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Division: Worldwide DevelopmentInformation Type: Clinical Pharmacology Study ReportControl: Active-control-without-placebo

Title: Population Pharmacokinetic Modeling report for Fluticasone Furoate, Umeclidinium and Vilanterol using Pooled Data from three Phase III studies (200812, CTT116853 and CTT116855) in adults with Chronic Pulmonary Obstructive Disease (208059)

Phase: III and IIIb

Compound Number: GSK573719+GW642444+GW685698 (GSK2834425)

Effective Date: 09-JAN-2018

Keywords: fluticasone furoate (FF), umeclidinium bromide (UMEC), vilanterol (VI), Population Pharmacokinetics (POP PK), Chronic Obstructive Pulmonary Disease (COPD), 200812, CTT116853, CTT116855

Author(s): (Clinical Pharmacology Modeling Simulation); (ICON Development Solutions)

Indication Studied: Chronic Obstructive Pulmonary Disease (COPD)

Clinical Study Report Revision History

Sponsor Signatory: (and Medical Officer)

Misba Beerahee, Ph.D,Senior Director, CPMS (Respiratory TA) on behalf of Val Kitchen, FRCP,VP, CPMS (Clinical Phramacology Modeling Simulation)

This study was performed in compliance with Good Clinical Practices and GlaxoSmithKline Standard Operating Procedures for all processes involved, including the archiving of essential documents.

This study complies with US 21 CFR312.120.

Copyright 2018 the GlaxoSmithKline group of companies. All rights reserved. Unauthorized copying or use of this information is prohibited.

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Table of Contents Page TITLE PAGE ........................................................................................................................ SPONSOR SIGNATURE PAGE ...................................................................................... ABBREVIATIONS .............................................................................................................. SYNOPSIS ........................................................................................................................... 1. INTRODUCTION ............................................................................................................ 2. STUDY OBJECTIVES & ENDPOINTS.......................................................................

2.1. Objective(s) .................................................................................................................. 2.2. Endpoint(s) ...................................................................................................................

3. STUDY DESIGN ............................................................................................................. 3.1. Study CTT116853 ....................................................................................................... 3.2. Study 200812 ............................................................................................................... 3.3. Study CTT116855 ....................................................................................................... 3.4. Selection of Study Population ...................................................................................

3.4.1. Inclusion/Exclusion Criteria .................................................................................. 3.5. Treatments ................................................................................................................... 3.6. Study Assessments and Procedures .......................................................................

3.6.1. Pharmacokinetic Assessments ............................................................................ 3.6.2. Assay Methods ....................................................................................................... 3.6.3. Analysis Populations ............................................................................................. 3.6.4. Changes in Conduct of the Study or Planned Analyses ..................................

4. PHARMACOKINETIC DATA ANALYSIS .................................................................. 4.1. Software Information................................................................................................... 4.2. Dataset Preparation .................................................................................................... 4.3. Sample Size Consideration ....................................................................................... 4.4. FF/UMEC/VI Dataset ..................................................................................................

4.4.1. FF Dataset .............................................................................................................. 4.4.2. UMEC Dataset........................................................................................................ 4.4.3. VI Dataset................................................................................................................

4.5. Covariates .................................................................................................................... 4.6. Data Handling Conventions .......................................................................................

4.6.1. Missing covariates ................................................................................................. 4.6.2. Missing concentrations (dependent variable).................................................... 4.6.3. Missing dosing times ............................................................................................. 4.6.4. Missing PK sampling times ..................................................................................

4.7. PK Outliers ................................................................................................................... 4.8. Modelling Procedure ...................................................................................................

4.8.1. Population PK Analysis ......................................................................................... 4.8.2. Exploratory Data Analysis .................................................................................... 4.8.3. Structural Model Development ............................................................................ 4.8.4. FF Structural Model ............................................................................................... 4.8.5. UMEC Structural Model ........................................................................................ 4.8.6. VI Structural Model ................................................................................................ 4.8.7. Visual Predictive Check ........................................................................................

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4.9. Derivation of Individual AUCss and Cmax ss ......................................................... 4.10. Summary Statistics ...................................................................................................

4.10.1. Information for PK Time-Concentration Data Tables and Listings .............. 4.10.2. PK parameter (AUCss and Cmax ss) Data Tables and Listings .................

5. STUDY (ANALYSIS) POPULATION RESULTS ...................................................... 5.1. Subject Demographics and Baseline Characteristics ...........................................

5.1.1. FF Population PK Dataset .................................................................................... 5.1.2. UMEC Population PK Dataset ............................................................................. 5.1.3. VI Population PK Dataset .....................................................................................

5.2. Protocol Deviations ..................................................................................................... 6. FF PHARMACOKINETIC RESULTS ..........................................................................

6.1. FF Concentration Data ............................................................................................... 6.2. Predictive Performance of Previous FF Model ....................................................... 6.3. FF Pharmacokinetic Base Model .............................................................................. 6.4. Effect of Covariates..................................................................................................... 6.5. FF Pharmacokinetic Final Model .............................................................................. 6.6. Effect of Race (Japanese heritage) on FF PK........................................................ 6.7. Effect of FF/VI Treatment on FF PK......................................................................... 6.8. FF Model Performance............................................................................................... 6.9. Derivation of Individual FF AUCss and Cmax ss ................................................... 6.10. Alternative Analysis to Evaluate Effect of East Asian Race on FF

Pharmacokinetics: Historical Data Comparison ............................................ 7. UMEC PHARMACOKINETIC RESULTS ...................................................................

7.1. UMEC Concentration Data ........................................................................................ 7.2. Predictive Performance of Previous UMEC Model ................................................ 7.3. UMEC Pharmacokinetic Base Model ....................................................................... 7.4. Effect of Covariates..................................................................................................... 7.5. UMEC Pharmacokinetic Final Model .......................................................................

Table 20 Final UMEC Pharmacokinetic Model (Run UMEC027):............................. 7.6. Effect of Age on UMEC PK ........................................................................................ 7.7. Effect of Weight on UMEC PK .................................................................................. 7.8. Effect of Smoking Status on UMEC PK ................................................................... 7.9. UMEC Model Performance ........................................................................................ 7.10. Derivation of Individual UMEC AUCss and Cmax ss ..........................................

8. VI PHARMACOKINETIC RESULTS ........................................................................... 8.1. VI Concentration Data ................................................................................................ 8.2. Predictive Performance of Previous VI model ........................................................ 8.3. VI Pharmacokinetic Base Model ............................................................................... 8.4. Effect of Covariates..................................................................................................... 8.5. VI Pharmacokinetic Final Model ............................................................................... 8.6. Effect of Weight on VI PK .......................................................................................... 8.7. Effect of Smoking Status on VI PK ........................................................................... 8.8. VI Model Performance ................................................................................................ 8.9. Derivation of Individual VI AUCss and Cmax ss ....................................................

9. SUMMARY PK ANALYSIS ..........................................................................................

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10. FF, UMEC, VI FOREST PLOT AND COMPARISON OF FF, UMEC AND VI EXPOSURE IN JAPANESE AND NON‑ JAPANESE SUBJECTS ........................... 11. DISCUSSION AND CONCLUSIONS........................................................................

11.1. Discussion .................................................................................................................. 11.2. Conclusions................................................................................................................

12. REFERENCES.............................................................................................................. 13. DATA SOURCE TABLES AND FIGURES ..............................................................

13.1. PK Data Excluded from Analysis ............................................................................ Table 1.1 Listing of PK Concentrations Excluded from Analysis ..............................

