Investigation of the Differences in the Pharmacokinetics of CYP2D6 Substrates, Desipramine, and Dextromethorphan in Healthy African Subjects Carrying the Allelic Variants CYP2D6*17 and CYP2D6*29, When Compared with Normal Metabolizers.

This study investigated the differences in the pharmacokinetics (PK) of dextromethorphan and desipramine in healthy African volunteers to understand the effect of allelic variants of the human cytochrome P450 2D6 (CYP2D6) enzyme, namely the diplotypes of CYP2D6*1/*2 (*1*1, *1*2, *2*2) and the genotypes of CYP2D6*17*17 and CYP2D6*29*29. Overall, 28 adults were included and split into 3 cohorts after genotype screening: CYP2D6*1/*2 (n = 12), CYP2D6*17*17 (n = 12), and CYP2D6*29*29 (n = 4). Each subject received a single oral dose of dextromethorphan 30 mg syrup on day 1 and desipramine 50 mg tablet on day 8. The PK parameters of area under the plasma concentration-time curve from time of dosing to time of last quantifiable concentration (AUClast ), and extrapolated to infinity (AUCinf ), and the maximum plasma concentration (Cmax ) were determined. For both dextromethorphan and desipramine, AUCinf and Cmax were higher in subjects of the CYP2D6*29*29 and CYP2D6*17*17 cohorts, as compared with subjects in the CYP2D6*1/*2 diplotype cohort and with normal metabolizers from the literature. All PK parameters, including AUCinf , Cmax , and the elimination half-life, followed a similar trend: CYP2D6*17*17 > CYP2D6*29*29 > CYP2D6*1/*2. The plasma and urinary drug/metabolite exposure ratios of both drugs were higher in subjects of the CYP2D6*17*17 and CYP2D6*29*29 cohorts, when compared with subjects in the CYP2D6*1/*2 diplotype cohort. All adverse events were mild, except in 1 subject with CYP2D6*17*17 who had moderately severe headache with desipramine. These results indicate that subjects with CYP2D6*17*17 and CYP2D6*29*29 genotypes were 5-10 times slower metabolizers than those with CYP2D6*1/*2 diplotypes. These findings suggest that dose optimization may be required when administering CYP2D6 substrate drugs in African patients. Larger studies can further validate these findings.

Correlation between the systemic clearance of drugs and their food effects in humans.

CONTEXT: Food effects were defined as positive, when coadministration of food causes an increase in the extent of absorption (AUC(0-∞)) of a drug when compared with fasted state drug administration and no effect when coadministration of food causes no change in AUC(0-∞). In general, low solubility drugs exhibit positive food effects due to improved solubility in fed state administration. But, certain high-solubility and high-permeability drugs that undergo extensive presystemic metabolism exhibit positive food effects because of the increased splanchnic hepatic blood flow in the fed state presumably causing a fraction of drug to bypass first-pass metabolism during absorption. OBJECTIVE: In this study, systemic clearance (Cl) of structurally diverse high-permeability and high-solubility drugs was correlated to their food effects to explore whether drugs undergoing low clearance exhibited no food effects and drugs undergoing high clearance exhibited positive food effects. METHODS: Six drugs exhibiting positive food effects and nine drugs exhibiting no food effects (for comparison) were selected for linear regression analysis. RESULTS: Regression analysis of the selected drugs indicated that percent food effects correlated linearly to Cl and fitted the equation: percent food effects = 0.9163 × Cl - 6.4789. The R(2), p-value and power of the regression model were >0.88, 0.9999, respectively indicating the direct correlation between Cl and food effects of the selected model drugs; other statistical tests validated the model. CONCLUSION: The model indicated that high-solubility and high-permeability drugs undergoing Cl of more than 27 L/h may exhibit statistically significant positive food effects.

Predictive models for drugs exhibiting negative food effects based on their biopharmaceutical characteristics.

CONTEXT: A drug is defined to exhibit food effects if its pharmacokinetic parameter, area under the curve (AUC0₋∞) is different when co-administered with food in comparison with its administration on a fasted stomach. Food effects of drugs administered in immediate release dosage forms were classified as positive, negative, and no food effects. OBJECTIVE: In this study, predictive models for negative food effects of drugs that are stable in the gastrointestinal tract and do not complex with Ca²âº are reported. METHODS: An empirical model was developed using five drugs exhibiting negative food effects and seven drugs exhibiting no food effects by multiple regression analysis, based on biopharmaceutical properties generated from in vitro experiments. An oral absorption model was adopted for simulating negative food effects of model compounds using in situ rat intestinal permeability. RESULTS: Analysis of selected model drugs indicated that percent food effects correlated to their dissociation constant, K (K(a) or K(b)) and Caco-2 permeabilities. The obtained predictive equation was: Food effect (%)=(2.60 x 105·P(app))--(2.91 x 105·K)--8.50. Applying the oral absorption model, the predicted food effects matched the trends of published negative food effects when the two experimental pH conditions of fed and fasted state intestinal environment were used. CONCLUSION: A predictive model for negative food effects based on the correlation of food effects with dissociation constant and Caco-2 permeability was established and simulations of food effects using rat intestinal permeability supported the drugs? published negative food effects. Thus, an empirical and a mechanistic model as potential tools for predicting negative food effects are reported.

Investigation of some factors contributing to negative food effects.

A drug is defined as exhibiting negative food effects, if the co-administration of food statistically decreases its area under the curve, AUC, when compared with its administration on a fasted stomach. In this study, the role of biopharmaceutical factors that contribute to negative food effects was studied using furosemide, nadolol, tacrine and atenolol (as model compounds exhibiting negative food effects), and prednisolone, hydrochlorothiazide and ibuprofen (as model compounds that do not show any food effects). The physiological pH of the upper intestinal tract is lower, at pH 5, in the postprandial state when compared with the preprandial state, pH 6.5. Drugs that exhibited negative food effects had low apical to basolateral Caco-2 permeabilities, low pKa/pKb and Log P values of less than 1. The drugs exhibiting negative food effects had low distribution coefficients at the pH conditions of the fed and fasted states. Furosemide, being a hydrophilic, poorly soluble acidic drug showed lower solubility in the fed state when compared with the fasted state. Basic drugs, atenolol, nadolol and tacrine, are ionized to a higher extent in the fed state and exhibit lower permeability and lower absorption when compared with the fasted state. Thus, drugs were found to exhibit negative food effects owing to their decrease in solubility or permeability in the upper intestinal tract of the fed state when compared with the fasted state.