Concentration-time Curve Ratio Research Articles

Quantitative Prediction of Repaglinide-Rifampicin Complex Drug Interactions Using Dynamic and Static Mechanistic Models: Delineating Differential CYP3A4 Induction and OATP1B1 Inhibition Potential of Rifampicin

Repaglinide is mainly metabolized by cytochrome P450 enzymes CYP2C8 and CYP3A4, and it is also a substrate to a hepatic uptake transporter, organic anion transporting polypeptide (OATP)1B1. The purpose of this study is to predict the dosing time-dependent pharmacokinetic interactions of repaglinide with rifampicin, using mechanistic models. In vitro hepatic transport of repaglinide, characterized using sandwich-cultured human hepatocytes, and intrinsic metabolic parameters were used to build a dynamic whole-body physiologically-based pharmacokinetic (PBPK) model. The PBPK model adequately described repaglinide plasma concentration-time profiles and successfully predicted area under the plasma concentration-time curve ratios of repaglinide (within ± 25% error), dosed (staggered 0-24 hours) after rifampicin treatment when primarily considering induction of CYP3A4 and reversible inhibition of OATP1B1 by rifampicin. Further, a static mechanistic "extended net-effect" model incorporating transport and metabolic disposition parameters of repaglinide and interaction potency of rifampicin was devised. Predictions based on the static model are similar to those observed in the clinic (average error ∼19%) and to those based on the PBPK model. Both the models suggested that the combined effect of increased gut extraction and decreased hepatic uptake caused minimal repaglinide systemic exposure change when repaglinide is dosed simultaneously or 1 hour after the rifampicin dose. On the other hand, isolated induction effect as a result of temporal separation of the two drugs translated to an approximate 5-fold reduction in repaglinide systemic exposure. In conclusion, both dynamic and static mechanistic models are instrumental in delineating the quantitative contribution of transport and metabolism in the dosing time-dependent repaglinide-rifampicin interactions.

Quantitative Prediction of the Impact of Drug Interactions and Genetic Polymorphisms on Cytochrome P450 2C9 Substrate Exposure

Cytochrome P450 (CYP) 2C9 is the most common CYP2C enzyme and makes up approximately onethird of total CYP protein content in the liver. It metabolises more than 100 drugs. The exposure of drugs mainly eliminated by CYP2C9 may be dramatically modified by drug-drug interactions (DDIs) and genetic variations. The objective of this study was to develop a modelling approach to predict the impact of genetic polymorphisms and DDIs on drug exposure in drugs metabolised by CYP2C9. We then developed dosing recommendations based on genotypes and compared them to current Epar/Vidal dosing guidelines. We created two models. The genetic model was designed to predict the impact of CYP2C9 polymorphisms on drug exposure. It links the area under the concentration-time curve (AUC) ratio (mutant to wild-type patients) to two parameters: the fractional contribution of CYP2C9 to oral clearance in vivo (i.e. CR or contribution ratio), and the fractional activity of the allele combination with respect to the homozygous wild type (i.e. FA or fraction of activity). Data were available for 77 couples (substrate, genotype). We used a three-step approach: (1) initial estimates of CRs and FAs were calculated using a first bibliographic dataset; (2) external validation of these estimates was then performed through the comparison between the AUC ratios predicted by the model and the observed values, using a second published dataset; and (3) refined estimates of CRs and FAs were obtained using Bayesian orthogonal regression involving the whole dataset and initial estimates of CRs and FAs. Posterior distributions of AUC ratios, CRs and FAs were estimated using Monte-Carlo Markov chain simulation. The drug interaction model was designed to predict the impact of DDIs on drug exposure. It links the AUC ratio (ratio of drug given in combination to drug given alone) to several parameters: the CR, the inhibition ratio (IR) of an inhibitor, and the increase in clearance (IC) due to an inducer. Data were available for 80 DDIs. IRs and ICs were calculated using the interaction model and an external validation was performed. Doses adjustments were calculated in order to obtain equal values for drug exposure in extensive and poor metabolisers and then compared to Epar/Vidal dosing guidelines. CRs were assessed for 26 substrates, FAs for five genotype classes including CYP2C9*2 and *3 allelic variants, IRs for 27 inhibitors and ICs for two inducers. For the genetic model, the mean prediction error of AUC ratios was -0.01, while the mean prediction absolute error was 0.36. For the drug interaction model, the mean prediction error of AUC ratios was 0.01, while the mean prediction absolute error was 0.22. Of the 26 substrates and CYP2C9*2 and *3 variants investigated, 30 couples (substrate, genotype) lead to a dose adjustment, as opposed to only ten couples identified in the Epar/Vidal recommendations. These models were already used for CYP2D6. They are accurate at predicting the impact of drug interactions and genetic polymorphisms on CYP2C9 substrate exposure. This approach will contribute to the development of personalized medicine, i.e. individualized drug therapy with specific dosing recommendations based on CYP genotype or drug associations.

