Nonlinear Mixed-effects Modeling Research Articles

CYP2D6 Phenotype Influences Pharmacokinetic Parameters of Venlafaxine: Results from a Population Pharmacokinetic Model in Older Adults with Depression.

In this study, we aimed to improve upon a published population pharmacokinetic (PK) model for venlafaxine (VEN) in the treatment of depression in older adults, then investigate whether CYP2D6 metabolizer status affected model-estimated PK parameters of VEN and its active metabolite O-desmethylvenlafaxine. The model included 325 participants from a clinical trial in which older adults with depression were treated with open-label VEN (maximum 300 mg/day) for 12 weeks and plasma levels of VEN and O-desmethylvenlafaxine were assessed at weeks 4 and 12. We fitted a nonlinear mixed-effect PK model using NONMEM to estimate PK parameters for VEN and O-desmethylvenlafaxine adjusted for CYP2D6 metabolizer status and age. At both lower doses (up to 150 mg/day) and higher doses (up to 300 mg/day), CYP2D6 metabolizers impacted PK model-estimated VEN clearance, VEN exposure, and active moiety (VEN + O-desmethylvenlafaxine) exposure. Specifically, compared with CYP2D6 normal metabolizers, (i) CYP2D6 ultra-rapid metabolizers had higher VEN clearance; (ii) CYP2D6 intermediate metabolizers had lower VEN clearance; (iii) CYP2D6 poor metabolizers had lower VEN clearance, higher VEN exposure, and higher active moiety exposure. Overall, our study showed that including a pharmacogenetic factor in a population PK model could increase model fit, and this improved model demonstrated how CYP2D6 metabolizer status affected VEN-related PK parameters, highlighting the importance of genetic factors in personalized medicine.

Characterization and Determinants of Long-Term Immune Recovery Under Suppressive Antiretroviral Therapy.

We developed a robust characterization of immune recovery trajectories in people living with HIV on antiretroviral treatment (ART) and relate our findings to epidemiological risk factors and bacterial pneumonia. Using data from the Swiss HIV Cohort Study and the Zurich Primary HIV Infection Cohort Study (n = 5907), we analyzed the long-term trajectories of CD4 cell and CD8 cell counts and their ratio in people living with HIV on ART for at least 8 years by fitting nonlinear mixed-effects models. The determinants of long-term immune recovery were investigated using generalized additive models. In addition, prediction accuracy of the modeled trajectories and their impact on the fit of a model for bacterial pneumonia was assessed. Overall, our population showed good immune recovery (median plateau [interquartile range]-CD4: 718 [555-900] cells/μL, CD8: 709 [547-893] cells/μL, CD4/CD8: 1.01 [0.76-1.37]). The following factors were predictive of recovery: age, sex, nadir/zenith value, pre-ART HIV-1 viral load, hepatitis C, ethnicity, acquisition risk, and timing of ART initiation. The fitted models proved to be an accurate and efficient way of predicting future CD4 and CD8 cell recovery dynamics: Compared with carrying forward the last observation, mean squared errors of the fitted values were lower by 1.3%-18.3% across outcomes. When modeling future episodes of bacterial pneumonia, using predictors derived from the recovery dynamics improved most model fits. We described and validated a method to characterize individual immune recovery trajectories of people living with HIV on suppressive ART. These trajectories accurately predict long-term immune recovery and the occurrence of bacterial pneumonia.

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.Graphical

Why the racing industry and equestrian disciplines need to implement population pharmacokinetics: To learn, explain, summarize, harmonize, and individualize.

Population pharmacokinetics (POP PK) is a powerful pharmacokinetic tool, which measures quantitatively, and explains the variability in drug exposure and drug effect between individuals. POP PK uses an observational (nonexperimental) approach; it is conducted in the target population living in its normal environment (e.g., farm and race-track). The strength of the POP PK approach lies in its greater relevance for the population studied in its different natural environments than experimental studies carried out in more or less biased laboratory conditions. In clinical settings, it is commonly necessary to restrict the number of samples per subject collected for analysis and the derived data cannot be analyzed using traditional individual data analytical methods; rather data are merged and analyzed with an appropriate statistical tool: the nonlinear mixed effect model (NLMEM). POP PK modeling is frequently used with the objective of adjusting drug dosage, and hence drug exposure, not only for the whole population but also for subgroups of animals (e.g., for a given breed, sex, and age). It can also have application at the individual subject level, in the context of precision medicine. For horses, the use of the POP PK/PD model will allow prescribers to estimate an individual Withdrawal Time for a given horse whose treatment they are supervising. Another potential field of application will be meta-analysis of existing data to generate new knowledge on a drug or to collate and synthesize, in an objective and transparent manner, existing data; this will facilitate harmonization of screening limits at an international level.

