Simultaneous optimal experimental design for in vitro binding parameter estimation.

Simultaneous optimization of in vitro ligand binding studies using an optimal design software package that can incorporate multiple design variables through non-linear mixed effect models and provide a general optimized design regardless of the binding site capacity and relative binding rates for a two binding system. Experimental design optimization was employed with D- and ED-optimality using PopED 2.8 including commonly encountered factors during experimentation (residual error, between experiment variability and non-specific binding) for in vitro ligand binding experiments: association, dissociation, equilibrium and non-specific binding experiments. Moreover, a method for optimizing several design parameters (ligand concentrations, measurement times and total number of samples) was examined. With changes in relative binding site density and relative binding rates, different measurement times and ligand concentrations were needed to provide precise estimation of binding parameters. However, using optimized design variables, significant reductions in number of samples provided as good or better precision of the parameter estimates compared to the original extensive sampling design. Employing ED-optimality led to a general experimental design regardless of the relative binding site density and relative binding rates. Precision of the parameter estimates were as good as the extensive sampling design for most parameters and better for the poorly estimated parameters. Optimized designs for in vitro ligand binding studies provided robust parameter estimation while allowing more efficient and cost effective experimentation by reducing the measurement times and separate ligand concentrations required and in some cases, the total number of samples.

Donanemab exposure and efficacy relationship using modeling in Alzheimer's disease.

INTRODUCTION: Donanemab is an amyloid-targeting therapy that specifically targets brain amyloid plaques. The objective of these analyses was to characterize the relationship of donanemab exposure with plasma biomarkers and clinical efficacy through modeling. METHODS: Data for the analyses were from participants with Alzheimer's disease from the phase 1 and TRAILBLAZER-ALZ studies. Indirect-response models were used to fit plasma phosphorylated tau 217 (p-tau217) and plasma glial fibrillated acidic protein (GFAP) data over time. Disease-progression models were developed using pharmacokinetic/pharmacodynamic modeling. RESULTS: The plasma p-tau217 and plasma GFAP models adequately predicted the change over time, with donanemab resulting in decreased plasma p-tau217 and plasma GFAP concentrations. The disease-progression models confirmed that donanemab significantly reduced the rate of clinical decline. Simulations revealed that donanemab slowed disease progression irrespective of baseline tau positron emission tomography (PET) level within the evaluated population. DISCUSSION: The disease-progression models show a clear treatment effect of donanemab on clinical efficacy regardless of baseline disease severity.

Donanemab Population Pharmacokinetics, Amyloid Plaque Reduction, and Safety in Participants with Alzheimer's Disease.

Donanemab is an amyloid-targeting therapy that resulted in robust amyloid plaque reduction and slowed Alzheimer's disease (AD) progression compared with placebo in the phase II TRAILBLAZER-ALZ study (NCT03367403). The objectives of the current analyses are to characterize (i) the population pharmacokinetics of donanemab, (ii) the relationship between donanemab exposure and amyloid plaque reduction (response), and (iii) the relationship between donanemab exposure and amyloid-related imaging abnormalities with edema or effusions (ARIA-E). Model development included data from participants with mild cognitive impairment or mild to moderate dementia due to AD from the phase Ib study on donanemab (NCT02624778) and participants with early symptomatic AD from the TRAILBLAZER-ALZ study. The analysis showed donanemab has a terminal elimination half-life of 11.8 days. Body weight and antidrug antibody titer impact donanemab exposure but not the pharmacodynamic response. Maintaining a donanemab serum concentration above 4.43 µg/mL (95% confidence interval: 0.956, 10.4) is associated with amyloid plaque reduction. The time to achieve amyloid plaque clearance (amyloid plaque level < 24.1 Centiloids) varied depending on the baseline amyloid level, where higher baseline levels were associated with fewer participants achieving amyloid clearance. The majority of participants achieved amyloid clearance by 52 weeks on treatment. Apolipoprotein ε4 carriers, irrespective of donanemab serum exposure, were 4 times more likely than noncarriers to have an ARIA-E event by 24 weeks.