Evaluation of the Use of Static and Dynamic Models to Predict Drug-Drug Interaction and Its Associated Variability: Impact on Drug Discovery and Early Development

Simcyp, a population-based simulator, is widely used for evaluating drug-drug interaction (DDI) risks in healthy and disease populations. We compare the prediction performance of Simcyp with that of mechanistic static models using different types of inhibitor concentrations, with the aim of understanding their strengths/weaknesses and recommending the optimal use of tools in drug discovery/early development. The inclusion of an additional term in static equations to consider the contribution of hepatic first pass to DDIs (AUCR(hfp)) has also been examined. A second objective was to assess Simcyp's estimation of variability associated with DDIs. The data set used for the analysis comprises 19 clinical interactions from 11 proprietary compounds. Except for gut interaction parameters, all other input data were identical for Simcyp and static models. Static equations using an unbound average steady-state systemic inhibitor concentration (I(sys)) and a fixed fraction of gut extraction and neglecting gut extraction in the case of induction interactions performed better than Simcyp (84% compared with 58% of the interactions predicted within 2-fold). Differences in the prediction outcomes between the static and dynamic models are attributable to differences in first-pass contribution to DDI. The inclusion of AUCR(hfp) in static equations leads to systematic overprediction of interaction, suggesting a limited role for hepatic first pass in determining inhibition-based DDIs for our data set. Our analysis supports the use of static models when elimination routes of the victim compound and the role of gut extraction for the victim and/or inhibitor in humans are not well defined. A fixed variability of 40% of predicted mean area under the concentration-time curve ratio is recommended.

In Vivo Information-Guided Prediction Approach for Assessing the Risks of Drug-Drug Interactions Associated with Circulating Inhibitory Metabolites

The in vivo drug-drug interaction (DDI) risks associated with cytochrome P450 inhibitors that have circulating inhibitory metabolites cannot be accurately predicted by conventional in vitro-based methods. A novel approach, in vivo information-guided prediction (IVIP), was recently introduced for CYP3A- and CYP2D6-mediated DDIs. This technique should be applicable to the prediction of DDIs involving other important cytochrome P450 metabolic pathways. Therefore, the aims of this study were to extend the IVIP approach to CYP2C9-mediated DDIs and evaluate the IVIP approach for predicting DDIs associated with inhibitory metabolites. The analysis was based on data from reported DDIs in the literature. The IVIP approach was modified and extended to CYP2C9-mediated DDIs. Thereafter, the IVIP approach was evaluated for predicting the DDI risks of various inhibitors with inhibitory metabolites. Although the data on CYP2C9-mediated DDIs were limited compared with those for CYP3A- and CYP2D6-mediated DDIs, the modified IVIP approach successfully predicted CYP2C9-mediated DDIs. For the external validation set, the prediction accuracy for area under the plasma concentration-time curve (AUC) ratios ranged from 70 to 125%. The accuracy (75-128%) of the IVIP approach in predicting DDI risks of inhibitors with circulating inhibitory metabolites was more accurate than in vitro-based methods (28-805%). The IVIP model accommodates important confounding factors in the prediction of DDIs, which are difficult to handle using in vitro-based methods. In conclusion, the IVIP approach could be used to predict CYP2C9-mediated DDIs and is easily modified to incorporate the additive effect of circulating inhibitory metabolites.

