Enhanced Method for Diagnosing Pharmacometric Models: Random Sampling from Conditional Distributions

Population Pharmacokinetics and Absolute Oral Bioavailability of Lasalocid after Single Intravenous and Intracrop Administration in Laying Hens

Lasalocid sodium is a polyether carboxylic ionophore agent authorized by the EU for use as a coccidiostat in broilers, turkeys, and pullets up to 16 weeks of age, except for laying hens. However, laying hens are the most common nontarget species exposed to lasalocid sodium, mainly due to cross-contamination from feed mills. This exposure may result in potential drug residue deposition in eggs, which could potentially expose consumers to the drug. The breeds commonly used for commercial egg production in Poland are Isa Brown and Green-legged Partridge hens, which have been found to significantly differ in egg-laying performance. This variability may also affect the pharmacokinetics of lasalocid. Data on lasalocid plasma pharmacokinetics in laying hens are lacking. In this study, we aimed to determine typical population pharmacokinetic parameters, absolute oral bioavailability, and how breed may influence the pharmacokinetics of lasalocid. Twenty-layer hens of the two breeds were used in this study. Lasalocid was administered orally at a single dose of either 1 mg or 5 mg/kg body weight or intravenously at a dose of 1 mg/kg body weight, in a crossover design with a three-week washout period between study periods. Blood samples were collected for 72 h, and lasalocid concentrations were measured using high-performance liquid chromatography with fluorescence detection. A population pharmacokinetic analysis was conducted using nonlinear mixed effects modeling. Standard numerical and graphical criteria were used to select the best model, and a stepwise covariate modeling approach was used to determine any influencing factors. The best model was a three-compartment mammillary model with first-order absorption, transit compartments, and linear elimination. The estimated absolute oral bioavailability was low (36%). It was found that breed significantly influenced not only absorption but also the elimination of lasalocid. This study revealed that lasalocid absorption and elimination varied between the two breeds. This variability in pharmacokinetics may result in breed-related differences in drug residue accumulation in eggs, and ultimately, the risk associated with consumer exposure to drug residues may also vary.

Joint modeling of tumor dynamics and progression-free survival in advanced breast cancer: Leveraging data from amcenestrant early phase I-II trials

A joint modeling framework was developed using data from 75 patients of early amcenestrant phase I-II AMEERA-1-2 dose escalation and expansion cohorts. A semi-mechanistic tumor growth inhibition (TGI) model was developed. It accounts for the dynamics of sensitive and resistant tumor cells, an exposure-driven effect on tumor proliferation of sensitive cells, and a delay in the initiation of treatment effect to describe the time course of target lesion tumor size (TS) data. Individual treatment exposure overtime was introduced in the model using concentrations predicted by a population pharmacokinetic model of amcenestrant. This joint modeling framework integrated complex RECISTv1.1 criteria information, linked TS metrics to progression-free survival (PFS), and was externally evaluated using the randomized phase II trial AMEERA-3. We demonstrated that the instantaneous rate of change in TS (TS slope) was an important predictor of PFS and the developed joint model was able to predict well the PFS of amcenestrant phase II monotherapy trial using only early phase I-II data. This provides a good modeling and simulation tool to inform early development decisions.

Prediction of Individual Disease Progression Including Parameter Uncertainty in Rare Neurodegenerative Diseases: The Example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS)

The aim of this study was to develop a model to predict individual subject disease trajectories including parameter uncertainty and accounting for missing data in rare neurological diseases, showcased by the ultra-rare disease Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS). We modelled the change in SARA (Scale for Assessment and Rating of Ataxia) score versus Time Since Onset of symptoms using non-linear mixed effect models for a population of 173 patients with ARSACS included in the prospective real-world multicenter Autosomal Recessive Cerebellar Ataxia (ARCA) registry. We used the Multivariate Imputation Chained Equation (MICE) algorithm to impute missing covariates, and a covariate selection procedure with a pooled p-value to account for the multiply imputed data sets. We then investigated the impact of covariates and population parameter uncertainty on the prediction of the individual trajectories up to 5 years after their last visit. A four-parameter logistic function was selected. Men were estimated to have a 25% lower SARA score at disease onset and a moderately higher maximum SARA score, and time to progression (T50) was estimated to be 35% lower in patients with age of onset over 15 years. The population disease progression rate started slowly at 0.1 points per year peaking to a maximum of 0.8 points per year (at 36.8 years since onset of symptoms). The prediction intervals for SARA scores 5 years after the last visit were large (median 7.4 points, Q1-Q3: 6.4-8.5); their size was mostly driven by individual parameter uncertainty and individual disease progression rate at that time.

Model-based simulation to support the approval of isatuximab alone or with dexamethasone for the treatment of relapsed/refractory multiple myeloma in Japanese patients

This study aimed to support dosing regimen selection for isatuximab as a single agent or in combination with dexamethasone for Japanese patients with relapsed/refractory multiple myeloma (RRMM). A joint model characterizing the dynamics of serum M-protein kinetics and its association with progression-free survival (PFS) was developed using data from 201 evaluable Japanese and non-Japanese patients with RRMM enrolled in two monotherapy phase I/II trials, where Japanese patients (n = 31) received isatuximab at 10 or 20 mg/kg once weekly (qw) for 4 weeks then every 2 weeks (q2w) in subsequent cycles (10 or 20 mg/kg qw-q2w). Among non-Japanese patients, 38 received isatuximab 20 mg/kg qw-q2w in combination with dexamethasone. Trial simulations were then performed to evaluate the effect of the isatuximab dosing regimens on both serum M-protein and PFS with and without dexamethasone. The model identified instantaneous changes in serum M-protein as the best on-treatment predictor for PFS. Trial simulations demonstrated that 20 mg/kg qw-q2w induced a greater decrease (30% vs. 22%) of serum M-protein at week 8 and prolonged median PFS by 2.4 weeks compared with 10 mg/kg qw-q2w. Although Japanese patients did not receive isatuximab plus dexamethasone in the phase I/II trial, simulations predicted that isatuximab 20 mg/kg qw-q2w plus dexamethasone would induce a greater decrease (67% vs. 43%) of serum M-protein and a prolonged median PFS by 7.2 weeks compared with isatuximab alone. Trial simulations support the approved isatuximab 20 mg/kg qw-q2w regimen when administered as a single agent and in combination with dexamethasone in Japanese patients.

Plasma pharmacokinetics of tigolaner, emodepside, and praziquantel following topical administration of a combination product (Felpreva®) and of intravenous administration of the individual active ingredients in cats

Felpreva® for cats contains the new acaricidal/insecticidal active ingredient tigolaner in a fixed combination with the nematocidal and cestocidal compounds emodepside and praziquantel, respectively. The plasma pharmacokinetics of tigolaner, emodepside, and praziquantel were evaluated in clinically healthy cats following topical (spot-on) treatment as fixed combination Felpreva®. For the determination of bioavailability intravenous administration of single active ingredients was also performed. After a single topical administration of Felpreva® using the target dose volume of 0.148 ​ml/kg to cats, tigolaner reached mean peak concentrations of 1352 ​μg/l with a T_max of 12 days and a mean half-life of 24 days. Simulation of repetitive topical administration every 91 days indicates only a low risk of accumulation after reaching steady state within two to three administrations. The volume of distribution calculated after intravenous dosing was 4 ​l/kg and plasma clearance was low with 0.005 ​l/h/kg. Overall plasma exposure was 1566 ​mg∗h/l after topical administration, providing an absolute bioavailability of 57%. Tigolaner was mainly cleared via the faeces (54% within 28 days), renal clearance was neglectable (< 0.5% within 28 days). Emodepside and praziquantel showed mean peak concentrations of 44 ​μg/l and 48 ​μg/l (reached after 1.5 days and 5 ​h, respectively). Overall plasma exposures were 20.6 and 3.69 ​mg∗h/l, respectively. The elimination half-life was 14.5 days for emodepside and 10 days for praziquantel after topical administration. After topical administration of Felpreva® using 2.5× and 5× dose multiples an almost proportional increase of plasma exposure was observed for all three active ingredients. With the addition of tigolaner, Felpreva® combines the established pharmacokinetic (PK) characteristics of emodepside and praziquantel contained in Profender® spot-on for cats with the favourable PK of tigolaner suitable for a 3-months protection against fleas and ticks.

Negative Impact of ST-Segment Elevation Myocardial Infarction and Morphine Dose on Ticagrelor Uptake and Pharmacodynamics: A Population PK/PD Analysis of Pooled Individual Participant Data

BACKGROUND

Ticagrelor is widely used in patients with stable and acute coronary artery disease. Understanding the factors that influence its pharmacokinetics (PK) and pharmacodynamics (PD) could improve therapeutic outcomes. We therefore performed a pooled population PK/PD analysis using individual patient data from two studies. We focused on the impact of morphine administration and ST-segment elevation myocardial infarction (STEMI) on the risk of high platelet reactivity (HPR) and dyspnea.