PK/PD modeling links accelerated resolution of COVID-19-related clinical symptoms to SARS-CoV-2 viral load reduction in patients following treatment with Bamlanivimab alone or Bamlanivimab and Etesevimab together.

The relationship between severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral load reduction and disease symptom resolution remains largely undefined for coronavirus disease 2019 (COVID-19). While the vaccine-derived immunity takes time to develop, neutralizing monoclonal antibodies offer immediate, passive immunity to patients with COVID-19. Bamlanivimab and etesevimab are two potent neutralizing monoclonal antibodies directed to the receptor binding domain of the spike protein of SARS-CoV-2. This study aims to describe the relationship between viral load and resolution of eight common COVID-19-related symptoms in patients following treatment with neutralizing monoclonal antibodies (bamlanivimab alone or bamlanivimab and etesevimab together), in a phase II clinical trial. Corresponding pharmacokinetics (PKs), viral load, and COVID-19-related symptom data were modeled using Nonlinear Mixed Effects Modeling to describe the time-course of eight COVID-19-related symptoms in an ordered categorical manner (none, mild, moderate, and severe), following administration of bamlanivimab or bamlanivimab and etesevimab together to participants with COVID-19. The PK/pharmacodynamic (PD) models characterized the exposure-viral load-symptom time course of the eight preselected COVID-19-related symptoms. Baseline viral load (BVL), change in viral load from baseline, and time since the onset of symptoms, demonstrated statistically significant effects on symptom score probabilities. Higher BVL generally indicated an increased probability of symptom severity. The severity of symptoms decreased over time, partially driven by the decrease in viral load. The effect of increasing time resulting in decreased severity of symptoms was over and above the effect of decreasing viral load. Administration of bamlanivimab alone or together with etesevimab results in a faster time to resolution of COVID-19-related symptoms compared to placebo.

Methodological comparison of in vitro binding parameter estimation: sequential vs. simultaneous non-linear regression.

PURPOSE: Analysis of simulated data was compared using sequential (NLR) and simultaneous non-linear regression (SNLR) to evaluate precision and accuracy of ligand binding parameter estimation. METHODS: Commonly encountered experimental error, specifically residual error of binding measurements (RE), experiment-to-experiment variability (BEV) and non-specific binding (B(NS)), were examined for impact of parameter estimation using both methods. Data from equilibrium, dissociation, association and non-specific binding experiments were fit simultaneously (SNLR) using NONMEM VI compared to the common practice of analyzing data from each experiment separately and assigning these as exact values (NLR) for estimation of the subsequent parameters. RESULTS: The greatest contributing factor to bias and variability in parameter estimation was RE of the measured concentrations of ligand bound; however, SNLR provided more accurate and less bias estimates. Subtraction of B(NS) from total ligand binding data provided poor estimation of specific ligand binding parameters using both NLR and SNLR. Additional methods examined demonstrated that the use of SNLR provided better estimation of specific binding parameters, whereas there was considerable bias using NLR. NLR cannot account for BEV, whereas SNLR can provide approximate estimates of BEV. CONCLUSION: SNLR provided superior resolution of parameter estimation in both precision and accuracy compared to NLR.

Prediction of prasugrel active metabolite concentrations from 2 downstream inactive metabolite concentrations using multilinear regression analysis.

Prasugrel is a thienopyridine prodrug that is metabolized to an active metabolite (Pras-AM), which inhibits adenosine diphosphate (ADP)-induced platelet aggregation. The study objective was to describe a multilinear regression correlation model that was used to quantitatively predict concentrations of Pras-AM from downstream inactive metabolites, R-119251 and R-106583, for the purpose of estimating Pras-AM exposure in patients in the TRITON-TIMI 38 substudies. The model development included 1462 Pras-AM, 1345 R-119251, and 1456 R-106583 concentration data points from 103 healthy participants with a prasugrel dose range of 15 to 80 mg. The model was shown to provide good correlation between predicted and observed concentrations with only a minor deviation of approximately 6% from the unity line and described the variability within approximately 4.5%. Examination of the data indicated that regardless of ethnicity, age, weight, moderate hepatic impairment, or renal impairment, predictions were reliable. Predicted Pras-AM concentrations in TRITON-TIMI 38 were comparable with historical data.

