Confirmatory analysis for phase III population pharmacokinetics

Sabatolimab (MBG453) model-informed drug development for dose selection in patients with myelodysplastic syndrome/acute myeloid leukemia and solid tumors

Sabatolimab is a novel immunotherapy with immuno-myeloid activity that targets T-cell immunoglobulin domain and mucin domain-3 (TIM-3) on immune cells and leukemic blasts. It is being evaluated for the treatment of myeloid malignancies in the STIMULUS clinical trial program. The objective of this analysis was to support the sabatolimab dose-regimen selection in hematologic malignancies. A population pharmacokinetic (PopPK) model was fit to patients with solid tumors and hematologic malignancies, which included acute myeloid leukemia, myelodysplastic syndrome (including intermediate-, high-, and very high-risk per Revised International Prognostic Scoring System), and chronic myelomonocytic leukemia. The PopPK model, together with a predictive model of sabatolimab distribution to the bone marrow and binding to TIM-3 was used to predict membrane-bound TIM-3 bone marrow occupancy. In addition, the total soluble TIM-3 (sTIM-3) kinetics and the pharmacokinetic (PK) exposure-response relationship in patients with hematologic malignancies were examined. At intravenous doses above 240 mg Q2w and 800 mg Q4w, we observed linear PK, a plateau in the accumulation of total sTIM-3, and a flat exposure-response relationship for both safety and efficacy. In addition, the model predicted membrane-bound TIM-3 occupancy in the bone marrow was above 95% in over 95% of patients. Therefore, these results support the selection of the 400 mg Q2w and 800 mg Q4w dosing regimens for the STIMULUS clinical trial program.

A model-based approach to predict individual weight loss with semaglutide in people with overweight or obesity

AIMS

To determine the relationship between exposure and weight-loss trajectories for the glucagon-like peptide-1 analogue semaglutide for weight management.

MATERIALS AND METHODS

Data from one 52-week, phase 2, dose-ranging trial (once-daily subcutaneous semaglutide 0.05-0.4 mg) and two 68-week phase 3 trials (once-weekly subcutaneous semaglutide 2.4 mg) for weight management in people with overweight or obesity with or without type 2 diabetes were used to develop a population pharmacokinetic (PK) model describing semaglutide exposure. An exposure-response model describing weight change was then developed using baseline demographics, glycated haemoglobin and PK data during treatment. The ability of the exposure-response model to predict 1-year weight loss based on weight data collected at baseline and after up to 28 weeks of treatment, was assessed using three independent phase 3 trials.

RESULTS

Based on population PK, exposure levels over time consistently explained the weight-loss trajectories across trials and dosing regimens. The exposure-response model had high precision and limited bias for predicting body weight loss at 1 year in independent datasets, with increased precision when data from later time points were included in the prediction.

CONCLUSION

An exposure-response model has been established that quantitatively describes the relationship between systemic semaglutide exposure and weight loss and predicts weight-loss trajectories for people with overweight or obesity who are receiving semaglutide doses up to 2.4 mg once weekly.

Model-Based Analysis of IGF-I Response, Dosing, and Monitoring for Once-Weekly Somapacitan in Children With GH Deficiency

Context

Growth hormone (GH) replacement therapy improves longitudinal growth and adult height in children with GH deficiency (GHD). GH stimulates insulin-like growth factor (IGF)-I release, the biomarker used for monitoring GH activity during treatment.

Objective

This study aims to provide model-based insights into the dose-IGF-I responses of once-weekly somapacitan, a novel long-acting GH, compared with daily GH in children with GHD.

Methods

Analyses included dosing information and 1473 pharmacokinetic samples from 210 somapacitan-treated pediatric patients with GHD across 3 trials, including phase 1 (NCT01973244), phase 2 (NCT02616562; REAL 3), and phase 3 (NCT03811535; REAL 4), as well as 1381 IGF-I samples from 186 patients with GHD treated with somapacitan in REAL 3 and REAL 4. Pharmacokinetic/pharmacodynamic modeling to characterize somapacitan dose-IGF-I response and predict the response to dosing day changes.

Results

Relationships were established between somapacitan dose, exposure, change from baseline IGF-I SD score (SDS), and height velocity (HV). A linear model permitted the development of a tool to calculate estimated average weekly IGF-I exposure from a single IGF-I sample obtained at any time within the somapacitan dosing interval at steady state. In practice, the use of this tool requires knowledge of somapacitan injection timing relative to IGF-I sample collection timing. IGF-I SDS simulations support flexible dosing day changes while maintaining at least 4 days between doses.