METHODS

A parent-metabolite population PK/PD model was developed based on data from 63 STEMI, 50 non-STEMI, and 25 chronic coronary syndrome (CCS) patients. Simulations were then run to evaluate the risk of non-response and adverse events associated with the identified variability factors.

RESULTS

The final PK model consisted of first-order absorption with transit compartments, distribution with two compartments for ticagrelor and one compartment for AR-C124910XX (active metabolite of ticagrelor), and linear elimination for both drugs. The final PK/PD model was an indirect turnover model with production inhibition. Morphine dose and STEMI, independently, had a significant negative effect on the absorption rate (reduction of log([Formula: see text]) by 0.21×morphine dose (mg) and by 2.37 in STEMI patients, both p < 0.001), and the presence of STEMI significantly impacted both efficacy and potency (both p < 0.001). The simulations run with the validated model showed a high rate of non-response in patients with those covariates (RR 1.19 for morphine, 4.11 for STEMI and 5.73 for morphine and STEMI, all three p < 0.001). By increasing ticagrelor dosage, the negative morphine effect was reversible in patients without STEMI and just limited in patients with STEMI.

CONCLUSION

The developed population PK/PD model confirmed the negative impact of morphine administration and presence of STEMI on ticagrelor PK and antiplatelet effect. Increasing ticagrelor doses seems effective in morphine users without STEMI, whereas the STEMI effect is not entirely reversible.

The effects of cyclosporine A or activated charcoal co-administration on the pharmacokinetics of enrofloxacin in chickens

The study aimed to investigate the possible role of efflux transporter proteins in the pharmacokinetics of enrofloxacin (ENR) in broilers in the model of co-administration of activated charcoal (AC) or cyclosporine A (CsA). The concentrations of enrofloxacin and its metabolite ciprofloxacin were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) and population approach was used for pharmacokinetic analysis. It was found that body weight has a significant effect on the volume of distribution in the central compartment and on the systemic clearance. Oral AC increased the systemic clearance of intravenously administered ENR suggesting some role of enterohepatic recirculation. For orally administered ENR, CsA increased the area under the curve which can be explained by the inhibition of efflux transporters. Metabolism of the antibacterial drug was not affected by cyclosporine. The data suggest a role of efflux transporter proteins in the pharmacokinetics of drugs in chickens and drug-drug interactions have to be considered when substrates and modulators of these transporters are co-administered.

Contribution of machine learning to tumor growth inhibition modeling for hepatocellular carcinoma patients under Roblitinib (FGF401) drug treatment

Machine learning (ML) opens new perspectives in identifying predictive factors of efficacy among a large number of patients’ characteristics in oncology studies. The objective of this work was to combine ML with population pharmacokinetic/pharmacodynamic (PK/PD) modeling of tumor growth inhibition to understand the sources of variability between patients and therefore improve model predictions to support drug development decisions. Data from 127 patients with hepatocellular carcinoma enrolled in a phase I/II study evaluating once‐daily oral doses of the fibroblast growth factor receptor FGFR4 kinase inhibitor, Roblitinib (FGF401), were used. Roblitinib  PKs was best described by a two‐compartment model with a delayed zero‐order absorption and linear elimination. Clinical efficacy using the longitudinal sum of the longest lesion diameter data was described with a population PK/PD model of tumor growth inhibition including resistance to treatment. ML, applying elastic net modeling of time to progression data, was associated with cross‐validation, and allowed to derive a composite predictive risk score from a set of 75 patients’ baseline characteristics. The two approaches were combined by testing the inclusion of the continuous risk score as a covariate on PD model parameters. The score was found as a significant covariate on the resistance parameter and resulted in 19% reduction of its variability, and 32% variability reduction on the average dose for stasis. The final PK/PD model was used to simulate effect of patients’ characteristics on tumor growth inhibition profiles. The proposed methodology can be used to support drug development decisions, especially when large interpatient variability is observed.

Pharmacokinetics and Dose Optimization Strategies of Para-Aminosalicylic Acid in Children with Rifampicin-Resistant Tuberculosis

Treatment options for children with Rifampicin-resistant tuberculosis (RR-TB) remain limited, and para-aminosalicylic acid (PAS) is still a relevant component of treatment regimens. Prevention of resistance to companion drugs by PAS is dose related, and at higher concentrations, PAS may exhibit significant bactericidal activity in addition to its bacteriostatic properties. The optimal dosing of PAS in children is uncertain, specifically for delayed-release granule preparations, which are the most used. A population pharmacokinetic model was developed describing PAS pharmacokinetics in children receiving routine RR-TB treatment. Model-based simulations evaluated current World Health Organization (WHO) weight-band doses against the adult pharmacokinetic target of 50 to 100 mg/liter for peak concentrations. Of 27 children included, the median (range) age and weight were 3.87 (0.58 to 13.7) years and 13.3 (7.15 to 30.5) kg, respectively; 4 (14.8%) were HIV positive. PAS followed one-compartment kinetics with first-order elimination and transit compartment absorption. The typical clearance in a 13-kg child was 9.79 liters/h. Increased PAS clearance was observed in both pharmacokinetic profiles from the only patient receiving efavirenz. No effect of renal function, sex, ethnicity, nutritional status, HIV status, antiretrovirals (lamivudine, abacavir, and lopinavir-ritonavir), or RR-TB drugs was detected. In simulations, target concentrations were achieved only using the higher WHO dose range of 300 mg/kg once daily. A transit compartment adequately describes absorption for the slow-release PAS formulation. Children should be dosed at the higher range of current WHO-recommended PAS doses and in a once-daily dose to optimize treatment.

Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients

Background and Objective

Previous pharmacokinetic (PK) studies of ciprofloxacin in intensive care (ICU) patients have shown large differences in estimated PK parameters, suggesting that further investigation is needed for this population. Hence, we performed a pooled population PK analysis of ciprofloxacin after intravenous administration using individual patient data from three studies. Additionally, we studied the PK differences between these studies through a post-hoc analysis.

Methods

Individual patient data from three studies (study 1, 2, and 3) were pooled. The pooled data set consisted of 1094 ciprofloxacin concentration–time data points from 140 ICU patients. Nonlinear mixed-effects modeling was used to develop a population PK model. Covariates were selected following a stepwise covariate modeling procedure. To analyze PK differences between the three original studies, random samples were drawn from the posterior distribution of individual PK parameters. These samples were used for a simulation study comparing PK exposure and the percentage of target attainment between patients of these studies.

Results

A two-compartment model with first-order elimination best described the data. Inter-individual variability was added to the clearance, central volume, and peripheral volume. Inter-occasion variability was added to clearance only. Body weight was added to all parameters allometrically. Estimated glomerular filtration rate on ciprofloxacin clearance was identified as the only covariate relationship resulting in a drop in inter-individual variability of clearance from 58.7 to 47.2%. In the post-hoc analysis, clearance showed the highest deviation between the three studies with a coefficient of variation of 14.3% for posterior mean and 24.1% for posterior inter-individual variability. The simulation study showed that following the same dose regimen of 400 mg three times daily, the area under the concentration–time curve of study 3 was the highest with a mean area under the concentration–time curve at 24 h of 58 mg·h/L compared with that of 47.7 mg·h/L for study 1 and 47.6 mg·h/L for study 2. Similar differences were also observed in the percentage of target attainment, defined as the ratio of area under the concentration–time curve at 24 h and the minimum inhibitory concentration. At the epidemiological cut-off minimum inhibitory concentration of Pseudomonas aeruginosa of 0.5 mg/L, percentage of target attainment was only 21%, 18%, and 38% for study 1, 2, and 3, respectively.

Conclusions

We developed a population PK model of ciprofloxacin in ICU patients using pooled data of individual patients from three studies. A simple ciprofloxacin dose recommendation for the entire ICU population remains challenging owing to the PK differences within ICU patients, hence dose individualization may be needed for the optimization of ciprofloxacin treatment.

A Dynamic Structural Equation Approach to Modeling Wage Dynamics and Cumulative Advantage across the Lifespan

Wages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes and related developmental dynamics, and we highlight the extensions and limitations of the DSEM framework.

"De-Shrinking" EBEs: The Solution for Bayesian Therapeutic Drug Monitoring

BACKGROUND

Therapeutic drug monitoring (TDM) aims at individualising a dosage regimen and is increasingly being performed by estimating individual pharmacokinetic parameters via empirical Bayes estimates (EBEs). However, EBEs suffer from shrinkage that makes them biased. This bias is a weakness for TDM and probably a barrier to the acceptance of drug dosage adjustments by prescribers.

