One-compartment Linear Model Research Articles

Population pharmacokinetics and dose optimization of ceftazidime in critically ill children

ObjectiveThe aim of this study was to develop a population pharmacokinetic model for ceftazidime in critically ill children in the pediatric intensive care unit (PICU) and optimize an appropriate dosing regimen for this population.MethodsWe performed a prospective pharmacokinetic study on critically ill children aged 0.03–15 years. A population pharmacokinetic model was developed using the NLME program. Statistical and graphical methods were used to assess the stability and predictive performance of the model. Monte Carlo simulations were conducted to determine the optimal ceftazidime dosing regimen to achieve 70% fT > minimum inhibitory concentration (MIC).ResultsThis study included 88 critically ill children and 100 ceftazidime serum concentrations. The pharmacokinetic characteristics of ceftazidime were best described by a one-compartment linear elimination model. The weight and estimated glomerular filtration rate (eGFR) were determinant covariates for the clearance (CL) of ceftazidime. The recommended ceftazidime dosage regimens achieved a probability of target attainment (PTA) >90% for critically ill children at MIC values of 2, 4, and 8 mg/L. For bacterial infection at an MIC of 16 mg/L, it is difficult to achieve effective pharmacodynamic (PD) targets in vivo with the commonly used dose of ceftazidime.ConclusionThe population pharmacokinetic model of ceftazidime was established in critically ill children. Based on this model, we recommend evidence-based, individualized dosing regimens for subgroups with different weights and renal functions. The current daily dosage for children adequately meets the treatment requirements for MICs of 2, 4, and 8 mg/L, while for bacterial infection at an MIC of 16 mg/L, an elevated dosage regimen may be required.Clinical Trial Registrationhttps://www.medicalresearch.org.cn/login, Identifier MR-42-22-000220.

Population Pharmacokinetics and Loading Dose Optimization of Intravenous Valproic Acid in Hospitalized Thai Patients.

Our goal is to create a population pharmacokinetic (PK) model and identify the best loading dose (LD) of intravenous valproic acid for hospitalized Thai patients. Data from patients who received intravenous valproic acid and underwent measurement of serum valproic acid concentrations during hospitalization were collected retrospectively. A nonlinear mixed-effects modeling approach was conducted to estimate the PK parameters of valproic acid. Covariates affecting the PK parameters of valproic acid were examined and ranked based on their impact on the model's performance. Monte Carlo simulations of 1000 patients were conducted to estimate the optimal LD of valproic acid. A total of 120 hospitalized patients (51.7% male) with 167 valproic acid concentrations were included in the study. A linear one-compartment model with constant residual error was the best base model. An age-covariate model was the best predictor of valproic acid clearance (CL). The typical values of CL and volume of distribution for valproic acid were 0.77 L/h and 14.56 L, respectively. The LD of 1000-1200 mg intravenous was identified as the pragmatic option as an empirical regimen for hospitalized Thai patients. The recommended time to initiate maintenance dose (MD) is 4-8 h following the LD. The population PK model and optimal LD of valproic acid in hospitalized Thai patients has been established, and it may be advisable to initiate the MD at a later time for the elderly.

Confirming the Suitability of a Gentamicin Dosing Strategy in Neonates Using the Population Pharmacokinetic Approach with Truncated Sampling Duration.

(1) Background: Gentamicin is known to be nephrotoxic and ototoxic. Although gentamicin dosage guidelines have been established for preterm and term neonates, reports do show attainment of recommended peak concentrations but toxic gentamicin concentrations are common in this age group. (2) Methods: This was a prospective, observational study conducted in Namibia with 52 neonates. A dose of 5 mg/kg gentamicin was administered over 3-5 s every 24 h in combination with benzylpenicillin 100,000 IU/kg/12 h or ampicillin 50 mg/kg/8 h. Two blood samples were collected from each participant using a truncated pharmacokinetic sampling schedule. (3) Results: The one-compartment linear pharmacokinetic model best described the data. Birthweight, postnatal age, and white blood cell count were predictive of clearance (CL), while birthweight was predictive of volume (V). For the typical neonate (median weight 1.57 kg, median postnatal age 4 days (0.011 years), median log-transformed WBC of 2.39), predicted CL and V were 0.069 L/h and 0.417 L, respectively-similar to literature values. Simulated gentamicin concentrations varied with respect to postnatal age and bodyweight. (4) Conclusions: A 5 mg/kg/24 h dosage regimen yielded simulated gentamicin concentrations with respect to age and birthweight similar to those previously reported in the literature to be safe and efficacious, confirming its appropriateness.

