implications.
Authors: M A Perera; E Gamazon; L H Cavallari; S R Patel; S Poindexter; R A Kittles; D Nicolae; N J Cox Journal: Clin Pharmacol Ther Date: 2011-01-26 Impact factor: 6.875
Authors: Hedi Schelleman; Bruno H Ch Stricker; Anthonius De Boer; Abraham A Kroon; Monique W M Verschuren; Cornelia M Van Duijn; Bruce M Psaty; Olaf H Klungel Journal: Drugs Date: 2004 Impact factor: 9.546