OBJECTIVE

The aim of this article is to propose a methodology that allows a correction of EBE shrinkage and an improvement in their precision.

METHODS

As EBEs are defined, they can be seen as a special case of ridge estimators depending on a parameter usually denoted λ. After a bias correction depending on λ, we chose λ so that the individual pharmacokinetic estimations have minimal imprecision. Our estimate is by construction always better than EBE with respect to bias (i.e. shrinkage) and precision.

RESULTS

We illustrate the performance of this approach with two different drugs: iohexol and isavuconazole. Depending on the patient's actual pharmacokinetic parameter values, the improvement given by our approach ranged from 0 to 100%.

CONCLUSION

This innovative methodology is promising since, to the best of our knowledge, no other individual shrinkage correction has been proposed.

SAMBA: A novel method for fast automatic model building in nonlinear mixed-effects models

The success of correctly identifying all the components of a nonlinear mixed-effects model is far from straightforward: it is a question of finding the best structural model, determining the type of relationship between covariates and individual parameters, detecting possible correlations between random effects, or also modeling residual errors. We present the Stochastic Approximation for Model Building Algorithm (SAMBA) procedure and show how this algorithm can be used to speed up this process of model building by identifying at each step how best to improve some of the model components. The principle of this algorithm basically consists in "learning something" about the "best model," even when a "poor model" is used to fit the data. A comparison study of the SAMBA procedure with Stepwise Covariate Modeling (SCM) and COnditional Sampling use for Stepwise Approach (COSSAC) show similar performances on several real data examples but with a much reduced computing time. This algorithm is now implemented in Monolix and in the R package Rsmlx.

Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real World Data from Electronic Health Records and Remnant Specimens

AIM

Our objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and electronic health records (EHRs) and explore the impact of patient's characteristics and pharmacogenetics on dexmedetomidine clearance.

METHODS

Dexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modeling. Stage one developed a model without genotype variables; Stage two added pharmacogenetic effects.

RESULTS

Our final study population included 354 post-cardiac surgery patients age 0 to 22 years (median 16 months). The data were best described with a two-compartment model with allometric scaling for weight and Hill maturation function for age. Population parameter estimates and 95% confidence intervals were 27.3 L/hr (24.0 - 31.1 L/hr) for total clearance (CL), 161 L (139 - 187 L) for central compartment volume of distribution (V₁ ), 26.0 L/hr (22.5 - 30.0 L/hr) for intercompartmental clearance (Q), and 7903 L (5617 - 11119 L) for peripheral compartment volume of distribution (V₂ ). The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5 - 42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99 - 7.08). Genotype was not statistically or clinically significant.

CONCLUSION

Our study demonstrates the use of real-world EHR data and remnant specimens to perform a population PK analysis and investigate covariate effects in a large pediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

Is the Fixed Periodic Treatment Effective for the Tumor System without Complete Information?

Objective

The treatment plans designed with the guidance of the mathematical model and adaptive strategy can trap tumor subpopulations in a periodic and controllable loop. But this process requires detailed information about the tumor system, which is difficult to obtain. Therefore, we wondered whether the fixed periodic treatment plans designed with the typical values of population parameters could be applied to a similar tumor system without complete information.

Methods

A binary tumor system constructed by an EGFR-mutant and a KRAS-mutant cell line was used to explore the applicability of the fixed periodic treatment plans. The dynamics of this system were described by combining the Lotka-Volterra model with the framework of the nonlinear mixed-effects model. The typical values of population parameters were used to design the plans, and the robust plans were screened through parameter variation. These screened plans were examined their applicability in animal experiments and simulations.

Results

In animal experiments where system parameters vary from -30% to 30%, the "osimertinib administration, withdrawal, FK866 administration and withdrawal" plan can trap subpopulations of the system in periodic cycles. In simulation, when there was an unknown resistant subpopulation, the screened fixed periodic treatment plans can still delay the evolution of resistance. The median outcomes of screened plans were better than conventional sequential treatment in most cases. There was no significant difference between the outcomes of the screened plan with median stability and the optimal therapy. The evolutionary trajectories of these two plans were similar.

Conclusion

According to the results, these fixed periodic plans should be tried in treatment even the information of the tumor system was incomplete.

Joint modelling and simulation of M-protein dynamics and progression-free survival for alternative isatuximab dosing with pomalidomide/dexamethasone

AIMS

Addition of isatuximab (Isa) to pomalidomide/dexamethasone (Pd) significantly improved progression-free survival (PFS) in patients with relapsed/refractory multiple myeloma (RRMM). We aimed to characterize the relationship between serum M-protein kinetics and PFS in the phase 3 ICARIA-MM trial (NCT02990338), and to evaluate an alternative dosing regimen of Isa by simulation.

METHODS

Data from the ICARIA-MM trial comparing Isa 10 mg/kg weekly for 4 weeks then every 2 weeks (QW-Q2W) in combination with Pd versus Pd in 256 evaluable RRMM patients were used. A joint model of serum M-protein dynamics and PFS was developed. Trial simulations were then performed to evaluate whether efficacy is maintained after switching to a monthly dosing regimen.

RESULTS

The model identified instantaneous changes (slope) in serum M-protein as the best on-treatment predictor for PFS and baseline patient characteristics impacting serum M-protein kinetics (albumin and β2-microglobulin on baseline levels, non-IgG type on growth rate) and PFS (presence of plasmacytomas). Trial simulations demonstrated that switching to a monthly Isa regimen at 6 months would shorten median PFS by 2.3 weeks and induce 42.3% patients to progress earlier.

CONCLUSIONS

Trial simulations supported selection of the approved Isa 10 mg/kg QW-Q2W regimen and showed that switching to a monthly regimen after 6 months may reduce clinical benefit in the overall population. However, patients with good prognostic characteristics and with a stable, very good partial response may switch to a monthly regimen after 6 months without compromising the risk of disease progression. This hypothesis will be tested in a prospective clinical trial.

Optimizing Adaptive Therapy Based on the Reachability to Tumor Resistant Subpopulation

Simple Summary

The intra-competition among tumor subpopulations is a promising target to modify and control the outgrowth of the resistant subpopulation. Adaptive therapy lives up to this principle well, but the gain of tumors with an aggressive resistant subpopulation is not superior to maximum tolerated dose therapy (MTD). How to integrate these two therapies to maximize the outcome? According to the model and system reachability, the ‘restore index’ is proposed to evaluate the timing of the transition from the treatment cycle of adaptive therapy to high-frequency administration, and to juggle the benefits of intra-competition and killing of the sensitive subpopulation. Based on the simulation and animal experiment, the effectiveness of this method in treating tumors with an aggressive resistant subpopulation has been confirmed.

Abstract

Adaptive therapy exploits the self-organization of tumor cells to delay the outgrowth of resistant subpopulations successfully. When the tumor has aggressive resistant subpopulations, the outcome of adaptive therapy was not superior to maximum tolerated dose therapy (MTD). To explore methods to improve the adaptive therapy’s performance of this case, the tumor system was constructed by osimertinib-sensitive and resistant cell lines and illustrated by the Lotka-Volterra model in this study. Restore index proposed to assess the system reachability can predict the duration of each treatment cycle. Then the threshold of the restore index was estimated to evaluate the timing of interrupting the treatment cycle and switching to high-frequency administration. The introduced reachability-based adaptive therapy and classic adaptive therapy were compared through simulation and animal experiments. The results suggested that reachability-based adaptive therapy showed advantages when the tumor has an aggressive resistant subpopulation. This study provides a feasible method for evaluating whether to continue the adaptive therapy treatment cycle or switch to high-frequency administration. This method improves the gain of adaptive therapy by taking into account the benefits of tumor intra-competition and the tumor control of killing sensitive subpopulation.

Pharmacokinetics and Drug-Drug Interactions of Abacavir and Lamuvudine Co-administered With Antituberculosis Drugs in HIV-Positive Children Treated for Multidrug-Resistant Tuberculosis

Given the high prevalence of multidrug-resistant (MDR)-TB in high HIV burden settings, it is important to identify potential drug-drug interactions between MDR-TB treatment and widely used nucleoside reverse transcriptase inhibitors (NRTIs) in HIV-positive children. Population pharmacokinetic models were developed for lamivudine (n = 54) and abacavir (n = 50) in 54 HIV-positive children established on NRTIs; 27 with MDR-TB (combinations of high-dose isoniazid, pyrazinamide, ethambutol, ethionamide, terizidone, fluoroquinolones, and amikacin), and 27 controls without TB. Two-compartment models with first-order elimination and transit compartment absorption described both lamivudine and abacavir pharmacokinetics, respectively. Allometric scaling with body weight adjusted for the effect of body size. Clearance was predicted to reach half its mature value ∼ 2 (lamivudine) and ∼ 3 (abacavir) months after birth, with completion of maturation for both drugs at ∼ 2 years. No significant difference was found in key pharmacokinetic parameters of lamivudine and abacavir when co-administered with routine drugs used for MDR-TB in HIV-positive children.