13.2. Demographics Source Tables................................................................................. Table 1.2 Summary of demographic/baseline covariates in the various

subpopulations (geographic ancestry or race and country/geographic region) from the Overall PopPK analysis......................................................

Table 1.3 Summary of demographic/baseline covariates in the various subpopulations (geographic ancestry or race and country/geographic region) by Study and by Treatment ...............................................................

13.3. Data Source Figures................................................................................................. Figure 2.1 Observed FF Concentration-Time Data from Present Dataset by

Race/Geographic Ancestry and Country/Region ........................................ Figure 2.2 Base FF Pharmacokinetic Model Goodness of Fit Plots (Run

FF014a) .............................................................................................................. Figure 2.3 Population Predicted (red circles) and Observed FF Concentrations

(black circles) versus Time after Previous Dose for the Base FF Pharmacokinetic Model (Run FF014a) .........................................................

Figure 2.4 Base FF Pharmacokinetic Model (Run FF014a) ETA versus Covariate Plots..................................................................................................

Figure 2.5 Final FF Pharmacokinetic Model Goodness of Fit Plots (Run FF021) .. Figure 2.6 Population Predicted (red circles) and Observed FF Concentrations

(black circles) versus Time after Previous Dose for the Final FF Pharmacokinetic Model (Run FF021) ...........................................................

Figure 2.7 Final FF Pharmacokinetic Model (Run FF021) ETA versus Covariate Plots..................................................................................................

Figure 3.1 Observed UMEC Concentration-Time Data from Present Dataset by Race/Geographic Ancestry and Country/Region ........................................

Figure 3.2 Base UMEC Pharmacokinetic Model Goodness of Fit Plots (Run UMEC013) .........................................................................................................

Figure 3.3 Population Predicted (red circles) and Observed UMEC Concentrations (black circles) versus Time after Previous Dose for the Base UMEC Pharmacokinetic Model (Run UMEC013) .......................

Figure 3.4 Base UMEC Pharmacokinetic Model (Run UMEC013) ETA versus Covariate Plots..................................................................................................

Figure 3.5 Final UMEC Pharmacokinetic Model Goodness of Fit Plots (Run UMEC027) .........................................................................................................

Figure 3.6 Population Predicted (red circles) and Observed UMEC Concentrations (black circles) versus Time after Previous Dose for the Final UMEC Pharmacokinetic Model (Run UMEC027) .......................

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Figure 3.7 Final UMEC Pharmacokinetic Model (Run UMEC027) ETA versus Covariate Plots..................................................................................................

Figure 4.1 Observed VI Concentration-Time Data from Present Dataset by Race/Geographic Ancestry and Country/Region ........................................

Figure 4.2 Base VI Pharmacokinetic Model Goodness of Fit Plots (Run VI005) ... Figure 4.3 Population Predicted (red circles) and Observed VI Concentrations

(black circles) versus Time after Previous Dose for the Base VI Pharmacokinetic Model (Run VI005).............................................................

Figure 4.4 Base VI Pharmacokinetic Model (Run VI005) ETA versus Covariate Plots ....................................................................................................................

Figure 4.5 Final VI Pharmacokinetic Model Goodness of Fit Plots (Run VI040) .... Figure 4.6 Population Predicted (red circles) and Observed VI Concentrations

(black circles) versus Time after Previous Dose for the Final VI Pharmacokinetic Model (Run VI040).............................................................

Figure 4.7 Final VI Pharmacokinetic Model (Run VI040) ETA versus Covariate Plot ......................................................................................................................

13.4. Data Source Tables .................................................................................................. Table 1.4 R Script to Determine Frequency of Concomitent Medications in

Source Population PK Dataset ....................................................................... Table 1.5 R Script to Summarize Subject Demographics in FF Population PK

Dataset ............................................................................................................... Table 1.6 R Script to Summarize Subject Demographics in UMEC Population

PK Dataset......................................................................................................... Table 1.7 R Script to Summarize Subject Demographics in VI Population PK

Dataset ............................................................................................................... Table 1.8 R Script to Create Plots of FF, UMEC and VI Concentration-Time

Data from Historical and Present Analysis Datasets .................................. Table 2.1 Summary of FF Pharmacokinetic Parameters by Study and

Treatment........................................................................................................... Table 2.2 Summary of FF Pharmacokinetic Parameters by Geographic

Ancestry and Region........................................................................................ Table 2.3 Summary of FF Pharmacokinetic Parameters by Study, Treatment,

Geographic Ancestry and Region .................................................................. Table 2.4 R script to obtain VPC plot for Predictive Performance of Historical

FF Model (dmp6731-1.1)................................................................................. Table 2.5 Nonmem control and output files for FF base model (FF014a) ............... Table 2.6 Nonmem control and output file for FF full model (FF020)....................... Table 2.7 Nonmem control and output file for FF final model (FF021) .................... Table 2.8 R script to obtain VPC plot for FF final model (FF021) ............................. Table 2.9 Nonmem control file to derive the exposure predictions (AUC(0-24)

and Cmax) with FF final model (FF021) ....................................................... Table 2.10 R Script to summarize the exposure predictions from FF final model

(FF021)............................................................................................................... Table 2.11 Nonmem control file for simulations to evaluate covariate effects in

FF final model (FF021) ....................................................................................

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Table 2.12 R Script to summarize the covariate effects in FF final model (FF021)...............................................................................................................

Table 2.13 Nonmem control and output files for FF model Run FF022 ................... Table 2.14 Nonmem control file to derive the exposure predictions (AUC(0-24)

and Cmax) with FF model Run FF022 .......................................................... Table 2.15 R Script to summarize the exposure predictions from FF model Run

FF022 ................................................................................................................. Table 2.16 Summary of FF Pharmacokinetic Parameters by Study and

Treatment for FF model Run FF022.............................................................. Table 2.17 Summary of FF Pharmacokinetic Parameters by Geographic

Ancestry and Region for FF model Run FF022 ........................................... Table 2.18 Summary of FF Pharmacokinetic Parameters by Study, Treatment,

Geographic Ancestry and Region for FF model Run FF022 ..................... Table 3.1 Summary of UMEC Pharmacokinetic Parameters by Study and

Treatment........................................................................................................... Table 3.2 Summary of UMEC Pharmacokinetic Parameters by Geographic

Ancestry or Race and Country/Geographical Region................................. Table 3.3 Summary of UMEC Pharmacokinetic Parameters by Study,

Treatment, Geographic Ancestry or Race and Country/Geographical Region ................................................................................................................

Table 3.4 R script to obtain VPC plot for Predictive Performance of Historical UMEC Model (umpop4_ka2; dmo#10612) ...................................................

Table 3.5 Nonmem control and output file for UMEC base model (UMEC013) ..... Table 3.6 Nonmem control and output file for UMEC full model (UMEC026) ......... Table 3.7 Nonmem control and output file for UMEC final model (UMEC027)....... Table 3.8 R script to obtain VPC plot for UMEC final model (UMEC027) ............... Table 3.9 Nonmem control file to derive the exposure predictions (AUC(0-24)

and Cmax) with UMEC final model (UMEC027) ......................................... Table 3.10 R Script to summarize the exposure predictions from UMEC final

model (UMEC027)............................................................................................ Table 3.11 Nonmem control file for simulations to evaluate covariate effects in

UMEC final model (UMEC027) ...................................................................... Table 3.12 R Script to summarize the covariate effects in UMEC final model

(UMEC027)........................................................................................................ Table 4.1 Summary of VI Pharmacokinetic Parameters by Study and

Treatment........................................................................................................... Table 4.2 Summary of VI Pharmacokinetic Parameters by Geographic

Ancestry or Race and Country/Geographical Region................................. Table 4.3 Summary of VI Pharmacokinetic Parameters by Study, Treatment,

Geographic Ancestry or Race and Country/Geographical Region ........... Table 4.4 R script to obtain VPC plot for Predictive Performance of Historical VI

Model (vipop2_1: dmp#10573)....................................................................... Table 4.5 R script to obtain VPC plot for Predictive Performance of Historical VI

Model (dmp#5911) ........................................................................................... Table 4.6 Nonmem control and output file for VI base model (VI005) ..................... Table 4.7 Nonmem control and output file for VI full model (VI039) .........................