Transporter-Mediated Drug–Drug Interactions Involving OATP Substrates: Predictions Based on In Vitro Inhibition Studies

Transporter-mediated drug–drug interactions (DDIs) are among the most important of the clinically relevant pharmacokinetic DDIs. We investigated the validity of a static prediction of area under the plasma concentration-time curve (AUC) ratios (AUCRs; AUC(with inhibitor)/AUC(control) using in vitro inhibition profiles, and selected the types of assumptions that improved the prediction accuracy with minimizing false-negative predictions. We used data from 58 DDI studies involving 12 substrates of hepatic organic anion–transporting polypeptides (OATPs). With original assumptions regarding the maximal increase in intestinal availability, maximum unbound concentration at the inlet to the liver, and inhibition of only the hepatic uptake process, the predicted AUCRs were comparable to those reported within a two/threefold error margin in 44/52 studies, whereas in 16 studies, the predictions were judged to be falsenegatives. When the inhibitory effects on both hepatic uptake and efflux/metabolisms were considered, the overall prediction accuracy became worse, although the false-negative prediction decreased to 11 studies. This illustrates that if appropriate assumptions are selected, unnecessary clinical DDI studies can be reasonably avoided.

Modeling Approach To Characterize Intraocular Doripenem Pharmacokinetics after Intravenous Administration to Rabbits, with Tentative Extrapolation to Humans

The aim of this study was to determine the penetration of doripenem administered intravenously into the rabbit aqueous and vitreous humors. Nineteen New Zealand White rabbits received a 20-mg dose of doripenem intravenously over 60 min. Specimens of aqueous humor, vitreous humor, and blood were obtained 30 min (n = 5), 1 h (n = 5), 2 h (n = 5), and 3 h (n = 4) after the beginning of the infusion and analyzed by high-performance liquid chromatography (HPLC). A pharmacokinetic (PK) model was developed to fit the experimental data. Doripenem concentrations in aqueous humor were lower than those in plasma ultrafiltrates at all sampling times, with an average aqueous humor-to-plasma ultrafiltrate area under the concentration-time curve ratio estimated as 8.3%. A pharmacokinetic model with peripheral elimination described the data adequately and was tentatively used to predict concentration-versus-time profiles and pharmacokinetic-pharmacodynamic (PK-PD) target attainment in patients under various dosing regimens. In conclusion, systematically administered doripenem does not seem to be a promising approach for the treatment of intraocular infections, especially since it could not be detected in the vitreous humor. However, this study has provided an opportunity to develop a new PK modeling approach to characterize the intraocular distribution of doripenem administered intravenously to rabbits, with tentative extrapolation to humans.

Predicting Drug Interaction Potential With a Physiologically Based Pharmacokinetic Model: A Case Study of Telithromycin, a Time-Dependent CYP3A Inhibitor

Telithromycin is a substrate and an inhibitor of cytochrome P450 3A (CYP3A4), with dose- and time-dependent nonlinear pharmacokinetics (PK). We hypothesized that the time-dependent inhibition (TDI) of CYP3A4 was responsible for the nonlinear PK of telithromycin and then used physiologically based PK (PBPK) modeling and simulation to verify this mechanism. Telithromycin PBPK models integrating in vitro, in silico, and in vivo PK data ruled out the contribution of enzyme/transporter saturation and suggested that TDI is a plausible mechanism for PK nonlinearity. The model successfully predicted the clinical interaction with the CYP3A4 substrate midazolam, as verified by external data not used for the model-building (intravenous (i.v.) and oral (p.o.) midazolam area under the concentration-time curve (AUC) ratio with/without concurrent telithromycin administration: 3.26 and 6.72 predicted vs. 2.20 and 6.11 observed, respectively). Models assuming reversible inhibition failed to predict such strong CYP3A4 inhibition. In the absence of in vitro TDI data, a PBPK model can be used to incorporate TDI mechanisms based on nonlinear PK data to predict clinical drug-drug interactions.

