Differences in Theophylline Clearance Between Patients With Chronic Hepatitis and Those With Liver Cirrhosis.

BACKGROUND: Theophylline, a xanthine derivative drug, is used for the treatment of respiratory diseases, such as asthma, and is primarily eliminated by hepatic metabolism. There is marked interindividual variability in theophylline clearance. Therefore, the aim of this study was to evaluate the influence of chronic hepatitis (CH), liver cirrhosis (LC), and other covariates on theophylline clearance by population pharmacokinetic (PPK) analysis. METHODS: The authors retrospectively obtained 496 trough concentrations of theophylline at steady state from 226 adult patients with bronchial asthma. The liver functions of the patients were classified into 3 categories: normal hepatic function, CH, and LC. The PPK analysis was performed using the NONMEM program. CH, LC, age, smoking status, coadministration of clarithromycin (CAM), and sex were considered as covariates that affected theophylline clearance. RESULTS: Theophylline clearance (CL/F per kg) was significantly influenced by CH, LC, smoking, and CAM. The final model of theophylline clearance was as follows: CL/F (L/h·kg) = 0.0484 × 1.40 × 0.861 × 0.889 × 0.557. Smoking is a well-known factor that markedly enhances CL/F through the induction of CYP1A enzymes, whereas CAM has been reported to inhibit CYP3A4. The final model for hepatic function showed that CL/F in CH and LC patients was 0.043 and 0.027 L/h/kg, respectively, and it was lower than that in patients with normal hepatic function. As theophylline clearance depends on intrinsic hepatic clearance, lower CL/F in patients with LC than in those with CH may be due to a decrease in the metabolic enzymatic capability of LC patients. CONCLUSIONS: Differences exist in theophylline clearance between CH and LC patients as per the PPK analysis.

Efficacy of DPP-4 inhibitors, GLP-1 analogues, and SGLT2 inhibitors as add-ons to metformin monotherapy in T2DM patients: a model-based meta-analysis.

AIMS: The aim of the present study was to quantitate the hypoglycaemic effects of dipeptidyl peptidase-4 inhibitors (DPP-4i), glucagon-like peptide-1 receptor agonists (GLP-1r) and sodium glucose cotransporter 2 inhibitors (SGLT2i) as add-on treatments to metformin monotherapy in patients with type 2 diabetes mellitus (T2DM) using a model-based meta-analysis (MBMA). METHODS: A systematic literature search of public databases was conducted to develop models that describe the time courses of the fasting plasma glucose (FPG)- and haemoglobin A1c (HbA1c)-lowering effects of three antidiabetic classes using NONMEM 7.3.0. RESULTS: Seventy-six publications were eligible for this study, and 873 FPG and 1086 HbA1c values were collected. We developed a physiological indirect response model that described the time courses of FPG and HbA1c and simulated reductions in these values 90 days after the initiation of add-on treatments. FPG and HbA1c reductions with once weekly exenatide, liraglutide and dulaglutide were greater than those with other drugs. Mean changes from baseline FPG and HbA1c with these drugs were as follows: exenatide (-22.5 and -16.6%), liraglutide (-22.1 and -16.3%), and dulaglutide (-19.3 and -14.3%). The hypoglycaemic effects of DPP-4i and SGLT2i were similar. CONCLUSIONS: Once weekly exenatide, liraglutide and dulaglutide provided better hypoglycaemic effects among the antidiabetic drugs analysed. Long-acting GLP-1r appears to be more useful for T2DM patients inadequately controlled with metformin monotherapy.

Population Pharmacokinetic Analysis of Phenytoin After Intravenous Administration of Fosphenytoin in Adult and Elderly Epileptic Patients.

