Nidal Al-Huniti

Multiple-dose pharmacodynamics and pharmacokinetics of anacetrapib, a potent cholesteryl ester transfer protein (CETP) inhibitor, in healthy subjects.

Cholesteryl ester transfer protein (CETP) is a plasma protein that catalyzes the heteroexchange of cholesteryl esters from high‐density lipoprotein (HDL) and triglycerides to apolipoprotein B–containing lipoproteins, especially very low–density lipoproteins (LDL‐C). 1, 2

Single‐dose pharmacokinetics and pharmacodynamics of anacetrapib, a potent cholesteryl ester transfer protein (CETP) inhibitor, in healthy subjects

AIMS Anacetrapib is an orally active and potent inhibitor of CETP in development for the treatment of dyslipidaemia. These studies endeavoured to establish the safety, tolerability, pharmacokinetics and pharmacodynamics of rising single doses of anacetrapib, administered in fasted or fed conditions, and to preliminarily assess the effect of food, age, gender and obesity on the single-dose pharmacokinetics and pharmacodynamics of anacetrapib. METHODS Safety, tolerability, anacetrapib concentrations and CETP activity were evaluated. RESULTS Anacetrapib was rapidly absorbed, with peak concentrations occurring at approximately 4 h post-dose and an apparent terminal half-life ranging from approximately 9 to 62 h in the fasted state and from approximately 42 to approximately 83 h in the fed state. Plasma AUC and C(max) appeared to increase in a less than approximately dose-dependent manner in the fasted state, with an apparent plateau in absorption at higher doses. Single doses of anacetrapib markedly and dose-dependently inhibited serum CETP activity with peak effects of approximately 90% inhibition at t(max) and approximately 58% inhibition at 24 h post-dose. An E(max) model best described the plasma anacetrapib concentration vs CETP activity relationship with an EC(50) of approximately 22 nm. Food increased exposure to anacetrapib; up to approximately two-three-fold with a low-fat meal and by up to approximately six-eight fold with a high-fat meal. Anacetrapib pharmacokinetics and pharmacodynamics were similar in elderly vs young adults, women vs men, and obese vs non-obese young adults. Anacetrapib was well tolerated and was not associated with any meaningful increase in blood pressure. CONCLUSIONS Whereas food increased exposure to anacetrapib significantly, age, gender and obese status did not meaningfully influence anacetrapib pharmacokinetics and pharmacodynamics.

Simulation and Prediction of the Drug-Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling

Naloxegol, a peripherally acting μ‐opioid receptor antagonist for the treatment of opioid‐induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P‐glycoprotein (P‐gp) transporter. By integrating in silico, preclinical, and clinical pharmacokinetic (PK) findings, minimal and full physiologically based pharmacokinetic (PBPK) models were developed to predict the drug‐drug interaction (DDI) potential for naloxegol. The models reasonably predicted the observed changes in naloxegol exposure with ketoconazole (increase of 13.1‐fold predicted vs. 12.9‐fold observed), diltiazem (increase of 2.8‐fold predicted vs. 3.4‐fold observed), rifampin (reduction of 76% predicted vs. 89% observed), and quinidine (increase of 1.2‐fold predicted vs. 1.4‐fold observed). The moderate CYP3A4 inducer efavirenz was predicted to reduce naloxegol exposure by ∼50%, whereas weak CYP3A inhibitors were predicted to minimally affect exposure. In summary, the PBPK models reasonably estimated interactions with various CYP3A modulators and can be used to guide dosing in clinical practice when naloxegol is coadministered with such agents.

Population pharmacokinetics of naloxegol in a population of 1247 healthy subjects and patients

AIMS Naloxegol, a polyethylene glycol conjugated derivative of the opioid antagonist naloxone, is in clinical development for treatment of opioid-induced constipation (OIC). The aim of the study was to develop a population pharmacokinetic model describing the concentration vs. time profile of orally administered naloxegol, and determine the impact of pre-specified demographic and clinical factors and concomitant medication on population estimates of apparent clearance (CL/F) and apparent central compartment volume of distribution (Vc /F). METHODS Analysis included 12,844 naloxegol plasma concentrations obtained from 1247 healthy subjects, patients with non-OIC and patients with OIC in 14 phase 1, 2b and 3 clinical studies. Pharmacokinetic analysis used the non-linear mixed effects modelling program. Goodness of fit plots and posterior predictive checks were conducted to confirm concordance with observed data. RESULTS The final model was a two compartment disposition model with dual absorptions, comprising one first order absorption (ka1 4.56 h(-1) ) and one more complex absorption with a transit compartment (ktr 2.78 h(-1) ). Mean (SE) parameter estimates for CL/F and Vc /F, the parameters assessed for covariate effects, were 115 (3.41) l h(-1) and 160 (27.4) l, respectively. Inter-individual variability was 48% and 51%, respectively. Phase of study, gender, race, concomitant strong or moderate CYP3A4 inhibitors, strong CYP3A4 inducers, P-glycoprotein inhibitors or inducers, naloxegol formulation, baseline creatinine clearance and baseline opioid dose had a significant effect on at least one pharmacokinetic parameter. Simulations indicated concomitant strong CYP3A4 inhibitors or inducers had relevant effects on naloxegol exposure. CONCLUSIONS Administration of strong CYP3A4 inhibitors or inducers had a clinically relevant influence on naloxegol pharmacokinetics.

