Between-subject variability: should high be the new normal?

Population Pharmacokinetic Model of Intravenous Immunoglobulin in Patients Treated for Various Immune System Disorders

PURPOSE

Intravenous immunoglobulin (IVIG) is used to treat various immune system disorders, but the factors influencing its disposition are not well understood. This study aimed to estimate the population pharmacokinetic parameters of IVIG and to investigate the effect of genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor (FcRn) and clinical variability on the pharmacokinetic properties of IVIG in patients with immune system disorders.

METHODS

Patients were recruited from 4 hospitals in Malaysia. Clinical data were recorded, and blood samples were taken for pharmacokinetic and genetic studies. Population pharmacokinetic parameters were estimated by nonlinear mixed-effects modeling in Monolix. Age, weight, baseline immunoglobulin G concentration, ethnicity, sex, genotype, disease type, and comorbidity were investigated as potential covariates. Models were evaluated using the difference in objective function value, goodness-of-fit plots, visual predictive checks, and bootstrap analysis.

FINDINGS

A total of 292 blood samples were analyzed from 79 patients. The IVIG concentrations were best described by a 2-compartment model with linear elimination. Weight was found to be an important covariate for volume of distribution in the central compartment (Vc), volume of distribution in the peripheral compartment (Vp), and clearance in the central compartment, whereas disease type was found to be an important covariate for Vp. Goodness-of-fit plots indicated that the model fit the data adequately. Genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor did not affect the pharmacokinetic properties of IVIG.

IMPLICATIONS

This study supports the use of dosage based on weight as per current practice. The study findings highlight that Vp is significantly influenced by the type of disease being treated with IVIG. This relationship suggests that different disease types, particularly inflammatory and autoimmune conditions, may alter tissue permeability and fluid distribution due to varying degrees of inflammation. Increased inflammation can lead to enhanced permeability and retention of IVIG in peripheral tissues, reflecting higher Vp values.

A tutorial for model-based evaluation and translation of cardiovascular safety in preclinical trials

Assessment of drug-induced effects on the cardiovascular (CV) system remains a critical component of the drug discovery process enabling refinement of the therapeutic index. Predicting potential drug-related unintended CV effects in the preclinical stage is necessary for first-in-human dose selection and preclusion of adverse CV effects in the clinical stage. According to the current guidelines for small molecules, nonclinical CV safety assessment conducted via telemetry analyses should be included in the safety pharmacology core battery studies. However, the manual for quantitative evaluation of the CV safety signals in animals is available only for electrocardiogram parameters (i.e., QT interval assessment), not for hemodynamic parameters (i.e., heart rate, blood pressure, etc.). Various model-based approaches, including empirical pharmacokinetic-toxicodynamic analyses and systems pharmacology modeling could be used in the framework of telemetry data evaluation. In this tutorial, we provide a comprehensive workflow for the analysis of nonclinical CV safety on hemodynamic parameters with a sequential approach, highlight the challenges associated with the data, and propose respective solutions, complemented with a reproducible example. The work is aimed at helping researchers conduct model-based analyses of the CV safety in animals with subsequent translation of the effect to humans seamlessly and efficiently.

Prediction of human pharmacokinetics from chemical structure: combining mechanistic modeling with machine learning

Pharmacokinetics (PK) is the result of a complex interplay between compound properties and physiology, and a detailed characterization of a molecule's PK during preclinical research is key to understanding the relationship between applied dose, exposure, and pharmacological effect. Predictions of human PK based on the chemical structure of a compound are highly desirable to avoid advancing compounds with unfavorable properties early on and to reduce animal testing, but data to train such models are scarce. To address this problem, we combine well-established physiologically based pharmacokinetic models with Deep Learning models for molecular property prediction into a hybrid model to predict PK parameters for small molecules directly from chemical structure. Our model predicts exposure after oral and intravenous administration with fold change errors of 1.87 and 1.86, respectively, in healthy subjects and 2.32 and 2.23, respectively, in patients with various diseases. Unlike pure Deep Learning models, the hybrid model can predict endpoints on which it was not trained. We validate this extrapolation capability by predicting full concentration-time profiles for compounds with published PK data. Our model enables early selection and prioritization of the most promising drug candidates, which can lead to a reduction in animal testing during drug discovery and development.