Pharmacokinetic Models for Inhaled Fluticasone Propionate and Salmeterol Xinafoate to Quantify Batch-to-Batch Variability.

Advair Diskus is an essential treatment for asthma and chronic obstructive pulmonary disease. It is a dry powder inhaler with a combination of fluticasone propionate (FP) and salmeterol xinafoate (SX). However, the pharmacokinetics (PK) batch-to-batch variability of the reference-listed drug (RLD) hindered its generic product development. This work developed the PK models for inhaled FP and SX that could represent potential batch variability. Two batches each of the reference and the test product (R1, R2, T1, T2) of Advair Diskus (100μg FP/50μg SX inhalation) were administered to 60 healthy subjects in a 4-period, 4-sequence crossover study. The failure of the bioequivalence (BE) between R1 and R2 confirmed the high between-batch variability of the RLD. Non-linear mixed effect modeling was used to estimate the population mean PK parameters for each batch. For FP, a 2-compartment model with a sequential dual zero-order absorption best described the PK profile. For SX, a 2-compartment model with a first-order absorption model best fit the data. Both models were able to capture the plasma concentration, the maximum concentration, and the total exposure (AUCinf) adequately for each batch, which could be used to simulate the BE study in the future. In vitro properties were also measured for each batch, and the batch with a higher fraction of the fine particle (diameter < 1µm, < 2µm) had a higher AUCinf. This positive correlation for both FP and SX could potentially assist the batch selection for the PK BE study.

Uncertainty Computation at Finite Distance in Nonlinear Mixed Effects Models-a New Method Based on Metropolis-Hastings Algorithm.

The standard errors (SE) of the maximum likelihood estimates (MLE) of the population parameter vector in nonlinear mixed effect models (NLMEM) are usually estimated using the inverse of the Fisher information matrix (FIM). However, at a finite distance, i.e. far from the asymptotic, the FIM can underestimate the SE of NLMEM parameters. Alternatively, the standard deviation of the posterior distribution, obtained in Stan via the Hamiltonian Monte Carlo algorithm, has been shown to be a proxy for the SE, since, under some regularity conditions on the prior, the limiting distributions of the MLE and of the maximum a posterior estimator in a Bayesian framework are equivalent. In this work, we develop a similar method using the Metropolis-Hastings (MH) algorithm in parallel to the stochastic approximation expectation maximisation (SAEM) algorithm, implemented in the saemix R package. We assess this method on different simulation scenarios and data from a real case study, comparing it to other SE computation methods. The simulation study shows that our method improves the results obtained with frequentist methods at finite distance. However, it performed poorly in a scenario with the high variability and correlations observed in the real case study, stressing the need for calibration.

Leishmania blood parasite dynamics during and after treatment of visceral leishmaniasis in Eastern Africa: A pharmacokinetic-pharmacodynamic model.

With the current treatment options for visceral leishmaniasis (VL), recrudescence of the parasite is seen in a proportion of patients. Understanding parasite dynamics is crucial to improving treatment efficacy and predicting patient relapse in cases of VL. This study aimed to characterize the kinetics of circulating Leishmania parasites in the blood, during and after different antileishmanial therapies, and to find predictors for clinical relapse of disease. Data from three clinical trials, in which Eastern African VL patients received various antileishmanial regimens, were combined in this study. Leishmania kinetoplast DNA was quantified in whole blood with real-time quantitative PCR (qPCR) before, during, and up to six months after treatment. An integrated population pharmacokinetic-pharmacodynamic model was developed using non-linear mixed effects modelling. Parasite proliferation was best described by an exponential growth model, with an in vivo parasite doubling time of 7.8 days (RSE 12%). Parasite killing by fexinidazole, liposomal amphotericin B, sodium stibogluconate, and miltefosine was best described by linear models directly relating drug concentrations to the parasite elimination rate. After treatment, parasite growth was assumed to be suppressed by the host immune system, described by an Emax model driven by the time after treatment. No predictors for the high variability in onset and magnitude of the immune response could be identified. Model-based individual predictions of blood parasite load on Day 28 and Day 56 after start of treatment were predictive for clinical relapse of disease. This semi-mechanistic pharmacokinetic-pharmacodynamic model adequately captured the blood parasite dynamics during and after treatment, and revealed that high blood parasite loads on Day 28 and Day 56 after start of treatment are an early indication for VL relapse, which could be a useful biomarker to assess treatment efficacy of a treatment regimen in a clinical trial setting.