Modelling the In Vivo and Ex Vivo DNA Damage Response after Internal Irradiation of Blood from Patients with Thyroid Cancer.

This work reports on a model that describes patient-specific absorbed dose-dependent DNA damage response in peripheral blood mononuclear cells of thyroid cancer patients during radioiodine therapy and compares the results with the ex vivo DNA damage response in these patients. Blood samples of 18 patients (nine time points up to 168 h post-administration) were analyzed for radiation-induced γ-H2AX + 53BP1 DNA double-strand break foci (RIF). A linear one-compartment model described the absorbed dose-dependent time course of RIF (Parameters: c characterizes DSB damage induction; k1 and k2 are rate constants describing fast and slow repair). The rate constants were compared to ex vivo repair rates. A total of 14 patient datasets could be analyzed; c ranged from 0.012 to 0.109 mGy-1, k2 from 0 to 0.04 h-1. On average, 96% of the damage is repaired quickly with k1 (range: 0.19-3.03 h-1). Two patient subgroups were distinguished by k1-values (n = 6, k1 > 1.1 h-1; n = 8, k1 < 0.6 h-1). A weak correlation with patient age was observed. While induction of RIF was similar among ex vivo and in vivo, the respective repair rates failed to correlate. The lack of correlation between in vivo and ex vivo repair rates and the applicability of the model to other therapies will be addressed in further studies.

Population pharmacokinetics of rotigotine extended-release microspheres for intramuscular injection in patients with early-stage Parkinson's disease.

Rotigotine extended-release microspheres is a weekly intramuscular injection formulation to treat Parkinson's disease. This study aimed to develop a population pharmacokinetics (PK) model for rotigotine extended-release microspheres to investigate its PK ethnic differences. Data for the study were obtained from three studies in China, Japan and the US. The population PK model was developed using the Phoenix NLME 8.3.5 software. Two parallel absorption models were created to include both zero- and first-order absorptions. The elimination phase was evaluated for one- and two-compartment linear models. Moreover, covariates including sex, body weight, body mass index, albumin, creatinine clearance and race were input into the model using a stepwise covariate method. We constructed a one-compartment linear model with the first parallel absorption model identified as the best-fitting model. Simulation results in patients with lighter body weight (45 kg) exhibited a 27% increase in Cmax,ss and a 31% increase in AUCtau,ss compared to those with median body weight (65 kg). Patients with heavier body weight (103 kg) showed a 27% decrease in Cmax,ss and a 29% decrease in AUCtau,ss compared to the median body weight group. Asian patients displayed only a 21% increase in Cmax,ss and a 6% increase in AUCtau,ss compared to non-Asian. While we could not fully conclude that race does not affect rotigotine exposure, dosage adjustments based on race were not deemed necessary. Exposure differences were mainly attributed to body weight, while dose adjustments were not needed for patients of different racial identities.

What clindamycin dose should be administered by continuous infusion during combination therapy with rifampicin? A prospective population pharmacokinetics study.

Despite its important drug-drug interaction, combined clindamycin/rifampicin therapy may achieve effective plasma clindamycin concentrations, provided clindamycin is administered by continuous infusion. However, the precise clindamycin dose remains unknown. This study was undertaken to determine the daily clindamycin dose to be administered by continuous infusion in combination with rifampicin to achieve effective plasma clindamycin concentrations. Two plasma clindamycin concentrations were determined prospectively for 124 patients with bone-and-joint infections treated with continuously infused clindamycin. Twenty patients received clindamycin monotherapy, 19 clindamycin combined with rifampicin and 85 received clindamycin successively without and with rifampicin. A population pharmacokinetic model was developed using NONMEM 7.5. Monte Carlo simulations were run to determine which regimens obtained clindamycin concentrations of at least 3 mg/L. A linear one-compartment model with first-order elimination accurately described the data. Clindamycin distribution volume was not estimated. Mean clindamycin clearances with rifampicin and without, respectively, were 33.6 and 10.9 L/h, with 12.8% interindividual variability. The lowest daily clindamycin dose achieving plasma concentrations of at least 3 mg/L in >90% of the patients, when combined with rifampicin, was 4200 mg/24 h. Our results support continuous infusion of 4200 mg of clindamycin/24 h, in combination with rifampicin. This high-dose regimen requires therapeutic drug monitoring-guided dose adaptation.