Conclusion

We characterized the dose-IGF-I response of somapacitan in children with GHD. To support physicians in IGF-I monitoring, we present a practical guide about expected weekly average IGF-I concentrations in these patients and provide insights on dosing day flexibility.

Latent variable indirect response modeling of clinical efficacy endpoints with combination therapy: application to guselkumab and golimumab in patients with ulcerative colitis

Accurate characterization of longitudinal exposure-response of clinical trial endpoints is important in optimizing dose and dosing regimens in drug development. Clinical endpoints are often categorical, for which much progress has been made recently in latent variable indirect response (IDR) modeling with single drugs. However, such applications have not yet been used for trials employing multiple drugs administered concurrently. This study aims to demonstrate that the latent variable IDR approach provides a convenient longitudinal exposure-response modeling framework to assess potential interaction effects of combination therapies. This is illustrated by an application to the exposure-response modeling of guselkumab, a monoclonal antibody in clinical development that blocks the interleukin-23p19 subunit, and golimumab, a monoclonal antibody that binds with high affinity to tumor necrosis factor-alpha. A Phase 2a study was conducted in 214 patients with moderate-to severe active ulcerative colitis for which longitudinal assessments of disease severity based on patient-reported measures of rectal bleeding, stool frequency, and symptomatic remission were evaluated as categorical endpoints, and fecal calprotectin as a continuous endpoint. The modeling results suggested independent pharmacodynamic guselkumab and golimumab effects on fecal calprotectin as a continuous endpoint, as well as interaction effects on the categorical endpoints that may be explained by an additional pathway of competitive interaction.

Improving categorical endpoint longitudinal exposure-response modeling through the joint modeling with a related endpoint

Exposure-response modeling is important to optimize dose and dosing regimens in clinical drug development. While primary clinical trial endpoints often have few categories and thus provide only limited information, sometimes there may be additional, more informative endpoints. Benefits of fully incorporating relevant information in longitudinal exposure-response modeling through joint modeling have recently been shown. This manuscript aims to further investigate the benefit of joint modeling of an ordered categorical primary endpoint with a related near-continuous endpoint, through the sharing of model parameters in the latent variable indirect response (IDR) modeling framework. This is illustrated by analyzing the data collected through up to 116 weeks from a phase 3b response-adaptive trial of ustekinumab in patients with psoriasis. The primary endpoint was based on the 6-point physician's global assessment (PGA) score. The Psoriasis area and severity Index (PASI) data, ranging from 0 to 72 with 0.1 increments, were also available. Separate and joint latent variable Type I IDR models of PGA and PASI scores were developed and compared. The results showed that the separate PGA model had a substantial structural bias, which was corrected by the joint modeling of PGA and PASI scores.

Impact of Pharmacokinetic and Pharmacodynamic Properties of Monoclonal Antibodies in the Management of Psoriasis

The treatment of psoriasis has been revolutionized by the emergence of biological therapies. Monoclonal antibodies (mAb) generally have complex pharmacokinetic (PK) properties with nonlinear distribution and elimination. In recent years, several population pharmacokinetic/pharmacodynamic (PK/PD) models capable of describing different types of mAb have been published. This study aims to summarize the findings of a literature search about population PK/PD modeling and therapeutic drug monitoring (TDM) of mAb in psoriasis. A total of 22 articles corresponding to population PK/PD models of tumor necrosis factor (TNF)-α inhibitors (adalimumab and golimumab), interleukin (IL)-23 inhibitors (guselkumab, tildrakizumab, and risankizumab), IL-23/IL-12 inhibitor (ustekinumab), and IL-17 inhibitors (secukinumab, ixekizumab, and brodalumab) were collected. A summary of the clinical trials conducted so far in psoriasis was included, together with the current structural population PK and PD models. The most significant and clinical covariates were body weight (BW) and the presence of immunogenicity on clearance (CL). The lack of consensus on PK/PD relationships has prevented establishing an adequate dosage and, therefore, accentuates the need for TDM in psoriasis.

Liraglutide pharmacokinetics and exposure-response in adolescents with obesity

BACKGROUND

Obesity in adolescence presents a major public health challenge, often leading to obesity in adulthood with associated chronic disease.

OBJECTIVES

This study aimed to perform a population pharmacokinetic and exposure-response analysis of liraglutide by meta-analysis of data from trials conducted in children, adolescents and adults with obesity.