Time-Varying Clearance in Milrinone Pharmacokinetics from Premature Neonates to Adolescents.

Milrinone is an inotrope and vasodilator used for prophylaxis or treatment of low cardiac output syndrome after weaning from cardiopulmonary bypass (CPB). It is renally eliminated and has an acceptable therapeutic range of 100-300μg/L, but weight-based dosing alone is associated with poor target attainment. We aimed to develop a population pharmacokinetic model for milrinone from premature neonates to adolescents, and to evaluate how age, renal function and recovery from CPB may impact dose selection. Fifty paediatric patients (aged 4 days to 16 years) were studied after undergoing cardiac surgery supported by CPB. Data from 29 premature neonates (23-28 weeks' postmenstrual age) treated for prophylaxis of low systemic blood flow were available for a pooled pharmacokinetic analysis. Population parameters were estimated using non-linear mixed effects modelling (NONMEM 7.5.1). There were 369 milrinone measurements available for analysis. A one-compartment model with zero-order input and first-order elimination was used to describe milrinone disposition. Population parameters were clearance 17.8L/70kg [95% CI 15.8-19.9] and volume 20.4L/h/70kg [95% CI 17.8-22.1]. Covariates included size, postmenstrual age and renal function for clearance, and size and postnatal age for volume. Milrinone clearance is reduced by 39.5% [95% CI 24.0-53.7] immediately after bypass, and recovers to baseline clearance with a half-time of 12.0h [95% CI 9.7-15.2]. Milrinone volume was 2.07 [95% CI 1.87-2.27] times greater at birth than the population standard and decreased over the first days of life with a half-time of 0.977days [95% CI 0.833-1.12]. Milrinone is predominately renally eliminated and so renal function is an important covariate describing variability in clearance. Increasing clearance over time likely reflects increasing cardiac output and renal perfusion due to milrinone and return to baseline following CPB.

Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles.

The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 modelvariables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.

Saliva monitoring of prednisolone in children with first onset steroid-sensitive nephrotic syndrome: Is it possible?

Prednisolone is the cornerstone of treatment for idiopathic nephrotic syndrome in children, but is associated with marked side-effects. Therapeutic drug monitoring using saliva would be a patient-friendly option to monitor prednisolone treatment. To assess the feasibility of saliva monitoring, we described the pharmacokinetics (PK) of unbound prednisolone in plasma and saliva of children with first onset steroid-sensitive nephrotic syndrome (SSNS). Children (age 2-16 years) with SSNS participating in a randomized, placebo-controlled trial with levamisole were treated with an 18-week tapering schedule of prednisolone. Five serial samples were collected at 4 (saliva) and 8weeks (saliva and plasma) after first onset. A nonlinear mixed-effects model was used to estimate the PK parameters of unbound prednisolone and the saliva-to-plasma ratio. Monte Carlo simulations were performed to assess the predictive performance of saliva monitoring. From 39 children, 109 plasma and 275 saliva samples were available. Estimates (relative squared error) of unbound plasma clearance and volume of distribution were 93 (5%) L h-1 70 kg-1 and 158 (7%) L 70 kg-1, respectively. Typical saliva-to-plasma ratio was 1.30 (8%). Monte Carlo simulations demonstrated that on basis of 4 saliva samples and a single plasma sample unbound plasma area-under-the-concentration-time curve can be predicted within 20% imprecision in 79% of the patients compared to 87% based on 4 plasma samples. Saliva proved to be a reliable and patient-friendly option to determine prednisolone plasma exposure in children with SSNS. This opens opportunities for further PK and pharmacodynamics studies of prednisolone in a variety of paediatric conditions.