Nonlinear Mixed-Effect Pharmacokinetic Modeling and Distribution of Doxycycline in Healthy Female Donkeys after Multiple Intragastric Dosing-Preliminary Investigation

Doxycycline (DXC) is a broad-spectrum antibacterial antimicrobial administered to horses for the treatment of bacterial infections which may also affect donkeys. Donkeys have a different metabolism than horses, leading to differences in the pharmacokinetics of drugs compared to horses. This study aimed to describe the population pharmacokinetics of DXC in donkeys. Five doses of DXC hyclate (10 mg/kg) were administered via a nasogastric tube, q12 h, to eight non-fasted, healthy, adult jennies. Serum, urine, synovial fluid and endometrium were collected for 72 h following the first administration. Doxycycline concentration was measured by competitive enzyme immunoassay. Serum concentrations versus time data were fitted simultaneously using the stochastic approximation expectation-maximization algorithm for nonlinear mixed effects. A one-compartment model with linear elimination and first-order absorption after intragastric administration, best described the available pharmacokinetic data. Final parameter estimates indicate that DXC has a high volume of distribution (108 L/kg) as well as high absorption (10.3 h^-1) in donkeys. However, results suggest that oral DXC at 10 mg/kg q12 h in donkeys would not result in a therapeutic concentration in serum, urine, synovial fluid or endometrium by comparison to the minimum inhibitory concentration of common equine pathogens. Further studies are recommended to identify appropriate dosage and dosing intervals of oral DXC in donkeys.

Conditional Non-parametric Bootstrap for Non-linear Mixed Effect Models

PURPOSE

Non-linear mixed effect models are widely used and increasingly integrated into decision-making processes. Propagating uncertainty is an important element of this process, and while standard errors (SE) on pa- rameters are most often computed using asymptotic approaches, alternative methods such as the bootstrap are also available. In this article, we propose a modified residual parametric bootstrap taking into account the different levels of variability involved in these models.

METHODS

The proposed approach uses samples from the individual conditional distribution, and was implemented in R using the saemix algorithm. We performed a simulation study to assess its performance in different scenarios, comparing it to the asymptotic approximation and to standard bootstraps in terms of coverage, also looking at bias in the parameters and their SE.

RESULTS

Simulations with an Emax model with different designs and sigmoidicity factors showed a similar coverage rate to the parametric bootstrap, while requiring less hypotheses. Bootstrap improved coverage in several scenarios compared to the asymptotic method especially for the variance param-eters. However, all bootstraps were sensitive to estimation bias in the original datasets.

CONCLUSIONS

The conditional bootstrap provided better coverage rate than the traditional residual bootstrap, while preserving the structure of the data generating process.

Pharmacokinetically guided dosing of oral sorafenib in pediatric hepatocellular carcinoma: A simulation study

Sorafenib improves outcomes in adult hepatocellular carcinoma; however, hand foot skin reaction (HFSR) is a dose limiting toxicity of sorafenib that limits its use. HFSR has been associated with sorafenib systemic exposure. The objective of this study was to use modeling and simulation to determine whether using pharmacokinetically guided dosing to achieve a predefined sorafenib target range could reduce the rate of HFSR. Sorafenib steady‐state exposures (area under the concentration curve from 0 to 12‐h [AUC_0–>12 h]) were simulated using published sorafenib pharmacokinetics at either a fixed dosage (90 mg/m²/dose) or a pharmacokinetically guided dose targeting an AUC_0–>12 h between 20 and 55 h µg/ml. Dosages were either rounded to the nearest quarter of a tablet (50 mg) or capsule (10 mg). A Cox proportional hazard model from a previously published study was used to quantify HFSR toxicity. Simulations showed that in‐target studies increased from 50% using fixed doses with tablets to 74% using pharmacokinetically guided dosing with capsules. The power to observe at least 4 of 6 patients in the target range increased from 33% using fixed dosing with tablets to 80% using pharmacokinetically guided with capsules. The expected HFSR toxicity rate decreased from 22% using fixed doses with tablets to 16% using pharmacokinetically guided dosing with capsules. The power to observe less than 6 of 24 studies with HFSR toxicity increased from 51% using fixed dosing with tablets to 88% using pharmacokinetically guided with capsules. Our simulations provide the rationale to use pharmacokinetically guided sorafenib dosing to maintain effective exposures that potentially improve tolerability in pediatric clinical trials.

Clinical-Based vs. Model-Based Adaptive Dosing Strategy: Retrospective Comparison in Real-World mRCC Patients Treated with Sunitinib

Different target exposures with sunitinib have been proposed in metastatic renal cell carcinoma (mRCC) patients, such as trough concentrations or AUCs. However, most of the time, rather than therapeutic drug monitoring (TDM), clinical evidence is preferred to tailor dosing, i.e., by reducing the dose when treatment-related toxicities show, or increasing dosing if no signs of efficacy are observed. Here, we compared such empirical dose adjustment of sunitinib in mRCC patients, with the parallel dosing proposals of a PK/PD model with TDM support. In 31 evaluable patients treated with sunitinib, 53.8% had an empirical change in dosing after treatment started (i.e., 46.2% decrease in dosing, 7.6% increase in dosing). Clinical benefit was observed in 54.1% patients, including 8.3% with complete response. Overall, 58.1% of patients experienced treatment discontinuation eventually, either because of toxicities or progressive disease. When choosing 50-100 ng/mL trough concentrations as a target exposure (i.e., sunitinib + active metabolite N-desethyl sunitinib), 45% patients were adequately exposed. When considering 1200-2150 ng/mL.h as a target AUC (i.e., sunitinib + active metabolite N-desethyl sunitinib), only 26% patients were in the desired therapeutic window. TDM with retrospective PK/PD modeling would have suggested decreasing sunitinib dosing in a much larger number of patients as compared with empirical dose adjustment. Indeed, when using target trough concentrations, the model proposed reducing dosing for 61% patients, and up to 84% patients based upon target AUC. Conversely, the model proposed increasing dosing in 9.7% of patients when using target trough concentrations and in 6.5% patients when using target AUC. Overall, TDM with adaptive dosing would have led to tailoring sunitinib dosing in a larger number of patients (i.e., 53.8% vs. 71-91%, depending on the chosen metrics for target exposure) than a clinical-based decision. Interestingly, sunitinib dosing was empirically reduced in 41% patients who displayed early-onset severe toxicities, whereas model-based recommendations would have immediately proposed to reduce dosing in more than 80% of those patients. This observation suggests that early treatment-related toxicities could have been partly avoided using prospective PK/PD modeling with adaptive dosing. Conversely, the possible impact of model-based adapted dosing on efficacy could not be fully evaluated because no clear relationship was found between baseline exposure levels and sunitinib efficacy measured at 3 months.

Fast screening of covariates in population models empowered by machine learning

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervised learning algorithms using importance scores. We compare various classical methods with three machine learning (ML) methods applied to NONMEM empirical Bayes estimates: random forest, neural networks (NNs), and support vector regression (SVR). The performance of the ML models is assessed using receiver operating characteristic (ROC) curves. The F1 score, which measures test accuracy, is used to compare ML and PMX approaches. Methods are applied to different scenarios of covariate influence based on simulated pharmacokinetics data. ML achieved similar or better F1 scores than stepwise covariate modeling (SCM) and conditional sampling for stepwise approach based on correlation tests (COSSAC). Correlations between covariates and the number of false covariates does not affect the performance of any method, but effect size has an impact. Methods are not equivalent with respect to computational speed; SCM is 30 and 100-times slower than NN and SVR, respectively. The results are validated in an additional scenario involving 100 covariates. Taken together, the results indicate that ML methods can greatly increase the efficiency of population covariate model building in the case of large datasets or complex models that require long run-times. This can provide fast initial covariate screening, which can be followed by more conventional PMX approaches to assess the clinical relevance of selected covariates and build the final model.

Population pharmacokinetics of free flucloxacillin in patients treated with oral flucloxacillin plus probenecid

Oral flucloxacillin may be coadministered with probenecid to reduce flucloxacillin clearance and increase attainment of pharmacokinetic-pharmacodynamic (PK/PD) targets. The aims of this study were to develop a population PK model of free flucloxacillin when administered orally with probenecid, and to identify optimal dosing regimens for this combination.