METHODS

The population pharmacokinetic analysis investigated the effect of covariates body weight, age group (children, adolescents and adults) and sex on liraglutide exposure in adolescents compared with previous results in adults. The exposure-response relationship of liraglutide for the change from baseline in body mass index standard deviation score (BMI SDS) was evaluated in adolescents and compared to that in adults.

RESULTS

Body weight was the main covariate affecting liraglutide exposure, with lower exposures at higher body weights, whereas age group was of no importance and sex was of little importance. An exposure-response relationship was demonstrated for liraglutide in both adolescents and adults as the decrease in BMI SDS from baseline increased in an exposure-dependent manner with increasing liraglutide exposure.

CONCLUSIONS

The population pharmacokinetic analysis supported similar liraglutide exposures in adolescents and adults; body weight was the most important covariate affecting exposure. An exposure-response relationship was established for liraglutide.

Levels of circulating semaglutide determine reductions in HbA1c and body weight in people with type 2 diabetes

Glucagon-like peptide-1 receptor agonists (GLP-1RA) are used for the treatment of type 2 diabetes. Whether clinically important responses and adverse events (AEs) are dependent on the route of administration has not been determined. We demonstrate that nearly identical exposure-response pharmacodynamic relationships are determined by plasma semaglutide levels achieved through oral versus injectable administration for changes in HbA1c, body weight, biomarkers of cardiovascular risk, and AEs such as nausea and vomiting. At typical exposure levels for oral semaglutide, the estimated response is 1.58% (oral) versus -1.62% (subcutaneous) for HbA1c and 3.77% (oral) versus 3.48% (subcutaneous) reduction in body weight relative to baseline after 6 months. Increased body weight is the most important variable associated with reduced semaglutide exposure for both formulations. Hence, interindividual variation in GLP-1R responsivity or route of administration are not major determinants of GLP-1RA effectiveness in the clinic.

Design and conduct considerations for studies in patients with impaired renal function

An impaired renal function, including acute and chronic kidney disease and end‐stage renal disease, can be the result of aging, certain disease conditions, the use of some medications, or as a result of smoking. In patients with renal impairment (RI), the pharmacokinetics (PKs) of drugs or drug metabolites may change and result in increased safety risks or decreased efficacy. In order to make specific dose recommendations in the label of drugs for patients with RI, a clinical trial may have to be conducted or, when not feasible, modeling and simulations approaches, such as population PK modeling or physiologically‐based PK modelling may be applied. This tutorial aims to provide an overview of the global regulatory landscape and a practical guidance for successfully designing and conducting clinical RI trials or, alternatively, on applying modeling and simulation tools to come to a dose recommendation for patients with RI in the most efficient manner.

Application of Beta-Distribution and Combined Uniform and Binomial Methods in Longitudinal Modeling of Bounded Outcome Score Data

Disease status is often measured with bounded outcome scores (BOS) which takes a discrete set of values on a finite range. The distribution of such data is often skewed, rendering the standard analysis methods assuming normal distribution inappropriate. Among the methods used for BOS analyses, two of them have the ability to predict the data within its natural range and accommodate data skewness: (1) a recently proposed beta-distribution based approach and (2) a mixture model known as CUB (combined uniform and binomial). This manuscript compares the two approaches, using an established mechanism-based longitudinal exposure-response model to analyze data from a phase 2 clinical trial in psoriatic patients. The beta-distribution-based approach was confirmed to perform well, and CUB also showed potential. A separate issue of modeling clinical trial data is that the collected baseline disease score range may be more limited than that of post-treatment disease score due to clinical trial inclusion criteria, a fact that is typically ignored in longitudinal modeling. The effect of baseline disease status restriction should in principle be adjusted for in longitudinal modeling.

Population Pharmacokinetics and Exposure-Response Modeling Analyses of Ustekinumab in Adults With Moderately to Severely Active Ulcerative Colitis

To characterize the pharmacokinetics (PK) and exposure-response (E-R) relationship of ustekinumab, an anti-interleukin-12/interleukin-23 (IL-12/IL-23) human monoclonal antibody, in the treatment of moderately to severely active ulcerative colitis (UC), population PK and E-R modeling analyses were conducted based on the data from the pivotal phase 3 induction and maintenance studies in UC patients. The observed serum concentration-time data of ustekinumab were adequately described by a 2-compartment linear PK model with first-order absorption and first-order elimination. Body weight, baseline serum albumin, sex, and antibodies to ustekinumab were the covariates to influence ustekinumab PK, but the magnitudes of the effects of these covariates were not considered clinically relevant, and dose adjustment was not warranted. Positive E-R relationships were demonstrated between ustekinumab exposure metrics and clinical endpoints (including clinical response, clinical remission, and endoscopic healing based on Mayo score) at induction week 8 and maintenance week 44, consistent with the effectiveness of ustekinumab in the induction and maintenance treatment of patients with UC. E-R modeling results suggest that ustekinumab ∼6 mg/kg intravenous induction and 90-mg subcutaneous every-8-week maintenance dose would produce greater efficacy than the 130 mg intravenous induction and the 90-mg subcutaneous every-12-week maintenance regimen, respectively. Our work provides a comprehensive evaluation of ustekinumab PK and E-R in a modeling framework to support ustekinumab dose recommendations in patients with UC.