Pregnancy-Related Effects on Lamivudine Pharmacokinetics in a Population Study with 228 Women

The aim of this study was to describe lamivudine (3TC) pharmacokinetics (PK) in HIV-infected nonpregnant and pregnant women and their fetuses. Samples were collected according to therapeutic drug monitoring from 228 women treated with lamivudine and retrospectively analyzed by a population approach. The samples were also collected from cord blood and amniotic fluid at birth. Lamivudine pharmacokinetics were ascribed to an open two-compartment model with linear absorption and elimination. Mean population parameter estimates (intersubject variability) for women were an absorption rate constant of 1.04 h(-1), an elimination clearance rate of 23.6 (0.266) liters · h(-1), a central volume of distribution of 109 (0.897) liters, an intercompartmental clearance rate of 6.7 liters/h, and a peripheral volume of distribution of 129 liters. A fetal compartment was linked to maternal circulation by mother-to-cord (or fetus) and cord-to-mother rate constants of 0.463 h(-1) and 0.538 h(-1), respectively. The amniotic fluid compartment was connected to the fetal compartment with an elimination rate constant of 0.163 h(-1) and a fixed-constant swallowing flow. The placental transfer expressed as fetal-to-maternal area under the concentration-time curve (AUC) ratio was 0.86, and the lamivudine amniotic fluid accumulation, expressed as the amniotic fluid-to-fetal AUC ratio, was 2.9. Pregnant women had a 22% higher apparent clearance than nonpregnant and parturient women; however, this increase did not lead to subexposure and should not require a dosage adjustment.

Pharmacokinetics of two formulations of omeprazole administered through a gastrostomy tube in patients with severe neurodevelopmental problems

Omeprazole is often administered through a gastrostomy tube as either (i) a Multiple Unit Pellet System (MUPS®) tablet disintegrated in water (MUPS® formulation), or (ii) a suspension in 8.4% sodium bicarbonate (suspension formulation). This bioavailability study evaluates this practice in tube-fed patients with severe neurodevelopmental problems. Nonblinded, two-phase cross-over trial. In seven of 10 patients, bioavailability was higher for the suspension formulation than for the MUPS® formulation. Median (90% confidence interval) area under the plasma concentration-time curve ratio (MUPS® over suspension) was 0.5 (0.06-2.37). In this population, omeprazole MUPS® formulation has no apparent advantage over the more easily administered suspension formulation.

Impact of Intraperitoneal Chemotherapy after Gastrectomy with Positive Cytological Findings in Peritoneal Washings

Background: There is no standard treatment available for gastric cancer patients whose sole ‘non-curative factor’ is positivecytological findings in peritoneal washings (CFPW). The aim of this study was to examine the safety, pharmacokinetics and efficacy for free intraperitoneal cancer cells of intraperitoneal chemotherapy with paclitaxel after gastrectomy with en bloc D2 lymph node dissection in cases of gastric cancer with positive CFPW. Methods: Ten patients with gastric cancer who underwent gastrectomy and systemic lymphadenectomy with D2 dissection, without any other non-curative factors besides positive CFPW, were treated with early postoperative intraperitoneal paclitaxel. Intra-chemotherapeutic toxicity and operative complications were measured using NCI-CTC version 3.0. Intraperitoneal and plasma paclitaxel concentrations were measured using a high-performance liquid chromatographic assay. Results: Grade 3/4 toxic effects included anemia (20%) and neutropenia (10%) that required no treatment. Operative complications were, for example, superficial surgical site infections (10%) that were treated with antibiotics. No viable cancer cells were observed in the intra-abdominal fluid 24 h after intraperitoneal administration of paclitaxel. The intraperitoneal/plasma area under the drug concentration-time curve ratio was 2,003.3:1. Conclusion: Intraperitoneal chemotherapy with paclitaxel is a safe and effective treatment modality for free intraperitoneal cancer cells.

An examination of the potential effect of lipids on the first‐pass metabolism of the lipophilic drug anethol trithione