Population pharmacokinetic analyses to evaluate the influence of intrinsic and extrinsic factors on exposure of prasugrel active metabolite in TRITON-TIMI 38.

Serial pharmacokinetic (PK) sampling in 1159 patients from TRITON-TIMI 38 was undertaken. A multilinear regression model was used to quantitatively predict prasugrel's active metabolite (Pras-AM) concentrations from its 2 downstream inactive metabolites. Population-based methods were then applied to Pras-AM concentration data to characterize the PK. The potential influence of body weight, body mass index, age, sex, renal function, diabetes, tobacco use, and other disease status on Bayesian estimates of Pras-AM exposures was assessed. The PK of Pras-AM was adequately described by a multicompartmental model and consistent with results from previous studies. The systemic exposure of prasugrel was not appreciably affected by body mass index, gender, diabetes, smoking, and renal impairment. Pras-AM mean exposure in patients weighing <60 kg (4.1%) was 30% (90% confidence interval [CI] 1.16-1.45) higher than exposure in patients > or =60 kg. Mean Pras-AM exposures for patients > or =75 years (10.5%) were 19% (90% CI: 1.11-1.28) higher compared with patients <75 years.

Inhibition of platelet aggregation with prasugrel and clopidogrel: an integrated analysis in 846 subjects.

This integrated analysis compared speed of onset, level of platelet inhibition, and response variability to prasugrel and clopidogrel in healthy subjects and in patients with stable coronary artery disease with data pooled from 24 clinical pharmacology studies. Data from subjects (N = 846) were categorized into the following treatment groups: prasugrel 60 mg loading dose (LD)/10 mg maintenance dose (MD), clopidogrel 300 mg LD/75 mg MD, or clopidogrel 600 mg LD/75 mg MDs. Maximum platelet aggregation (MPA) and inhibition of platelet aggregation (IPA) to 5 and 20 muM ADP were assessed by turbidimetric aggregometry. A linear mixed-effect model compared the MPA and IPA between treatments over time points evaluated in the integrated database, and covariates affecting platelet inhibition were identified. Prasugrel 60 mg LD resulted in faster onset, greater magnitude, and more consistent levels of inhibition of platelet function compared to either clopidogrel 300 mg or 600 mg LDs. Greater and more consistent levels of platelet inhibition were observed with the prasugrel 10 mg MD compared to the clopidogrel 75 mg MD. This integrated analysis confirms the findings of earlier individual studies, that prasugrel achieves faster onset of greater extent and more consistent platelet inhibition compared to the approved and higher loading doses of clopidogrel. Gender, race, body weight, and age were identified as statistically significant covariates impacting platelet inhibition.

Prasugrel, a new thienopyridine antiplatelet drug, weakly inhibits cytochrome P450 2B6 in humans.

Prasugrel, a thienopyridine prodrug, is hydrolyzed in vivo by esterases to a thiolactone followed by a single cytochrome P450 (CYP)-dependent step to an active metabolite that is a potent inhibitor of adenosine diphosphate-induced platelet aggregation. This open-label, multiple-dose, 2-period, fixed-sequence study assessed CYP2B6 inhibition by prasugrel using bupropion as a probe substrate, where its active metabolite, hydroxybupropion, is almost exclusively formed by CYP2B6. Thirty healthy subjects received a single 150-mg oral dose of sustained-release bupropion. After a 7-day washout, a 60-mg prasugrel loading dose, followed by a 10-mg daily maintenance dose for 10 days, was administered. Bupropion (150 mg) was given with prasugrel on day 7 of this phase. Prasugrel weakly inhibited CYP2B6 activity as it increased bupropion Cmax and AUC0-infinity by 14% and 18%, respectively, and decreased hydroxybupropion Cmax and AUC0-infinity by 32% and 23%. These results are consistent with patients receiving prasugrel not requiring dose adjustments when treated with drugs primarily metabolized by CYP2B6.

Effect of atorvastatin on the pharmacokinetics and pharmacodynamics of prasugrel and clopidogrel in healthy subjects.