Tisagenlecleucel Model-Based Cellular Kinetic Analysis of Chimeric Antigen Receptor-T Cells

Tisagenlecleucel is a chimeric antigen receptor–T cell therapy that facilitates the killing of CD19⁺ B cells. A model was developed for the kinetics of tisagenlecleucel and the impact of therapies for treating cytokine release syndrome (tocilizumab and corticosteroids) on expansion. Data from two phase II studies in pediatric and young adult relapsed/refractory B cell acute lymphoblastic leukemia were pooled to evaluate this model and evaluate extrinsic and intrinsic factors that may impact the extent of tisagenlecleucel expansion. The doubling time, initial decline half‐life, and terminal half‐life for tisagenlecleucel were 0.78, 4.3, and 220 days, respectively. No impact of tocilizumab or corticosteroids on the expansion rate was observed. This work represents the first mixed‐effect model‐based analysis of chimeric antigen receptor–T cell therapy and may be clinically impactful as future studies examine prophylactic interventions in patients at risk of higher grade cytokine release syndrome and the effects of these interventions on chimeric antigen receptor–T cell expansion.

Semaglutide s.c. Once-Weekly in Type 2 Diabetes: A Population Pharmacokinetic Analysis

INTRODUCTION

Semaglutide, a new treatment option approved for the treatment of patients with type 2 diabetes mellitus, is a glucagon-like peptide-1 receptor agonist to be injected subcutaneously once weekly. This analysis used a population pharmacokinetic model of semaglutide to identify clinically relevant covariates for exposure.

METHODS

A total of 1612 patients with up to seven pharmacokinetic observations each were included in the analysis. All subjects had type 2 diabetes mellitus and were enrolled in one of five trials in the phase III development program for subcutaneous semaglutide once weekly (the SUSTAIN program). The treatment duration of the trials varied from 30 to 104 weeks.

RESULTS

No clinically relevant effects on the exposure were seen for sex, age, race, ethnicity, renal function, or injection site used, and semaglutide exposure was stable over time. Of the covariates chosen, only body weight had a relevant effect on the exposure of semaglutide. Few subjects developed semaglutide antibodies, and the antibodies had no effect on exposure. Dose proportionality was shown for the 0.5 mg and 1.0 mg maintenance doses of semaglutide.

CONCLUSION

The population pharmacokinetic study showed that semaglutide exposure is not affected by covariates other than body weight at either a maintenance dose of 0.5 or 1.0 mg semaglutide. Therefore, we conclude that no semaglutide dose adjustments are needed in different populations. This finding is to be further explored in an exposure-response analysis.

TRIAL REGISTRATION

The trials were registered at ClinicalTrials.gov (identifiers: NCT02054897, NCT01930188, NCT01885208, NCT01720446 and NCT02207374).

FUNDING

Novo Nordisk A/S, Bagsværd, Denmark.

Full covariate modelling approach in population pharmacokinetics: understanding the underlying hypothesis tests and implications of multiplicity

AIMS

To clarify the hypothesis tests associated with the full covariate modelling (FCM) approach in population pharmacokinetic analysis, investigate the potential impact of multiplicity in population pharmacokinetic analysis, and evaluate simultaneous confidence intervals (SCI) as an approach to control multiplicity.

METHODS

Clinical trial simulations were performed using a simple one-compartment pharmacokinetic model. Different numbers of covariates, sample sizes, effect sizes of covariates, and correlations among covariates were explored. The false positive rate (FPR) and power were evaluated.

RESULTS

The FPR for the FCM approach dramatically increases with number of covariates. The chance of incorrectly selecting ≥1 seemingly clinically relevant covariates can be increased from 5% to a 40-70% range for 10-20 covariates. The SCI approach may provide appropriate control of the family-wise FPR, allowing more appropriate decision making. As a result, the power detecting real effects without incorrectly identifying non-existing effects can be greatly improved by the SCI approach compared to the approach in current practice. The performance of the SCI approach is driven by the ratio of sample size to number of covariates. The FPR can be controlled at 5% and 10% using the SCI approach when the ratio was ≥20 and 10, respectively.