Correction to: Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm

Correction to: Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm

Population pharmacokinetics and dosing optimization of perampanel in children with epilepsy: A real-world study.

The purposes of this study were to explore the pharmacokinetics of perampanel (PER) in children with epilepsy, identify factors that contribute to pharmacokinetic variations among subjects, evaluate the connection between PER exposure and clinical outcome, and establish an evidence-based approach for tailoring individualized antiepileptic treatment in this specific population. In this prospective study, PER plasma concentrations and genetic information on metabolic enzymes were obtained from 194 patients younger than 18 years. The disposition kinetics of PER in pediatric patients following oral dosing were characterized using nonlinear mixed effect models. The effective range for the plasma concentration of PER was determined by assessing the efficacy and safety of PER treatment and analyzing the relationship between drug exposure and clinical response. Monte Carlo simulations were then performed to evaluate and optimize the current dosing regimens. The pharmacokinetic profile of PER was adequately described by a one-compartment model with first-order absorption and elimination. Body weight, total bilirubin level, and concomitant oxcarbazepine were found to have significant influences on PER pharmacokinetics. Model estimates of apparent clearance and volume of distribution were .016 ± .009 L/h/kg and 1.47 ± .78 L/kg, respectively. The effective range predicted from plasma concentration data in responders was 215-862 μg/L. Dosing scenarios stratified according to essential covariates were proposed through simulation analysis. In this study, we captured the pharmacokinetic/pharmacodynamic characteristics of PER in pediatric epilepsy patients through analysis of real-world data and adopted a pharmacometric approach to support an individualized dosing strategy for PER in this specific population.

High-Dose Isoniazid Lacks EARLY Bactericidal Activity against Isoniazid-resistant Tuberculosis Mediated by katG Mutations: A Randomized Phase II Clinical Trial.

Rationale: Observational studies suggest that high-dose isoniazid may be efficacious in treating multidrug-resistant tuberculosis. However, its activity against Mycobacterium tuberculosis (M.tb) with katG mutations (which typically confer high-level resistance) is not established. Objectives: To characterize the early bactericidal activity (EBA) of high-dose isoniazid in patients with tuberculosis caused by katG-mutated M.tb. Methods: A5312 was a phase IIA randomized, open-label trial. Participants with tuberculosis caused by katG-mutated M.tb were randomized to receive 15 or 20 mg/kg isoniazid daily for 7 days. Daily sputum samples were collected for quantitative culture. Intensive pharmacokinetic sampling was performed on Day 6. Data were pooled across all A5312 participants for analysis (drug-sensitive, inhA-mutated, and katG-mutated M.tb). EBA was determined using nonlinear mixed-effects modeling. Measurements and Main Results: Of 80 treated participants, 21 had katG-mutated M.tb. Isoniazid pharmacokinetics were best described by a two-compartment model with an effect of NAT2 acetylator phenotype on clearance. Model-derived maximum concentration and area under the concentration-time curve in the 15 and 20 mg/kg groups were 15.0 and 22.1 mg/L and 57.6 and 76.8 mg ⋅ h/L, respectively. Isoniazid bacterial kill was described using an effect compartment and a sigmoidal maximum efficacy relationship. Isoniazid potency against katG-mutated M.tb was approximately 10-fold lower than in inhA-mutated M.tb. The highest dose of 20 mg/kg did not demonstrate measurable EBA, except against a subset of slow NAT2 acetylators (who experienced the highest concentrations). There were no grade 3 or higher drug-related adverse events. Conclusions: This study found negligible bactericidal activity of high-dose isoniazid (15-20 mg/kg) in the majority of participants with tuberculosis caused by katG-mutated M.tb. Clinical trial registered with www.clinicaltrials.gov (NCT01936831).