In this study, an examination of the potential effect of lipids on the first-pass metabolism of anethol trithione (ATT) was investigated. ATT is metabolized rapidly and extensively in liver into 4-hydroxy-anethole trithione (ATX), which was confirmed using the rat intestinal perfusion with the mesenteric cannulation model. Male Sprague-Dawley rats were orally administered of the lipid-based formulations (prepared by medium chain triglycerides (MCT)), the cyclodextrin formulation and the suspension formulation, respectively. For 6.75 mg/kg groups, ATX/ATT area under the plasma concentration-time curve (AUC) ratio decreased by 87% and 76% after administration of the MCT-based formulations and the cyclodextrin formulation, when compared with the suspension formulation (p < 0.05), respectively; for 2.25 mg/kg groups, it decreased by 53% in the MCT group when compared with the cyclodextrin group (p < 0.05). The saturation of pre-system metabolism of ATT was observed after administration of the MCT-based formulations and the cyclodextrin formulation, likely as a result of enhanced absorption and therefore presentation of higher drug concentrations to liver, when compared with the suspension formulation. A trend toward lower systemic metabolite to parent ratios was evident after administration of the lipid formulations, when compared with the cyclodextrin formulation; however, this was not statistically significant. Further studies on the potential for lipids to inhibit hepatic metabolism are therefore warranted.

Omeprazole limited sampling strategies to predict area under the concentration–time curve ratios: implications for cytochrome P450 2C19 and 3A phenotyping

To develop a limited sampling strategy (LSS) to predict area under the concentration-time curve (AUC) ratios of omeprazole (AUC(OPZ)) to its metabolites 5-hydroxyomeprazole (AUC(5OH)) and omeprazole sulfone (AUC(SUL)) as phenotyping parameters for cytochrome P450 (CYP) 2C19 and 3A. Data were obtained from 37 (4 women) Caucasian, Chinese, and Korean healthy adults from three published studies. The AUC(OPZ), AUC(5OH), and AUC(SUL) were calculated via noncompartmental analysis. Observed AUC(OPZ, OBS)/AUC(5OH, OBS) and AUC(OPZ, OBS)/AUC(SUL, OBS) were determined. Plasma concentrations of omeprazole, 5-hydroxyomeprazole, and omeprazole sulfone at 1, 1.5, 2, 3, 4, 6, and 8 h post-dose were used to generate limited sampling strategy (LSS) models to predict AUC(OPZ,PRE)/AUC(5OH,PRE) and AUC(OPZ,PRE/)AUC(SUL,PRE). Bias and precision were assessed via percentage mean prediction error (%MPE) and percentage mean absolute error (%MAE), with acceptable limits being <15%. For CYP2C19, the AUC(OPZ,OBS)/AUC(5OH,OBS) was [mean ± standard deviation (SD)] 2.10 ± 1.63. Five LSS models of AUC(OPZ,PRE)/AUC(5OH,PRE) were generated, but none met the bias or precision criteria. Upon stratification by CYP2C19 genotype and ethnicity, a three-timepoint (at 1, 2, and 4h) LSS model accurately predicted AUC(OPZ)/AUC(5OH) in Caucasian CYP2C19*1/*1 subjects. For CYP3A, AUC(OPZ,OBS)/AUC(SUL,OBS) (mean ± SD) was 1.79 ± 0.67. All LSS models had unacceptable %MAE, even when stratified by CYP2C19 genotype and ethnicity. A LSS model to predict AUC(OPZ)/AUC(5OH), and thus CYP2C19 activity, was generated for Caucasian CYP2C19*1/*1 subjects. However, additional model validation is needed prior to general use. LSS models to predict AUC(OPZ)/AUC(SUL), and thus CYP3A activity, were not possible, even upon stratification by CYP2C19 genotype and ethnicity.

Analysis and Prediction of Drug Transfer into Human Milk Taking into Consideration Secretion and Reuptake Clearances across the Mammary Epithelia

Medication use during lactation is a matter of concern due to unnecessary exposure of infants to drugs. Although some studies have predicted the extent of drug transfer into milk from physicochemical parameters, drug concentration-time profiles in milk have not been predicted or even analyzed yet. In the present study, a drug transfer model was constructed by defining secretion and reuptake clearances (CL(sec) and CL(re), respectively) between milk and plasma based on unbound drug concentrations. Through the use of this model, drug concentration-time profiles were analyzed in human milk and plasma based on data collected from the literature. CL(sec) and CL(re) values were obtained successfully for 49 drugs. Because the CL(sec) and CL(re) values were in general similar for each drug, transport across the mammary epithelia was mediated by passive diffusion in most cases. This study demonstrated that the logarithmically transformed values of CL(sec) and CL(re) can be predicted from physicochemical parameters with adjusted R(2) values of 0.705 and 0.472, respectively. Moreover, 66.7 and 77.8% of predicted CL(sec) and CL(re) values were within 3-fold error ranges of the observed values for 45 and 27 drugs, respectively. Finally, time profiles of drug concentrations in milk were simulated from physicochemical parameters. The milk-to-plasma area under the concentration-time curve ratios also were predicted successfully within 3-fold error ranges of the observed values for 71.9% of the drugs analyzed. The method described herein therefore may be useful in predicting drug concentration-time profiles in human milk for newly developed drugs.