Pharmacokinetic analysis of acute and dietary exposure to piperonyl butoxide in the mouse

Piperonyl butoxide (PBO) is a popular insecticide synergist present in thousands of commercial, agricultural, and household products. PBO inhibits cytochrome P450 activity, impairing the ability of insects to detoxify insecticides. PBO was recently discovered to also inhibit Sonic hedgehog signaling, a pathway required for embryonic development, and rodent studies have demonstrated the potential for in utero PBO exposure to cause structural malformations of the brain, face, and limbs, or more subtle neurodevelopmental abnormalities. The current understanding of the pharmacokinetics of PBO in mice is limited, particularly with respect to dosing paradigms associated with developmental toxicity. To establish a pharmacokinetic (PK) model for oral exposure, PBO was administered to female C57BL/6J mice acutely by oral gavage (22–1800 mg/kg) or via diet (0.09 % PBO in chow). Serum and adipose samples were collected, and PBO concentrations were determined by HPLC-MS/MS. The serum concentrations of PBO were best fit by a linear one-compartment model. PBO concentrations in visceral adipose tissue greatly exceeded those in serum. PBO concentrations in both serum and adipose tissue decreased quickly after cessation of dietary exposure. The elimination half-life of PBO in the mouse after gavage dosing was 6.5 h (90 % CI 4.7–9.5 h), and systemic oral clearance was 83.3 ± 20.5 mL/h. The bioavailability of PBO in chow was 41 % that of PBO delivered in olive oil by gavage. Establishment of this PK model provides a foundation for relating PBO concentrations that cause developmental toxicity in the rodent models to Sonic hedgehog signaling pathway inhibition.

Implementation of non-linear mixed effects models defined by fractional differential equations.

Fractional differential equations (FDEs), i.e. differential equations with derivatives of non-integer order, can describe certain experimental datasets more accurately than classic models and have found application in pharmacokinetics (PKs), but wider applicability has been hindered by the lack of appropriate software. In the present work an extension of NONMEM software is introduced, as a FORTRAN subroutine, that allows the definition of nonlinear mixed effects (NLME) models with FDEs. The new subroutine can handle arbitrary user defined linear and nonlinear models with multiple equations, and multiple doses and can be integrated in NONMEM workflows seamlessly, working well with third party packages. The performance of the subroutine in parameter estimation exercises, with simple linear and nonlinear (Michaelis-Menten) fractional PK models has been evaluated by simulations and an application to a real clinical dataset of diazepam is presented. In the simulation study, model parameters were estimated for each of 100 simulated datasets for the two models. The relative mean bias (RMB) and relative root mean square error (RRMSE) were calculated in order to assess the bias and precision of the methodology. In all cases both RMB and RRMSE were below 20% showing high accuracy and precision for the estimates. For the diazepam application the fractional model that best described the drug kinetics was a one-compartment linear model which had similar performance, according to diagnostic plots and Visual Predictive Check, to a three-compartment classic model, but including four less parameters than the latter. To the best of our knowledge, it is the first attempt to use FDE systems in an NLME framework, so the approach could be of interest to other disciplines apart from PKs.

Population pharmacokinetics of tigecycline in critically ill patients.