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Table 4.8 Nonmem control and output file for VI final model (VI040)....................... Table 4.9 R script to obtain VPC plot for VI final model (VI040) ............................... Table 4.10 Nonmem control file to derive the exposure predictions (AUC(0-24)

and Cmax) with VI final model (VI040) ......................................................... Table 4.11 R Script to summarize the exposure predictions from VI final model

(VI040) ................................................................................................................ Table 4.12 Nonmem control file for simulations to evaluate covariate effects in

VI final model (VI040) ...................................................................................... Table 4.13 R Script to summarize the covariate effects in VI final model (VI040) . Table 5.1 Summary of Fluticasone Furoate Plasma Concentration Data

(pg/mL) (FF Population) – Study CTT116853................................................. Table 5.2 Summary of Fluticasone Furoate Plasma NQ Values – Study

CTT116853........................................................................................................ Table 5.3 Summary of FF Plasma Concentration Data (pg/mL) (FF Population)

– Study CTT116855 ......................................................................................... Table 5.4 Summary of Fluticasone Furoate Plasma NQ Values – Study

CTT116855........................................................................................................ Table 5.5 Summary of FF Plasma Concentration Data (pg/mL) (FF Population)

– Study 200812 ................................................................................................. Table 5.6 Summary of FF Plasma NQ Values – Study 200812 ................................ Table 5.7 Summary of UMEC Plasma Concentration Data (pg/mL) (UMEC

Population) – Study CTT116853.................................................................... Table 5.8 Summary of UMEC Plasma NQ Values – Study CTT116853 ................. Table 5.9 Summary of UMEC Plasma Concentration Data (pg/mL) (UMEC

Population) – Study CTT116855.................................................................... Table 5.10 Summary of UMEC Plasma NQ Values – Study CTT116855 ............... Table 5.11 Summary of UMEC Plasma Concentration Data (pg/mL) (UMEC

Population) – Study 200812 ........................................................................... Table 5.12 Summary of UMEC Plasma NQ Values – Study 200812 ....................... Table 5.13 Summary of VI Plasma Concentration Data (pg/mL) (VI Population)

– Study CTT116853 ......................................................................................... Table 5.14 Summary of VI Plasma NQ Values – Study CTT116853 ....................... Table 5.15 Summary of VI Plasma Concentration Data (pg/mL) (VI Population)

– Study CTT116855 ......................................................................................... Table 5.16 Summary of VI Plasma NQ Values – Study CTT116855 ....................... Table 5.17 Summary of VI Plasma Concentration Data (pg/mL) (VI Population)

– Study 200812 ................................................................................................. Table 5.18 Summary of VI Plasma NQ Values – Study 200812 ............................... Table 5.19 Summary of Fluticasone Furoate Plasma Concentration Data

(pg/mL) by Geographic Ancestry or Race and Country/Geographical Region (FF Population)....................................................................................

Table 5.20 Summary of Umeclidinium Plasma Concentration Data (pg/mL) by Geographic Ancestry or Race and Country/Geographical Region (UMEC Population) ..........................................................................................

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Table 5.21 Summary of Vilanterol Plasma Concentration Data (pg/mL) by geographic Ancestry or Race and Country/Geographical Region (VI Population).........................................................................................................

Table 5.22 R Script to Determine Overall Proportion of BQL Concentrations in Population PK Datasets ......................................................................................

Table 6.1 R Script For FF/UMEC/VI Forest Plot .......................................................... Table 6.2 Individual Listing of FF AUCss and Cmax ss for Forest Plots ................. Table 6.3 Individual Listing of UMEC AUCss and Cmax ss for Forest Plots .......... Table 6.4 Individual Listing of VI AUCss and Cmax ss for Forest Plots .................. Table 6.5 R Script to Plot FF, UMEC and VI Exposures in Japanese and Non-

Japanese COPD Subjects Following FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg)......................................................................................................

14. ATTACHMENTS .......................................................................................................... 14.1. Reporting and Analysis Plan ...................................................................................

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ABBREVIATIONS

ALAG Absorption lag-timeAUCss Area under the concentration-time curve at steady stateBQL Below quantification limitCI Confidence intervalCL/F Apparent clearanceCmax ss Maximum Concentration at steady stateCOPD Chronic Obstructive Pulmonary Disease CPMS Clinical Pharmacology Modeling and SimulationCWRES Conditional weighted residualsCrCL Creatinine clearanceETA NONMEM Inter-Individual ErrorFEV1 Forced expiratory volume in one secondFF Fluticasone FuroateICS Inhaled corticosteroidIIV Inter-individual variabilityIOV Inter-occasion variabilityITT Intent-to-TreatK Elimination rate constantLABA Long-acting β2-adrenergic receptor agonistLAMA Long-acting muscarinic receptor antagonistLLQ Lower Limit of Quantificationmcg MicrogramsNONMEM Nonlinear Mixed Effects ModelOFV Objective function valuePI Prediction intervalPK PharmacokineticPOP PK Population pharmacokineticsPPFEV1 Percent predicted FEV1 at baselineRAP Reporting and Analysis Plant1/2 Elimination half-lifeTHETA NONMEM Population Fixed Effect EstimateUMEC UmeclidiniumV/F Apparent volume of distributionVI Vilanterol VPC Visual predictive check

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Trademark Information

Trademarks of the GlaxoSmithKline group of companies

Trademarks not owned by the GlaxoSmithKline group of companies

ANORO ELLIPTA NONMEMBREO ELLIPTA PDx-PopHARPTM RRELVAR ELLIPTA SASTRELEGY

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Synopsis

Name of company: GlaxoSmithKline Research & Development Limited

Name of finished product:

Not available at the time of this report

Name of active substance:

Fluticasone furoate/umeclidinium bromide/vilanterol (FF/UMEC/VI) (GW685698/GSK573719/ GW642444)

Study Number: 208059 (200812+CTT116853+CTT116855)

Title: Population Pharmacokinetic Modeling report for Fluticasone Furoate, Umeclidinium and Vilanterol using Pooled Data from three Phase III studies (200812, CTT116853 and CTT116855) in adults with Chronic Pulmonary Obstructive Disease (208059)

Publication(s): None at the time of this report

Phase of Development: III and IIIb

Objectives:

The primary objectives of the analyses were:

to characterize the population PK of FF, UMEC and VI in adults with COPD following administration of FF/UMEC/VI in an ELLIPTA inhaler and following administration of FF/VI+UMEC, FF/VI, UMEC/VI.

to identify influential covariates, among age, race, gender, weight, body mass index, smoking status, concurrent medications (cytochrome P450 inducers/inhibitors, Pgp inhibitors), lung function status in terms of reversibility post albuterol/salbutamol, percent predicted FEV1 at screening (PPFEV1) and creatinine clearance on the PK of FF, UMEC and VI in patients with COPD.

Endpoints:

Non-linear mixed effects model (NONMEM) generated post-hoc estimates for FF, UMEC and VI population PK parameters and associated inter-subject variability and residual error: Apparent clearance (CL/F), apparent volume of distribution (V/F), Ka

(absorption rate constant), (model dependent) Derived PK parameters:

Area under the curve at steady state (AUCss) and maximum observed concentration at steady state (Cmax ss).