STUDY OBJECTIVE: To investigate the potential effect of atorvastatin 80 mg/day on the pharmacokinetics and pharmacodynamics of the thienopyridines prasugrel and clopidogrel. DESIGN: Open-label, randomized, crossover, two-arm, parallel-group study. SETTING: Single clinical research center in the United Kingdom. PARTICIPANTS: Sixty-nine healthy men aged 18-60 years. Intervention. Subjects received either a loading dose of prasugrel 60 mg followed by a maintenance dose of 10 mg/day or a loading dose of clopidogrel 300 mg followed by 75 mg/day. The drug was given as monotherapy for 10 days, and after a 6-day run-in period with atorvastatin 80 mg/day, the same dosage of atorvastatin was continued with the respective thienopyridine for 10 days. A 14-day washout period separated the treatment regimens. MEASUREMENTS AND MAIN RESULTS: Blood samples were collected before and at various time points after dosing on days 1 and 11 for determination of plasma concentrations of metabolites and for measurement of platelet aggregation induced by adenosine 5'-diphosphate 20 microM and vasodilator-stimulated phosphoprotein (VASP). Coadministration of atorvastatin did not alter exposure to active metabolites of prasugrel or clopidogrel after the loading dose and thus did not alter inhibition of platelet aggregation (IPA). During maintenance dosing, atorvastatin administration resulted in 17% and 28% increases in the area under the plasma concentration-time curve (AUC) values of prasugrel's and clopidogrel's active metabolites, respectively. These small changes in AUC did not result in a significant change in IPA response to prasugrel but did result in a significant increase in IPA during clopidogrel maintenance dosing at some, but not all, of the time points on day 11. Coadministration of atorvastatin with either prasugrel or clopidogrel had no effect on VASP phosphorylation relative to the thienopyridine alone after the loading dose. CONCLUSION: Coadministration of atorvastatin 80 mg/day with prasugrel or clopidogrel did not negatively affect the antiplatelet response to either drug after a loading dose or during maintenance dosing. The lack of a clinically meaningful effect of high-dose atorvastatin on the pharmacodynamic response to prasugrel after the loading or maintenance dose indicates that no dosage adjustment should be necessary in patients receiving these drugs concomitantly.

Effect of potent CYP2D6 inhibition by paroxetine on atomoxetine pharmacokinetics.

The purpose of this study was to characterize the effect of potent CYP2D6 inhibition byparoxetine on atomoxetine disposition in extensive metabolizers. This was a single-blind, two-period, sequential studyin 22 healthy individuals. In period 1, 20 mg atomoxetine bid was administered to steady state. In period 2, 20 mg paroxetine was administered qd for 17 days. On days 12 through 17, 20 mg atomoxetine bid were coadministered. Plasma pharmacokinetics of atomoxetine, 4-hydroxyatomoxetine, and N-desmethylatomoxetine was determined at steady state in each treatment period. Plasma pharmacokinetics of paroxetine were determined after the 11th and 17th doses. Paroxetine increased C(ss,max), AUC0-12, and t1/2 of atomoxetine by approximately 3.5-, 6.5-, and 2.5-fold, respectively. After coadministration with paroxetine, increases in N-desmethylatomoxetine and decreases in 4-hydroxyatomoxetine concentrations were observed. No changes in paroxetine pharmacokinetics were observed after coadministration with atomoxetine. It was concluded that inhibition of CYP2D6 by paroxetine markedly affected atomoxetine disposition, resulting in pharmacokinetics similar to poor metabolizers of CYP2D6 substrates.

Relationship between exposure to prasugrel active metabolite and clinical outcomes in the TRITON-TIMI 38 substudy.