Objective: In critically ill patients, the change of pathophysiological status may affect the pharmacokinetic (PK) process of drugs. The purpose of this study was to develop a PK model for tigecycline in critically ill patients, identify the factors influencing the PK and optimiz dosing regimens. Method: The concentration of tigecycline was measured LC-MS/MS. We established population PK model with the non-linear mixed effect model and optimized the dosing regimens by Monte Carlo simulation. Result: A total of 143 blood samples from 54 patients were adequately described by a one-compartment linear model with first-order elimination. In the covariate screening analysis, the APACHEII score and age as significant covariates. The population-typical values of CL and Vd in the final model were 11.30 ± 3.54L/h and 105.00 ± 4.47L, respectively. The PTA value of the standard dose regimen (100mg loading dose followed by a 50mg maintenance dose at q12h) was 40.96% with an MIC of 2mg/L in patients with HAP, the ideal effect can be achieved by increasing the dosage. No dose adjustment was needed for Klebsiella pneumoniae for AUC0-24/MIC targets of 4.5 and 6.96, and the three dose regimens almost all reached 90%. A target AUC0-24/MIC of ≥17.9 reached 100% in patients with cSSSI in the three tigecycline dose regimens, considering MIC ≤ 0.25mg/L. Conclusion: The final model indicated that APACHEII score and age could affect the Cl and Vd of tigecycline, respectively. The standard dose regimen of tigecycline was often not able to obtain satisfactory therapeutic effects for critically ill patients. For patients with HAP and cIAI caused by one of three pathogens, the efficacy rate can be improved by increasing the dose, but for cSSSI infections caused by Acinetobacter baumannii and K. pneumoniae, it is recommended to change the drug or use a combination of drugs.

A Population Pharmacokinetic Analysis of Emicizumab in Patients with Acquired Hemophilia a Enrolled in a Phase III Study (AGEHA)

INTRODUCTION: Emicizumab is a bispecific antibody mimicking the cofactor function of activated factor VIII. A population pharmacokinetic (PK) analysis was performed to characterize the PK of emicizumab in patients with acquired hemophilia A (PwAHA) leveraging a model that had been developed in patients with congenital hemophilia A (PwCHA) [1]. METHODS: Plasma emicizumab concentration data from 12 PwAHA, who received emicizumab subcutaneously in a phase III study (AGEHA) and were included in its primary analysis [2], were analyzed by a nonlinear mixed-effect modeling approach. A linear one-compartment model with first-order absorption and elimination was employed for the structural model. Covariate investigation was limited to minimal given the possibly poor power for identifying right covariates and their right effects due to the much smaller sample size than in PwCHA (N = 381). A full covariate modeling approach was applied to include and infer the covariate effects that had been identified to be statistically significant in PwCHA, i.e., body weight (BW) on the apparent clearance (CL/F) and apparent volume of distribution (V/F), age on the bioavailability (parameterized as relative bioavailability [Frel] to a typical age), and albumin level (ALB) on the CL/F, except for race on the V/F because all patients in this analysis were Asian, without statistical testing for inclusion or exclusion. Because the age and ALB (50 to 92 years and 20 to 40 g/L, respectively) included some values out of the ranges that had been evaluated in PwCHA (1.22 to 77 years and 33 to 57 g/L, respectively), these covariate effects were separately estimated for ≤ 77 and > 77 years and for < 33 and ≥ 33 g/L, respectively, without statistical testing for separation or integration. Other covariate effects that had been identified not to be statistically significant in PwCHA were not repeatedly explored in this analysis. A stepwise covariate modeling approach was applied to explore the effects of a potential new covariate of sex, which had not been tested in PwCHA because all patients were male, on the CL/F, V/F, and absorption rate constant (KA) with statistical testing for inclusion and exclusion. Effects of renal and hepatic functions (normal to severely impaired and normal to moderately impaired, respectively; no patients had severe hepatic impairment) on the CL/F, V/F, and KA were explored graphically in a post hoc manner. Parameter estimates were corrected as appropriate when compared with PwCHA. RESULTS: In PwAHA, all prior identified covariate effects within the ranges previously evaluated in PwCHA exhibited consistent directions (positive or negative) in the point estimates with those in PwCHA, and their 95% confidence intervals (CIs) involved the point estimates in PwCHA. The effects of age > 77 years and ALB < 33 g/L had 95% CIs involving not only the point estimates for ≤ 77 years and ≥ 33 g/L, respectively, but also the null value. Effects of sex were not statistically significant. No consistent effects were observed with the severity of renal or hepatic impairment. The 95% CIs of the CL/F/Frel and V/F/Frel in PwAHA involved the point estimates in PwCHA regardless of the presence or absence of covariate effect correction, indicating no clear effects of being a PwAHA itself. The 95% CI of the KA in PwAHA fell below the point estimate in PwCHA, indicating a possibly slower absorption than in PwCHA; however, its impact on the steady-state exposure was predicted to be limited. Simulations validated the observed achievement of the efficacious mean steady-state trough concentration of > 30 μg/mL with the tested maintenance dose of 1.5 mg/kg once weekly in AGEHA as in PwCHA [2,3], supporting the appropriateness of applying the maintenance dose for PwAHA. CONCLUSIONS: No remarkable differences from PwCHA in the covariates or their effects on the PK of emicizumab were indicated in PwAHA. This finding would warrant application of the same covariate-based dose adjustment as in PwCHA (i.e., only BW is considered) for PwAHA. REFERENCES: 1. Clin Pharmacokinet 2020;59:1611-25. 2. ISTH 2022 Congress. Abstract OC 40.2. 3. Clin Pharmacokinet 2021;60:931-41.