Population Pharmacokinetics of Posaconazole in Immune-Compromised Children and Assessment of Target Attainment in Invasive Fungal Disease

BACKGROUND AND OBJECTIVE

Posaconazole (PSZ) is a triazole antifungal for the management of invasive fungal disease (IFD) in adults and children. Although PSZ is available as an intravenous (IV) solution, oral suspension (OS) and delayed-release tablets (DRTs), OS is the preferred formulation for pediatric use because of potential safety concerns associated with an excipient in the IV formulation and difficulty in swallowing intact tablets by children. However, poor biopharmaceutical characteristics of the OS formulation leads to an unpredictable dose-exposure profile of PSZ in children, potentially risking therapeutic failure. The goal of this study was to characterize the population pharmacokinetics (PK) of PSZ in immunocompromised children and assess therapeutic target attainment.

METHODS

Serum concentrations of PSZ were collected retrospectively from records of hospitalized patients. A population PK analysis was performed in a nonlinear mixed-effects modeling framework with NONMEM (v7.4). The PK parameters were scaled to body weight, then potential covariate effects were assessed. The final PK model was used to evaluate recommended dosing schemes through simulation of target attainment (as a percentage of the population having steady-state trough concentrations above the recommended target) using Simulx (v2021R1).

RESULTS

Repeated measurement data of 202 serum concentrations of total PSZ were acquired from 47 immunocompromised patients between 1 and 21 years of age receiving PSZ either intravenously or orally, or both. A one-compartment PK model with first-order absorption and linear elimination best fit the data. The estimated absolute bioavailability (95% confidence interval) for suspension (Fs) was 16% (8-27%), which was significantly lower than the reported tablet bioavailability (Ft) [67%]. Fs was reduced by 62% and 75% upon concomitant administration with pantoprazole (PAN) and omeprazole (OME), respectively. Famotidine resulted in a reduction of Fs by only 22%. Both fixed dosing and weight-based adaptive dosing provided adequate target attainment when PAN or OME were not coadministered with the suspension.

CONCLUSIONS

The results of this study revealed that both fixed and weight-based adaptive dosing schemes can be appropriate for target attainment across all PSZ formulations, including suspension. Additionally, covariate analysis suggests that concomitant proton pump inhibitors should be contraindicated during PSZ suspension dosing.

Conjunction of semi-mechanistic in vitro-in vivo modeling and population pharmacokinetics as a tool for virtual bioequivalence analysis - a case study for a BCS class II drug

Virtual bioequivalence trial (VBE) simulations based on (semi)mechanistic in vitro-in vivo (IVIV) modeling have gained a huge interest in the pharmaceutical industry. Sophisticated commercially available software allows modeling variable drug fates in the gastrointestinal tract (GIT). Surprisingly, the between-subject and inter-occasion variability (IOV) of the distribution volumes and clearances are ignored or simplified, despite substantially contributing to varied plasma drug concentrations. The paper describes a novel approach for IVIV-based VBE by using population pharmacokinetics (popPK). The data from two bioequivalence trials with a poorly soluble BCS class II drug were analyzed retrospectively. In the first trial, the test drug product (biobatch 1) did not meet the bioequivalence criteria, but after a reformulation, the second trial succeeded (biobatch 2). The popPK model was developed in the Monolix software (Lixoft SAS, Simulation Plus) based on the originator's plasma concentrations. The modified Noyes-Whitney model was fitted to the results of discriminative biorelevant dissolution tests of the two biobatches and seven other reformulations. Then, the IVIV model was constructed by joining the popPK model with fixed drug disposition parameters, the drug dissolution model, and mechanistic approximation of the GIT transit. It was used to simulate the drug concentrations at different IOV levels of the primary pharmacokinetic parameters and perform the VBE. Estimated VBE success rates for both biobatches well reflected the outcomes of the bioequivalence trials. The predicted 90% confidence intervals for the area under the time-concentration curves were comparable with the observed values, and the 10% IOV allowed the closest approximation to the clinical results. Simulations confirmed that a significantly lower maximum drug concentration for biobatch 1 was responsible for the first clinical trial's failure. In conclusion, the proposed workflow might aid formulation screening in generic drug development.