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Methodology:

Study CTT116853 was a phase IIIa, randomized, double-blind, double-dummy, parallel group study evaluating once daily FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) inhalation powder via a single ELLIPTA inhaler versus twice daily budesonide/formoterol (400 mcg/12 mcg). Eligible subjects were randomized 1:1 to one of the two treatments. A total of 1,810 subjects were included in the Intent-to-Treat (ITT) population. The total duration of the study was approximately 27 weeks, consisting of a 2-week run-in period, 24-week treatment period and a 1-week safety follow-up period.

Study 200812 was a phase IIIb, 24-week, randomized, double-blind, parallel group multicenter study evaluating FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) via a single ELLIPTA plus matching placebo versus FF/VI + UMEC delivered via two ELLIPTA inhalers, all taken once daily. Eligible subjects were randomized 1:1 to one of the two treatments. A total of 1,055 subjects were included in the ITT population. The total duration of the study was approximately 27 weeks, consisting of a 2-week run-in period, 24-week treatment period and a 1-week follow-up period.

Study CTT116855 was a phase IIIa, randomized, double-blind, 3-arm parallel group study evaluating FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) inhalation powder via a single ELLIPTA inhaler versus FF/VI (100 mcg/25 mcg) inhalation powder (RELVAR ELLIPTA or BREO ELLIPTA) and UMEC/VI (62.5 mcg/25 mcg) inhalation powder (ANORO ELLIPTA), all given once daily in the morning. Eligible subjects were randomized 2:2:1 to the FF/UMEC/VI, FF/VI or UMEC/VI treatments. This study enrolled 10,355 subjects in the ITT population. The total duration of the study was approximately 55 weeks, consisting of a 2-week run-in period, 52-week treatment period and a 1-week safety follow-up period.

PK Sampling Scheme:

For CTT116853, a subset of 74 subjects (64 sparse and 10 serial) treated with FF/UMEC/VI) provided PK samples for the POP PK analyses of FF, UMEC and VI.

For Study 200812, a subset of 227 subjects provided PK samples (163 sparse and 64 serial) at Visits 4 (wk 12) and 5 (wk 24) for the POP PK analyses of FF, UMEC and VI.

For Study CTT116855, a subset of 520 subjects provided PK samples (all sparse) at Visits 4 (wk 16) and 5 (wk 28) for the POP PK analyses of FF, UMEC and VI.

Analysis Methods:

FF, UMEC and VI plasma concentration – time data were used for population PK analyses using non-linear mixed effects modeling with NONMEM v7.4.

Initially, Monte Carlo simulations using the previously reported population PK models for FF, UMEC and VI were undertaken to assess the ability of these models to describe the observed data from Studies 200812, CTT116853 and CTT116855 by overlaying the observations onto the 90% prediction intervals from the simulations.

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A model-based estimation approach was undertaken whereby the plasma data for FF, UMEC and VI from Studies 200812, CTT116853 and CTT116855 were combined. The previously reported population PK models for FF, UMEC and VI served as starting points for the structural model development. The data below the limit of quantification (BQL) were treated as censored data and all data were analyzed with the full likelihood approach (M3 method). Covariate analysis was undertaken once the base structural model had been developed.

The adequacies of the population PK models were assessed through diagnostic plots and visual predictive checks (VPC). The post-hoc individual parameter estimates from each model for FF, UMEC and VI were utilized to estimate individual systemic exposure measures. The geometric mean and the associated 95% confidence intervals for AUCssand Cmax ss at steady state were summarized for each analyte by study, treatment, geographic ancestry or race and country/geographical region.

Results:

Analysis Population: A total of 821 subjects from 3 studies contributed to population PK analysis. Demographic and baseline characteristics of subjects were similar across each of the 3 population PK datasets (FF, UMEC and VI).

Demographics Summary in 208059 Population PK Datasets

FF UMEC VI

N 714 622 817

Age (yr), median (range) 66 (41-88) 66 (41-88) 66 (41-88)

Sex, n(%)FemaleMale

206 (29)508 (71)

169 (27)453 (73)

233 (29)584 (71)

BMI (kg/m2) median (range) 25.3 (14.4-49.2) 25.3 (14.4-49.2) 25.3 (14.4-49.2)Weight (kg) median (range) 72.0 (35.4-154) 72.0 (35.4-154) 71.9 (35.4-154)

Race, n (%)African American/AfricanAsian – East AsianAsian – JapaneseWhite – Arabic/North AfricanWhite – White/Caucasian/European

23 (3)117 (16)93 (13)2 (

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Carlo simulations using the previously reported FF, UMEC and VI models from the FF/VI and UMEC/VI programs.

The PK of FF in 200812, CTT116853 and CTT116855 was well-described by a two-compartment model with first-order absorption and first-order elimination. The only covariates found to be statistically significant were Japanese heritage and FF/VI on inhaled clearance (CL/F) but no dose adjustment was warranted based on the predicted systemic exposure.

FF Population PK Final Model Parameter EstimatesParameter Estimate

[95% CI]CL/F [L/h] 513 [493, 534]V2/F [L] 1.36 FIXEDQ/F [L/h] 268 FIXEDV3/F [L] 111 FIXEDKA [h-1] 0.0821

[0.0805, 0.0837]Japanese heritage on CL/F

0.647[0.628, 0.666]

FF/VI on CL/F 1.42[1.38, 1.46]

Based on the post-hoc PK parameter estimates for FF (dose 100 mcg once-daily), steady-state systemic exposures were derived and are summarized by treatment, geographic ancestry or race and by country/geographical region in the tables below.

Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to FF following administration of 100 mcg FF by Treatment in Subjects with COPD

Analysis Treatment N Cmax ss (pg/mL) AUCss (pg*h/mL)208059 FF/UMEC/VI 413 18.7 [18.0, 19.4] 230 [219, 242]

FF/VI+UMEC 106 19.5 [17.9, 21.1] 239 [213, 267]FF/VI 195 13.3 [12.6, 14.0] 158 [148, 169]

Historical AnalysesCTT116853 FF/UMEC/VI 74 13.2 [11.2, 15.1] 188 [160, 216]

HZC112206, HZC112207, HZC110946

FF 333 11.5 [10.5, 12.4] 181 [167, 196]

HZC112206, HZC112207, HZC110946

FF/VI 391 11.9 [10.9, 12.9] 182 [170, 195]

208059 = Studies CTT116853, CTT116855 and 200812

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Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to FF following administration of 100 mcg FF by Geographic Ancestry or Race and Country/Geographical Region in Subjects with COPD

Treatment N Cmax ss (pg/mL) AUCss (pg*h/mL)RaceWhite FF/UMEC/VI 288 17.6 [16.9, 18.3] 215 [204, 228] 208059 FF/VI+UMEC 92 18.9 [17.2, 20.6] 234 [206, 266]

FF/VI 101 13.2 [12.3, 14.2] 156 [143, 171]Japanese heritage 208059 FF/UMEC/VI 56 25.3 [22.7, 28.2] 311 [270, 358]

FF/VI+UMEC 14 24.0 [20.5, 28.0] 274 [235, 320]FF/VI 23 19.6 [16.6, 23.1] 241 [194, 298]

CTT116855 FF/UMEC/VI 33 26.2 [22.3, 30.7] 328 [266, 404]

FF/VI 23 19.6 [16.6, 23.1] 241 [194, 298] 200812 FF/UMEC/VI 23 24.1 [20.8, 27.9] 288 [239, 347]

FF/VI+UMEC 14 24.0 [20.5, 28.0] 274 [235, 320]