Effects of Voriconazole Exposure on the Pharmacokinetics of Tacrolimus in Lung Transplantation Patients, Based on Therapeutic Drug Monitoring Data

Tacrolimus and voriconazole are usually used simultaneously in lung transplantations. Voriconazole can increase tacrolimus concentrations by inhibiting the cytochromeP450 (CYP) enzyme, which poses a great challenge for dose adjustment. The aim of this study is to clarify the correlation between voriconazole exposure and tacrolimus trough concentrations (C0 ), and to establish a population pharmacokinetic model including voriconazole trough concentrations (VOZ) as a covariate for dose optimization. All data were retrospectively collected from lung transplantation patients who were subjected to therapeutic drug monitoring of tacrolimus and voriconazole. The correlation between C0 and VOZ or voriconazole daily doses was analyzed by Spearman's correlation. A total of 52 patients accounting for 351 pairs of tacrolimus and voriconazole trough concentrations were included. C0 and C0 /daily dose of tacrolimus (DD) had a significant correlation with VOZ (P<.01) rather than voriconazole daily doses. A linear one-compartment model with first-order absorption and elimination was used as the basic model for population pharmacokinetic analysis. Body weight (WT), DD, VOZ, and hematocrit (HCT) were included as covariates in the final model. With the increase in voriconazole concentrations, the apparent total clearance (clearance/bioavailability, CL/F) of tacrolimus decreased significantly. The simulation results showed that the highest proportion of C0 within the target range can only reach <50% when the optimal initial drug regimen was given. Therefore, both tacrolimus and voriconazole concentrations need to be continuously monitored during treatments in lung transplantation patients, and the tacrolimus dose can be optimized according to VOZ based on the established pharmacokinetic model.

Pharmacokinetic analysis of meropenem therapeutic drug monitoring data (TDM) in critically ill adult patients

Meropenem is a carbapenem antibiotic widely used in treatment of severe infections in ICU. Critically ill patients’ pathophysiological features may cause changes in the pharmacokinetics of meropenem, such as augmented/impaired renal clearance, as well as an increase in the volume of distribution of the drug. Considerable variability in meropenem concentration for the same dosage regimen, severity of the diseases and the escalating antibiotic resistance support the need for an individualization of the dosing in critically ill patients. Estimation of meropenem pharmacokinetic (PK) parameters was performed using the NPAG (non-parametric adaptive grid) program from the Pmetrics package based on peak-trough TDM data. A one-compartment linear PK model with zero-order input and first-order elimination was used to analyze data of the 36 critically ill patients (66 measured meropenem concentrations totally) and to predict pharmacodynamic (PD) parameter values (%T&gt;MIC) based on the time course of free meropenem concentration for empirically prescribed dosage regimens by MIC level. The estimated PK parameters of the meropenem model were in good agreement with those published in the literature earlier. A great interindividual variability for PK parameters from 44.5% up to 167% was revealed. Different regression lines between meropenem clearance and clearance creatinine (CLCr) were registered in patients with CLCr [1] 7 L/h versus &gt; 7 L/h: statistically significant regression (n=30, p=0.015) versus no correlation (n=6, р=0.85), respectively. Bayesian feedback TDM-based meropenem dose personalization is the most practical approach to ensure adequate drug exposure in critically ill patients, especially in patients with augmented renal clearance.

