Comparison of the predictive accuracy of the physiologically based pharmacokinetic (PBPK) model and population pharmacokinetic (PPK) model of vancomycin in Japanese patients with MRSA infection.

INTRODUCTION: The latest therapeutic drug monitoring guidelines for vancomycin (VCM) recommend that area under the concentration-time curve is estimated based on model-informed precision dosing and used to evaluate efficacy and safety. Therefore, we predicted VCM concentrations in individual methicillin-resistant Staphylococcus aureus-infected patients using existing a physiologically based pharmacokinetic (PBPK) model and 1- and 2-compartment population pharmacokinetic (PPK) models and confirmed and verified the accuracy of the PBPK model in estimating VCM concentrations with the PPK model. METHODS: The subjects of the study are 20 patients, and the predicted concentrations were evaluated by comparing the observed and predicted trough and peak values of VCM concentrations for individual patients. RESULTS: The results showed good correlation between the observed and predicted trough and peak concentrations of VCM was observed generally in the PBPK model, R2 values of 0.72, 0.62, and 0.40 with trough values of 0.49, 0.40, and 0.34 with peak values for PBPK model, 1-compartment, and 2-compartment model, respectively. CONCLUSIONS: Although the performance of the PBPK model is not as predictive as the PPK model, generally similar predictive trends were obtained, suggesting that it may be a valuable tool for rapid and accurate prediction of AUC for VCM.

Population Pharmacokinetic Model for Unbound Concentrations of Daptomycin in Patients with MRSA Including Patients Undergoing Hemodialysis.

BACKGROUND AND OBJECTIVE: Unbound daptomycin concentrations are responsible for pharmacologically beneficial and adverse effects, although most previous reports have been limited to the use of total concentrations. We developed a population pharmacokinetic model to predict both total and unbound daptomycin concentrations. METHODS: Clinical data were collected from 58 patients with methicillin-resistant Staphylococcus aureus including patients undergoing hemodialysis. A total of 339 serum total and 329 unbound daptomycin concentrations were used for model construction. RESULTS: Total and unbound daptomycin concentration was explained by a model that assumed first-order distribution with two compartments, and first-order elimination. Normal fat body mass was identified as covariates. Renal function was incorporated as a linear function of renal clearance and independent non-renal clearance. The unbound fraction was estimated to be 0.066 with a standard albumin of 45 g/L and standard creatinine clearance of 100 mL/min. Simulated unbound daptomycin concentration was compared with minimum inhibitory concentration as a measure of clinical effectiveness and exposure-level-related induction of creatine phosphokinase elevation. The recommended doses were 4 mg/kg for patients with severe renal function [creatinine clearance (CLcr) ≤ 30 mL/min] and 6 mg/kg for patients with mild to moderate renal function (CLcr > 30 and ≤ 60 mL/min). A simulation indicated that dose adjusted by body weight and renal function improved target attainment. CONCLUSIONS: This population pharmacokinetics model for unbound daptomycin could help clinicians to select the appropriate dose regimen for patients undergoing daptomycin treatment and reduce associated adverse effects.

Population Pharmacokinetics, Pharmacogenomics, and Adverse Events of Osimertinib and its Two Active Metabolites, AZ5104 and AZ7550, in Japanese Patients with Advanced Non-small Cell Lung Cancer: a Prospective Observational Study.