CONCLUSION

The FCM approach still lies within the framework of statistical testing, and therefore multiplicity is an issue for this approach. It is imperative to consider multiplicity reporting and adjustments in FCM modelling practice to ensure more appropriate decision making.

The Utility of a Population Approach in Drug-Drug Interaction Assessments: A Simulation Evaluation

This study aims at evaluating the utility of the population pharmacokinetics approach in therapeutic protein drug-drug-interaction (DDI) assessment. Simulations were conducted for 2 representative victim drugs, methotrexate and trastuzumab, using a parallel-group design with and without the interaction drug. The effect of a perpetrator on the exposure of the victim drug is described as the ratio of clearance/apparent clearance of the victim drug given with or without the perpetrator. The power of DDI assessment was calculated as the percentage of runs with 90% confidence interval of the estimated DDI effect within 80% to 125% for the scenarios of no DDI, benchmarked with the noncompartmental approach with intensive sampling. The impact of the number of subjects, the number of sampling points per subject, sampling time error, and model misspecification on the power of DDI determination were evaluated. Results showed that with equal numbers of subjects in each arm, the population pharmacokinetics approach with sparse sampling may need about the same or a higher number of subjects compared to a noncompartmental approach in order to achieve similar power. Increasing the number of subjects, even if only in the study drug alone arm, can increase the power. Sampling or dosing time error had notable impacts on the power for methotrexate but not for trastuzumab. Model misspecification had no notable impacts on the power for trastuzumab. Overall, the population pharmacokinetics approach with sparse sampling built in phase 2/3 studies allows appropriate DDI assessment with adequate study design and analysis and can be considered as an alternative to dedicated DDI studies.

Impact of demographics and disease progression on the relationship between glucose and HbA1c

CONTEXT

Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012).

OBJECTIVE

To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model.

DATA

Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component.

PARTICIPANTS

Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races.

ANALYSIS

Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model.

RESULTS

The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship.

CONCLUSION

Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.

Liraglutide 3.0 mg for Weight Management: A Population Pharmacokinetic Analysis

BACKGROUND AND OBJECTIVES

This analysis used a population pharmacokinetic approach to identify covariates that influence plasma exposure of liraglutide 3.0 mg, a glucagon-like peptide-1 (GLP-1) receptor agonist approved for weight management in overweight and obese individuals.

METHODS

Samples for pharmacokinetic analysis were drawn at weeks 2, 12 and 28 of the phase IIIa SCALE Obesity and Prediabetes (N = 2339) and SCALE Diabetes (N = 584) trials. Dose proportionality of liraglutide in obese subjects was investigated using data from a phase II dose-finding study (N = 331).

RESULTS

Dose-proportional exposure of liraglutide up to and including 3.0 mg was confirmed. Body weight and sex influenced exposure of liraglutide 3.0 mg, while age ≥70 years, race, ethnicity and baseline glycaemic status did not. Compared with a reference subject weighing 100 kg, exposure of liraglutide 3.0 mg was 44 % lower for a subject weighing 234 kg (90 % CI 41-47), 41 % higher for a subject weighing 60 kg (90 % CI 37-46), and 32 % higher (90 % CI 28-35) in females than males with the same body weight. Neither injection site nor renal function significantly influenced exposure of liraglutide 3.0 mg (post hoc analysis).

CONCLUSION

Population pharmacokinetics of liraglutide up to and including 3.0 mg daily in overweight and obese adults demonstrated dose-proportional exposure, and limited effect of covariates other than sex and body weight. These findings were similar to those previously observed with liraglutide up to 1.8 mg in subjects with type 2 diabetes mellitus. Further analysis of exposure-response relationship and its effect on dose requirements is addressed in a separate publication.

Population pharmacokinetic and pharmacodynamic analysis of BIIB023, an anti-TNF-like weak inducer of apoptosis (anti-TWEAK) monoclonal antibody

AIMS

Tumour necrosis factor-like weak inducer of apoptosis (TWEAK) is implicated in the pathogenesis of lupus nephritis. This study evaluated the pharmacokinetics, using the population approach, and pharmacodynamics of BIIB023, an anti-TWEAK monoclonal antibody, in healthy Chinese, Japanese and Caucasian volunteers.