METHODS

We performed a prospective observational study of adults (45 participants) treated with oral flucloxacillin 1000 mg and probenecid 500 mg 8-hourly for proven or probable staphylococcal infections. Steady-state mid-dose-interval flucloxacillin measurements (45 concentrations) were combined with existing data from a crossover study of healthy participants receiving flucloxacillin with and without probenecid (11 participants, 363 concentrations). We developed a population pharmacokinetic model of free flucloxacillin concentrations within Monolix, and used Monte Carlo simulation to explore optimal dosing regimens to attain PK/PD targets proposed in the literature (free drug time above minimum inhibitory concentration).

RESULTS

Flucloxacillin disposition was best described by a 1-compartment model with a lag time and first-order absorption. Free flucloxacillin clearance depended on probenecid, allometrically-scaled fat free mass (FFM) and estimated glomerular filtration rate (eGFR). Predicted PK/PD target attainment was suboptimal with standard dosing regimens with flucloxacillin alone, but substantially improved in the presence of probenecid.

CONCLUSION

The simulation results reported can be used to identify dose regimens that optimise flucloxacillin exposure according to eGFR and FFM. Patients with higher FFM and eGFR may require the addition of probenecid and 6-hourly dosing to achieve PK/PD targets. The regimen was well-tolerated, suggesting a potential for further evaluation in controlled clinical trials to establish efficacy.

A novel method based on unbiased correlations tests for covariate selection in nonlinear mixed effects models: The COSSAC approach

Building a covariate model is a crucial task in population pharmacokinetics and pharmacodynamics in order to understand the determinants of the interindividual variability. Identifying a good covariate model usually requires many runs. Several procedures have been proposed in the past to automatize this task. The most commonly used is Stepwise Covariate Modeling (SCM). Here, we present a novel stepwise method based on statistical tests between individual parameters sampled from their conditional distribution and the covariates. This strategy, called the COnditional Sampling use for Stepwise Approach based on Correlation tests (COSSAC), makes use of the information contained in the current model to choose which parameter‐covariate relationship to try next. This strategy greatly reduces the number of covariate models tested, while retaining on its search path the models improving the log‐likelihood (LL). In this article, we detail the COSSAC method and its implementation in Monolix, and evaluate its performance. The performance was assessed by comparing COSSAC to the traditional SCM method on 17 representative data sets. For the large majority of cases (15 out of 17), the final covariate model is identical (11 cases) or very similar (4 cases with LL differences less than 3.84) with both procedures. Yet, COSSAC requires between 2 to 20 times fewer runs than SCM. This represents a decisive speed up, especially for models that take long to run and would not be tractable using the SCM method.

Determination of vancomycin exposure target and individualised dosing recommendations for neonates: model-informed precision dosing

INTRODUCTION

Few studies incorporating population pharmacokinetic/pharmacodynamic (Pop-PK/PD) modelling have been conducted to quantify the exposure target of vancomycin in neonates. A retrospective observational cohort study was undertaken in neonates to determine this target and dosing recommendations (chictr.org.cn, ChiCTR1900027919).

METHODS

A Pop-PK model was developed to estimate PK parameters. Causalities between acute kidney injury (AKI) occurrence and vancomycin use were verified using Naranjo criteria. Thresholds of vancomycin exposure in predicting AKI or efficacy were identified via classification and regression tree analysis. Associations between exposure thresholds and clinical outcomes, including AKI and efficacy, were analysed by logistic regression. Dosing recommendations were designed using Monte Carlo simulations based on the optimised exposure target.

RESULTS

Pop-PK modelling included 182 neonates with 411 observations. On covariate analysis, neonatal physiological maturation, renal function and concomitant use of vasoactive agents (VAS) significantly affected vancomycin PK. Seven cases of vancomycin-induced AKI were detected. Area under the concentration-time curve from 0-24 hours (AUC_0-24) ≥ 485 mg•h/L was an independent risk factor for AKI after adjusting for VAS co-administration. The clinical efficacy of vancomycin was analysed in 42 patients with blood culture-proven staphylococcal sepsis. AUC_0-24 to minimum inhibitory concentration (AUC_0-24/MIC) ≥ 234 was the only significant predictor of clinical effectiveness. Monte Carlo simulations indicated that regimens in Neonatal Formulary 7 and Red Book (2018) were unsuitable for all neonates.

CONCLUSION

An AUC_0-24 of 240-480 (assuming MIC = 1 mg/L) is a recommended exposure target of vancomycin in neonates. Model-informed dosing regimens are valuable in clinical practice.

PK/PD modeling of a clazosentan thorough QT study with hysteresis in concentration-QT and RR-QT

Clazosentan's potential QT liability was investigated in a thorough QT study in which clazosentan was administered intravenously as a continuous infusion of 20 mg/h immediately followed by 60 mg/h. Clazosentan prolonged the placebo-corrected change-from-baseline QT interval corrected for RR with Fridericia's formula (ΔΔQTcF) with the maximum QT effect occurring 4 h after the maximum drug concentration, apparently associated with vomiting. The delayed effect precluded the standard linear modeling approach. This analysis aimed at characterizing the concentration-QT relationship in consideration of RR-QT hysteresis, concentration-ΔΔQTcF hysteresis, and the influence of vomiting. Nonlinear mixed-effects modeling was applied to characterize pharmacokinetics and pharmacodynamics, i.e., ΔΔQTcF. Simulations were used to predict ΔΔQTcF for expected therapeutic dose used in Phase 3 clinical development. Correction for RR-QT hysteresis did not influence ΔΔQTcF to a relevant extent. Pharmacokinetics of clazosentan were best described by a linear two-compartment model. The delayed QT prolongation was characterized by an indirect-response model with loglinear drug effect. Vomiting had no statistically significant influence on QT prolongation despite apparent differences between subjects vomiting and not vomiting, probably since vomiting occurred mostly after the main QT prolongation. Following a simulated 3-h infusion of 15 mg/h of clazosentan, the upper bound of the predicted 90% CI for mean ΔΔQTcF was expected to exceed the 10-ms regulatory threshold of concern with maximum effect 3.5 h after end of infusion. TRN: NCT03657446, 05 Sep 2018.

Non-Linear Mixed-Effects Pharmacokinetic Modeling of the Novel COX-2 Selective Inhibitor Vitacoxib in Cats

The objective of this study was to develop a non-linear mixed-effects (NLME) model to describe the disposition kinetics of vitacoxib in cats following intravenous (I.V) and oral (P.O) (single and multiple) dosing. Data from six consecutive studies with 16 healthy neutered domestic short hair cats were pooled together to build a pharmacokinetic (PK) model using NLME. Population PK parameters were estimated using the stochastic approximation expectation maximization (SAEM) algorithm implemented in Monolix 2019R2. A two-compartment mammillary disposition model with simultaneous zero- and first-order absorption best described the PK of vitacoxib in plasma after oral dosing. The systemic CL of vitacoxib was found to be low (110 ml/h), with a steady-state volume of distribution (VSS) of 3.42 L in cats. Results from the automated covariate search in Monolix 2019R2 showed that bodyweight had a significant effect on the central volume of distribution of vitacoxib. Lastly, using Monte Carlo simulations, we investigated the time course of several dosages of vitacoxib from 0.01 to 8 mg/kg. Using this simulation set, we found a range of reasonable dosages that produce therapeutic plasma concentrations of vitacoxib for 24 h or more in cats.

Population pharmacokinetics of mycophenolic acid in pediatric patients with juvenile dermatomyositis and optimization of limited sampling strategy

Juvenile dermatomyositis (JDM) is a rare systemic autoimmune disease specifically affecting children. Mycophenolate mofetil (MMF) is an immunosuppressant used to treat JDM. Mycophenolic acid (MPA) is an active metabolite of MMF. This study aimed to develop a population pharmacokinetic (PPK) model of MPA in children with JDM and optimize the limited sampling strategy (LSS). Fifteen JDM patients treated with MMF, at a median age of 7.35 (range, 3.09-16.1) years, were included. Blood samples were collected at 30 minutes pre-dose, 20 minutes, 60 minutes and 180 minutes post-dose to measure the MPA concentrations. Data were retrospectively collected from the electronic medical records. A two-compartment model with first-order absorption, lag time in absorption, and first-order elimination was developed. Height and co-administered cotrimoxazole were added as the covariates to the model. Concentrations at different time points were simulated and area under the concentration-time curve (AUC_0-12 h) was calculated. By removing one sampling point at a time, AUC_0-12 h from three-point sampling strategy was re-calculated via Bayesian approach. AUC_0-12 h from the three-point sampling strategy (by removing the point at 20 minutes post-dose) had the strongest correlation with AUC_0-12 h from the four-point sampling strategy (Pearson's r = 0.971).