Distribution characteristics of clarithromycin and azithromycin, macrolide antimicrobial agents used for treatment of respiratory infections, in lung epithelial lining fluid and alveolar macrophages

The distribution characteristics of clarithromycin (CAM) and azithromycin (AZM), macrolide antimicrobial agents, in lung epithelial lining fluid (ELF) and alveolar macrophages (AMs) were evaluated. In the in vivo animal experiments, the time-courses of the concentrations of CAM and AZM in ELF and AMs following oral administration (50 mg/kg) to rats were markedly higher than those in plasma, and the area under the drug concentration-time curve (AUC) ratios of ELF/plasma of CAM and AZM were 12 and 2.2, and the AUC ratios of AMs/ELF were 37 and 291, respectively. In the in vitro transport experiments, the basolateral-to-apical transport of CAM and AZM through model lung epithelial cell (Calu-3) monolayers were greater than the apical-to-basolateral transport. MDR1 substrates reduced the basolateral-to-apical transport of CAM and AZM. In the in vitro uptake experiments, the intracellular concentrations of CAM and AZM in cultured AMs (NR8383) were greater than the extracellular concentrations. The uptake of CAM and AZM by NR8383 was inhibited by ATP depletors. These data suggest that the high distribution of CAM and AZM to AMs is due to the sustained distribution to ELF via MDR1 as well as the high uptake by the AMs themselves via active transport mechanisms.

Glucuronidation of Anticancer Prodrug PR-104A: Species Differences, Identification of Human UDP-Glucuronosyltransferases, and Implications for Therapy

PR-104, the phosphate ester of a dinitrobenzamide mustard [PR-104A; 2-((2-bromoethyl)-2-{[(2-hydroxyethyl) amino] carbonyl}-4,6-dinitroanilino)ethyl methanesulfonate], is currently in clinical trial as a hypoxia- and aldo-keto reductase 1C3 (AKR1C3)-activated prodrug for cancer therapy. Here, we investigate species (human, dog, rat, mouse) differences in metabolism to the corresponding O-glucuronide, PR-104G, and identify the human UDP-glucuronosyltransferase (UGT) isoforms responsible. After intravenous PR-104, plasma area under the concentration-time curve ratios (PR-104G/PR-104A) decreased in the order of dog (2.3) > human (1.3) > mouse (0.03) > rat (0.005). The kinetics of uridine 5'-diphosphoglucuronic acid-dependent glucuronidation by liver microsomes in vitro fitted the single-enzyme Michaelis-Menten equation with similar K(m) (∼150 μM) but differing V(max) (472, 88, 37, and 14 nmol/h/mg for dog, human, rat, and mouse, respectively), suggesting that facile glucuronidation is responsible for the anomalously rapid clearance of PR-104A in dogs. In vitro-in vivo extrapolation of PR-104A glucuronidation kinetics is consistent with this also being a major clearance pathway in humans. Recombinant UGT screening identified UGT2B7 as the only commercially available human isoform able to conjugate PR-104A, and UGT2B7 protein concentrations were highly correlated (r = 0.93) with PR-104A glucuronidation by liver microsomes from 24 individuals. The active hydroxylamine metabolite of PR-104A, PR-104H, was also glucuronidated by UGT2B7, although with slightly lower specificity and much lower rates. UGT2B7 mRNA expression was highly variable in human tumor databases. Glucuronidation of PR-104A greatly suppressed nitroreduction by AKR1C3 and NADPH-supplemented anoxic human liver S9 (9000g postmitochondrial supernatant). In conclusion, PR-104A is glucuronidated by UGT2B7 with high specificity and seems to make a major contribution to clearance of PR-104A in humans, but it also has the potential to confer resistance in some human tumors.