In TRITON-TIMI 38, levels of the prasugrel active metabolite (pras-AM) were measured in a population pharmacokinetic substudy that characterized the intrinsic and extrinsic factors influencing exposure. Higher exposure to the pras-AM was observed in low-weight or very elderly patients. The authors hypothesized that this higher exposure might explain the higher risk of non-coronary artery bypass graft (CABG)-related TIMI-related bleeding observed in these 2 patient populations. The relationship between estimated exposure to the pras-AM and clinical outcomes was assessed in 1159 prasugrel-treated patients enrolled in the substudy using multivariable logistic regression analysis. There was no relationship between pras-AM exposure and efficacy through 3 days or after 3 days. Higher estimated pras-AM exposure was associated with a higher incidence of non-CABG-related TIMI major or minor bleeding after 3 days (P < .05) but not through 3 days from start of study drug. Factors associated with increased risk for non-CABG-related TIMI bleeding (≥75 years and <60 kg) also identified subgroups with higher exposure to the pras-AM. Within low body weight and very elderly subgroups, bleeding was largely confined to patients having the highest exposure to the pras-AM, indicating that a prasugrel lower dose in these subgroups may reduce the risk of bleeding while maintaining efficacy.

Integrated analysis of pharmacokinetic data across multiple clinical pharmacology studies of prasugrel, a new thienopyridine antiplatelet agent.

An integrated analysis of pharmacokinetic (PK) parameter estimates for prasugrel, from 16 phase I clinical pharmacology studies, consolidated exposure estimates from 506 healthy male and female participants and evaluated the effect of specific intrinsic and extrinsic factors on exposure to prasugrel's active metabolite (AM, R-138727). A linear mixed effect model was fitted with study and subject nested within study as random effects and subject factors as fixed effects. Prasugrel AM exposure was similar in males and females, in participants <65 years and ≥65 years, in smokers and nonsmokers, in drinkers and nondrinkers of alcohol, and in Asians, Caucasians, and participants of African and Hispanic descent. Prasugrel AM exposure increased as body weight decreased and was 40% higher in participants <60 kg than in participants ≥60 kg. Exposure in Asians was 40% higher than that in Caucasians, but this difference could be explained by the lower overall weight of the Asian participants and a disproportionately large difference between ethnic groups in lighter participants, especially those <60 kg. These results characterize prasugrel's PK across a range of studies and highlight body weight as the most influential covariate on prasugrel AM exposure, with implications for prasugrel maintenance dosing in clinical practice.

Effect of age on the pharmacokinetics and pharmacodynamics of prasugrel during multiple dosing: an open-label, single-sequence, clinical trial.

BACKGROUND: A substantial portion of patients at risk for acute coronary syndrome (ACS) are >65 years old. Prasugrel is a novel antiplatelet agent approved for the treatment of ACS patients undergoing percutaneous coronary intervention, and will be used in this population. OBJECTIVE: This study assessed the effect of age >or=65 years on the pharmacokinetics (PK) and pharmacodynamics (PD) of the active metabolite (R-138727) of prasugrel in healthy subjects taking aspirin (acetylsalicylic acid). METHODS: This was an open-label, single-sequence trial conducted in a single clinical research centre in the UK. A total of 17 subjects aged 65-80 years and 15 subjects aged 20-39 years received a prasugrel 5-mg once-daily maintenance dose for 10 days followed by 10-mg once daily maintenance doses for 10 days. All subjects also received aspirin 75 mg daily. Serial blood samples were collected pre-dose and at various times post-dose for measurement of the active metabolite of prasugrel in plasma on days 10 and 20, following the last 5- and 10-mg prasugrel dose, respectively. PK parameters of the active metabolite of prasugrel included area under the plasma concentration-time curve (AUC) from time zero to the time of the last quantifiable concentration (AUC(last)), maximum plasma concentration (C(max)) and time to C(max) (t(max)). Maximal platelet aggregation (MPA), assessed by light transmission aggregometry using adenosine diphosphate (ADP) 20 micromol/L, was assessed at baseline and on day 10 (5-mg maintenance dose) and day 20 (10-mg maintenance dose). Bleeding times (BTs) were determined on days -5, 1, 10, 11, 20 and 21 using a modified Ivy technique. RESULTS: AUC(last) did not differ significantly between age groups. The steady-state trough MPA to ADP 20 micromol/L during 10-mg maintenance dosing was 30.6% and 26.6% in elderly and young subjects, respectively. Mean MPA was consistently higher in elderly subjects compared with young subjects; however, differences were generally less than ten percentage points. BTs did not differ between the two populations during 5-mg maintenance dosing; however, during 10-mg maintenance dosing, BTs were up to 67% longer in young compared with elderly subjects. A higher frequency of minor bleeding during 10-mg maintenance dosing was observed in elderly subjects compared with young subjects. CONCLUSIONS: These data indicate that prasugrel PK and MPA were similar in healthy subjects regardless of age. Compared with younger subjects, elderly subjects had shorter BTs but a greater frequency of mild bleeding-related adverse events.