METHODS

In this single-dose, randomized, double-blind, phase 1 study of BIIB023 in healthy volunteers, BIIB023 was administered by intravenous infusion (3 or 20 mg kg(-1) ) on Day 1; follow-up occurred through Day 71. BIIB023 serum concentration was measured using a validated enzyme-linked immunosorbent assay; BIIB023 concentration-time data were subjected to noncompartmental analysis. Population pharmacokinetic analysis was performed using data from this study and a prior phase 1 study of BIIB023 in subjects with rheumatoid arthritis. Soluble TWEAK and

TWEAK

BIIB023 complex were evaluated.

RESULTS

There were no differences in BIIB023 pharmacokinetics requiring dose adjustment among the three ethnic groups or between healthy volunteers and arthritis patients. BIIB023 central compartment volume (3050 ml) and clearance (7.42 ml h(-1) ) were comparable to those observed for other monoclonal antibody drugs. BIIB023 serum exposure increased in a dose-dependent manner in all groups, but not in direct proportion to dose level; at concentrations below ~10 μg ml(-1) , nonlinear clearance was observed. Soluble TWEAK levels decreased to below the level of quantitation after BIIB023 treatment, with concomitant changes in

TWEAK

BIIB023 complex levels.

CONCLUSIONS

No clinically meaningful differences were observed in BIIB023 pharmacokinetic and pharmacodynamic properties in healthy Chinese, Japanese and Caucasian volunteers; pharmacodynamic measures suggested target engagement. TWEAK may be an attractive therapeutic target for lupus nephritis treatment.

Population pharmacokinetics of sonidegib (LDE225), an oral inhibitor of hedgehog pathway signaling, in healthy subjects and in patients with advanced solid tumors

PURPOSE

Sonidegib (Odomzo) selectively inhibits smoothened and suppresses the growth of hedgehog pathway-dependent tumors. A population pharmacokinetic (PK) analysis of sonidegib in healthy subjects and patients with advanced solid tumors was conducted to characterize PK, determine variability, and estimate covariate effects.

METHODS

PK data from five phase 1 or 2 studies (N = 436) in the dose range from 100 to 3000 mg were analyzed using NONMEM. A two-compartment base model with first-order absorption, lag time, linear elimination, and bioavailability that decreased with dose was updated to describe the PK of sonidegib. Covariate analyses were performed and were incorporated into the population PK full model.

RESULTS

The base and full models were robust with a good fit to the study data. Population-predicted geometric means (inter-individual variability, CV%) of apparent oral clearance, apparent volume of distribution at steady state, accumulation ratio, and elimination half-life were 9.5 L/h (71.4 %), 9163 L (74.9 %), 21 (131 %) and 29.6 days (109 %). Clinically relevant covariate effects were: A high-fat meal increased sonidegib bioavailability fivefold, healthy volunteers had threefold higher clearance, sonidegib bioavailability decreased with increasing dose levels, and PPI coadministration reduced sonidegib bioavailability by 30 %. Sonidegib PK was not significantly impacted by baseline age, weight, total bilirubin, alanine aminotransferase, albumin, creatinine clearance, gender, and ethnicity (Western countries versus Japanese).

CONCLUSION

No dose adjustment is needed for mild hepatic impairment, mild and moderate renal impairment, age, weight, gender, or ethnicity. This population PK model adequately characterizes sonidegib PK characteristics and can be used for various simulations and applications.

Comparable liraglutide pharmacokinetics in pediatric and adult populations with type 2 diabetes: a population pharmacokinetic analysis

Background and Objective

The safety, tolerability, and pharmacokinetics of the once-daily human glucagon-like peptide-1 (GLP-1) analog liraglutide have been evaluated in pediatric patients aged greater than 10 years with type 2 diabetes (T2D). In this study, a population pharmacokinetic analysis was compared to the pediatric pharmacokinetic data with those from two clinical pharmacology trials in adults with T2D.

Methods

A one-compartment pharmacokinetic model previously found to adequately describe the pharmacokinetics of liraglutide in adults with T2D was applied to the evaluation of 13 pediatric subjects (10–17 years of age) with T2D. Steady-state estimates for apparent clearance (CL/F) for individual subjects and corresponding dose were used to derive the area under the plasma–concentration time curve from 0–24 h (AUC₂₄) and investigate dose proportionality in the pediatric trial. A covariate analysis evaluated the effects of body weight, gender, and age category (pediatric/adult) on liraglutide exposure.