BACKGROUND: Potential novel strategies for adverse event (AE) management of osimertinib therapy, including therapeutic drug monitoring and the use of biomarkers, have not yet been fully investigated. This study aimed to evaluate (1) the relationship between exposure to osimertinib, especially its active metabolites (AZ5104 and AZ7550), and AEs, and (2) the relationship between germline polymorphisms and AEs. METHODS: We conducted a prospective, longitudinal observational study of 53 patients with advanced non-small cell lung cancer receiving osimertinib therapy from February 2019 to April 2022. A population pharmacokinetic model was developed to estimate the area under the serum concentration-time curve from 0 to 24 h (AUC0-24) of osimertinib and its metabolites. Germline polymorphisms were analyzed using TaqMan® SNP genotyping and CycleavePCR® assays. RESULTS: There was a significant association between the AUC0-24 of AZ7550 and grade ≥ 2 paronychia (p = 0.043) or anorexia (p = 0.011) and between that of osimertinib or AZ5104 and grade ≥ 2 diarrhea (p = 0.026 and p = 0.049, respectively). Furthermore, the AUC0-24 of AZ5104 was significantly associated with any grade ≥ 2 AEs (p = 0.046). EGFR rs2293348 and rs4947492 were associated with severe AEs (p = 0.019 and p = 0.050, respectively), and ABCG2 rs2231137 and ABCB1 rs1128503 were associated with grade ≥ 2 AEs (p = 0.008 and p = 0.038, respectively). CONCLUSION: Higher exposures to osimertinib, AZ5104, and AZ7550 and polymorphisms in EGFR, ABCG2, and ABCB1 were related to higher severity of AEs; therefore, monitoring these may be beneficial for osimertinib AE management.

Pharmacodynamic Model-Based Safety Management of Eribulin-Induced Myelosuppression in Patients With Breast Cancer.

BACKGROUND: Neutropenia is a major dose-limiting toxicity of cancer chemotherapy. Semimechanistic mathematical models have been applied to describe the time course of neutrophil counts. The objectives of this study were to develop a mathematical model describing changes in neutrophil counts during eribulin treatment, to apply the empirical Bayes method to predict the probability of developing neutropenia ≥ grade 3 during eribulin treatment in each patient, and to propose the implementation of this mathematical tool in clinical practice for individual safety management. METHODS: The present model analysis and subsequent external evaluation were performed using the data of 481 patients with breast cancer, previously obtained from a postmarketing surveillance (training set) and a phase 2 clinical study (validation set). The model we previously reported (Kawamura et al 2018) was modified to improve its predictive capability. The individual time course of neutrophil changes during the treatment period was predicted by the empirical Bayes method using the observed neutrophil counts at baseline and the first measurement after the first eribulin dose. To evaluate the predictability of this method, the predicted neutrophil counts were compared with those of the observed values. RESULTS: The developed model provided good individual predictions, as indicated by the goodness-of-fit plots between the predicted and observed neutrophil counts, especially for a lower neutrophil count range. Days required to reach the nadir after the dose were also well-predicted. The sensitivity, specificity, and accuracy of the prediction of neutropenia grade ≥3 were 76%, 53%, and 71%, respectively. CONCLUSIONS: We developed a mathematical method for predicting and managing the risk of neutropenia during eribulin treatment. This method is generally applicable to other cases of chemotherapy-induced neutropenia and can be a new practical tool for individual safety management.

Population Pharmacokinetic Model of Amiodarone and N-Desethylamiodarone Focusing on Glucocorticoid and Inflammation.

Some population pharmacokinetic models for amiodarone (AMD) did not incorporate N-desethylamiodarone (DEA) concentration. Glucocorticoids activate CYP3A4 activity, metabolizing AMD. In contrast, CYP3A4 activity may decrease under inflammation conditions. However, direct evidence for the role of glucocorticoid or inflammation on the pharmacokinetics of AMD and DEA is lacking. The pilot study aimed to address this gap using a population pharmacokinetic analysis of AMD and DEA. A retrospective cohort observational study in adult patients who underwent AMD treatment with trough concentration measurement was conducted at Tokyo Women's Medical University, Medical Center East from June 2015 to March 2019. Both structural models of AMD and DEA applied 1-compartment models, which included significant covariates using a stepwise forward selection and backward elimination method. The eligible 81 patients (C-reactive protein level: 0.26 [interquartile range; 0.09-1.92] mg/dL) had a total of 408 trough concentrations for both AMD and DEA. The median trough concentrations were 0.49 [0.31-0.81] µg/mL for AMD and 0.43 [0.28-0.71] µg/mL for DEA during a median follow-up period of 446 [147-1059] d. Three patients received low-dose oral glucocorticoid. The final model identified that AMD clearance was 7.9 L/h, and the apparent DEA clearance was 10.3 L/h. Co-administered glucocorticoids lowered apparent DEA clearance by 35%. These results indicate that co-administered glucocorticoids may increase DEA concentrations in patients without severe inflammation.