Effect of ranitidine on the pharmacokinetics and pharmacodynamics of prasugrel and clopidogrel.

OBJECTIVE: Clopidogrel is an oral thienopyridine antiplatelet agent indicated for the treatment of atherothrombotic events in patients with acute coronary syndrome (ACS). Prasugrel, a novel oral thienopyridine, is under investigation for the reduction of atherothrombotic events in patients with ACS undergoing percutaneous coronary intervention. Prasugrel's solubility decreases with increasing pH, suggesting that concomitantly-administered medications that increase gastric pH may lower the rate and/or extent of prasugrel absorption. This study evaluated the influence of ranitidine coadministration on the pharmacokinetics and pharmacodynamics of the respective active metabolite of prasugrel and clopidogrel. RESEARCH DESIGN AND METHODS: In this open-label, two-period, two-treatment, crossover study, 47 healthy male subjects were randomized to one of two study arms, receiving either prasugrel (60-mg loading dose [LD], 10-mg maintenance dose [MD] for 7 days; n = 23) or clopidogrel (600-mg LD, 75-mg MD for 7 days; n = 24). In one treatment period, subjects received prasugrel or clopidogrel alone, and in the alternate period received the same thienopyridine with ranitidine (150 mg twice daily, starting 1 day before the LD). Pharmacokinetic parameter estimates (AUC(0-t last), C(max), and t(max)) and inhibition of platelet aggregation (IPA) by light transmission aggregometry were assessed at multiple time points after the LD and final MD. RESULTS: Ranitidine had no clinically significant effect on the area under the plasma-concentration-time curve (AUC) and did not affect the time to C(max) (t(max)) for active metabolites of either prasugrel or clopidogrel. It reduced the geometric mean maximum concentrations of active metabolite (C(max)) after a prasugrel and clopidogrel LD by 14% and 10%, respectively, but these differences were not statistically significant. When coadministered with a 60-mg prasugrel LD, ranitidine did not affect the time to, or magnitude of, peak IPA, but did result in a modest reduction at 0.5 h from 67.4 to 55.1% (p < 0.001). Ranitidine did not affect prasugrel IPA during MD. For clopidogrel, IPA was not affected by ranitidine. Prasugrel and clopidogrel were both well-tolerated, with/without ranitidine. CONCLUSIONS: Results from this study suggest that there is no significant drug-drug interaction between oral ranitidine therapy and concomitantly-administered prasugrel or clopidogrel.

Population pharmacokinetics and pharmacodynamics of prasugrel and clopidogrel in aspirin-treated patients with stable coronary artery disease.

The aim of the current analysis was to characterize the population PK of prasugrel and clopidogrel metabolites, the resulting PD response, and identification of covariates for key PK/PD parameters. Aspirin-treated subjects with coronary artery disease were randomized to double-blind treatment with clopidogrel 600 mg loading dose (LD) followed by daily 75 mg maintenance dose (MD) or prasugrel 60 mg LD and daily 10 mg MD for 28 days. Plasma concentrations of prasugrel active metabolite (Pras-AM) and prasugrel's inactive thiolactone metabolite (Pras-thiolactone) were simultaneously fit to a multicompartmental model; a similar model adequately described clopidogrel's active metabolite (Clop-AM) PK. By linking to the PK model through the active metabolite concentrations, the PK/PD model characterized the irreversible inhibition of platelet aggregation through a sigmoidal Emax model. Although dose, sex, and weight were identified as significant covariates in the prasugrel PK model, only the effect of body weight produced significant changes in Pras-AM exposure. Generally, these factors resulted in only minor changes in Pras-AM exposures such that, overall, the change in the resulting maximal platelet aggregation (MPA) was predicted to be < or =10% points on average. The clopidogrel PK model included dose as a covariate indicating that a significantly less-than-proportional increase in Clop-AM exposure is expected over the dose range of 75-600 mg, thus, the model-predicted PD response is lower than might be anticipated given an 8-fold difference in dose and lower than that typically achieved following prasugrel 60 mg LD. The greater PD response with prasugrel compared with clopidogrel was accounted for by greater conversion of dose to active metabolite.