Population Pharmacokinetics of Rezafungin in Patients with Fungal Infections

Rezafungin is a novel antifungal agent of the echinocandin class with potent activity against species of Candida and Aspergillus, including subsets of resistant strains, and Pneumocystis jirovecii. The objective of this analysis was to develop a population pharmacokinetic (PK) model to characterize the disposition of rezafungin in plasma following intravenous (IV) administration in healthy volunteers and in patients with candidemia and/or invasive candidiasis. The population PK model was based on a previous model from phase 1 data; formal covariate analyses were conducted to identify any relationships between subject characteristics and rezafungin PK variability. A four-compartment model with linear elimination and zero-order drug input provided a robust fit to the pooled data. Several statistically significant relationships between subject descriptors (sex, infection status, serum albumin, and body surface area [BSA]) and rezafungin PK parameters were identified, but none were deemed clinically relevant. Previous dose justification analyses conducted using data from phase 1 subjects alone are expected to remain appropriate. The final model provided a precise and unbiased fit to the observed concentrations and can be used to reliably predict rezafungin PK in infected patients.

Wide size dispersion and use of body composition and maturation improves the reliability of allometric exponent estimates

To evaluate study designs and the influence of dispersion of body size, body composition and maturation of clearance or reliable estimation of allometric exponents. Non-linear mixed effects modeling and parametric bootstrap were employed to assess how the study sample size, number of observations per subject, between subject variability (BSV) and dispersion of size distribution affected estimation bias and uncertainty of allometric exponents. The role of covariate model misspecification was investigated using a large data set ranging from neonates to adults. A decrease in study sample size, number of observations per subject, an increase in BSV and a decrease in dispersion of size distribution, increased the uncertainty of allometric exponent estimates. Studies conducted only in adults with drugs exhibiting normal (30%) BSV in clearance may need to include at least 1000 subjects to be able to distinguish between allometric exponents of 2/3 and 1. Nevertheless, studies including both children and adults can distinguish these exponents with only 100 subjects. A marked bias of 45% (95%CI 41-49%) in the estimate of the allometric exponent of clearance was obtained when maturation and body composition were ignored in infants. A wide dispersion of body size (e.g. infants, children and adults) is required to reliably estimate allometric exponents. Ignoring differences in body composition and maturation of clearance may bias the exponent for clearance. Therefore, pharmacometricians should avoid estimating allometric exponent parameters without suitable designs and covariate models. Instead, they are encouraged to rely on the well-developed theory and evidence that clearance and volume parameters in humans scale with theory-based exponents.

Pharmacokinetics, Pharmacodynamics, and Tolerability of AZD5718, an Oral 5-Lipoxygenase-Activating Protein (FLAP) Inhibitor, in Healthy Japanese Male Subjects

BACKGROUND AND OBJECTIVE

AZD5718, a 5-lipoxygenase-activating protein (FLAP) inhibitor, is in clinical development for treatment of coronary artery disease (CAD) and chronic kidney disease (CKD). This study evaluated AZD5718 pharmacokinetics, pharmacodynamics, and tolerability in healthy male Japanese subjects.

METHODS

Four cohorts of eight Japanese subjects were randomized to receive oral doses of AZD5718 (60, 180, 360, and 600 mg) or matching placebo administered as a single dose on Day 1 and as once-daily doses from Day 3 to Day 10 in fasted conditions. Pharmacokinetic, pharmacodynamic, and safety data were collected.