Population Pharmacokinetics of Cotadutide in Subjects with Type 2 Diabetes.

Cotadutide is a balanced dual glucagon-like peptide-1/glucagon receptor agonist under development for the treatment of nonalcoholic steatohepatitis and chronic kidney disease with type 2 diabetes. The objectives of the analysis were to characterize the population pharmacokinetics of cotadutide following daily subcutaneous injection in subjects with type 2 diabetes and to evaluate the effect of demographic and clinical variables of interest on cotadutide pharmacokinetics. This study analyzed 8834 plasma concentrations of cotadutide from 759 subjects with type 2 diabetes who received daily subcutaneous doses from 20 to 600 μg from six clinical studies. The impact of covariates on cotadutide pharmacokinetics was quantified, and body weight effect on cotadutide exposure was further evaluated using a simulation approach. The model performance was evaluated through prediction-corrected visual predictive checks. A one-compartment model with first-order absorption and elimination described cotadutide pharmacokinetic data well. The mean values for cotadutide apparent clearance, apparent distribution volume, absorption rate constant, and half-life were 1.04 L/h (interindividual variability [IIV]: 26.5%), 18.7 L (IIV: 28.7%), 0.343 h-1 (IIV: 38.6%), and 12.9 h, respectively. Higher body weight, lower albumin, and higher alanine aminotransferase were associated with an increase in cotadutide clearance, while an increase in anti-drug antibody titers was associated with a decrease in cotadutide clearance. These statistically significant effects were not considered clinically significant and did not warrant dose adjustment. Effects of other tested baseline covariates (age, sex, body mass index, hemoglobin A1c, renal function, duration of diabetes) were not found to statistically significantly affect cotadutide pharmacokinetics. Cotadutide pharmacokinetics was adequately described by a one-compartment linear model with first-order absorption and elimination. Body weight-based dosing is not necessary for cotadutide based on the simulation using the final population pharmacokinetic modeling. This model will be used to evaluate exposure-response relationships for efficacy and safety in different indications that are being studied for cotadutide.

L-carnitine does not improve valproic acid poisoning management: a cohort study with toxicokinetics and concentration/effect relationships

BackgroundValproic acid (VPA) poisoning is responsible for life-threatening neurological and metabolic impairments. Despite only low-level evidence of effectiveness, L-carnitine has been used for years to prevent or reverse VPA-related toxicity. We aimed to evaluate the effects of L-carnitine used to treat acute VPA poisoning on the time-course of plasma VPA concentrations and VPA-related toxicity. We designed a single-center cohort study including all VPA-poisoned patients admitted to the intensive care unit. We studied VPA toxicokinetics using a nonlinear mixed-effects model-based population approach and modeled individual plasma VPA/blood lactate concentration relationships. Then, we evaluated L-carnitine-attributed effects by comparing VPA elimination half-lives and time-courses of blood lactate levels and organ dysfunction [assessed by the Sequential Organ Failure Assessment (SOFA) score] between matched L-carnitine-treated and non-treated patients using a multivariate analysis including a propensity score.ResultsSixty-nine VPA-poisoned patients (40F/29 M; age, 41 years [32–47]) (median [25th–75th percentiles]; SOFA score, 4 [1–6]) were included. The presumed VPA ingested dose was 15 g [10–32]. Plasma VPA concentration on admission was 231 mg/L [147–415]. The most common manifestations were coma (70%), hyperlactatemia (3.9 mmol/L [2.7–4.9]) and hyperammonemia (127 mmol/L [92–159]). VPA toxicokinetics well fitted a one-compartment linear model with a mean elimination half-life of 22.9 h (coefficient of variation, 28.1%). Plasma VPA (C)/blood lactate concentration (E) relationships were well described by an exponential growth equation [E={E}_{0}times {e}^{kcdot C}; with baseline E0 = 1.3 mmol/L (43.9%) and rate constant of the effect, k = 0.003 L/mg (59.5%)]. Based on a multivariate analysis, peak blood lactate concentration was the only factor independently associated with L-carnitine administration (odds ratio, 1.9, 95% confidence interval, 1.2–2.8; P = 0.004). We found no significant contribution of L-carnitine to enhancing VPA elimination, accelerating blood lactate level normalization and/or preventing organ dysfunction.ConclusionsVPA poisoning results in severe toxicity. While L-carnitine does not contribute to enhancing VPA clearance, its impact on accelerating blood lactate level normalization and/or preventing organ dysfunction remains uncertain. Investigating VPA toxicokinetics and concentration/effect relationships may help understanding how to improve VPA-poisoned patient management.