Increased active metabolite formation explains the greater platelet inhibition with prasugrel compared to high-dose clopidogrel.

Prasugrel pharmacodynamics and pharmacokinetics after a 60-mg loading dose (LD) and daily 10-mg maintenance doses (MD) were compared in a 3-way crossover study to clopidogrel 600-mg/75-mg and 300-mg/75-mg LD/MD in 41 healthy, aspirin-free subjects. Each LD was followed by 7 days of daily MD and a 14-day washout period. Inhibition of platelet aggregation (IPA) was assessed by turbidometric aggregometry (20 and 5 microM ADP). Prasugrel 60-mg achieved higher mean IPA (54%) 30 minutes post-LD than clopidogrel 300-mg (3%) or 600-mg (6%) (P < 0.001) and greater IPA by 1 hour (82%) and 2 hours (91%) than the 6-hour IPA for clopidogrel 300-mg (51%) or 600-mg (69%) (P < 0.01). During MD, IPA for prasugrel 10-mg (78%) exceeded that of clopidogrel (300-mg/75-mg, 56%; 600-mg/75-mg, 52%; P < 0.001). Active metabolite area under the concentration-time curve (AUC0-tlast) after prasugrel 60-mg (594 ng.hr/mL) was 2.2 times that after clopidogrel 600-mg. Prasugrel active metabolite AUC0-tlast was consistent with dose-proportionality from 10-mg to 60-mg, while clopidogrel active metabolite AUC0-tlast exhibited saturable absorption and/or metabolism. In conclusion, greater exposure to prasugrel's active metabolite results in faster onset, higher levels, and less variability of platelet inhibition compared with high-dose clopidogrel in healthy subjects.

Mechanism-based inactivation of CYP3A by HIV protease inhibitors.

Human immunodeficiency virus (HIV) protease inhibitors (PIs) are inhibitors of CYP3A enzymes, but the mechanism is poorly defined. In this study, time- and concentration-dependent decreases in activity as defined by maximum rate of inactivation (k(inact)) and inhibitor concentration that gives 50% maximal inactivation (K(I)) of CYP3A by amprenavir, indinavir, lopinavir, nelfinavir, ritonavir, and saquinavir were quantified using testosterone 6beta-hydroxylation as a marker for CYP3A activity with recombinant CYP3A4(+b(5)), recombinant CYP3A5, and pooled human liver microsomes (HLMs). All the PIs, except indinavir, displayed inactivation with CYP3A4(+b(5)) and HLMs. Ritonavir was the most potent (K(I) = 0.10 and 0.17 microM) and demonstrated high k(inact) values (0.32 and 0.40 min(-1)) with both CYP3A4(+b(5)) and HLMs. Ritonavir was not significantly depleted by high-affinity binding with CYP3A4(+b(5)) and confirmed that estimation of reversible inhibition was confounded with irreversible inhibition. For CYP3A5, nelfinavir exhibited the highest k(inact) (0.47 min(-1)), but ritonavir was the most potent (K(I) = 0.12 microM). Saquinavir and indinavir did not show time- and concentration-dependent decreases in activity with CYP3A5. Spectrophototmetrically determined metabolic intermediate complex formation was observed for all of the PIs with CYP3A4(+b(5)), except for lopinavir and saquinavir. The addition of nucleophilic and free aldehyde trapping agents and free iron and reactive oxygen species scavengers did not prevent inactivation of CYP3A4(+b(5)) by ritonavir, amprenavir, or nelfinavir, but glutathione decreased the inactivation by saquinavir (17%) and catalase decreased the inactivation by lopinavir (39%). In conclusion, all the PIs exhibited mechanism-based inactivation, and predictions of the extent and time course of drug interactions with PIs could be underestimated if based solely on reversible inhibition.