Results

Dose proportionality in the dose range of 0.3–1.8 mg was indicated by the model-derived AUC₂₄ slope: 1.05 (95 % CI 0.96–1.15). Consistent with findings from adult trials, body weight and gender were relevant covariates for liraglutide exposure in the pediatric population. The CL/F estimates, and thus exposure, for the pediatric subjects with T2D were similar to those in the adult trials.

Conclusion

Based on this population pharmacokinetic analysis, the liraglutide dose regimen that was found to be clinically effective in adults is predicted to achieve the same range of exposure in the pediatric population (10–17 years of age) with a pre-trial body weight range of 57–214 kg.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-014-0229-z) contains supplementary material, which is available to authorized users.

Preserved pharmacokinetic exposure and distinct glycemic effects of insulin degludec and liraglutide in IDegLira, a fixed-ratio combination therapy

Insulin degludec/liraglutide (IDegLira) is a novel fixed-ratio combination of the basal insulin insulin degludec (IDeg) and liraglutide, a glucagon-like peptide-1 analog. The pharmacokinetics (PK) and pharmacodynamics of IDegLira were assessed versus its components. A single-dose, randomized, 4-period crossover clinical pharmacology study in healthy subjects compared the bioavailability of IDegLira with its monocomponents. Dose proportionality, covariate effects on exposure, and exposure-response for change in glycated hemoglobin were analyzed based on data from a randomized treat-to-target phase 3 study in subjects with type 2 diabetes. Overall, the PK properties of IDeg and liraglutide were preserved for IDegLira. Liraglutide exposure was lower when dosed as IDegLira but met the criterion for equivalence. No relevant deviations from dose proportionality for the IDegLira components were observed. Covariate effects on exposure were consistent with previous results. Glycemic response to IDegLira was larger than with IDeg or liraglutide alone, reflecting their distinct glucose-lowering effects throughout the dose/exposure range.

Population pharmacokinetics of dolutegravir in HIV-infected treatment-naive patients

Aim

Dolutegravir is the newest integrase inhibitor approved for HIV treatment and has demonstrated potent antiviral activity in patient populations with a broad range of treatment experience. This analysis aimed to characterize the population pharmacokinetics of dolutegravir in treatment-naive patients and to evaluate the influence of patient covariates.

Methods

A population pharmacokinetic model was developed using a non-linear mixed effect modelling approach based on data from 563 HIV-infected, treatment-naive adult patients in three phase 2/3 trials who received dolutegravir (ranging from 10–50 mg once daily) alone or in combination with abacavir/lamivudine or tenofovir/emtricitabine.

Results

The pharmacokinetics of dolutegravir were adequately described by a linear one compartment model with first order absorption, absorption lag time and first order elimination. Population estimates for apparent clearance, apparent volume of distribution, absorption rate constant and absorption lag time were 0.901 l h^–1, 17.4 l, 2.24 h⁻¹, and 0.263 h, respectively. Weight, smoking status, age and total bilirubin were predictors of clearance, weight was a predictor of volume of distribution and gender was a predictor of bioavailability. However, the magnitude of the effects of these covariates on steady-state dolutegravir plasma exposure was relatively small (<32%) and was not considered clinically significant. Race/ethnicity, HBV/HCV co-infection, CDC classification, albumin, creatinine clearance, alanine aminotransferase or aspartate aminotransferase did not influence the pharmacokinetics of dolutegravir in this analysis.

Conclusions

A population model that adequately characterizes dolutegravir pharmacokinetics has been developed. No dolutegravir dose adjustment by patient covariates is necessary in HIV-infected treatment-naive patients.

Liraglutide pharmacokinetics and dose-exposure response in Asian subjects with Type 2 diabetes from China, India and South Korea

AIMS

To investigate the population pharmacokinetics and exposure-response relationship of liraglutide, a human glucagon-like peptide-1 (GLP-1) analogue, in Asian subjects with Type 2 diabetes mellitus.

METHODS

Data were derived from a published 16-week, randomized, double-blind, double-dummy, active-controlled, parallel-group trial of liraglutide in China, India and South Korea. The analysis utilized 2061 pharmacokinetic (PK) samples from 605 subjects exposed to liraglutide 0.6, 1.2 or 1.8 mg once daily. Demographic factors (body weight, age, gender, country) of importance for liraglutide clearance were evaluated. An exploratory exposure-response analysis was conducted to investigate effects on glycated haemoglobin (HbA1c) and body weight.