RESULTS

The pharmacokinetics characteristics of AZD5718 in Japanese male subjects were similar to those reported in a previous study, and the pharmacokinetics were characterized as rapid absorption with median time to reach maximum concentration (T_max) of 1-2 h Creatine-normalized urine maximum concentration (C_max) with mean half-lives ranging from 8 to 21 h, and supra-proportional increase in exposure over the 60-600 mg dose range evaluated. Also, an increase in steady-state area under the concentration-time curve (AUC) compared to the first dose was observed. After both single and multiple doses of AZD5718, a clear dose/concentration-effect relationship was shown for urinary leukotriene E₄ (LTE₄) versus AZD5718 exposure with > 80 % inhibition at plasma concentrations in the lower nM range. No clinically relevant safety and tolerability findings were observed.

CONCLUSIONS

The observed pharmacokinetics and pharmacodynamics were similar to reported data for non-Japanese healthy subjects, which support further evaluation of AZD5718 at similar doses/exposures in Japanese and non-Japanese subjects for future evaluation in patients with CAD and CKD.

A systematic review of population pharmacokinetic analyses of polyclonal immunoglobulin G therapy

BACKGROUND

Population pharmacokinetics (popPK) using the nonlinear mixed-effect (NLME) modeling approach is an essential tool for guiding dose individualization. Several popPK analyses using the NLME have been conducted to characterize the pharmacokinetics of immunoglobulin G (IgG).

OBJECTIVE

To summarize the current information on popPK of polyclonal IgG therapy.

METHOD

A systematic search was conducted in the PubMed and Web of Science databases from inception to December 2020. Additional relevant studies were also included by reviewing the reference list of the reviewed articles. All popPK studies that employed the NLME modeling approach were included and data were synthesized descriptively.

RESULTS

This review included seven studies. Most of the popPK models were developed in patients with primary immunodeficiency (PID). IgG pharmacokinetics was described as a two-compartment model in five studies, while it was described as a one-compartment model in two other studies. Among all tested covariates, weight was consistently identified as a significant predictor for clearance (CL) of IgG. Whereas, weight and disease type were found to be significant predictors for the volume of distribution in central compartment (Vc). In a typical 70 kg adult, the median estimated values of Vc and CL were 4.04 L and 0.144 L/day, respectively. The between subject variability of Vc was considered large. Only two studies evaluated their models using external data.

CONCLUSIONS

Seven popPK studies of IgG were found and discussed, with only weight being a significant covariate across all studies. Future studies linking pharmacokinetics with pharmacodynamics in PID and other patient populations are required.

Estimation of Body Fat Percentage for Clinical Pharmacokinetic Studies in Children

Obesity is a prevalent childhood condition and the degree of adiposity appears likely to be an important covariate in the pharmacokinetics (PKs) of many drugs. We undertook these studies to facilitate the evaluation and, where appropriate, quantification of the covariate effect of body fat percentage (BF%) on PK parameters in children. We examined two large databases to determine the values and variabilities of BF% in children with healthy body weights and in those with obesity, comparing the accuracy and precision of BF% estimation by both clinical methods and demographically derived techniques. Additionally, we conducted simulation studies to evaluate the utility of the several methods for application in clinical trials. BF% was correlated with body mass index (BMI), but was highly variable among both children with healthy body weights and those with obesity. Bio-impedance and several demographically derived techniques produced mean estimates of BF% that differed from dual x-ray absorptiometry by < 1% (accuracy) and a SD of 5% or less (precision). Simulation studies confirmed that when the differences in precision among the several methods were small compared with unexplained between-subject variability of a PK parameter, the techniques were of similar value in assessing the contribution of BF%, if any, as a covariate for that PK parameter. The combination of sex and obesity stage explained 68% of the variance of BF% with BMI. The estimation of BF% from sex and obesity stage can routinely be applied to PK clinical trials to evaluate the contribution of BF% as a potential covariate.