East Asian heritage FF/UMEC/VI 113 22.0 [20.2, 24.0] 279 [250, 312]FF/VI+UMEC 14 24.0 [20.5, 28.0] 274 [235, 320]FF/VI 83 13.6 [12.5, 14.8] 162 [146, 179]

Country/RegionJapan FF/UMEC/VI 56 25.3 [22.7, 28.2] 311 [270, 358]

FF/VI+UMEC 14 24.0 [20.5, 28.0] 274 [235, 320]FF/VI 23 19.6 [16.6, 23.1] 241 [194, 298]

Korea FF/UMEC/VI 23 21.4 [17.6, 25.9] 313 [234, 420]FF/VI 28 12.1 [10.9, 13.5] 143 [126, 163]

China FF/UMEC/VI 34 17.9 [15.1, 21.1] 216 [175, 266]FF/VI 32 11.5 [10.4, 12.8] 135 [118, 155]

East Asia FF/UMEC/VI 113 22.0 [20.2, 24.0] 279 [250, 312]FF/VI+UMEC 14 24.0 [20.5, 28.0] 274 [235, 320]FF/VI 83 13.6 [12.5, 14.8] 162 [146, 179]

208059 = Studies CTT116853, CTT116855 and 200812; East Asian heritage = Asia – East Asian heritage + Asian –Japanese heritage; East Asia = Japan + China + Korea

The PK of UMEC in 200812, CTT116853 and CTT116855 was well-described by a two-compartment model with first-order absorption and first-order elimination. Weight, age and smoking status were found to be significant covariates on CL/F and weight was also a significant covariate on the apparent volume of distribution of the central compartment (V2/F). However, no dose adjustment was warranted for these covariatesbased on the predicted systemic exposure.

The final parameter estimates for the UMEC population PK model are presented in the table below.

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UMEC Population PK Final Model Parameter Estimates208059

Parameter Estimate[95% CI]

CL/F [L/h] 149 [138, 160]V2/F [L] 1100 [1030, 1170]Q/F [L/h] 854 FIXEDV3/F [L] 16200 FIXEDKA [h-1] 18.6 [16.2, 21.0]

Weight exponent on CL/F 0.580 [0.409, 0.751]Age exponent on CL/F -0.648 [-0.979, -0.317]Smoking effect on CL/F 1.28 [1.13, 1.45]

Weight exponent on V2/F 0.797 [0.614, 0.980]

Based on the post-hoc PK parameter estimates for UMEC (dose 62.5 mcg once-daily), steady-state systemic exposures were derived and are summarized by treatment, geographic ancestry or race and by country/geographical region in the tables below. Please note that although systemic exposures are summarized by geographic ancestry or race and by country/geographical region, race was not identified as significant covariate to affect UMEC PK parameters.

Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to UMEC following administration of 62.5 mcg UMEC by Treatment in Subjects with COPD


FF/VI+UMEC 106 51.4 [46.9, 56.4] 359 [325, 397]UMEC/VI 103 67.6 [60.4, 75.6] 408 [368, 452]

Historical AnalysesCTT116853 FF/UMEC/VI 74 55.7 [50.4, 60.9] 341 [301, 381]

DB2116975 UMEC and UMEC/VI (DB2113373)

827 69.3 [67.0, 71.6] 312 [302, 323]

DB2116975 UMEC/VI (DB2113373)

410 68.5 [65.2, 71.9] 308 [293, 328]

DB2116975 UMEC (DB2113373) 417 70.3 [67.0, 73.8] 318 [303, 334]208059 = Studies CTT116853, CTT116855 and 200812

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Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to UMEC following administration of 62.5 mcg UMEC by Geographic Ancestry or Race and Country/Geographical Region in Subjects with COPD


UMEC/VI 55 60.3 [51.5, 70.5] 353 [307, 406]Japanese heritage 208059 FF/UMEC/VI 56 85.6 [78.9, 92.8] 529 [476, 587]

FF/VI+UMEC 14 68.8 [57.9, 81.8] 490 [413, 580]UMEC/VI 17 86.4 [62.5, 119] 496 [378, 650]

CTT116855 FF/UMEC/VI 33 87.8 [77.9, 99.1] 516 [446, 597]

UMEC/VI 17 86.4 [62.5, 119] 496 [378, 650] 200812 FF/UMEC/VI 23 82.4 [74.3, 91.4] 548 [468, 642]

FF/VI+UMEC 14 68.8 [57.9, 81.8] 490 [413, 580]

East Asian heritage FF/UMEC/VI 113 73.9 [68.6, 79.6] 499 [460, 541]FF/VI+UMEC 14 68.8 [57.9, 81.8] 490 [413, 580]UMEC/VI 47 77.9 [66.4, 91.3] 486 [421, 562]


FF/VI+UMEC 14 68.8 [57.9, 81.8] 490 [413, 580]UMEC/VI 17 86.4 [62.5, 119] 496 [378, 650]

Korea FF/UMEC/VI 23 75.1 [63.5, 97.9] 551 [462, 658]UMEC/VI 11 78.8 [63.5, 97.9] 498 [386, 642]

China FF/UMEC/VI 34 57.3 [49.4, 66.5] 423 [357, 502]UMEC/VI 19 70.4 [53.6, 92.6] 472 [364, 612]

East Asia FF/UMEC/VI 113 73.9 [68.6, 79.6] 499 [460, 541]FF/VI+UMEC 14 68.8 [57.9, 81.8] 490 [413, 580]UMEC/VI 47 77.9 [66.4, 91.3] 486 [421, 562]


The PK of VI in 200812, CTT116853 and CTT116855 was well-described by a two-compartment model with first-order absorption and first-order elimination. Weight and smoking status were found to be significant covariates on CL/F and V2/F, respectively. However, no dose adjustment was warranted for these covariates based on the predicted systemic exposures.

The final parameter estimates for the VI population PK model are presented in the table below.

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VI Population PK Final Model Parameter EstimatesParameter Estimate

[95% CI]CL/F [L/h] 73.5 [69.7, 77.3]V2/F [L] 352 [333, 371]Q/F [L/h] 242 [230, 254]V3/F [L] 2250 [1670, 2830]KA [h-1] 19.6 FIXED

Weight exponent on CL/F 0.444 [0.281, 0.607]Smoking effect on V2/F 1.46 [1.34, 1.59]

Based on the post-hoc PK parameter estimates for VI (dose 25 mcg once-daily), steady-state systemic exposures were derived and are summarized by treatment, by geographic ancestry or race and by country/geographic region in the tables below. Please note that although systemic exposures are summarized by geographic ancestry or raceand by country/geographic region, race was not identified as significant covariate to affect VI PK parameters.

Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to VI following administration of 25 mcg VI by Treatment in Subjects with COPD


FF/VI+UMEC 106 64.4 [60.4, 68.6] 349 [321, 380]FF/VI 195 56.4 [53.7, 59.2] 351 [330, 372]UMEC/VI 103 64.4 [59.6, 69.6] 350 [321, 381]

Historical AnalysesCTT116853 FF/UMEC/VI 74 101 [91.1, 112] 666 [604, 728]

DB2116795 UMEC/VI (DB2113361)

402 128 [122, 135] 617 [592, 642]

VI (DB2113361) 404 128 [122, 135] 611 [587, 635]UMEC/VI (DB2113373)

410 128 [122, 135] 612 [589, 637]

VI (DB2113373) 421 128 [122, 135] 613 [589, 637]

HZC112206, HZC112207, HZC110946,HZC111348

VI 714 42.3 [40.7, 44.0] 262 [254, 269]

HZC112206, HZC112207, HZC110946,HZC111348

FF/VI 338 40.1 [37.9, 42.4] 261 [251, 272]

208059 = Studies CTT116853, CTT116855 and 200812

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Model-Predicted Systemic Exposure (Geometric mean [95% CI]) to VI following administration of 25 mcg VI by Geographic Ancestry or Race and Country/Geographical Region in Subjects with COPD


FF/VI 101 55.1 [51.5, 58.9] 339 [308, 373]UMEC/VI 55 59.4 [53.5, 66.0] 322 [286, 361]

Japanese heritage 208059 FF/UMEC/VI 56 77.8 [69.4, 87.3] 389 [348, 434]


CTT116855 FF/UMEC/VI 33 76.2 [64.0, 90.8] 354 [315, 396]

FF/VI 23 62.0 [52.6, 73.0] 387 [343, 438]UMEC/VI 17 75.9 [60.0, 96.1] 367 [305, 442]

200812 FF/UMEC/VI 23 80.3 [70.0, 92.1] 446 [361, 551]

FF/VI+UMEC 14 67.5 [59.7, 76.4] 381 [330, 440]

East Asian heritage FF/UMEC/VI 113 72.7 [67.3, 78.6] 386 [357, 418]FF/VI+UMEC 14 67.5 [59.7, 76.4] 381 [330, 440]FF/VI 83 58.8 [54.7, 63.2] 371 [344, 400]UMEC/VI 47 70.6 [62.9, 79.3] 367 [305, 442]



Korea FF/UMEC/VI 23 66.9 [64.3, 69.5] 357 [343, 372]FF/VI 28 56.1 [50.0, 63.0] 350 [311, 395]UMEC/VI 11 70.7 [55.1, 90.8] 389 [297, 510]

China FF/UMEC/VI 34 62.0 [53.9, 71.3] 336 [289, 391]FF/VI 32 59.0 [52.4, 66.5] 378 [326, 438]UMEC/VI 19 66.1 [55.6, 78.6] 399 [310, 514]

East Asia FF/UMEC/VI 113 72.7 [67.3, 78.6] 386 [357, 418]FF/VI+UMEC 14 67.5 [59.7, 76.4] 381 [330, 440]FF/VI 83 58.8 [54.7, 63.2] 371 [344, 400]UMEC/VI 47 70.6 [62.9, 79.3] 367 [305, 442]


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Conclusions:

All FF, UMEC, VI plasma concentrations were well interspersed with historical data and FF, UMEC and VI PK were all adequately described by a two-compartment model with first-order absorption.

For FF, Japanese heritage and FF/VI treatment were significant covariates on apparent inhaled clearance. For UMEC, weight, age and smoking status on apparent inhaled clearance and weight on apparent volume of distribution were significant covariates. For VI, weight on apparent inhaled clearance and smoking status on apparent volume of distribution were significant covariates. The majority of thesecovariates have been previously identified in historical analyses.

Neither the increase in FF systemic exposure in subjects of Japanese heritage vs. non-Japanese heritage or in subjects receiving FF/VI vs. FF/UMEC/VI is likely to be clinically relevant as these systemic exposures remain well below the threshold for FF-induced reduction of serum cortisol.

In a similar manner, neither the decrease in UMEC CL/F with increasing age or decreasing weight or decrease in VI CL/F with decreasing weight or the increased V2/F in COPD subjects who smoke are likely to be clinically relevant.

Overall, population pharmacokinetic analyses (similar to historical) demonstrated that the effects of these covariates on PK were marginal and no dose adjustment was deemed necessary for FF, UMEC or VI based on these covariates.

Steady state AUCss and Cmax ss for FF/UMEC/VI were consistent with historical data for FF/VI and UMEC/VI and there was no clinically relevant difference in FF, UMEC or VI systemic exposure when administered as FF/UMEC/VI, FF/VI+UMEC or the dual combinations FF/VI and/or UMEC/VI.

In conclusion, population PK analysis for FF/UMEC/VI using combined data from CTT116855, 200812 and CTT116853 were consistent with those for the components when given in dual combination. The models described adequately the PK of FF, UMEC and VI in patients with COPD. No dose adjustments are warranted based on age, weight, smoking status or race.

Effective Date: 09-JAN-2018

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1. INTRODUCTION

This report describes the population pharmacokinetic (POP PK) analysis performed for fluticasone furoate (FF compound number GW685698), umeclidinium (UMEC compound number GSK573719) and vilanterol (VI compound number GW642444) in a subset of patients with chronic obstructive pulmonary disease (COPD) recruited in studies 200812, CTT116853 and CTT116855.

Chronic obstructive pulmonary disease (COPD) is a progressive disease characterized by increasing obstruction to airflow and the progressive development of respiratory symptoms including chronic cough, increased sputum production, dyspnea and wheezing.

The PK of FF, UMEC and VI have been previously characterized in COPD patients following monotherapy and when administered as dual combination FF/VI or UMEC/VI using non-linear mixed effects modelling (NONMEM). Additionally, these models adequately described the PK of FF, UMEC and VI following administration of FF/UMEC/VI in a single inhaler when data from CTT116853 was overlaid on predicted concentrations from simulated models. Although none of the drug-drug interaction studies or previous population PK analyses conducted during clinical development of mono and dual therapy treatments suggested PK interaction, the current analysis was planned to assess the effect on PK (as well as effect of covariates on PK) when the 3 drugs were administered in a single inhaler. Given the relatively small PK subsets in the phase III studies, and the sparse nature of PK sampling in these studies, a model-based population PK using non-linear mixed effects was considered the most robust approach for assessing the PK of FF, UMEC and VI in the COPD population. The results and conclusions of this analysis will be used to support and augment multiple global regulatory submissions.

The population PK methodology and analysis following FF/UMEC/VI in these studies focused on characterizing the systemic exposure (rate and extent) of the individual analytes, FF, UMEC and VI, in a limited number of subjects with COPD. The main aim of the analysis was to characterize the PK of FF, UMEC and VI in adults with COPD. A covariate analysis was undertaken to identify potential covariates that influence the PK of FF, UMEC or VI. The individual post-hoc parameter estimates from the final PK models were used to derive the steady-state systemic exposure for each analyte. The population PK analyses were based on the approved Reporting and Analysis Plan [208059 Reporting and Analysis Plan] and relevant regulatory guidance documents [FDA, 1999; EMA, 2007].

2. STUDY OBJECTIVES & ENDPOINTS

2.1. Objective(s)

The primary objectives of the analyses were:

to characterize the population PK of FF, UMEC and VI in adults with COPD following administration of FF/UMEC/VI in a single inhaler and following administration of FF/VI+UMEC, FF/VI, UMEC/VI.

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to identify influential covariates, such as age, race, gender, weight, body mass index, smoking status, concurrent medications (cytochrome P450 inhibitors, Pgp inhibitors), lung function status in terms of reversibility post albuterol/salbutamol, percent predicted FEV1 at screening (PPFEV1) and creatinine clearance on the PK of FF, UMEC and VI in patients with COPD.

2.2. Endpoint(s)

Non-linear mixed effects model (NONMEM) generated post-hoc estimates for FF, UMEC and VI POP PK parameters and associated inter-subject variability and residual error: Apparent clearance (CL/F), apparent volume of distribution (V/F), Ka

(absorption rate constant) (model-dependent) Derived PK parameters:

Area under the curve at steady state (AUCss) and maximum observed concentration at steady state (Cmax ss).