RESULTS

Estimated liraglutide exposure (area under the curve; AUC) appeared to increase proportionally with increasing liraglutide dose (0.6-1.8 mg). The covariate analysis confirmed previous findings in a global clinical trial. Body weight was a predictor of liraglutide exposure; compared to a reference subject of 67 kg, exposure was 32% lower for maximum (115 kg) and 54% higher for minimum (37 kg) observed body weights. Gender, age and country had no relevant effect on exposure. Exposure-response analysis supported the use of 1.2mg as maintenance dose with the option of individual dose escalation to 1.8 mg to optimize treatment outcomes.

CONCLUSIONS

Exposure appeared to increase proportionally with increasing liraglutide dose in Asian subjects with Type 2 diabetes mellitus. The only PK relevant predictor of exposure was body weight. The exposure-response relationships for HbA1c and body weight in Asian subjects were similar to observations in global populations.

Covariate selection in pharmacometric analyses: a review of methods

Covariate selection is an activity routinely performed during pharmacometric analysis. Many are familiar with the stepwise procedures, but perhaps not as many are familiar with some of the issues associated with such methods. Recently, attention has focused on selection procedures that do not suffer from these issues and maintain good predictive properties. In this review, we endeavour to put the main variable selection procedures into a framework that facilitates comparison. We highlight some issues that are unique to pharmacometric analyses and provide some thoughts and strategies for pharmacometricians to consider when planning future analyses.

Utility of population pharmacokinetic modeling in the assessment of therapeutic protein-drug interactions

Assessment of pharmacokinetic (PK) based drug-drug interactions (DDI) is essential for ensuring patient safety and drug efficacy. With the substantial increase in therapeutic proteins (TP) entering the market and drug development, evaluation of TP-drug interaction (TPDI) has become increasingly important. Unlike for small molecule (e.g., chemical-based) drugs, conducting TPDI studies often presents logistical challenges, while the population PK (PPK) modeling may be a viable approach dealing with the issues. A working group was formed with members from the pharmaceutical industry and the FDA to assess the utility of PPK-based TPDI assessment including study designs, data analysis methods, and implementation strategy. This paper summarizes key issues for consideration as well as a proposed strategy with focuses on (1) PPK approach for exploratory assessment; (2) PPK approach for confirmatory assessment; (3) importance of data quality; (4) implementation strategy; and (5) potential regulatory implications. Advantages and limitations of the approach are also discussed.

Therapeutic protein drug-drug interactions: navigating the knowledge gaps-highlights from the 2012 AAPS NBC Roundtable and IQ Consortium/FDA workshop

The investigation of therapeutic protein drug-drug interactions has proven to be challenging. In May 2012, a roundtable was held at the American Association of Pharmaceutical Scientists National Biotechnology Conference to discuss the challenges of preclinical assessment and in vitro to in vivo extrapolation of these interactions. Several weeks later, a 2-day workshop co-sponsored by the U.S. Food and Drug Administration and the International Consortium for Innovation and Quality in Pharmaceutical Development was held to facilitate better understanding of the current science, investigative approaches and knowledge gaps in this field. Both meetings focused primarily on drug interactions involving therapeutic proteins that are pro-inflammatory cytokines or cytokine modulators. In this meeting synopsis, we provide highlights from both meetings and summarize observations and recommendations that were developed to reflect the current state of the art thinking, including a four-step risk assessment that could be used to determine the need (or not) for a dedicated clinical pharmacokinetic interaction study.

Characterizing the impact of renal impairment on the clinical pharmacology of biologics

Similar to small-molecule drugs, there is also concern for protein-based therapeutics about their clinical use in patients with renal impairment including renal insufficiency and end-stage renal disease, which may modulate the efficacy and/or safety profile of these compounds. Theoretical considerations and clinical evidence suggest that the kidneys play a relevant role in the catabolism and thus elimination of only those protein therapeutics that have a size below the cutoff for glomerular filtration of approximately 60 kDa. Thus, the effect of renal impairment on protein therapeutics seems to be predictable and only relevant for compounds below this molecular weight cutoff. This is supported by clinical evidence that shows a lack of effect of renal impairment on large proteins such as monoclonal antibodies, whereas smaller proteins below the cutoff such as interleukin-10, growth hormone, erythropoietin, and anakinra experience a gradual decrease of their clearance and increase of their systemic exposure with increasing severity of renal impairment. Thus, dedicated renal impairment studies are warranted in the clinical development program of protein therapeutics that undergo glomerular filtration to establish the scientific rationale for their safe and efficacious use in patients with renal insufficiency.

Role of Statistical Random-Effects Linear Models in Personalized Medicine

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization.