Model-based approach to sampling optimization in studies of antibacterial drugs for infants and young children.

Clinical trials for pediatric indications and new pediatric drugs face challenges, including the limited blood volume due to the patients' small bodies. In Japan, the Evaluation Committee on Unapproved or Off-labeled Drugs with High Medical Needs has discussed the necessity of pediatric indications against the background of a lack of Japanese pediatric data. The limited treatment options regarding antibiotics for pediatric patients are associated with the emergence of antibiotic-resistant bacteria. Regulatory guidelines promote the use of model-based drug development to reduce practical and ethical constraints for pediatric patients. Sampling optimization is one of the key study designs for pediatric drug development. In this simulation study, we evaluated the precision of the empirical Bayes estimates of pharmacokinetic (PK) parameters based on the sampling times optimized by published pediatric population PK models. We selected three previous PK studies of cefepime and ciprofloxacin in infants and young children as paradigms. The number of sampling times was reduced from original full sampling times to two to four sampling times based on the Fisher information matrix. We observed that the precision of empirical Bayes estimates of the key PK parameters and the predicted efficacy based on the reduced sampling times were generally comparable to those based on the original full sampling times. The model-based approach to sampling optimization provided a maximization of PK information with a minimum burden on infants and young children for the future development of pediatric drugs.

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.

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 pharmacokinetics of tazobactam/ceftolozane in Japanese patients with complicated urinary tract infection and complicated intra-abdominal infection.

Tazobactam/ceftolozane is a combination of a ß-lactamase inhibitor and a cephalosporin antibiotic, with recommended dosage for patients with normal renal function of tazobactam 0.5 g/ceftolozane 1 g administered as a 1-h intravenous infusion every 8 h. The doses in patients with moderate and severe renal impairment are recommended to be reduced by half and 1/4th, respectively. The dose in patients undergoing dialysis is a single loading dose of 750 mg followed after 8 h by a 150 mg maintenance dose. In order to evaluate pharmacokinetics (PK) in Japanese patients, individual Bayes PK parameters were derived using the previously developed population PK models. Furthermore, attainment of PK/pharmacodynamic target in Japanese patients was calculated to confirm the recommended dosage. Based on PK data from 200 Japanese patients in the phase 3 studies, including patients with mild and moderate renal impairment, individual tazobactam/ceftolozane PK parameters were derived. No clinically relevant difference was observed in tazobactam/ceftolozane exposures between Japanese and non-Japanese patients. All Japanese patients achieved a target percent of time that free ceftolozane concentrations are above the minimum inhibitory concentration (MIC) of 30% for MICs of up to 8 µg/mL. Also for tazobactam, all Japanese patients achieved a target percent of time that the free tazobactam concentration exceeds a threshold concentration (1 µg/mL) of 20%. The results suggest that the doses will be efficacious in the Japanese population. The results indicate that the recommended dose in patients with normal renal function or renal impairment is appropriate in Japanese patients.

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.

Population Pharmacodynamic Analysis of Uric Acid-Lowering Effects of Febuxostat Based on Electronic Medical Records in Two Hospitals.

The aim of this study was to develop a population pharmacodynamic (PPD) model to describe uric acid (UA)-lowering effects in patients treated with febuxostat based on electronic medical records in 2 independent hospitals (university and city hospitals). Interhospital differences in the PPD model were also evaluated. We conducted the following 2 approaches to build the PPD models. A PPD model was developed separately using individual hospital data, and structural models and covariates between the two hospitals were compared (approach A). Another PPD model was developed using all available data from both hospitals, and differences between the 2 hospitals were evaluated by performing a covariate analysis on all PPD parameters (approach B). PPD analyses were performed by NONMEM using data from 358 patients. In both approaches, one indirect response model was established. In approach A, 2 diuretics (loops and thiazides) and renal function tests (Scr or BUN) were selected as covariates for the UA baseline level (serum UA levels just before the febuxostat treatment), whereas 2 diuretics and BUN were selected in approach B. A covariate analysis indicated that loops and thiazides increased UA baseline levels by 7%-14% and 6%-11%, respectively. In approach B, "hospital" was identified as a significant covariate for the UA baseline level; the baseline level was 7% higher in the city hospital. A PPD analysis may provide a precise description of the time course of the UA-lowering effects of febuxostat and quantitatively detect an interhospital difference in the UA baseline level.

Population pharmacodynamic analysis of hemoglobin A1c-lowering effects by adding treatment of DPP-4 inhibitors (sitagliptin) in type 2 diabetes mellitus patients based on electronic medical records.

AIM: To develop a population pharmacodynamic (PPD) model describing the time course for the hemoglobin A1c (HbA1c)-lowering effects of adding treatment of DPP-4 inhibitors and to assess the efficacy of combination therapy in type 2 diabetes mellitus patients based on electronic medical records. METHODS: Information on patients was collected retrospectively from electronic medical records. Of the 4 DPP-4 inhibitors used, we focused on sitagliptin as it had the best time-response relationships. A physiological indirect response model was developed to describe changes in HbA1c levels. RESULTS: An indirect response model, based on the 1300 HbA1c levels of 160 patients, described the time course for the HbA1c-lowering effects of adding sitagliptin. The combination with pioglitazone decreased the HbA1c synthesis rate by 7.74% relative to without pioglitazone. Bayesian forecasting based on the final PDD model using the first two HbA1c observations, before and within 30days after the addition of sitagliptin, gave a precise prediction of HbA1c-lowering effects individually. CONCLUSIONS: Our PPD model quantitatively described the beneficial effects of combination therapy with pioglitazone and sitagliptin. The proposal methodology is also expected to be applicable to other medicines based on electronic medical records in clinical practice.

Population pharmacodynamic analysis of LDL-cholesterol lowering effects by statins and co-medications based on electronic medical records.

AIMS: HMG-CoA reductase inhibitors are available for use in low density lipoprotein-cholesterol (LDL-C) lowering therapy. The purposes of this study were to develop a population pharmacodynamic (PPD) model to describe the time course for the LDL-C lowering effects of statins and assess the efficacy of combination therapy based on electronic medical records. METHODS: Patient backgrounds, laboratory tests and prescribed drugs were collected retrospectively from electronic medical records. Patients who received atorvastatin, pitavastatin or rosuvastatin were enrolled. A physiological indirect response model was used to describe the changes observed in LDL-C concentrations. The PPD analysis was performed using nonmem 7.2.0 with the first order conditional estimation method with interaction (FOCE-INTER). RESULTS: An indirect response Imax model, based on the 2863 LDL-C concentrations of 378 patients, successfully and quantitatively described the time course for the LDL-C lowering effects of three statins. The combination of ezetimibe, a cholesterol absorption inhibitor, decreased the LDL synthesis rate (Kin ) by 10.9%. A simulation indicated that the combined treatment of ezetimibe with rosuvastatin (2.5 mg day(-1) ) led to superior clinical responses than those with high doses of rosuvastatin (5.0 mg day(-1) ) monotherapy, even in patients with higher baseline LDL-C concentrations prior to the treatment. CONCLUSIONS: A newly constructed PPD model supported previous evidence for the beneficial effects of ezetimibe combined with rosuvastatin. In addition, the established framework is expected to be applicable to other drugs without pharmacokinetic data in clinical practice.