Pharmacokinetic/Pharmacodynamic Analysis and Dose Optimization of Cefmetazole and Flomoxef against Extended-Spectrum ß-Lactamase-Producing Enterobacterales in Patients with Invasive Urinary Tract Infection Considering Renal Function.

The optimal regimens of cefmetazole and flomoxef for the treatment of urinary tract infections caused by extended-spectrum ß-lactamase (ESBL)-producing Enterobacterales are not well defined. Our study found that the pharmacokinetic/pharmacodynamic targets for cefmetazole and flomoxef were 70% T > MIC, which is suggestive of bactericidal activity. A Monte Carlo simulation (MCS) was performed using the published data to calculate a new probability of target attainment (PTA ≥ 90%) for each renal function. The MCS was performed with 1000 replicates, and clinical breakpoints were calculated to attain PTA ≥ 90% for creatinine clearance (CCR) of 10, 30, 50, and 70 mL/min. The 90% ≥ PTA (70% T > MIC) of cefmetazole and flomoxef in patients who received a standard regimen (0.5 or 1 g, 1 h injection) for each renal function was calculated. Our results suggest that in patients with CCR of less than 30, 31−59, and more than 60 mL/min, the optimal dosage of cefmetazole would be 1 g q12 h, 1 g q8 h, and 1 g q6 h, respectively. Furthermore, in patients with CCR of less than 10, 10−50, and more than 50 mL/min, the optimal dosage of flomoxef would be 1 g q24 h, 1 g q8 h or 12 h, and 1 g q6 h, respectively.

Population pharmacokinetic analysis and dosage recommendations for digoxin in Japanese patients with atrial fibrillation and heart failure using real-world data.

BACKGROUND: Digoxin is an important treatment option for reducing the ventricular rate in patients with atrial fibrillation (AF) and heart failure (HF). Digoxin has a narrow therapeutic window and large interindividual variability. A low target blood concentration, especially ≤0.9 ng/mL, is recommended for patients with HF who are taking digoxin. This study aimed to develop a population pharmacokinetic model and to identify clinical factors that affect digoxin exposure and an optimal digoxin dosing regimen in Japanese patients with AF and HF. METHODS: A population pharmacokinetic analysis was performed by using a nonlinear mixed effects model based on 3465 concentration points from 391 patients (>18 years) who were receiving oral digoxin. Using trough serum digoxin concentrations and clinical data, a population pharmacokinetic model was developed for determining covariates of clearance. A 1-compartment model was used to examine the interindividual variability of the oral clearance (CL/F) of digoxin. An appropriate dosage of digoxin was identified using Monte Carlo simulation. RESULTS: The final model demonstrated that creatinine clearance (CLCR) and the use of amiodarone were factors that contributed to the CL/F of digoxin. Monte Carlo simulation results showed that with a daily maintenance dose of 0.25 mg, the intoxication risk window of a trough serum concentration of ≥0.9 ng/mL could be reached in more than half of patients regardless of renal function category or concurrent use of amiodarone. The appropriate maintenance dosage was 0.125 mg daily for most Japanese patients with AF and HF. However, with a daily dose of 0.125 mg, a trough serum concentration of ≥0.9 ng/mL could be reached in more than half of patients with renal impairments (CLCR 30 mL/min) or concurrent use of amiodarone. A daily maintenance dose of 0.0625 mg was acceptable for these patients. CONCLUSIONS: CLCR and the use of amiodaron were found to contribute to digoxin clearance using a population pharmacokinetic methodology. For Japanese patients with AF and HF, 0.125 mg is an appropriate daily digoxin maintenance dose, but a dose reduction is required for patients with CLCR <30 mL/min or concurrent amiodarone use.