3. STUDY DESIGN

3.1. Study CTT116853

Study CTT116853 [GlaxoSmithKline Document Number 2013N180749_04] was a phase IIIa, randomized, double-blind, double-dummy, parallel group study evaluating once daily FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) inhalation powder via a single ELLIPTA inhaler versus twice daily budesonide/formoterol (400 mcg/12 mcg). Eligible subjects were to be randomized 1:1 to one of the two treatments. A total of 1,810 subjects were included in the ITT population. The total duration of the study was approximately 27 weeks, consisting of a 2-week run-in period, 24-week treatment period and a 1-week safety follow-up period. The study schematic is displayed in Figure 1.

A subset of 74 subjects (64 subjects with sparse sampling and 10 subjects with serialsampling) treated with FF/UMEC/VI) provided PK samples for the POP PK analyses of FF, UMEC and VI (PK population).

Figure 1 Study CTT116853 Schematic Diagram

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3.2. Study 200812

Study 200812 [GlaxoSmithKline Document Number 2015N261999_03] was a phase IIIb, 24-week, randomized, double-blind, parallel group multicenter study evaluating FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) via a single ELLIPTA plus matching placebo versus FF/VI + UMEC delivered via two ELLIPTA inhalers, all taken once daily. Eligible subjects were to be randomized 1:1 to one of the two treatments. A total of 1,055 subjects were included in the ITT population. The total duration of the study was approximately 27 weeks, consisting of a 2-week run-in period, 24-week treatment period and a 1-week follow-up period. The study schematic is displayed in Figure 2.

A subset of 227 subjects provided PK samples (163 subjects with sparse samples and 64subjects with serial samples) at Visits 4 (wk 12) and 5 (wk 24) for the POP PK analyses of FF, UMEC and VI (PK population).

Figure 2 Study 200812 Schematic Diagram

3.3. Study CTT116855

Study CTT116855 [GlaxoSmithKline Document Number 2013N176913_05] was a phase IIIa, randomized, double-blind, 3-arm parallel group study evaluating FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) inhalation powder via a single ELLIPTA inhaler versus FF/VI (100 mcg/25 mcg) inhalation powder (RELVAR ELLIPTA or BREO ELLIPTA) and UMEC/VI (62.5 mcg/25 mcg) inhalation powder (ANORO ELLIPTA), all given once daily in the morning. Eligible subjects were to be randomized 2:2:1 to the FF/UMEC/VI, FF/VI or UMEC/VI treatments. The study schematic is displayed in Figure 3.

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This study enrolled 10,355 subjects in the ITT population. The total duration of the study was approximately 55 weeks, consisting of a 2-week run-in period, 52-week treatment period and a 1-week safety follow-up period. A subset of 520 subjects provided PK samples (all sparse) at Visits 4 (wk 16) and 5 (wk 28) for the POP PK analyses of FF, UMEC and VI (PK population).

Figure 3 Study CTT116855 Schematic Diagram

3.4. Selection of Study Population

3.4.1. Inclusion/Exclusion Criteria

All studies included male and female subjects aged ≥ 40 years, with clinical history of COPD and a history of at least 10 pack-years of cigarette smoking at Screening (Visit 1). Additionally, subjects were required to have a score of ≥ 10 on the COPD Assessment Test (CAT) and a post-albuterol/salbutamol FEV1/FVC ratio of ≤ 0.70 at Screening. For Studies CTT116855 and 200812, subjects were required to have post-albuterol/salbutamol 50% ≤ FEV1 < 80% of predicted normal and a documented history of ≥ 2 moderate exacerbations or a documented history of ≥ 1 severe COPD exacerbation (hospitalized) in the previous 12 months or a post-bronchodilator FEV1 < 50% predicted normal and a documented history of ≥ 1 moderate or severe COPD exacerbation in the previous 12 months. For Study CTT116853, subjects were required to have a post albuterol/salbutamol FEV1 < 50% of predicted normal or a post-bronchodilator FEV₁

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Table 1 Treatments Assessed in Population PK Analysis

Treatment Arm Analyte Study PopPK Dataset

FF/UMEC/VI FF, UMEC, VI CTT116853CTT116855200812

FF PopPKUMEC PopPKVI PopPK

FF/VI+UMEC FF, UMEC, VI 200812 FF PopPKUMEC PopPKVI PopPK

FF/VI FF, VI CTT116855 FF PopPKVI PopPK

UMEC/VI UMEC, VI CTT116855 UMEC PopPKVI PopPK

3.6. Study Assessments and Procedures

3.6.1. Pharmacokinetic Assessments

A summary of the PK sampling schedule for each of the three studies is presented in Table 2.

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Table 2 Summary of PK Sampling Schedule by Study

Study Treatment Arms Sampling Schedule (nominal)

200812 FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg)

FF/VI + UMEC (100 mcg/25 mcg + 62.5 mcg)

PK Subset A (Sparse PK Samples):

Week 12 (V4): pre-dose and in the window of 5-15 min post-dose

Week 24 (V5): in the window of 5-15 min and 45 – 90 min post-dose

PK Subset B (Serial PK Samples):

Week 12 (V4): pre-dose and in the windows of 5-15 min, 45-90 min, 2.5-4 h, 6-8 h, 10-12 h and 23-24 h post-dose

CTT116853 FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg)

Budesonide/formoterol (400 mcg/12 mcg)

PK Subset A (Sparse PK Samples):



PK Subset B (Serial PK Samples):

Week 24 (V6): pre-dose and in the windows of 5-15 min, 45-90 min, 2.5-4 h, 6-8 h, 10-12 h and 23-24 h post-dose

CTT116855 FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg)

FF/VI (100 mcg/25 mcg)

UMEC/VI (62.5 mcg/25 mcg)

PK Subset (Sparse PK Samples):



V4 = Visit 4; V5 = Visit 5; V6 = Visit 6.

3.6.2. Assay Methods

Plasma samples were analyzed for FF, UMEC and VI using validated analytical methods based on solid phase extraction, followed by high-pressure liquid chromatography with tandem mass spectrometric analysis for detection. The lower limit of quantification (LLQ) for FF, UMEC and VI in plasma was 10.0 pg/mL and the higher limit of quantification (HLQ) was 1000 pg/mL for FF and VI and 2000 pg/mL for UMEC [GlaxoSmithKline Document Number 2014N190410_00, UMEC/VI; GlaxoSmithKline

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Document Number 2014N211586_00, FF; GlaxoSmithKline Document Number 2014N204417_00, Amendment 01 UMEC/VI and GlaxoSmithKline Document Number 2016N285561_00, Amendment 2 UMEC/VI].

For each analytical method, quality control samples (QC) were prepared at 4 different analyte concentrations. These samples, stored with study samples, were analyzed with each batch of samples against separately prepared calibration standards. For the analysis to be acceptable, no more than one-third of the QC results were to deviate from the nominal concentration by more than 15%, and at least 50% of the results from each QC concentration should be within 15% of nominal. The applicable analytical runs met all predefined run acceptance criteria.

Bioanalysis of PK samples was performed by WuXi AppTech, Shanghai, China , under the direct auspices of the Platform Technology and Sciences (PTS) Division, GSK.

The computer systems that were used on these studies to acquire and quantify the bioanalytical data included Analyst (Versions 1.5.1) and Watson Laboratory Information Management System (Version 7.2). All bioanalytical data are stored in the Archive at WuXi AppTech, Shanghai, P.R. China under Study References 15BAS0277.

3.6.3. Analysis Populations

Intent-to-Treat (ITT) Population: The ITT Population was defined as all subjects who were randomized, excluding those who were randomized in error and did not receive a dose of study medication. A subject who was recorded as a screen or run-in failure and also randomized, but did not receive a dose of study treatment, was considered to be randomized in error. Any other subject who received a randomization number will be considered to have been randomized.