The effect of quinidine, a strong P‐glycoprotein inhibitor, on the pharmacokinetics and central nervous system distribution of naloxegol

Naloxegol is a PEGylated, oral, peripherally acting μ‐opioid receptor antagonist approved in the United States for treatment of opioid‐induced constipation in patients with noncancer pain. Naloxegol is metabolized by CYP3A, and its properties as a substrate for the P‐glycoprotein (PGP) transporter limit its central nervous system (CNS) permeability. This double‐blind, randomized, 2‐part, crossover study in healthy volunteers evaluated the effect of quinidine (600 mg PO), a CYP3A/PGP transporter inhibitor, on the pharmacokinetics and CNS distribution of naloxegol (25 mg PO). In addition, the effects of quinidine on morphine (5 mg/70 kg IV)‐induced miosis and exposure to naloxegol were assessed. Coadministration of quinidine and naloxegol increased naloxegols AUC 1.4‐fold and Cmax 2.5‐fold but did not antagonize morphine‐induced miosis, suggesting that PGP inhibition does not increase the CNS penetration of naloxegol. Naloxegol pharmacokinetics was unaltered by coadministration of morphine and either quinidine or placebo; conversely, pharmacokinetics of morphine and its metabolites (in the presence of quinidine) were unaltered by coadministration of naloxegol. Naloxegol was safe and well tolerated, alone or in combination with quinidine, morphine, or both. The observed increase in exposure to naloxegol in the presence of quinidine is primarily attributed to quinidines properties as a weak CYP3A inhibitor.

Effects of CYP3A Modulators on the Pharmacokinetics of Naloxegol

Naloxegol, a peripherally acting μ‐opioid receptor antagonist, was recently approved in the United States for the treatment of opioid‐induced constipation. This study evaluated the effects of CYP3A inhibition and induction on the pharmacokinetics, safety, and tolerability of naloxegol. Separate open‐label, nonrandomized, fixed‐sequence, 3‐period, 3‐treatment, crossover studies of naloxegol (25 mg by mouth [PO]) in the absence or presence of the inhibitors ketoconazole (400 mg PO) and diltiazem extended release (240 mg PO), or the inducer rifampin (600 mg PO) were conducted in healthy volunteers. Area under the curve (AUC∞) for naloxegol was increased with coadministration of either ketoconazole (12.9‐fold) or diltiazem (3.4‐fold) and decreased by 89% with coadministration of rifampin compared with AUC∞ for naloxegol alone. Naloxegol was generally safe and well tolerated when given alone or coadministered with the respective CYP3A modulators; 1 subject discontinued because of elevations in liver enzymes attributed to rifampin. The exposure of naloxegol was affected substantially by ketoconazole, diltiazem, and rifampin, suggesting that it is a sensitive in vivo substrate of CYP3A4.

Population pharmacokinetics of TC-5214, a nicotinic channel modulator, in phase I and II clinical studies

TC‐5214 (dexmecamylamine) is a nicotinic channel modulator that has previously been evaluated for treatment of major depression disorder (MDD) and is currently being evaluated by Targacept as a treatment for overactive bladder. A comprehensive population pharmacokinetic (POP PK) model of TC‐5214 was developed using nonlinear mixed‐effects modeling of pooled plasma concentration data from 6 early phase I studies in 179 healthy participants or patients with non‐MDD and 1 phase II study in 68 MDD patients. Concentration–time profiles of TC‐5214 after either single or multiple oral doses of TC‐5214 was described by a one‐compartment model with first‐order absorption with lag time and first‐order elimination. Covariate analysis revealed that creatinine clearance was a significant covariate on clearance and that body weight significantly influenced the central volume of distribution. The final model (with identified covariates) was used to simulate steady‐state exposure for patients with impaired renal function. Results from forest plots reveal that patients with moderate to severe renal impairment or end stage renal disease are associated with significantly higher Cssmax and AUC compared to patients with normal renal function. The proposed final POP PK model could be employed in defining a TC‐5214 dosage regimen in patients with impaired renal function.