Pharmacometric analysis of seasonal influenza epidemics and the effect of vaccination using sentinel surveillance data.

The identification of influenza epidemics and assessment of the efficacy of vaccination against this infection are major challenges for the implementation of effective public health strategies, such as vaccination programs. In this study, we developed a new pharmacometric model to evaluate the efficacy of vaccination based on infection surveillance data from the 2010/2011 to 2018/2019 influenza seasons in Japan. A novel susceptible-infected-removed plus vaccination model, based on an indirect response structure with the effect of vaccination, was applied to describe seasonal influenza epidemics using a preseasonal collection of data regarding serological H1 antibody titer positivity and the fraction of virus strains. Using this model, we evaluated Kin (a parameter describing the transmission rate of symptomatic influenza infection) for different age groups. Furthermore, we defined a new parameter (prevention factor) showing the efficacy of vaccination against each viral strain and in different age groups. We found that the prevention factor of vaccination against influenza varied among age groups. Notably, children aged 5-14 years showed the highest Kin value during the 10 influenza seasons and the greatest preventive effect of vaccination (prevention factor = 70.8%). The propagation of influenza epidemics varies in different age groups. Children aged 5-14 years most likely play a leading role in the transmission of influenza. Prioritized vaccination in this age group may be the most effective strategy for reducing the prevalence of influenza in the community.

Classification Tree Analysis Based On Machine Learning for Predicting Linezolid-Induced Thrombocytopenia.

Linezolid-induced thrombocytopenia is related to linezolid exposure, baseline platelet count and patient background. Although the relationship usually reflects the time of onset of thrombocytopenia, if the platelet maturation process is taken into account, the platelet decrease can be considered to have started at the beginning of treatment. To predict linezolid-induced thrombocytopenia, classification and regression tree (CART) analysis based on machine learning has been applied to identify predictive factors and cutoff values. We examined 74 patient data with or without linezolid-induced thrombocytopenia. Linezolid concentration and platelet count change, baseline platelet count, age, body weight and creatinine clearance estimate were evaluated as predictive factors for linezolid-induced thrombocytopenia. CART analysis selected the final tree containing two cutoff values: a platelet count reduction to less than 2.3% from baseline at 96 h after the initial dose and a linezolid concentration greater than or equal to 13.5 mg/L at 96 h after the initial dose. The targets for therapeutic intervention were concluded to be the linezolid concentration and the platelet change from baseline at 96 h after the initial dose. These cutoff values occur prior to the onset of thrombocytopenia and should be monitored to avoid linezolid-induced thrombocytopenia.

Pharmacodynamic analysis of hypertension caused by lenvatinib using real-world postmarketing surveillance data.

Lenvatinib is a tyrosine kinase inhibitor of the vascular endothelial growth factor receptor used against nonoperative thyroid cancer; however, hypertension is a major dose-limiting side effect. In this study, hypertension caused by lenvatinib was described through a novel population pharmacodynamic model using postmarketing surveillance data obtained in Japan. The model consists of two maximum effect model components based on the (1) concentration of lenvatinib in plasma and (2) cumulative area under the curve of lenvatinib. In addition, antihypertensive drug of either an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker or calcium channel blocker accounted for by lowering effect on diastolic blood pressure. Based on virtual simulations, the combination of antihypertensive drug and dose adjustment of lenvatinib showed a reduction in the probability of grade greater than or equal to 3 hypertension. The present model provides useful guidance in managing hypertension during treatment with lenvatinib in the real-world setting.

Prediction of Fracture Risk From Early-Stage Bone Markers in Patients With Osteoporosis Treated With Once-Yearly Administered Zoledronic Acid.