Pharmacokinetics of Intravenous, Intramuscular, Oral, and Transdermal Administration of Flunixin Meglumine in Pre-wean Piglets

Castration and tail-docking of pre-wean piglets are common procedures that are known to induce pain and would benefit from pain mitigation. Flunixin meglumine (FM) is a non-steroidal anti-inflammatory drug currently approved in the United States for pyrexia in swine and lameness pain in cattle. The objective of this study was to establish the pharmacokinetic (PK) parameters resulting from intravenous (IV), intramuscular (IM), oral (PO) and transdermal (TD) administration of FM in pre-wean piglets. FM was administered to thirty-nine pre-wean piglets at a target dose of 2.2 mg/kg for IV and IM and 3.3 mg/kg for PO and TD route. Plasma was collected at twenty-seven time points from 0 to 9 days after FM administration and concentrations were determined using ultra-high performance liquid chromatography coupled with mass spectrometry (UPLC-MS). Pharmacokinetic data were analyzed using noncompartmental analysis (NCA) methods and nonlinear mixed-effects (NLME). Initial plasma concentration for IV (C₀) 11,653 μg/L and mean peak plasma concentrations (C_max) 6,543 μg/L (IM), 4,883 μg/L (PO), and 31.5 μg/L (TD) were measured. The time points of peak FM concentrations (t_max) were estimated 30 min, 1 h, and 24 h for IM, PO, and TD, respectively. The bioavailability (F) of PO and IM FM was estimated at >99%, while the bioavailability of TD FM was estimated to be 7.8%. The reported C_max of FM after IM and PO administration is consistent with therapeutic concentration ranges that mitigate pain in other species and adult pigs. However, the low estimated concentration of FM after TD dosing is not expected to mitigate pain in pre-wean piglets. The low F of TD FM suggests that expanding the surface area of application is unlikely to be sufficient to establish an effective TD dose for pain, while the high bioavailability for PO FM should allow for an effective dose regimen to be established.

Fine-Tuning of Energy Levels Regulates SUC2 via a SNF1-Dependent Feedback Loop

Nutrient sensing pathways are playing an important role in cellular response to different energy levels. In budding yeast, Saccharomyces cerevisiae, the sucrose non-fermenting protein kinase complex SNF1 is a master regulator of energy homeostasis. It is affected by multiple inputs, among which energy levels is the most prominent. Cells which are exposed to a switch in carbon source availability display a change in the gene expression machinery. It has been shown that the magnitude of the change varies from cell to cell. In a glucose rich environment Snf1/Mig1 pathway represses the expression of its downstream target, such as SUC2. However, upon glucose depletion SNF1 is activated which leads to an increase in SUC2 expression. Our single cell experiments indicate that upon starvation, gene expression pattern of SUC2 shows rapid increase followed by a decrease to initial state with high cell-to-cell variability. The mechanism behind this behavior is currently unknown. In this work we study the long-term behavior of the Snf1/Mig1 pathway upon glucose starvation with a microfluidics and non-linear mixed effect modeling approach. We show a negative feedback mechanism, involving Snf1 and Reg1, which reduces SUC2 expression after the initial strong activation. Snf1 kinase activity plays a key role in this feedback mechanism. Our systems biology approach proposes a negative feedback mechanism that works through the SNF1 complex and is controlled by energy levels. We further show that Reg1 likely is involved in the negative feedback mechanism.

Higher plasma asparaginase activity after intramuscular than intravenous Erwinia asparaginase

It is unclear if dosing intervals for Erwinase can be extended with intramuscular (i.m.) versus intravenous (i.v.) dosing. Children with acute lymphoblastic leukemia received Erwinase at 30 000-42 000 IU/m² i.v. or i.m. I.m. Erwinase (n = 22) achieved activity above 0.1 IU/mL for longer than i.v. Erwinase (n = 33) (3.4 vs 2.9 days, P = 0.0007). With 30 000 IU/m² Monday, Wednesday, Friday, more patients achieved adequate concentrations over the weekend with i.m. vs i.v. dosing (P = 5 × 10^-36 ). A schedule with i.v. doses on Monday and Wednesday and i.m. doses on Friday of 30 000 IU/m² maintained activity > 0.1 IU/mL over the weekend in 80% of patients.

Population Pharmacokinetic/Pharmacodynamic Modeling of Glenzocimab (ACT017) a Glycoprotein VI Inhibitor of Collagen-Induced Platelet Aggregation

Glenzocimab (ACT017) is a humanized monoclonal antigen‐binding fragment (Fab) directed against the human platelet glycoprotein VI, a key receptor for collagen and fibrin that plays a major role in thrombus growth and stability. Glenzocimab is being developed as an antiplatelet agent to treat the acute phase of ischemic stroke. During a phase I study in healthy volunteers, the population pharmacokinetics (PK) and pharmacodynamics (PD) of glenzocimab were modeled using Monolix software. The PK/PD model thus described glenzocimab plasma concentrations and its effects on ex vivo collagen‐induced platelet aggregation. Glenzocimab was found to have dose‐proportional, 2‐compartmental PK with a central distribution volume of 4.1 L, and first and second half‐lives of 0.84 and 9.6 hours. Interindividual variability in clearance in healthy volunteers was mainly explained by its dependence on body weight. The glenzocimab effect was described using an immediate effect model with a dose‐dependent half maximal inhibitory concentration: Larger doses resulted in a stronger effect at the same glenzocimab plasma concentration. The mechanism of the overproportional concentration effect at higher doses remained unexplained. PK/PD simulations predicted that 1000‐mg glenzocimab given as a 6‐hour infusion reduced platelet aggregation to 20% in 100% of subjects at 6 hours and in 60% of subjects at 12 hours after dosing. Simulations revealed a limited impact of creatinine clearance on exposure, suggesting that no dose adjustments were required with respect to renal function. Future studies in patients with ischemic stroke are now needed to establish the relationship between ex vivo platelet aggregation and the clinical effect.

Efficient Pharmacokinetic Modeling Workflow With the MonolixSuite: A Case Study of Remifentanil

MonolixSuite is a software widely used for model‐based drug development. It contains interconnected applications for data visualization, noncompartmental analysis, nonlinear mixed effect modeling, and clinical trial simulations. Its main assets are ease of use via an interactive graphical interface, computation speed, and efficient parameter estimation even for complex models. This tutorial presents a step‐by‐step pharmacokinetic (PK) modeling workflow using MonolixSuite, including how to visualize the data, set up a population PK model, estimate parameters, and diagnose and improve the model incrementally.

Bayesian Individual Dynamic Predictions with Uncertainty of Longitudinal Biomarkers and Risks of Survival Events in a Joint Modelling Framework: a Comparison Between Stan, Monolix, and NONMEM

Given a joint model and its parameters, Bayesian individual dynamic prediction (IDP) of biomarkers and risk of event can be performed for new patients at different landmark times using observed biomarker values. The aim of the present study was to compare IDP, with uncertainty, using Stan 2.18, Monolix 2018R2 and NONMEM 7.4. Simulations of biomarker and survival were performed using a nonlinear joint model of prostate-specific antigen (PSA) kinetics and survival in metastatic prostate cancer. Several scenarios were evaluated, according to the strength of the association between PSA and survival. For various landmark times, a posteriori distribution of PSA kinetic individual parameters was estimated, given individual observations, with each software. Samples of individual parameters were drawn from the posterior distribution. Bias and imprecision of individual parameters as well as coverage of 95% credibility interval for PSA and risk of death were evaluated. All software performed equally well with small biases on individual parameters. Imprecision on individual parameters was comparable across software and showed marked improvements with increasing landmark time. In terms of coverage, results were also comparable and all software were able to well predict PSA kinetics and survival. As for computing time, Stan was faster than Monolix and NONMEM to obtain individual parameters. Stan 2.18, Monolix 2018R2 and NONMEM 7.4 are able to characterize IDP of biomarkers and risk of event in a nonlinear joint modelling framework with correct uncertainty and hence could be used in the context of individualized medicine.

Population Pharmacokinetic Modelling of Pyrazinamide and Pyrazinoic Acid in Patients with Multi-Drug Resistant Tuberculosis

BACKGROUND AND OBJECTIVES

Pyrazinamide, a drug used in the regimen for the treatment of drug-sensitive tuberculosis, is also used for the treatment of multidrug-resistant tuberculosis (MDR-TB). We aimed to describe the population pharmacokinetics of pyrazinamide and its major metabolite, pyrazinoic acid, in patients with MDR-TB and characterise the effects of demographic variables.

