Browsing by Subject "genotype-phenotype correlation"

Interindividual variability in drug responses can complicate the determination of drug doses and increase drug-related risks. The variability can be caused by pharmacokinetics or pharmacodynamics of drug. One significant factor giving rise to the variability in the pharmacokinetics is the genetic polymorphism of cytochrome P450 (CYP) enzymes. CYP2C19 and CYP2D6 are highly polymorphic enzymes and many of their polymorphisms are well-known. For both genes there exist null alleles producing the enzyme with complete lack of function and alleles producing increased enzyme activity. Additionally there are alleles of CYP2D6 leading to partially deficient enzyme function. Based on the genotype of the CYP gene individuals can be divided into four phenotype groups describing the enzyme activity: poor, intermediate, extensive and ultrarapid metabolizers. According to the clinical observations the pharmacokinetics of CYP2C19 and CYP2D6 substrates in the individuals genotyped as poor metabolizers often significantly differentiates from the pharmacokinetics in the individuals belonging to other phenotype groups. Between the other phenotype groups the pharmacokinetic variability caused by the genotype seems to be often covered by other reasons causing variability in the pharmacokinetics. The pharmaceutical industry could benefit from methods that could predict the interindividual variability in the drug responses before the clinical studies. The pharmacokinetic variability caused by the genetic polymorphism of CYP enzymes has been predicted with different kinds of static and dynamic physiologically based pharmacokinetic simulation models. The models have taken the CYP genotype into account by non-substratespesific or substratespesific methods. The models have succeeded to predict the clinically observed interindividual variability in the pharmacokinetics of substrates. The goal of this study was to find out if in vitro metabolism data obtained with human liver microsomes genotyped for CYP2C19 or CYP2D6 could be used to predict the interindividual variability in the pharmacokinetics of drugs. The effect of polymorphism on metabolism was examined by incubating the substrates with microsomes with different CYP2C19 or CYP2D6 genotypes. S-mephenytoin, omeprazole and Y1 (compound developed by the pharmaceutical company Orion Oyj) were used as substrates for CYP2C19. Neither the rate of metabolism of S-mephenytoin nor omeprazole appeared to be dependent on the CYP2C19 genotype, with the exception of the poor metabolizer genotype. Use of microsomes genotyped for the other CYP2C19 phenotypes to obtain predictive in vitro metabolism data might therefore not be reasonable. More significant dependence of the Y1 metabolism on the CYP2C19 genotype could not be completely excluded. When examining the effect of polymorphism on non-selective metabolic reactions, the activity of metabolizing enzymes other than the polymorphic enzyme should always be taken into consideration: in this study, CYP3A4 activity biased the results initially achieved with omeprazole and Y1. Dextromethorphan and bufuralol were used as substrates for CYP2D6 and their rates of metabolism correlated well with the CYP2D6 genotype. So microsomes genotyped for CYP2D6 could possibly be used to obtain predictive in vitro metabolism data. If genotyped microsomes are to be used in the pharmaceutical industry to predict the interindividual variability in the pharmacokinetics, factors increasing reliability of the results should be considered first and more studies should be conducted.