Impact of Ignoring Extraction Ratio When Predicting Drug-Drug Interactions, Fraction Metabolized, and Intestinal First-Pass Contribution

Many mathematical models for in vitro to in vivo prediction of drug-drug interactions (DDIs) of orally administered victim drugs have been developed. However, to date, none of these models have been applicable to all intravenously administered victim drugs. We derived and conducted a sensitivity/error analysis of a modification to the existing multiple mode interaction prediction model such that it is applicable to all intravenously administered victim drugs. Using this model we showed that ignoring the hepatic extraction ratio (EH) (as low as 0.3) of intravenously administered victim drugs can result in 1) substantial underestimation of f(m, CYPi) (the fraction of hepatic clearance of the victim drug via a given enzymatic pathway) and 2) error in dissecting the contribution of intestinal and hepatic components of DDIs for orally administered drugs. Using this model we describe DDI boundaries (degree of inhibition or induction) at which ignoring the EH of commonly used victim drugs results in ≥30% error in the predicted area under the concentration-time curve (AUC) ratio or contribution of intestinal interaction to a DDI (CYP3A probes only). For the most widely used victim drug midazolam, these boundaries for AUC ratio are net inhibition (I/K(i) or λ/k(deg)) ≥1.3 or fold induction ≥2.1; for intestinal contribution the boundaries are 0.37 and 1.5, respectively. To accurately predict the intravenous AUC ratio, intestinal contribution, or f(m, CYPi) 1) for all induction DDIs irrespective of EH of the victim drug and 2) for modest to potent inhibition DDIs even when the EH is moderate (≥0.3), we propose that our model be used.

Maternal-Fetal Pharmacokinetics and Dynamics of a Single Intrapartum Dose of Maraviroc in Rhesus Macaques

Single-dose nevirapine (NVP) is effective in reducing mother-to-child transmission (MTCT) of HIV; however, the subsequent development of drug resistance is problematic. The pharmacokinetic profile of the HIV entry inhibitor maraviroc after a single intrapartum dose in rhesus macaques was studied to determine whether maraviroc could serve as an alternative to NVP in a single-dose strategy. Four pregnant macaques received an oral dose of maraviroc 2 h before delivery, and both infant and maternal plasma maraviroc concentrations and CCR5 receptor occupancy on CD4(+) lymphocytes were measured over time. Maximum plasma maraviroc concentrations were found at delivery (2-h-postintrapartum dose) in both the mothers and infants, with median concentrations of 974 ng/ml (range, 86 to 2,830 ng/ml) and 22 ng/ml (range, 4 to 99 ng/ml), respectively. Maraviroc was detected in the plasma of mothers up to 48 h after dosing but only as long as 3.5 h in the infants. The median fetal-maternal area under the concentration-time curve (AUC) ratio was 0.009 (range, 0.000 to 0.015). Maraviroc receptor occupancy data showed evidence of unprotected CCR5 receptors on CD4(+) cells in the mothers 24 to 48 h after dosing. Extremely low CCR5 expression on CD4(+) cells of newborn macaques prevented determination of receptor occupancy in the infants. In rhesus macaques, maraviroc was poorly transferred across the placenta and was quickly cleared from the infants' blood. The low concentrations of fetal maraviroc and short pharmacokinetic profile in infants suggest that a single maternal intrapartum dose of maraviroc would not be effective in reducing the risk of MTCT of HIV.

Effects of myricetin, an antioxidant, on the pharmacokinetics of losartan and its active metabolite, EXP-3174, in rats: possible role of cytochrome P450 3A4, cytochrome P450 2C9 and P-glycoprotein inhibition by myricetin

