Extension of a mechanistic predictive pharmacokinetic model to accommodate physiological and biochemical changes associated with obesity and morbid obesity allowed prediction of changes in drug clearance on the basis of in vitro data, with reasonable accuracy across a range of compounds that are metabolized by different enzymes. Prediction of the effects of obesity on drug clearance, normalized by various body size scalars, is of potential value in the design of clinical studies during drug development and in the introduction of dosage adjustments that are likely to be needed in clinical practice.

The genetically polymorphic cytochrome P450 2C9 (CYP2C9) metabolizes many important drugs. Among them, phenytoin has been used as a probe to determine CYP2C9 phenotype by measuring the urinary excretion of its major metabolite, S-enantiomer of 5-(4-hydroxyphenyl)-5-phenylhydantoin (p-HPPH). Phenytoin pharmacokinetic is also dependent on the activity of CYP2C19 and p-glycoprotein (ABCB1). To determine the influence of CYP2C9, CYP2C19 and ABCB1 genetic polymorphisms on phenytoin metabolism in a Black population, 109 healthy Beninese subjects received a single 300 mg oral dose of phenytoin. Blood was drawn 4 h after drug intake and urine was collected during the first 8 h. Plasma phenytoin and urine S- and R-enantiomers of p-HPPH were determined by high-performance liquid chromatography. Urinary excretion of (S)-p-HPPH [defined as urinary volumex(S)-p-HPPH urinary concentration] and PMR (defined as the ratio of p-HPPH in urine to 4 h phenytoin plasma concentration), both markers of CYP2C9 activity, were used to determine the functional relevance of new variants of CYP2C9 (*5, *6, *8, *9 and *11) in this population. Plasma phenytoin concentration was significantly associated with ABCB1 haplotype/genotype (P=0.05, Kruskal-Wallis test) and levels increased significantly in the genotype order: wild-type, T3421A and Block-2 genotypes (P=0.015, Jonckheere-Terpstra test). Urinary excretion of (S)-p-HPPH and PMR were significantly associated with the CYP2C9 genotype (P=0.001, analysis of variance (ANOVA) and P<0.0001, Kruskal-Wallis test, respectively) and decreased in the order: CYP2C9*1/*1, CYP2C9*1/*9, CYP2C9*9/*9, CYP2C9*1/*8, CYP2C9*8/*9, CYP2C9*9/*11, CYP2C9*1/*5, CYP2C9*6/*9, CYP2C9*1/*6, CYP2C9*8/*11, CYP2C9*5/*8 and CYP2C9*5/*6 (P<0.001, Jonckheere-Terpstra test). A combined analysis of CYP2C9, 2C19 and ABCB1 revealed that only ABCB1 predicted phenytoin concentration at 4 h and explained 8% of the variability (r=0.08, P=0.04). On the other hand, only CYP2C9 was predictive for the urinary excretion of (S)-p-HPPH and PMR (r=0.21, P=0.001 and r=0.25, P<0.001, respectively). Furthermore, significant relation was found between urinary excretion of (R)-p-HPPH and CYP2C9 genotype (P=0.035) and levels significantly increased in the genotype order: CYP2C9*1/*9, CYP2C9*1/*1, CYP2C9*9/*11, CYP2C9*1/*8 and CYP2C9*1/*5 (P<0.001, Jonckheere-Terpstra test). In summary, the present study demonstrates that, in a Black population, CYP2C9*5, *6, *8 and *11 variants, but not CYP2C9*9, are associated with a decreased phenytoin metabolism. The data also confirm the limited contribution of MDR1 gene to inter-individual phenytoin pharmacokinetic variation.

Aims  To investigate the distribution of cytochrome P450 2C9 (CYP2C9) and 2C19 (CYP2C19) genotype frequencies in the Beninese and Belgian Caucasian populations. Methods  Beninese (n = 111) and Belgian (n = 121) were genotyped for CYP2C9*2, *3, *4, *5, and *11 as well as for CYP2C19*2 and*3. Results  The distribution of alleles was: CYP2C9*1: 95.5 vs. 82.2% (P < 0.001); CYP2C9*2: 0 vs. 10% (P < 0.001); CYP2C9*3: 0 vs. 7.4% (P < 0.01); CYP2C9*4: both 0%; CYP2C9*5: 1.8 vs. 0% (P = 0.05); and CYP2C9*11: 2.7 vs. 0.4% (P < 0.05). The frequencies of the CYP2C19*2 allele were 13 vs. 9.1%, respectively. CYP2C19*3 was not detected in either population. The 95% confidence intervals for the differences of frequencies of CYP2C9*1, CYP2C9*2, CYP2C9*3, CYP2C9*4, CYP2C9*5, CYP2C9*11, CYP2C19*1, CYP2C19*2 and CYP2C19*3 between  Belgian  and  Beninese  were  7%,  19%;  − 14%,  − 6%;  − 11%, − 4%; − 1%, 1%; 0%, 4%; 0%, 5%; − 10%, 2%; − 2%, 10%; − 1%; respectively. The distributions of CYP2C9 genotypes in the Beninese and Belgian individuals were: CYP2C9*1/*1: 91 vs. 67% (P < 0.00001); CYP2C9*1/*2: 0 vs. 18.2% (P < 0.0001); CYP2C9*1/*3: 0 vs. 11.6% (P < 0.001); CYP2C9*1/*5: 3.6 vs. 0% (P = 0.05); CYP2C9*1/*11: 5.4 vs. 0.8% (P = 0.05); CYP2C9*2/*3: 0 vs. 1.6% (NS); CYP2C9*3/*3: 0 vs. 0.8% (NS). The distributions of CYP2C19 genotypes between these ethnic groups were: CYP2C19*1/*1: 73.9 vs. 83.5% (NS); CYP2C19*1/*2: 26.1 vs. 14.9% (P < 0.05); CYP2C9*2/*2: 0 vs. 1.6% (NS). Conclusions  Differences of allele frequencies between Beninese and Belgian populations were statistically significant for CYP2C9*2, *3, *5 and *11, but not for CYP2C9*4 or for CYP2C19*2 and *3.

The CYP2C9*5 and *6 alleles are associated with decreased enzyme activity in vivo compared with the wild-type variant, whereas the CYP2C9*8 and *11 variants did not appear to have large in vivo effects.