Effects of dalteparin on anti-Xa activities cannot be predicted in critically ill COVID-19 patients.

Critically ill COVID‐19 patients are at high risk of thromboembolic events despite routine‐dosed low‐molecular‐weight heparin thromboprophylaxis. However, in recent randomized trials increased‐intensity thromboprophylaxis seemed futile and possibly even harmful. In this explorative pharmacokinetic (PK) study we measured anti‐Xa activities on frequent timepoints in 15 critically ill COVID‐19 patients receiving dalteparin and performed PK analysis by nonlinear mixed‐effect modelling. A linear one‐compartment model with first‐order kinetics provided a good fit. However, wide interindividual variation in dalteparin absorption (variance 78%) and clearance (variance 34%) was observed, unexplained by routine clinical covariates. Using the final PK model for Monte Carlo simulations, we predicted increased‐intensity dalteparin to result in anti‐Xa activities well over prophylactic targets (0.2‐0.4 IU/mL) in the majority of patients. Therapeutic‐intensity dalteparin results in supratherapeutic anti‐Xa levels (target 0.6‐1.0 IU/mL) in 19% of patients and subtherapeutic levels in 22%. Therefore, anti‐Xa measurements should guide high‐intensity dalteparin in critically ill COVID‐19 patients.

Population pharmacokinetics and exposure‐response modeling analyses of guselkumab in patients with psoriatic arthritis

Guselkumab is an anti‐interleukin‐23 human monoclonal antibody effective in treating psoriatic arthritis (PsA). To characterize the pharmacokinetics (PKs) and exposure‐response relationship of guselkumab in PsA, population PKs, and exposure‐response modeling, analyses were conducted using data from pivotal phase III studies of subcutaneous guselkumab in patients with PsA. The observed serum concentration‐time data of guselkumab were adequately described by a one‐compartment linear PK model with first‐order absorption and elimination. Covariates identified as contributing to the observed guselkumab PK variability were body weight and diabetes comorbidity; however, the magnitude of the effects of these covariates was not considered clinically relevant, and dose adjustment was not warranted for the patient population investigated. Positive exposure‐response relationships were demonstrated with landmark and longitudinal exposure‐response analyses between guselkumab exposure and clinical efficacy end points (American College of Rheumatology [ACR] 20%, 50%, and 70% improvement criteria and Investigator’s Global Assessment [IGA] of psoriasis) at weeks 20 and/or 24, with no clinically relevant differences observed in improvement of PsA signs and symptoms between the two guselkumab treatment regimens evaluated (100 mg every 4 weeks or 100 mg at weeks 0 and 4, then every 8 weeks). Baseline Disease Activity Score in 28 joints (DAS28), Psoriasis Area and Severity Index (PASI) score, and/or C‐reactive protein level were identified as influencing covariates on guselkumab exposure‐response model parameters. These results provide a comprehensive evaluation of subcutaneous guselkumab PKs and exposure‐response relationship that supports the dose regimen of 100 mg at weeks 0 and 4, then every 8 weeks in patients with PsA.

Population Pharmacokinetics of Diethylcarbamazine in Patients with Lymphatic Filariasis and Healthy Individuals.