Population pharmacokinetic study of imipramine in Taiwan people healthy volunteers

Imipramine is an antidepressant drug (ADs) that shows therapeutic efficacy in a maximum of 60–80% of patients who have experienced a major depressive episode (unipolar or bipolar). The purpose of the study was to investigate the pharmacokinetics of a multi-oral dose of Imipramine 25 mg tablet in a Taiwan healthy population. The study was a standard two-way, crossover, randomized, and single dose daily for 5 days study with a two-week washout period in 30 healthy volunteers who received 25 mg imipramine tablets (test and reference formulation). After drug administration, blood samples were taken according to the planned times over a period of 24 hours. The plasma concentrations of Imipramine were determined using the validated high-performance liquid chromatography method with ultraviolet detection. All the pharmacokinetic parameters for Imipramine in healthy volunteers were calculated using nonlinear mixed-effect modeling and standard non-compartmental methods. Values (relative standard error (RSE) %) for first-order absorption rate constant (Ka), oral clearance (Cl/F), and apparent volume of distribution (Vd/F) were 1.05 (7.11) 1/h, 6.99(0.27) L/h, and 71.7.9(4.80) L. The median for the time to peak plasma Imipramine concentration (Tmax) for the test and reference drug was 2(1.1-4) hours and 4(1.9-5) hours respectively. In conclusion, the imipramine pharmacokinetic model in the Taiwan healthy population was similar to other studied populations.

Pharmacokinetics of PEGasparaginase in Infants with Acute Lymphoblastic Leukemia.

PEGasparaginase is known to be a critical drug for treating pediatric acute lymphoblastic leukemia (ALL), however, there is insufficient evidence to determine the optimal dose for infants who are less than one year of age at diagnosis. This international study was conducted to identify the pharmacokinetics of PEGasparaginase in infants with newly diagnosed ALL and gather insight into the clearance and dosing of this population. Infants with ALL who received treatment with PEGasparaginase were included in our population pharmacokinetic assessment employing non-linear mixed effects modelling (NONMEM). 68 infants with ALL, with a total of 388 asparaginase activity samples, were included. PEGasparaginase doses ranging from 400 to 3,663IU/m2 were administered either intravenously or intramuscularly. A one-compartment model with time-dependent clearance, modeled using a transit model, provided the best fit to the data. Body weight was significantly correlated with clearance and volume of distribution. The final model estimated a half-life of 11.7days just after administration, which decreased to 1.8days 14days after administration. Clearance was 19.5% lower during the post-induction treatment phase compared to induction. The pharmacokinetics of PEGasparaginase in infants diagnosed under one year of age with ALL is comparable to that of older children (1-18years). We recommend a PEGasparaginase dosing at 1,500IU/m2 for infants without dose adaptations according to age, and implementing therapeutic drug monitoring as standard practice.

Population longitudinal analysis of Gait Profile Score and North Star Ambulatory Assessment in children with Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is a rare X-linked recessive disorder characterized by loss-of-function mutations in the gene encoding dystrophin. These mutations lead to progressive functional deterioration including muscle weakness, respiratory insufficiency, and musculoskeletal deformities. Three-dimensional gait analysis (3DGA) has been used as a tool to analyze gait pathology through the quantification of altered joint kinematics, kinetics, and muscle activity patterns. Among 3DGA indices, the Gait Profile Score (GPS), has been used as a sensitive overall measure to detect clinically relevant changes in gait patterns in children with DMD. To enhance our understanding of the clinical translation of 3DGA, we report here the development of a population nonlinear mixed-effect model that jointly describes the disease progression of the 3DGA index, GPS, and the functional endpoint, North Star Ambulatory Assessment (NSAA). The final model consists of a quadratic structure for GPS progression and a linear structure for GPS-NSAA correlation. Our model was able to capture the improvement in function in GPS and NSAA in younger subjects, as well as the decline of function in older subjects. Furthermore, the model predicted NSAA (CFB) at 1 year reasonably well for DMD subjects ≤7 years old at baseline. The model tended to slightly underpredict the decline in NSAA after 1 year for those >7 years old at baseline, but the prediction summary statistics were well maintained within the standard deviation of observed data. Quantitative models such as this may help answer clinically relevant questions to facilitate the development of novel therapies in DMD.

The pharmacokinetics and pharmacodynamics of ibogaine in opioid use disorder patients.