The prevention of fractures is the ultimate goal of osteoporosis treatments. To achieve this objective, developing a method to predict fracture risk in the early stage of osteoporosis treatment would be clinically useful. This study aimed to develop a mathematical model quantifying the long-term fracture risk after 2 annual doses of 5 mg of once-yearly administered zoledronic acid or placebo based on the short-term measurement of bone turnover markers or bone mineral density (BMD). The data used in this analysis were obtained from a randomized, placebo-controlled, double-blind, 2-year study of zoledronic acid that included 656 patients with primary osteoporosis. Two-year individual bone resorption marker (tartrate-resistant acid phosphatase 5b [TRACP-5b]) and lumbar spine (L2-L4) BMD profiles were simulated using baseline values and short-term measurements (at 3 months for TRACP-5b and 6 months for BMD) according to the pharmacodynamic model. A new parametric time-to-event model was developed to describe the risk of clinical fractures. Fracture risk was estimated using TRACP-5b or BMD and the number of baseline vertebral fractures. As a result, the fracture risk during the 2 years was successfully predicted using TRACP-5b or BMD. The 90% prediction intervals well covered the observed fracture profiles in both models. Therefore, TRACP-5b or BMD is useful to predict the fracture risk of patients with osteoporosis, and TRACP-5b would be more useful because it is an earlier marker. Importantly, the developed model allows clinicians to inform patients of their predicted response at the initial stage of zoledronic acid treatment.

Population Pharmacokinetics of Voriconazole in Patients With Invasive Aspergillosis: Serum Albumin Level as a Novel Marker for Clearance and Dosage Optimization.

BACKGROUND: Voriconazole (VRCZ) is an antifungal triazole recommended as an effective first-line agent for treating invasive aspergillosis. OBJECTIVES: To develop a population pharmacokinetic model of VRCZ and trough concentration-based dosing simulation for dynamic patient conditions. METHODS: The authors combined plasma VRCZ data from intensive sampling, and retrospective trough concentration monitoring for analysis. Nonlinear mixed-effects modeling with subsequent model validation was performed. The recommended dosage regimens were simulated based on the developed model. RESULTS: The study participants included 106 patients taking oral VRCZ. A linear one-compartment model with first-order elimination and absorption best described the observed data. The CYP2C19 phenotypes did not influence the pharmacokinetic parameters. Serum albumin (SA) levels and gamma-glutamyl transferase significantly correlated with the VRCZ clearance rate, whereas the actual body weight influenced the volume. A visual predictive check showed good consistency with the observed data, whereas SA levels across the treatment course correlated with linear clearance, irrespective of the CYP2C19 phenotype. Patients with SA levels ≤30 g/L had lower linear clearance than that in patients with SA levels >30 g/L. Dosing simulation based on the developed model indicated that patients with SA levels of ≤30 g/L required a lower daily maintenance dose to attain the therapeutic trough level. CONCLUSIONS: SA level was identified as a novel marker associated with VRCZ clearance. This marker may be a practical choice for physicians to perform therapeutic drug monitoring and optimize VRCZ dosage.

Pharmacokinetic and pharmacodynamic analysis of neutropenia following nab-paclitaxel administration in Japanese patients with metastatic solid cancer.