Diethylcarbamazine (DEC) is a drug of choice to treat lymphatic filariasis (LF) either used alone or in combination as mass drug administration (MDA) preventive strategies. The objective of this study was to develop a population pharmacokinetics (PK) model for DEC in subjects infected with lymphatic filariasis (LF) compared to healthy individuals, and to evaluate the effect of covariates on the volume of distribution (V/F) and oral clearance (CL/F) of DEC. This was an open-label cohort study of treatment-naive Wuchereria bancrofti-infected (n = 32) and uninfected (n = 24) adults residing in the Agboville District of Côte d'Ivoire. The population pharmacokinetics model for DEC was built using Phoenix NLME 8.0 software. The covariates included in the model-building process were age, gender, body weight, infection status, creatinine clearance (CLCR), and aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. A total of 56 adults were enrolled in the study, and a total of 728 samples were obtained over 168 h. A one-compartment linear pharmacokinetics model with first-order absorption with an absorption lag time (Tlag) best described the data. After determining the pharmacokinetics (PK) parameters of DEC, body weight and gender were found to be the significant covariates for DEC V/F. The final population pharmacokinetics model adequately described the pharmacokinetics of DEC in the studied population. Model-based simulation indicated that the body weight significantly impacted the exposure in both the male and female populations. This analysis may further support the drug-drug interaction model development of DEC with different coadministered drugs or agents in disease control programs. (This study is registered at clinicaltrials.gov under identifier NCT02845713.).

Dose tailoring of tacrolimus based on a non-linear pharmacokinetic model in children with refractory nephrotic syndrome

The population pharmacokinetics (PPK) of tacrolimus (TAC) in children with refractory nephrotic syndrome (RNS) have not been well-characterized. This study aimed to investigate the significant factors affecting the TAC PPK characteristics of children with RNS and to optimize the dosing regimen.A total of 494 concentrations from 108 children were obtained from routine therapeutic drug monitoring between 2016 and 2018. Information regarding the demographic features, laboratory test results, genetic polymorphisms of CYP3A5 (rs776746) and co-therapy medications were collected. PPK analysis was performed using the nonlinear mixed-effects modelling (NONMEM) software and two modelling strategies (the linear one-compartment model and nonlinear Michaelis–Menten model) were evaluated and compared.CYP3A5 genotype, weight, daily dose of TAC and daily dose of diltiazem were retained in the final linear model. The absorption rate constant (Ka) was set at 4.48 h−1 in the linear model, and the apparent clearance (CL/F) and volume of distribution (V/F) in the final linear model were 14.2 L/h and 172 L, respectively. CYP3A5 genotype, weight and daily dose of diltiazem were the significant factors retained in the final nonlinear model. The maximal dose rate (Vmax) and the average steady-state concentration at half-Vmax (Km) in the final nonlinear model were 2.15 mg/day and 0.845 ng/ml, respectively. The nonlinear model described the pharmacokinetic data of TAC better than the linear model in children with RNS. A dosing regimen was proposed based on weight, CYP3A5 genotype and daily dose of diltiazem according to the final nonlinear PK model, which may facilitate individualized drug therapy with TAC.

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

Voriconazole (VRCZ) is an antifungal triazole recommended as an effective first-line agent for treating invasive aspergillosis. To develop a population pharmacokinetic model of VRCZ and trough concentration-based dosing simulation for dynamic patient conditions. 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. 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. 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.

Meropenem population pharmacokinetics in patients with decompensated cirrhosis and severe infections.

Meropenem pharmacokinetics (PK) may be altered in patients with cirrhosis, hampering target attainment. We aimed to describe meropenem PK in patients with decompensated cirrhosis and severe bacterial infections, identify the sources of PK variability and assess the performance of different dosing regimens to optimize the PK/pharmacodynamic (PD) target. Serum concentrations and covariates were obtained from patients with severe infections under meropenem treatment. A population PK analysis was performed using non-linear mixed-effects modelling and the final model was used to simulate meropenem exposure to assess the PTA. Fifty-four patients were enrolled in the study. Data were best described by a one-compartment linear model. The estimated typical mean value for clearance (CL) was 8.35 L/h and the estimated volume of distribution (V) was 28.2 L. Creatinine clearance (CLCR) and MELD score significantly influenced meropenem CL, and acute-on-chronic liver failure (ACLF) significantly affected V. Monte Carlo simulations showed that a lower meropenem dose would be needed as CLCR decreases and as the MELD score increases. Patients with ACLF would have lower peak meropenem concentrations but similar steady-state concentrations compared with patients with no ACLF. Our study identified two new covariates that influence meropenem PK in patients with decompensated cirrhosis in addition to CLCR: MELD score and ACLF. Dosing regimens are recommended to reach several PK/PD targets considering these clinical variables and any MIC within the susceptibility range.