Individualized Dosing With High Inter-Occasion Variability Is Correctly Handled With Model-Informed Precision Dosing-Using Rifampicin as an Example

Rifampicin exhibits complexities in its pharmacokinetics (PK), including high inter-occasion variability (IOV), which is challenging for dose individualization. Model-informed precision dosing (MIPD) can be used to optimize individual doses. In this simulation-based study we investigated the magnitude of IOV in rifampicin PK on an exposure level, the impact of not acknowledging IOV when performing MIPD, and the number of sampling occasions needed to forecast the dose. Subjects with drug-susceptible tuberculosis (TB) were simulated from a previously developed population PK model. To explore the magnitude of IOV, the area under the plasma concentration-time curve from time zero up to 24 h (AUC_0–24h) after 35 mg/kg in the typical individual was simulated for 1,000 sampling occasions at steady-state. The impact of ignoring IOV for dose predictions was investigated by comparing the prediction error of a MIPD approach including IOV to an approach ignoring IOV. Furthermore, the number of sampling occasions needed to predict individual doses using a MIPD approach was assessed. The AUC_0–24h in the typical individual varied substantially between simulated sampling occasions [95% prediction interval (PI): 122.2 to 331.2 h mg/L], equivalent to an IOV in AUC_0–24h of 25.8%, compared to an inter-individual variability of 25.4%. The median of the individual prediction errors using a MIPD approach incorporating IOV was 0% (75% PI: −14.6% to 0.0%), and the PI for the individual prediction errors was narrower with than without IOV (median: 0%, 75% PI: −14.6% to 20.0%). The most common target dose in this population was forecasted correctly in 95% of the subjects when IOV was included in MIPD. In subjects where doses were not predicted optimally, a lower dose was predicted compared to the target, which is favorable from a safety perspective. Moreover, the imprecision (relative root mean square error) and bias in predicted doses using MIPD with IOV decreased statistically significant when a second sampling occasion was added (difference in imprecision: −9.1%, bias: −7.7%), but only marginally including a third (difference in imprecision: −0.1%, bias: −0.1%). In conclusion, a large variability in exposure of rifampicin between occasions was shown. In order to forecast the individual dose correctly, IOV must be acknowledged which can be achieved using a MIPD approach with PK information from at least two sampling occasions.

Choosing the Allometric Exponent in Covariate Model Building

BACKGROUND

Allometric scaling is often used to describe the covariate model linking total body weight (WT) to clearance (CL); however, there is no consensus on how to select its value.

OBJECTIVES

The aims of this study were to assess the influence of between-subject variability (BSV) and study design on (1) the power to correctly select the exponent from a priori choices, and (2) the power to obtain unbiased exponent estimates.

METHODS

The influence of WT distribution range (randomly sampled from the Third National Health and Nutrition Examination Survey, 1988-1994 [NHANES III] database), sample size (N = 10, 20, 50, 100, 200, 500, 1000 subjects), and BSV on CL (low 20%, normal 40%, high 60%) were assessed using stochastic simulation estimation. A priori exponent values used for the simulations were 0.67, 0.75, and 1, respectively.

RESULTS

For normal to high BSV drugs, it is almost impossible to correctly select the exponent from an a priori set of exponents, i.e. 1 vs. 0.75, 1 vs. 0.67, or 0.75 vs. 0.67 in regular studies involving < 200 adult participants. On the other hand, such regular study designs are sufficient to appropriately estimate the exponent. However, regular studies with < 100 patients risk potential bias in estimating the exponent.

CONCLUSION

Those study designs with limited sample size and narrow range of WT (e.g. < 100 adult participants) potentially risk either selection of a false value or yielding a biased estimate of the allometric exponent; however, such bias is only relevant in cases of extrapolating the value of CL outside the studied population, e.g. analysis of a study of adults that is used to extrapolate to children.

Learning a complex dose-response relationship with the computer simulation CoaguSim

BACKGROUND AND PURPOSE

Coagulation is a complex physiological process that includes numerous feedback and feedforward reactions. Learning about coagulation and the use of anticoagulants is complicated by the dynamic and non-linear nature of the processes involved. The purpose of this study was to implement and evaluate the effects of a computer simulation-enabled workshop on students' understanding of the time course of warfarin effect.