PURPOSE: To develop a pharmacokinetic (PK) and pharmacodynamic (PD) model for neutropenia following nab-paclitaxel administration and identify factors associated with drug disposition and changes in neutrophil counts in patients with solid cancer. METHODS: PK/PD analysis by nonlinear mixed effects approach was performed using the data from 27 patients who participated in phase I studies of nab-paclitaxel monotherapy conducted in Japan. The patients were treated with either weekly (80, 100, or 125 mg/m2) or every 3 weeks (200, 260, or 300 mg/m2). The observed paclitaxel concentrations in whole blood and neutrophil counts in the first cycle were used for PK/PD analysis. Covariate analysis was performed to identify factors affecting PK and the decrease in neutrophil counts. RESULTS: The developed 3-compartment, non-linear PK model described relationships of body surface area with total body clearance and volume of distribution for the peripheral compartment. Covariate factors affecting neutrophil counts were age and serum albumin level. Simulation based on the developed PK/PD model showed a substantial impact of age and serum albumin level on the time course of neutrophil counts after nab-paclitaxel administration. Advanced age was related to greater decrease in neutrophil counts, and serum albumin level, inversely related to change in neutrophil counts. CONCLUSION: We have developed a novel PK/PD model for nab-paclitaxel in which age and serum albumin level were considered clinically important covariate factors. This model needs to be further validated using a larger patient population.

Population Pharmacokinetics and Exposure-Response of Lithium Carbonate in Patients Based on Tubular Reabsorption Mechanisms.

BACKGROUND AND OBJECTIVE: Lithium, which is used to treat bipolar disorder, has a narrow therapeutic blood concentration range and quickly reaches clinically toxic levels. We performed a population pharmacokinetic analysis with a lithium tubular reabsorption model including urinary pH and investigated the relationship between blood lithium concentration and tremor as a side effect. METHODS: Routine clinical data, including 389 serum concentrations, were collected from 214 patients orally administered an adjusted amount of lithium carbonate. Pharmacokinetics were described using a one-compartment distribution model with first-order absorption and elimination. The fractions of the MID (Li+ + LiCO3-) and ION (2Li+ + CO32-) forms were calculated using the Henderson-Hasselbalch equation, and the influences of these fractions on clearance (CL) were evaluated. The rate of tremor development was analyzed using a logit model. RESULTS: Oral apparent CL (CL/F) was explained by nonrenal CL and renal CL, and renal CL was varied by the fractions of lithium forms influenced by urinary pH. The contribution of MID to CL was slightly larger than that of ION. The rate of tremor development was estimated to be more than 30% when the trough lithium concentration was greater than 1.26 mEq L-1. CONCLUSION: Renal function and urinary pH are important indices in lithium treatment, so the serum concentration of lithium may be predicted based on the renal function and urinary pH.

Pharmacodynamic analysis of eribulin safety in breast cancer patients using real-world postmarketing surveillance data.

Postmarketing surveillance is useful to collect safety data in real-world clinical settings. In this study, we applied postmarketing real-world data on a mechanistic model analysis for neutropenic profiles of eribulin in patients with recurrent or metastatic breast cancer. Demographic and safety data were collected using an active surveillance method from eribulin-treated recurrent or metastatic breast cancer patients. Changes in neutrophil counts over time were analyzed using a mechanistic pharmacodynamic model. Pathophysiological factors that might affect the severity of neutropenia were investigated, and neutropenic patterns were simulated for different treatment schedules. Clinical and laboratory data were collected from 401 patients (5199 neutrophil count measurements) who had not received granulocyte colony-stimulating factor and were eligible for pharmacodynamic analysis. The estimated mean parameters were as follows: mean transit time = 104.5 h, neutrophil proliferation rate constant = 0.0377 h-1 , neutrophil elimination rate constant = 0.0295 h-1 , and linear coefficient of drug effect = 0.0413 mL/ng. Low serum albumin levels and low baseline neutrophil counts were associated with severe neutropenia. The probability of grade ≥3 neutropenia was predicted to be 69%, 27%, and 27% for patients on standard, biweekly, and triweekly treatment scenarios, respectively, based on virtual simulations using the developed pharmacodynamic model. In conclusion, this is the first application of postmarketing surveillance data to a model-based safety analysis. This analysis of safety data reflecting authentic clinical settings will provide useful information on the safe use and potential risk factors of eribulin.

Population Pharmacokinetics of Vancomycin in Patients Undergoing Allogeneic Hematopoietic Stem-Cell Transplantation.