BACKGROUND: Fosphenytoin, the diphosphate ester salt of phenytoin, is widely used to treat status epilepticus. The aim of this study was to develop a population pharmacokinetic (PPK) model to describe serum phenytoin concentrations after the intravenous administration of fosphenytoin in adult and elderly epileptic patients. METHODS: Patient backgrounds, laboratory tests, and prescribed drugs were retrospectively collected from electronic medical records. Patients who received fosphenytoin were enrolled. The PPK analysis was performed using NONMEM 7.3.0 with the first-order conditional estimation method with interaction. Age, sex, laboratory tests, and coadministered drugs were selected as candidates for covariates. Significance levels for forward inclusion and backward elimination were set at 0.05 and 0.01, respectively. The study protocol was approved by the Fukuoka Tokushukai Ethics Committee. RESULTS: A total of 340 serum phenytoin concentrations from 200 patients treated with fosphenytoin were available. The median age and body weight of the population were 71 years and 53.4 kg, respectively. A linear 1-compartment model with the conversion rate of fosphenytoin to phenytoin clearly described the pharmacokinetics of phenytoin after the intravenous administration of fosphenytoin. Age was detected as a covariate of clearance (CL): CL (L/h) = 1.99 × (body weight/53.4) × (age/71). Goodness-of-fit plots revealed the high-predictive performance of the final PPK model, and systematic deviations were not observed. The final model was validated by a prediction-corrected visual predictive check and bootstrap analysis. CONCLUSIONS: We herein developed a PPK model to describe phenytoin concentrations after the intravenous administration of fosphenytoin. Age was identified as a significant covariate for CL.

Effects of magnesium oxide on pharmacokinetics of L-dopa/carbidopa and assessment of pharmacodynamic changes by a model-based simulation.

BACKGROUND: Magnesium oxide (MgO) is often co-prescribed with L-dopa/carbidopa (LDCD) to improve constipation in Parkinson's disease patients. The mixing of L-dopa and MgO has been shown to degrade L-dopa; however, there is no interaction study on humans. We proposed mechanisms for the interaction between LDCD and MgO and conducted pharmacokinetic studies on rats and humans. To assess pharmacodynamic changes with the MgO treatment, we applied a model-based meta-analysis (MBMA). METHODS: The effects of MgO on the stabilities of L-dopa and carbidopa were evaluated in in vitro studies. We conducted pharmacokinetic interaction studies of MgO and LDCD on rats and healthy volunteers. A clinical study was conducted with an open-label, non-randomized, single-arm, and two-phase study. In MBMA, we constructed a population pharmacokinetic/pharmacodynamic model of L-dopa and predicted the effects of the MgO treatment on the pharmacodynamics of L-dopa. RESULTS: In vitro results suggested that carbidopa was unstable under alkaline pH conditions. Reductions in plasma LDCD concentrations were observed after oral-MgO/oral-LDCD, but not in oral-MgO/i.v.-LDCD treatments in rats, suggesting that the gastrointestinal tract is an interaction site. A healthy volunteer study showed that MgO was also associated with significant decreases of 35.3 and 80.9% in the AUC0-12 of L-dopa and carbidopa, respectively. A model-based simulation suggested that the MgO treatment was undesirable for the effectiveness of L-dopa. CONCLUSIONS: This is the first study to show a clear pharmacokinetic interaction between LDCD and MgO in humans. Further investigations to confirm the effects of MgO on the pharmacodynamics of L-dopa are required.

Safety, Tolerability, and Pharmacokinetics of NK-104-NP.

Pulmonary hypertension (PH) is a disease with poor prognosis, caused by the obstruction/stenosis of small pulmonary arteries. Statin is known to have vasodilating and anti-inflammatory property and is considered to be a candidate of therapeutic agents for the treatment of PH, but its efficacy has not been verified in clinical trials. We have formulated pitavastatin incorporating nanoparticles composed of poly (lactic-co-glycolic acid) (NK-104-NP) to improve drug delivery to the pulmonary arteries and evaluated their safety and pharmacokinetics in healthy volunteers. To accomplish this purpose, phase I clinical trials were conducted. In the single intravenous administration regimen, 40 healthy subjects were enrolled and PK (pharmacokinetic) parameters in 4 groups (1, 2, 4, and 8 mg as pitavastatin calcium) were as follows: 1.00 hour after the administration, the plasma concentration of pitavastatin reached Cmax (the maximum drug concentration) in all groups. Cmax, AUC0-t (area under the curve from time 0 to the last measurable concentration) and AUC0-∞ (area under the curve from time 0 extrapolated to infinite time) were increased in a dose-dependent manner. Population pharmacokinetic analysis based on these results indicated no accumulation of pitavastatin after repeated administration of NK-104-NP for 7 days. In this 7-day administration trial, the mean Cmax and AUC0-∞ of pitavastatin were not significantly different between days 1 and 7, suggesting that pitavastatin is unlikely to accumulate after repeated administration. In these trials, three adverse events (AEs) were reported, but they were resolved without any complications and judged to have no causal relationships with NK-104-NP. These results indicate that the innovative nanotechnology-based medicine NK-104-NP exhibited dose-dependent pharmacokinetics and was well tolerated with no significant AEs in healthy volunteers.