Evaluation of Aztreonam Dosing Regimens in Patients With Normal and Impaired Renal Function: A Population Pharmacokinetic Modeling and Monte Carlo Simulation Analysis

Aztreonam is a monocyclic β‐lactam antibiotic often used to treat infections caused by Enterobacteriaceae or Pseudomonas aeruginosa. Despite the long history of clinical use, population pharmacokinetic modeling of aztreonam in renally impaired patients is not yet available. The aims of this study were to assess the impact of renal impairment on aztreonam exposure and to evaluate dosing regimens for patients with renal impairment. A population model describing aztreonam pharmacokinetics following intravenous administration was developed using plasma concentrations from 42 healthy volunteers and renally impaired patients from 2 clinical studies. The final pharmacokinetic model was used to predict aztreonam plasma concentrations and evaluate the probability of pharmacodynamic target attainment (PTA) in patients with different levels of renal function. A 2‐compartment model with first‐order elimination adequately described aztreonam pharmacokinetics. The population mean estimates of aztreonam clearance, intercompartmental clearance, volume of distribution of the central compartment, and volume of distribution of the peripheral compartment were 4.93 L/h, 9.26 L/h, 7.43 L, and 6.44 L, respectively. Creatinine clearance and body weight were the most significant variables to explain patient variability in aztreonam clearance and volume of distribution, respectively. Simulations using the final pharmacokinetic model resulted in a clinical susceptibility break point of 4 and 8 mg/L, respectively, based on the clinical use of 1‐ and 2‐g loading doses with the same or reduced maintenance dose every 8 hours for various renal deficiency patients. The population pharmacokinetic modeling and PTA estimation support adequate PTAs (>90% PTA) from the aztreonam label for dose adjustment of aztreonam in patients with moderate and severe renal impairment.

The Identification of Potent, Selective, and Orally Available Inhibitors of Ataxia Telangiectasia Mutated (ATM) Kinase: The Discovery of AZD0156 (8-{6-[3-(Dimethylamino)propoxy]pyridin-3-yl}-3-methyl-1-(tetrahydro-2H-pyran-4-yl)-1,3-dihydro-2H-imidazo[4,5-c]quinolin-2-one)

ATM inhibitors, such as 7, have demonstrated the antitumor potential of ATM inhibition when combined with DNA double-strand break-inducing agents in mouse xenograft models. However, the properties of 7 result in a relatively high predicted clinically efficacious dose. In an attempt to minimize attrition during clinical development, we sought to identify ATM inhibitors with a low predicted clinical dose (<50 mg) and focused on strategies to increase both ATM potency and predicted human pharmacokinetic half-life (predominantly through the increase of volume of distribution). These efforts resulted in the discovery of 64 (AZD0156), an exceptionally potent and selective inhibitor of ATM based on an imidazo[4,5- c]quinolin-2-one core. 64 has good preclinical phamacokinetics, a low predicted clinical dose, and a high maximum absorbable dose. 64 has been shown to potentiate the efficacy of the approved drugs irinotecan and olaparib in disease relevant mouse models and is currently undergoing clinical evaluation with these agents.

Population pharmacokinetic and exposure simulation analysis for cediranib (AZD2171) in pooled Phase I/II studies in patients with cancer

AIMS A population pharmacokinetic (PK) model was developed for cediranib to simulate cediranib exposure for different doses, including comedication with strong uridine glucuronosyl transferase/P-glycoprotein inducers such as rifampicin, in cancer patients. METHODS Plasma concentrations and covariates from 625 cancer patients after single or multiple oral cediranib administrations ranging from 0.5 to 90 mg in 19 Phase I and II studies were included in the analysis. Stepwise covariate modelling was used to develop the population PK model. The final model was used to simulate cediranib exposure in cancer patients to evaluate cediranib target coverage and the need for dose adjustment for covariates or coadministration with rifampicin. RESULTS A two-compartment model with sequential zero- and first-order absorption and first-order elimination adequately described the cediranib concentration-time courses. Body weight and age were identified as having statistically significant impact on cediranib PK, but only <21% impact on AUC and maximum concentrations. Simulated lower bounds of 90% prediction interval or median of unbound cediranib concentrations after cediranib 15 or 20 mg exceeded the IC50 for vascular endothelial growth factor receptors-1, -2 and -3. Exposures of cediranib 20 or 30 mg with coadministration of rifampicin were comparable to those of 15 or 20 mg, respectively, without coadministration. CONCLUSIONS No covariate was identified to require dose adjustment for cediranib. Cediranib exposure following 15 or 20 mg daily dose administration is adequate overall for inhibition of in vitro estimated vascular endothelial growth factor receptor-1, -2 and -3 activities. An increase in cediranib dose may be needed for cediranib coadministered with strong uridine glucuronosyl transferase/P-glycoprotein inducers such as rifampicin.