Vancomycin is a commonly used antimicrobial agent for patients undergoing allogeneic hematopoietic stem-cell transplantation (allo-HSCT). Vancomycin has large inter- and intraindividual pharmacokinetic variability, which is mainly described by renal function; various studies have indicated that vancomycin pharmacokinetics are altered in special populations. However, little is known regarding vancomycin pharmacokinetics in patients undergoing allo-HSCT. Therefore, we aimed to develop a population pharmacokinetic (PopPK) model of vancomycin in patients undergoing allo-HSCT for effective and safe antimicrobial therapy and to develop a vancomycin dosing nomogram for a vancomycin optimal-dosing strategy. In total, 285 observations from 95 patients undergoing allo-HSCT were available. The final PopPK parameter estimates were central volume of distribution (V1, L), 39.2; clearance (L/h), 4.25; peripheral volume of distribution (V2, L), 56.1; and intercompartmental clearance (L/h), 1.95. The developed vancomycin model revealed an increase in V1 and V2 compared with those in the general population that consisted of patients with methicillin-resistant Staphylococcus aureus. Moreover, serum creatinine was reduced because of an increase in the plasma fraction because of destruction of hematopoietic stem cells accompanying allo-HSCT pretreatment, suggesting that the Cockcroft-Gault equation-based creatinine clearance value was overestimated. To our knowledge, this is the first PopPK study to develop a dosing nomogram for vancomycin in patients undergoing allo-HSCT and was proven to be useful in optimizing the dosage and dosing interval of vancomycin in these patients. This strategy will provide more useful information for vancomycin therapy with an evidence-based dose adjustment.

An analysis on distribution and inter-relationships of biomarkers under rivaroxaban in Japanese patients with non-valvular atrial fibrillation (CVI ARO 1).

Prothrombin time (PT) has been widely used for measuring anticoagulation intensity under rivaroxaban therapy, but precise information has not been well established yet. Consecutive 96 non-valvular atrial fibrillation (NVAF) under rivaroxaban between Jan/June, 2015 were recruited. Serum concentration (SC) and PT with 5 representative reagents available in Japan (Neoplastin Plus®, Thromborel S®, Thrombocheck PT®, Thrombocheck PT Plus®, and Recombiplastin®) at 2-4 hours after (peak) and before intake of rivaroxaban (trough) were measured at outpatient clinic in the cardiovascular institute (CVI ARO study 1). Nonlinear mixed-effects modelling was used to model the population pharmacokinetics and pharmacodynamics of rivaroxaban. An oral one-compartment model was employed to describe the population pharmacokinetics of rivaroxaban. The pharmacokinetics of rivaroxaban were affected by creatinine clearance, alanine aminotransferase, and use of CYP3A4 or P-gp inhibitors. PTs with 5 reagents were predicted by pharmacodinamic models with SC, hematocrit, serum albumin, and age, with medium predicting ability (highest/lowest R2 = 0.746/0.658 in Recombiplastin/Thromborel S, respectively). This population analysis in NVAF patients under rivaroxaban therapy demonstrated that pharmacokinetics of rivaroxaban was described by an oral one-compartment model with expected covariates, and can be assessed by PT with available reagents in Japan with medium predicting ability.

Population pharmacokinetics of teicoplanin in hospitalized elderly patients using cystatin C as an indicator of renal function.