EDUCATIONAL ACTIVITY AND SETTING

A computer simulation of coagulation (CoaguSim) was developed to support an undergraduate pharmacy therapeutics workshop. Workshop activities were designed to allow students to generate and test their own hypotheses via CoaguSim based on a case scenario involving treatment with the anti-clotting drug warfarin.

FINDINGS

One hundred and fifteen final year bachelor of pharmacy (BPharm) students participated in the case study. Their mean scores for five multiple choice questions (MCQs) on warfarin pharmacokinetic and pharmacodynamic variability increased significantly from 45% (pre-workshop) to 81% (post-workshop), p < 0.05. A focus group interview also provided support that students learned by generating and testing their hypotheses via CoaguSim during the workshop.

DISCUSSION AND SUMMARY

The new workshop improved pharmacy students' understanding of the dose-response relationship of warfarin. Further development of the simulation to include other drugs is underway.

Pharmacokinetics of Snake Venom

Understanding snake venom pharmacokinetics is essential for developing risk assessment strategies and determining the optimal dose and timing of antivenom required to bind all venom in snakebite patients. This review aims to explore the current knowledge of snake venom pharmacokinetics in animals and humans. Literature searches were conducted using EMBASE (1974–present) and Medline (1946–present). For animals, 12 out of 520 initially identified studies met the inclusion criteria. In general, the disposition of snake venom was described by a two-compartment model consisting of a rapid distribution phase and a slow elimination phase, with half-lives of 5 to 48 min and 0.8 to 28 h, respectively, following rapid intravenous injection of the venoms or toxins. When the venoms or toxins were administered intramuscularly or subcutaneously, an initial absorption phase and slow elimination phase were observed. The bioavailability of venoms or toxins ranged from 4 to 81.5% following intramuscular administration and 60% following subcutaneous administration. The volume of distribution and the clearance varied between snake species. For humans, 24 out of 666 initially identified publications contained sufficient information and timed venom concentrations in the absence of antivenom therapy for data extraction. The data were extracted and modelled in NONMEM. A one-compartment model provided the best fit, with an elimination half-life of 9.71 ± 1.29 h. It is intended that the quantitative information provided in this review will provide a useful basis for future studies that address the pharmacokinetics of snakebite in humans.

Pharmacokinetics of S-ketamine during prolonged sedation at the pediatric intensive care unit

BACKGROUND

S-ketamine is the S(+)-enantiomer of the racemic mixture ketamine, an anesthetic drug providing both sedation and analgesia. In clinical practice, significant interpatient variability in drug effect of S-ketamine is observed during long-term sedation.

AIMS

The aim of this study was to evaluate the pharmacokinetic variability of S-ketamine in children aged 0-18 years during long-term sedation. Twenty-five children (median age: 0.42 years, range: 0.02-12.5) received continuous intravenous administrations of 0.3-3.6 mg/kg/h S-ketamine for sedation during mechanical ventilation. Infusion rates were adjusted to the desired level of sedation and analgesia based on the COMFORT-B score and Visual Analog Scale. Blood samples were drawn once daily at random time-points, and at 1 and 4 hours after discontinuation of S-ketamine infusion. Time profiles of plasma concentrations of S-ketamine and active metabolite S-norketamine were analyzed using nonlinear mixed-effects modeling software. Clearance and volume of distribution were allometrically scaled using the ¾ power model.

RESULTS

A total of 86 blood samples were collected. A 2-compartment and 1-compartment model adequately described the PK of S-ketamine and S-norketamine, respectively. The typical parameter estimates for clearance and central and peripheral volumes of distribution were: CL_S-KETAMINE =112 L/h/70 kg, V1_S-KETAMINE =7.7 L/70 kg, V2_S-KETAMINE =545L/70 kg, Q_S-kETAMINE =196 L/h/70 kg, and CL_{S-NORKETAMINE} =53 L/h/70 kg. Interpatient variability of CL_S-KETAMINE and CL_{S-NORKETAMINE} was considerable with values of 40% and 104%, respectively, leading to marked variability in steady-state plasma concentrations.

CONCLUSION

Substantial interpatient variability in pharmacokinetics in children complicates the development of adequate dosage regimen for continuous sedation.