METHODS

This was a non-randomised clinical study involving 51 adult patients admitted for the intensive phase of MDR-TB treatment. Blood samples were collected at pre-dose and at 0.5, 1, 1.5, 2, 3, 4, 8, 16 and 24 h after drug administration. Plasma concentrations of pyrazinamide and pyrazinoic acid were analysed using a validated LC-MS/MS method. Nonlinear mixed-effects modelling using Monolix 2018R1 software was employed to estimate population pharmacokinetic parameters.

RESULTS

A one-compartment pharmacokinetic model with transit compartment absorption process and first-order elimination best described the pyrazinamide and pyrazinoic acid concentration-time data. The estimated population pharmacokinetic parameters were 0.7 h, 3.38 h^-1, 57.1 l, 4.37 L/h and 10.5 L/h for mean transit time, absorption rate constant, apparent distribution volume for pyrazinamide, and apparent clearance for pyrazinamide and pyrazinoic acid (CLm/F), respectively. These parameters were not affected by patient age, HIV status or sex. The parameter variability in CLm/F was the highest (83.5%), while the rest of the parameters ranged from 16.2 to 58%.

CONCLUSIONS

The developed population pharmacokinetic model adequately described the disposition of pyrazinamide and pyrazinoic acid and can be useful for dose determination of pyrazinamide in patients with MDR-TB.

Mathematical modelling identifies the role of adaptive immunity as a key controller of respiratory syncytial virus in cotton rats

Respiratory syncytial virus (RSV) is a common virus that can have varying effects ranging from mild cold-like symptoms to mortality depending on the age and immune status of the individual. We combined mathematical modelling using ordinary differential equations (ODEs) with measurement of RSV infection kinetics in primary well-differentiated human bronchial epithelial cultures in vitro and in immunocompetent and immunosuppressed cotton rats to glean mechanistic details that underlie RSV infection kinetics in the lung. Quantitative analysis of viral titre kinetics in our mathematical model showed that the elimination of infected cells by the adaptive immune response generates unique RSV titre kinetic features including a faster timescale of viral titre clearance than viral production, and a monotonic decrease in the peak RSV titre with decreasing inoculum dose. Parameter estimation in the ODE model using a nonlinear mixed effects approach revealed a very low rate (average single-cell lifetime > 10 days) of cell lysis by RSV before the adaptive immune response is initiated. Our model predicted negligible changes in the RSV titre kinetics at early times post-infection (less than 5 dpi) but a slower decay in RSV titre in immunosuppressed cotton rats compared to that in non-suppressed cotton rats at later times (greater than 5 dpi) in silico. These predictions were in excellent agreement with the experimental results. Our combined approach quantified the importance of the adaptive immune response in suppressing RSV infection in cotton rats, which could be useful in testing RSV vaccine candidates.

Pharmacokinetic Modeling of Ceftiofur Sodium Using Non-linear Mixed-Effects in Healthy Beagle Dogs

Ceftiofur (CEF) sodium is a third-generation broad-spectrum cephalosporin commonly used in an extra-label manner in dogs for the treatment of respiratory and urinary system infections. To contribute to the literature supporting CEF use in companion animals, we have developed a compartmental, non-linear mixed-effects (NLME) model of CEF pharmacokinetics in dogs (PK). We then used the mathematical model to predict (via Monte Carlo simulation) the duration of time for which plasma concentrations of CEF and its pharmacologically active metabolites remained above minimum inhibitory concentrations (respiratory tract Escherichia coli spp.). Twelve healthy beagle dogs were administered either 2.2 mg/kg ceftiofur-sodium (CEF-Na) intravenously (I.V) or 2.2 mg/kg CEF-Na subcutaneously (S.C). Plasma samples were collected over a period of 72 h post-administration. To produce a measurement of total CEF, both CEF and CEF metabolites were derivatized into desfuroylceftiofur acetamide (DCA) before analysis by UPLC-MS/MS. No adverse effects were reported after I.V or S.C dosing. The NLME PK models were parameterized using the stochastic approximation expectation maximization algorithm as implemented in Monolix 2018R2. A two-compartment mamillary model with first-order elimination and first-order S.C absorption best described the available kinetic data. Final parameter estimates indicate that CEF has a low systemic clearance (0.25 L/h/kg) associated with a low global extraction ratio E = 0.02) and a moderate volume of distribution (2.97 L/kg) in dogs. The absolute bioavailability after S.C administration was high (93.7%). Gender was determined to be a significant covariate in explaining the variability of S.C absorption. Our simulations predicted that a dose of 2.2 mg/kg CEF-Na S.C would produce median plasma concentrations of CEF of at least 0.5 μg/mL (MIC₅₀) for ~30 h.

Nonlinear mixed-effects pharmacokinetic modeling of the novel COX-2 selective inhibitor vitacoxib in dogs

The objective of this study was to develop a nonlinear mixed-effects model of vitacoxib disposition kinetics in dogs after intravenous (I.V.), oral (P.O.), and subcutaneous (S.C.) dosing. Data were pooled from four consecutive pharmacokinetic studies in which vitacoxib was administered in various dosing regimens to 14 healthy beagle dogs. Plasma concentration versus time data were fitted simultaneously using the stochastic approximation expectation maximization (SAEM) algorithm for nonlinear mixed-effects as implemented in Monolix version 2018R2. Correlations between random effects and significance of covariates on population parameter estimates were evaluated using multiple samples from the posterior distribution of the random effects. A two-compartment mamillary model with first-order elimination and first-order absorption after P.O. and S.C. administration, best described the available pharmacokinetic data. Final parameter estimates indicate that vitacoxib has a low-to-moderate systemic clearance (0.35 L hr^-1  kg^-1 ) associated with a low global extraction ratio, but a large volume of distribution (6.43 L/kg). The absolute bioavailability after P.O. and S.C. administration was estimated at 10.5% (fasted) and 54.6%, respectively. Food intake was found to increase vitacoxib oral bioavailability by a fivefold, while bodyweight (BW) had a significant impact on systemic clearance, thereby confirming the need for BW adjustment with vitacoxib dosing in dogs.

Optimal Scheduling of Bevacizumab and Pemetrexed/Cisplatin Dosing in Non-Small Cell Lung Cancer

Bevacizumab-pemetrexed/cisplatin (BEV-PEM/CIS) is a first-line therapeutic for advanced nonsquamous non-small cell lung cancer. Bevacizumab potentiates PEM/CIS cytotoxicity by inducing transient tumor vasculature normalization. BEV-PEM/CIS has a narrow therapeutic window. Therefore, it is an attractive target for administration schedule optimization. The present study leverages our previous work on BEV-PEM/CIS pharmacodynamic modeling in non-small cell lung cancer-bearing mice to estimate the optimal gap in the scheduling of sequential BEV-PEM/CIS. We predicted the optimal gap in BEV-PEM/CIS dosing to be 2.0 days in mice and 1.2 days in humans. Our simulations suggest that the efficacy loss in scheduling BEV-PEM/CIS at too great of a gap is much less than the efficacy loss in scheduling BEV-PEM/CIS at too short of a gap.

Steady-state population pharmacokinetics of terizidone and its metabolite cycloserine in patients with drug-resistant tuberculosis

AIMS

Despite terizidone being part of the second-line recommended drugs for treatment of drug-resistant tuberculosis (DR-TB), information on its pharmacokinetics is scarce. The aim of this study was to describe the steady-state population pharmacokinetics (PPK) of terizidone and its primary metabolite cycloserine in patients with DR-TB and determine the effect of patient characteristics.

METHODS

This clinical study involved 39 adult DR-TB patients admitted to Brewelskloof Hospital in Cape Town, South Africa for intensive treatment phase. Blood samples were collected at predose and 0.5, 1, 2, 3, 3.5, 4, 8, 16 and 24 hours after drug administration. The estimation of PPK parameters was performed using nonlinear mixed-effects modelling software Monolix 2018R1. Free-fat mass was used to perform allometric scaling on disposition parameters.

RESULTS

A 1-compartment model best described the pharmacokinetics of terizidone and cycloserine. A modified transit compartment model described the absorption of terizidone. The parameters of terizidone model were mean transit time (1.7 h), absorption rate constant (2.97 h^-1 ), apparent volume of distribution (Vp/F: 13.4 L) and apparent total clearance (0.51 L h^-1 ). In the joint model, apparent fraction of terizidone converted to cycloserine was 0.29 while apparent clearance of terizidone via other routes and apparent cycloserine clearance was 0.1 L h^-1 and 2.94 L h^-1 , respectively. Serum albumin had significant effect on Vp/F.

CONCLUSIONS

The developed PPK model described well the concentration-time profile for terizidone and cycloserine in DR-TB patients. High albumin concentration was associated with low Vp/F.