Ibogaine is a hallucinogenic drug that may be used to treat opioid use disorder (OUD). The relationships between pharmacokinetics (PKs) of ibogaine and its metabolites and their clinical effects on side effects and opioid withdrawal severity are unknown. We aimed to study these relationships in patients with OUD undergoing detoxification supported by ibogaine. The study was performed in 14 subjects with OUD. They received a single dose of 10mg/kg ibogaine hydrochloride. Plasma PKs of ibogaine, noribogaine, and noribogaine glucuronide were obtained during 24 h. Cytochrome P450 isoenzyme 2D6 (CYP2D6) genotyping was performed. The PKs were analyzed by means of nonlinear mixed effects modeling and related with corrected QT interval (QTc) prolongation, cerebellar ataxia, and opioid withdrawal severity. The PK of ibogaine were highly variable and significantly correlated to CYP2D6 genotype (p < 0.001). The basic clearance of ibogaine (at a CYP2D6 activity score (AS) of 0) was 0.82 L/h. This increased with 30.7 L/h for every point of AS. The relation between ibogaine plasma concentrations and QTc was best described by a sigmoid Emax model. Spearman correlations were significant (p < 0.03) for ibogaine but not noribogaine with QTc (p = 0.109) and cerebellar effects (p = 0.668); neither correlated with the severity of opioid withdrawal symptoms. The clearance of ibogaine is strongly related to CYPD2D6 genotype. Ibogaine cardiac side effects (QTc time) and cerebellar effects are most likely more driven by ibogaine rather than noribogaine. Future studies should aim at exploring lower doses and/or applying individualized dosing based on CYP2D6 genotype.

Population pharmacokinetics of a novel PCSK9 antisense oligonucleotide.

The aim of this study was to characterize the population pharmacokinetics of AZD8233, an antisense oligonucleotide (ASO) that targets the PCSK9 transcript to reduce hepatocyte PCSK9 protein production and plasma levels. AZD8233 utilizes generation 2.5S-constrained ethyl motif (cET) chemistry and is conjugated to a triantennary N-acetylgalactosamine (GalNAc3) ligand for targeted hepatocyte uptake. A non-linear mixed-effect modelling approach utilizing NONMEM software was applied to AZD8233 concentration-time data from 3416 samples in 219 participants from four phase 1-2 studies, one in healthy volunteers (NCT03593785) and three in patients with dyslipidaemia (NCT04155645, NCT04641299 and NCT04823611). The final model described the AZD8233 plasma concentration-time profile from four phase 1-2 studies in healthy volunteers or participants with dyslipidaemia, covering a dose range of 4 to 120 mg. The pharmacokinetics of AZD8233 were adequately described by a two-compartment model with first-order absorption. The supra-proportional increase in maximum plasma concentration (Cmax) across the observed dose range was described by non-linear Michaelis-Menten elimination (maximum elimination rate, 9.9mg/h [12% relative standard error]; concentration yielding half-maximal elimination rate, 4.8mg/L [18% relative standard error]). Body weight, sex, estimated glomerular filtration rate and disease status (healthy participant vs. patient with dyslipidaemia) were identified as factors affecting exposure to AZD8233. Covariate analysis showed body weight to be the main factor affecting exposure to AZD8233, which largely explained the higher Cmax observed in the Asian population relative to non-Asians.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort.

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

Pharmacokinetics of propofol in severely obese surgical patients.

Existing PK models of propofol include sparse data from very obese patients. The aim of this study was to develop a PK model based on standardised surgical conditions and spanning from normal-weight up to, and including, a high number of very obese patients. Adult patients scheduled for laparoscopic cholecystectomy or bariatric surgery were studied. Anaesthesia was induced with propofol 2 mg/kg adjusted body weight over 2 min followed by 6 mg/kg/h adjusted body weight over 30 min. For the remainder of the operation anaesthesia was maintained with sevoflurane. Remifentanil was dosed according to clinical need. Eight arterial samples were drawn in a randomised block sampling regimen over a span of 24 h. Time-concentration data were analysed by population PK modelling using non-linear mixed-effects modelling. Four hundred and seventy four serum propofol concentrations were collected from 69 patients aged 19-60 years with a BMI 21.6-67.3 kg/m2. Twenty one patients had a BMI above 50 kg/m2. A 3-compartment PK model was produced wherein three different body weight descriptors and sex were included as covariates in the final model. Total body weight was found to be a covariate for clearance and Q3; lean body weight for V1, V2 and Q2; predicted normal weight for V3 and sex for V1. The fixed allometric exponent of 0.75 applied to all clearance parameters improved the performance of the model. Accuracy and precision were 1.4% and 21.7% respectively in post-hoc performance evaluation. We have developed a new PK model of propofol that is suitable for all adult weight classes. Specifically, it is based on data from an unprecedented number of individuals with very high BMI.