OBJECTIVE: Serum cystatin C (CysC) has recently been proposed as an alternative marker to serum creatinine (SCR) for estimating renal clearance. In the present study, we performed a population pharmacokinetic analysis of teicoplanin (TEIC), which is mainly eliminated through the kidneys, using CysC as a predictor for renal clearance. METHODS: Thirty-six patients with MRSA infections who were administrated to the National Hospital Organization Beppu Medical Center between January 2012 and December 2013 were enrolled and gave 123 sets of blood TEIC concentration data. Renal clearance was estimated by the Hoek equation using CysC, by creatinine clearance predicted by the Cockcroft-Gault equation using SCR, or directly by CysC. One compartment open model with inter-individual variabilities for renal clearance and the volume of distribution as well as an additional residual error model was used to estimate population pharmacokinetic parameters for TEIC. RESULTS: The model with the best predictability was that with CysC as a predictor for renal clearance; it showed better significance than the models using estimated the glomerular filtration rate by the Hoek equation or CLcr. The final model was as follows: CL (L/hr) = 0.510 × (CysC/1.4)-0.68 × Total body weight/600.81, omega (CL) = 19.8% CV, VC (L) = 78.1, omega (V) = 42.7% CV. CONCLUSION: The present results show the usefulness of CysC to more accurately predict the pharmacokinetics of drugs mainly eliminated through the kidneys, such as TEIC. However, since the sample size in this study was relatively small, further investigations on renal clearance predictability using CysC are needed.

Population pharmacokinetics of cyclosporine A in Japanese renal transplant patients: comprehensive analysis in a single center.

PURPOSE: Cyclosporine A (CyA), a potent immunosuppressive agent used in renal transplantation, has a narrow therapeutic window and a large variability in blood concentrations. This study aimed to develop a population pharmacokinetic (PPK) model of CyA in living-donor renal transplant patients at a single center and identify factors influencing CyA pharmacokinetics (PK). METHODS: A total of 660 points (preoperative) and 4785 points (postoperative) of blood concentration data from 98 patients who underwent renal transplantation were used. Pre- and postoperative CyA model structure and PPK parameters were separately estimated with a non-linear mixed-effect model, and subsequently, covariate analysis of postoperative data were comprehensively estimated, including preoperative PK parameters. RESULTS: A two-compartment model with first-order absorption and absorption lag time was selected in this study. Aspartate aminotransferase, body surface area (BSA), pretransplant area under the whole blood concentration-time curve/dose, and postoperative days were identified as the covariates on oral clearance. BSA was selected as a covariate of the distribution volume of the central compartment. In addition, diabetes mellitus was selected as a covariate of the first-order absorption rate. CONCLUSIONS: This PPK study used the largest number of blood concentration data among previous reports of living-donor renal transplant patients. Moreover, all patients received the same immunosuppressive regimen in a single center. Therefore, the validity of the selected covariates is reliable with high precision. The developed PPK model and selected covariates provide useful information about factors influencing CyA PK and greatly contributes to the identification of the most suitable dosing regimen for CyA.

Mechanism Underlying Linezolid-induced Thrombocytopenia in a Chronic Kidney Failure Mouse Model.

OBJECTIVE: To investigate the relationship between renal function and linezolid (LZD)-induced thrombocytopenia and elucidate the underlying mechanism using a chronic renal disease (CRD) mouse model. MATERIALS AND METHODS: CRD was induced in 5-week-old male Institute of Cancer Research (ICR) mice by 5/6 nephrectomy. After this procedure, LZD (25 and 100 mg/kg) was administered intraperitoneally once every day for 28 days. Platelet counts, white blood cell (WBC) counts, and hematocrit (HCT) levels were measured every 7 days. 2-14C-thymidine (0.185 MBq) was administrated intravenously to LZD-administered mice to evaluate the thymidine uptake ability of bone marrow. RESULTS: Platelet counts were significantly lower in the LZD-administered CRD group than in the LZD-nonadministered groups at 14, 21, and 28 days (P < 0.05); however, these changes were not observed in LZD-administered mice with normal renal function, regardless of the duration of LZD administration. No significant changes were observed in WBC counts or HCT levels in any LZD-administered CRD mouse. Moreover, radioactive levels in bone marrow were not significantly different in each group. CONCLUSIONS: These results indicate that LZD-induced decreases in platelet counts were enhanced by renal impairment in vivo, suggesting that LZD-induced thrombocytopenia is not caused by nonimmune-mediated bone marrow suppression.