Development of visual predictive checks accounting for multimodal parameter distributions in mixture models

The assumption of interindividual variability being unimodally distributed in nonlinear mixed effects models does not hold when the population under study displays multimodal parameter distributions. Mixture models allow the identification of parameters characteristic to a subpopulation by describing these multimodalities. Visual predictive check (VPC) is a standard simulation based diagnostic tool, but not yet adapted to account for multimodal parameter distributions. Mixture model analysis provides the probability for an individual to belong to a subpopulation (IPmix) and the most likely subpopulation for an individual to belong to (MIXEST). Using simulated data examples, two implementation strategies were followed to split the data into subpopulations for the development of mixture model specific VPCs. The first strategy splits the observed and simulated data according to the MIXEST assignment. A shortcoming of the MIXEST-based allocation strategy was a biased allocation towards the dominating subpopulation. This shortcoming was avoided by splitting observed and simulated data according to the IPmix assignment. For illustration purpose, the approaches were also applied to an irinotecan mixture model demonstrating 36% lower clearance of irinotecan metabolite (SN-38) in individuals with UGT1A1 homo/heterozygote versus wild-type genotype. VPCs with segregated subpopulations were helpful in identifying model misspecifications which were not evident with standard VPCs. The new tool provides an enhanced power of evaluation of mixture models.

Can We Improve Stavudine's Safety Profile in Children? Pharmacokinetics of Intracellular Stavudine Triphosphate with Reduced Dosing

Stavudine remains a useful replacement option for treatment for HIV⁺ children. WHO reduced the adult dose to 30 mg twice daily, which maintains efficacy and lowers mitochondrial toxicity. We explored intracellular stavudine triphosphate levels in children receiving a reduced dose of 0.5 to 0.75 mg/kg of body weight twice daily to investigate whether a similar dose optimization can safely be made. A population pharmacokinetic model was developed to describe the pharmacokinetics of intracellular stavudine triphosphate in 23 HIV⁺ children and 24 HIV⁺ adults who received stavudine at 0.5 mg/kg and 20 mg twice daily for 7 days, respectively. Simulations were employed to optimize the pediatric dosing regimen to match exposures in adults receiving the current WHO-recommended dose of 30 mg twice daily. A biphasic disposition model with first-order appearance and disappearance described the pharmacokinetics of stavudine triphosphate. The use of allometric scaling with fat-free mass characterized well the pharmacokinetics in both adults and children, and no other significant effect could be detected. Simulations of 30 mg twice daily in adults predicted median (interquartile range [IQR]) stavudine triphosphate minimum drug concentration (C _min) and maximum drug concentration (C _max) values of 13 (10 to 19) and 45 (38 to 53) fmol/10⁶ cells, respectively. Targeting this exposure, simulations in HIV⁺ children were used to identify a suitable weight-band dosing approach (0.5 to 0.75 mg/kg), which was predicted to achieve median (IQR) C _min and C _max values of 13 (9 to 18) and 49 (40 to 58) fmol/10⁶ cells, respectively. Weight-band dosing using a stavudine dose of 0.5 to 0.75 mg/kg is proposed, and it shows comparable exposures to adults receiving the current WHO-recommended dose of 30 mg twice daily. Our pharmacokinetic results suggest that the decreased stavudine dose in children >2 years would have a reduced toxic effect while retaining antiretroviral efficacy.

Population pharmacokinetics of serelaxin in patients with acute or chronic heart failure, hepatic or renal impairment, or portal hypertension and in healthy subjects

AIMS

Serelaxin is a recombinant human relaxin-2 peptide being developed for the treatment of acute heart failure (AHF). The present analyses aimed to evaluate serelaxin pharmacokinetics following intravenous administration and to identify covariates that may explain pharmacokinetic variability in healthy subjects and patients.

METHODS

Serum concentration-time data for 613 subjects from nine phase I and II studies were analysed using a nonlinear mixed-effects model to estimate population pharmacokinetics and identify significant covariates. A quantile regression analysis was also conducted to assess the relationship between clearance and covariates by including sparse data from a phase III study.

RESULTS

A three-compartment disposition model was established to describe serelaxin pharmacokinetics. Three out of 23 covariates, including baseline body mass index (BMI) and estimated glomerular filtration rate (eGFR) and study A1201, were identified as significant covariates for clearance but with a moderate impact on steady-state concentration, reducing the intersubject variability from 44% in the base model to 41% in the final model with covariates. The steady-state volume of distribution (Vss) was higher in patients with AHF (544 ml kg^-1 ) or chronic heart failure (434 ml kg^-1 ), compared with typical nonheart failure subjects (347 ml kg^-1 ). Quantile regression analysis showed that a 20% increase in BMI or a 20% decrease in eGFR decreased serelaxin clearance by 9.2% or 5.2%, respectively.

CONCLUSIONS

Patients with HF showed higher Vss but similar clearance (and therefore steady-state exposure) vs. non nonheart failure subjects. BMI and eGFR were identified as the main covariates explaining intersubject variability in clearance; however, the impact of these covariates on steady-state concentration was moderate and therefore unlikely to be clinically relevant.

Analysis of variability in length of sleep state bouts reveals memory-free sleep subcomponents consistent among primary insomnia patients

The statistical distributions of bout lengths for the different (macro) sleep states (wake, N1, N2, N3, and REM sleep) are essential to understanding whether any memory-free subcomponent ("micro state") is involved in the organization of sleep. Micro state detection can be prevented by the fusion of data including various sources of variability, in particular by the differences in sleep architecture between individuals, along sleep time (or nighttime), or between different nights. In this analysis, a mathematical model of sleep was adopted to disentangle these features and advance the understanding of the dynamics and mechanisms of sleep and its states. The analysis involved 116 primary insomnia patients taking placebo before going to bed and undergoing polysomnography for one night. The individual sequences of macro sleep states had been previously modeled with a mixed-effect nonhomogeneous modified Markov chain model, from which individual conditional probability distributions for the bout durations were derived in this analysis as functions of sleep time. The probability distributions, affected by neither subject, night-time, nor multiple-night pooling, substantially changed at ¼ and ¾ sleep time, had modified exponential shape, and were best described as the sum of one to four exponentials, depending on the sleep state. The time constants and proportions of bouts contributing to each exponential were similar in the different subjects, changing over sleep time. Variability in bout durations thus indicated the presence of multiple memory-free sleep subcomponents whose mean residence times and access probabilities could be identified and shown to be consistent among the studied subjects. NEW & NOTEWORTHY We present a new methodology for deriving, from polysomnography data, the individual conditional probability for the duration of the bouts of wake, N1, N2, N3, and REM sleep. We evaluated the variability of this probability within and between primary insomnia patients and along sleep time. The multiexponential shapes of the probability distributions within the individuals revealed memory-free mechanisms and sleep subcomponents with consistent features in the studied population.

Pharmacokinetics and Drug-Drug Interactions of Lopinavir-Ritonavir Administered with First- and Second-Line Antituberculosis Drugs in HIV-Infected Children Treated for Multidrug-Resistant Tuberculosis

Lopinavir-ritonavir forms the backbone of current first-line antiretroviral regimens in young HIV-infected children. As multidrug-resistant (MDR) tuberculosis (TB) frequently occurs in young children in high-burden TB settings, it is important to identify potential interactions between MDR-TB treatment and lopinavir-ritonavir. We describe the pharmacokinetics of and potential drug-drug interactions between lopinavir-ritonavir and drugs routinely used for MDR-TB treatment in HIV-infected children. A combined population pharmacokinetic model was developed to jointly describe the pharmacokinetics of lopinavir and ritonavir in 32 HIV-infected children (16 with MDR-TB receiving treatment with combinations of high-dose isoniazid, pyrazinamide, ethambutol, ethionamide, terizidone, a fluoroquinolone, and amikacin and 16 without TB) who were established on a lopinavir-ritonavir-containing antiretroviral regimen. One-compartment models with first-order absorption and elimination for both lopinavir and ritonavir were combined into an integrated model. The dynamic inhibitory effect of the ritonavir concentration on lopinavir clearance was described using a maximum inhibition model. Even after adjustment for the effect of body weight with allometric scaling, a large variability in lopinavir and ritonavir exposure, together with strong correlations between the pharmacokinetic parameters of lopinavir and ritonavir, was detected. MDR-TB treatment did not have a significant effect on the bioavailability, clearance, or absorption rate constants of lopinavir or ritonavir. Most children (81% of children with MDR-TB, 88% of controls) achieved therapeutic lopinavir trough concentrations (>1 mg/liter). The coadministration of lopinavir-ritonavir with drugs routinely used for the treatment of MDR-TB was found to have no significant effect on the key pharmacokinetic parameters of lopinavir or ritonavir. These findings should be considered in the context of the large interpatient variability found in the present study and the study's modest sample size.