The effects of myricetin, a natural flavonoid, on the pharmacokinetics of losartan and its active metabolite, EXP-3174, were investigated in rats. Losartan and myricetin interact with cytochrome P450 (CYP) enzymes and P-glycoprotein, and the increase in the use of health supplements may result in myricetin being taken concomitantly with losartan as a combination therapy to treat or prevent cardiovascular diseases. The pharmacokinetic parameters of losartan and EXP-3174 were determined after oral administration of losartan (9 mg/kg) to rats in the presence or absence of myricetin (0.4, 2 and 8 mg/kg). The effects of myricetin on P-glycoprotein as well as CYP3A4 and CYP2C9 activity were also evaluated. Myricetin inhibited CYP3A4 and CYP2C9 enzyme activity with a 50% inhibition concentration of 7.8 and 13.5 microm, respectively. In addition, myricetin significantly enhanced the cellular accumulation of rhodamine 123 in MCF-7/ADR cells overexpressing P-glycoprotein in a concentration-dependent manner. The pharmacokinetic parameters of losartan were significantly altered by myricetin compared with the control. The presence of myricetin (2 or 8 mg/kg) increased the area under the plasma concentration-time curve of losartan by 31.4-61.1% and peak plasma concentration of losartan by 31.8-50.2%. Consequently, the absolute bioavailability of losartan in the presence of myricetin increased significantly (P < 0.05, 2 mg/kg; P < 0.01, 8 mg/kg) compared with the control. There was no significant change in the time to reach the peak plasma concentration, apparent volume of distribution at steady state or terminal half-life of losartan in the presence of myricetin. Furthermore, concurrent use of myricetin (8 mg/kg) significantly decreased the metabolite-parent area under the plasma concentration-time curve ratio by 20%, implying that myricetin may inhibit the CYP-mediated metabolism of losartan to its active metabolite, EXP-3174. The enhanced bioavailability of losartan may be mainly due to inhibition of the CYP3A4- and CYP2C9-mediated metabolism of losartan in the small intestine or in the liver, and the P-glycoprotein efflux pump in the small intestine by myricetin.

Brain Microdialysis Study of Meropenem in Two Patients with Acute Brain Injury

Concentrations of unbound meropenem in the cerebral extracellular fluid (ECF) of two patients with acute brain injury were assessed by microdialysis. Brain ECF unbound-meropenem concentrations were lower than serum unbound-meropenem concentrations, with brain-to-serum area under the concentration-time curve ratios of 0.73 and 0.14. A pharmacokinetic model was developed to fit the experimental data adequately.

In Vitro–In Vivo Extrapolation Predicts Drug–Drug Interactions Arising from Inhibition of Codeine Glucuronidation by Dextropropoxyphene, Fluconazole, Ketoconazole, and Methadone in Humans

Because codeine (COD) is eliminated primarily via glucuronidation, factors that alter COD glucuronide formation potentially affect the proportion of the dose converted to the pharmacologically active metabolite morphine. Thus, in vitro-in vivo extrapolation approaches were used to identify potential drug-drug interactions arising from inhibition of COD glucuronidation in humans. Initial studies characterized the kinetics of COD-6-glucuronide (C6G) formation by human liver microsomes (HLM) and demonstrated an 88% reduction in the Michaelis constant (K(m)) (0.29 versus 2.32 mM) for incubations performed in the presence of 2% bovine serum albumin (BSA). Of 13 recombinant UDP-glucuronosyltransferase (UGT) enzymes screened for COD glucuronidation activity, only UGT2B4 and UGT2B7 exhibited activity. The respective S(50) values (0.32 and 0.27 mM) generated in the presence of BSA were comparable with the mean K(m) observed in HLM. Known inhibitors of UGT2B7 activity in vitro or in vivo and drugs marketed as compound formulations with COD were investigated for inhibition of C6G formation by HLM. Inhibition screening identified potential interactions with dextropropoxyphene, fluconazole, ketoconazole, and methadone. Inhibitor constant values generated for dextropropoxyphene (3.5 microM), fluconazole (202 microM), ketoconazole (0.66 microM), and methadone (0.32 microM) predicted 1.60- to 3.66-fold increases in the area under the drug plasma concentration-time curve ratio for COD in vivo. Whereas fluconazole and ketoconazole inhibited UGT2B4- and UGT2B7-catalyzed COD glucuronidation to a similar extent, inhibition by dextropropoxyphene and methadone resulted largely from an effect on UGT2B4. Interactions with dextropropoxyphene, fluconazole, ketoconazole, and methadone potentially affect the intensity and duration of COD analgesia.