Effect of OATP1B1 genotypes on plasma concentrations of endogenous OATP1B1 substrates and drugs, and their association in healthy volunteers.

This study aimed to elucidate the impact of OATP1B1 genotype (*1b/*1b, *1b/*15, and *15/*15) on plasma concentrations of endogenous OATP1B1 substrates. Healthy volunteers with OATP1B1 *1b/*1b (n = 10), *1b/*15 (n = 7), or *15/*15 (n = 2) received oral administration of a cocktail of statins (atorvastatin, pitavastatin, rosuvastatin, and fluvastatin). Mean area under the plasma concentration of atorvastatin, pitavastatin, and rosuvastatin in OATP1B1 *15/*15 were 2.2, 1.7 and 1.58-times greater than the corresponding values in OATP1B1 *1b/*1b, respectively, whereas that of fluvastatin was identical to those in other OATP1B1 genotypes. OATP1B1 *15/*15 also showed higher mean plasma concentrations of OATP1B1 endogenous substrates compared with the other OATP1B1 genotypes, such as coproporphyrin I, glycochenodeoxycholate sulfate (GCDCA-S), lithocholate sulfate (LCA-S), glycolithocholate sulfate (GLCA-S) and taurolithocholate sulfate (TLCA-S), but not total or direct bilirubin, chenodeoxycholate-24-glucuronide, or ω-dicarboxylic long-chain fatty acids. Area under the plasma concentration-time curves of plasma coproporphyrin I and GLCA-S discriminated OATP1B1 genotype *15/*15 from the other genotypes. In combination with previously published clinical studies, these results support the notion that coproporphyrin I, and GLCA-S and GCDCA-S could be a surrogate probe for assessing human in vivo OATP1B1 activities.

Characterization of changes in HbA1c in patients with and without secondary failure after metformin treatments by a population pharmacodynamic analysis using mixture models.

The objective of the present study was to develop a population pharmacodynamic (PPD) model to describe the glycated hemoglobin (HbA1c)-lowering effects of metformin in type 2 diabetes mellitus patients with and without secondary failure and to characterize changes in HbA1c levels in the two subpopulations using a mixture model. Information on patients was collected retrospectively from electronic medical records. In this study, the mixture model was used to characterize the bimodal effects of metformin. A PPD analysis was performed using NONMEM 7.3.0. A physiological indirect response model, based on 829 HbA1c levels of 69 patients, described the time course for the HbA1c-lowering effects of metformin. Evidence for the different effectiveness of metformin subpopulations was provided using the mixture model. In the final PPD model, the inhibition effect was constant over a study duration in a patient subpopulation without secondary failure. In contrast, the inhibition effect decreased as a function of time after start of metformin treatment in a subpopulation with secondary failure. These results indicated that HbA1c improvements appeared to deteriorate over time in patients with secondary failure. In a PPD analysis of metformin, it was possible to assign patients with secondary failure using the mixture model.

Small-Dosing Clinical Study: Pharmacokinetic, Pharmacogenomic (SLCO2B1 and ABCG2), and Interaction (Atorvastatin and Grapefruit Juice) Profiles of 5 Probes for OATP2B1 and BCRP.

The aims of this study were (1) to investigate the effects of atorvastatin (10 mg, therapeutic dose) and grapefruit juice (GFJ), inhibitors of OATP2B1, on the pharmacokinetics of substrates for OATP2B1 and BCRP under oral small-dosing conditions (300 µg sulfasalazine, 250 µg rosuvastatin, 300 µg glibenclamide, 1200 µg celiprolol, and 600 µg sumatriptan), and (2) to evaluate the contribution of SLCO2B1*3 and ABCG2 c.421C>A polymorphisms to the pharmacokinetics of the 5 test drugs in 23 healthy volunteers. In the 3 phases, the test drugs were administered to volunteers with either water (control phase), atorvastatin, or GFJ. GFJ but not atorvastatin reduced the exposure of the test drugs significantly more than the control phase, suggesting that all 5 test drugs are substrates for OATP2B1. The SLCO2B1*3 genotype had no effect on the pharmacokinetics of the test drugs. In contrast, the exposure of sulfasalazine and rosuvastatin was significantly higher in ABCG2 421C/A than in ABCG2 421C/C individuals at all 3 phases, even under small-dosing conditions.