PK Population: The PK population comprised of all subjects in the ITT Population from each study from whom a PK sample was obtained and analysed for FF, UMEC or VI, and has time of dosing and time of PK sample draw relative to dosing. This population was used for creation of the AXPOPPK dataset.

FF PK Population: The FF PK population was used for FF POP PK analysis. The FF PK population comprised of all subjects in the ITT Population from each study from whom a PK sample was obtained, analysed for FF concentration and a result reported in the FF concentration-time dataset. Additionally, subjects in the FF PK analysis population had time of dosing and time of PK sample draw relative to dosing for at least one PK sample at a visit at which PK was scheduled and at which FF was analysed and information on all covariates that were included in the final dataset.

UMEC PK Population: The UMEC PK population was used for UMEC POP PK analysis. The UMEC PK population comprised of all subjects in the ITT Population from each study from whom a PK sample was obtained, analysed for UMEC concentration and a result reported in the UMEC concentration-time dataset. Additionally, subjects in the UMEC PK analysis population had time of dosing and time of PK sample draw relative to dosing for at least one PK sample at a visit at which PK was scheduled and at which

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UMEC was analysed and information on all covariates that were included in the final dataset.

VI PK Population: The VI PK population was used for VI POP PK analysis. The VI PK population comprised of all subjects in the ITT Population from each study from whom a PK sample was obtained, analysed for VI concentration and a result reported in the VI concentration-time dataset. Additionally, subjects in the VI PK analysis population hadtime of dosing and time of PK sample draw relative to dosing for at least one PK sample at a visit at which PK was scheduled and at which VI was analysed and information on all covariates that were included in the final dataset.

3.6.4. Changes in Conduct of the Study or Planned Analyses

Thirty-three (33) separate concomitant medications (that were on the prohibited/excluded medicine list such as cytochrome P450 3A4 inhibitors and P-glycoprotein inhibitors) were included in the source population PK dataset across the three studies. Less than 5% of subjects had any one of the 33 concomitant medications. Therefore, the potential impact of these concomitant medications on the PK of FF, UMEC or VI was not formally explored during the covariate analysis. The R code to determine the frequency of each of the 33 concomitant medications included in the source population PK dataset is presented in Table 1.4.

In the dataset specifications included in the RAP, all dosing records were to be assigned with the NONMEM event item (EVID) of 1. For the final analysis datasets, the first dosing record for each visit was assigned with EVID=4 to establish steady-state conditions at each visit. Subsequent dosing records at each visit were assigned EVID=1.

The RAP proposed that the covariate analysis would be performed using a step-wise forward addition/backward elimination procedure. Given the difficulties encountered in obtaining models that converged successfully, a full covariate model approach was utilized. Potential covariates were screened using graphical exploration and were included in a full model. Covariates were removed from the full model based on the point estimate and standard errors of the estimates.

In the historical FF/VI analysis (GlaxoSmithKline Document Number2011N122282_00), during assessment of race covariate, Japanese and other East Asian subjects (from other countries such as Korea), were evaluated together in a single combined “East Asian, Japanese and South East Asian” race category due to the small number of subjects in each individual category. In the current analysis (208059), study CTT116855 planned to recruit a minimum of 50 subjects each in Japan, China and Korea and study 200812 planned to recruit approximately 50 subjects in Japan in each treatment arm and all were invited to participate in PK sample collection. Therefore, the present analysis assessed subjects of Japanese heritage or East Asian heritage separately for their effects on FF, UMEC and VI PK. However, to allow a direct comparison with the historical FF/VI data, an additional analysis was also conducted using a single East Asian race category which included subjects nominating either East Asian ancestry or Japanese ancestry resident in any country. This secondary analysis is discussed in Section 6.10.

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4. PHARMACOKINETIC DATA ANALYSIS

4.1. Software Information

The population PK modeling and simulations were performed using NONMEM v7.3.0(ICON Development Solutions) under Windows 7 Professional operating system with Intel Visual FORTRAN Complier Professional, version 11.1, interfaced with PDx-Pop v5.2 (ICON Development Solutions). Stochastic Approximation Expectation Maximization (SAEM) with interaction was selected as the estimation method. Supporting applications for data handling, exploratory diagnostics and simulation included R (the R Foundation for Statistical Computing v3.1.1). Summary statistics of FF, UMEC and VI plasma concentrations by time interval and % observations below the quantification limit (BQL) in each interval were created using the SAS version supported by ICON at the time of analysis.

4.2. Dataset Preparation

The population PK data were provided by Veramed, a supplier of statistics and programming services for GSK. The specifications for the format of the data are provided in Section 9.1 of the population PK RAP. FF, UMEC and VI population PK data was prepared from SDTM PC datasets of each study. The data was made available to the Clinical Pharmacology, Modeling and Simulations (CPMS) group in a comma separated value (.csv) format. For this analysis, the description of geographic ancestry noted for each subject has been recorded as a “race” covariate.

4.3. Sample Size Consideration

No formal sample size calculations were performed for the population PK analyses for any of the 3 studies. The number of subjects on each treatment is listed in Table 3. The FF analysis dataset consisted of a total of 2948 observations from 714 subjects. The UMEC analysis dataset consisted of a total of 2589 observations from 622 subjects. The VI analysis dataset consisted of a total of 3331 observations from 817 subjects.

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Table 3 Number of Subjects for Population PK Analyses

PK dataset Treatment Arm 200812 CTT116853 CTT116855

714 subjects in FF PK dataset

FF/UMEC/VI 121 74 218

FF/VI NA NA 195

FF/VI + UMEC 106 NA NA

622 subjects in UMEC PK dataset

FF/UMEC/VI 121 74 218

UMEC/VI NA NA 103


817 subjects in VI PK dataset

FF/UMEC/VI 121 74 218

FF/VI NA NA 195


UMEC/VI NA NA 103

NA = Not Applicable

4.4. FF/UMEC/VI Dataset

4.4.1. FF Dataset

The FF dataset used in this analysis was constructed by combining FF time-concentration data from FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) from 200812, CTT116853 and CTT116855 with data from FF/VI (100 mcg/25 mcg) from 200812 (from FF/VI+UMECarm) and CTT116855.

4.4.2. UMEC Dataset

The UMEC dataset used in this analysis was constructed by combining UMEC time-concentration data from FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) from 200812, CTT116853 and CTT116855 with data from UMEC (62.5 mcg) from 200812 (from FF/VI+UMEC arm) and data from UMEC/VI (62.5 mcg/25 mcg) from CTT116855.

4.4.3. VI Dataset

The VI dataset used in this analysis was constructed by combining VI time-concentration data from FF/UMEC/VI (100 mcg/62.5 mcg/25 mcg) from 200812, CTT116853 and CTT116855 with data from FF/VI (100 mcg/25 mcg) from 200812 (from FF/VI+UMECarm) and CTT116855 and data from UMEC/VI (62.5 mcg/25 mcg) from CTT116855.

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4.5. Covariates

Covariates listed in Table 4 were included in the FF, UMEC and VI population PK datasets and were planned to be evaluated during the population PK modeling process. The concomitant medications are described in detail in Section 9.1 of the population PK Reporting and Analysis Plan

Table 4 Pre-planned Covariates for Population PK Analyses

Age

Body Weight

Body Mass Index

Gender

Race (White, African American/African Heritage, Asian, Others).

Subjects were further categorized based on country or geographic region: Japan, China, Korea or East Asia (Japan + China + Korea)

or by ancestry East Asian (Asian - Japanese Heritage + Asian - East Asian Heritage).

Percent Predicted FEV1 at Screening

Concomitant medications

Post Albuterol/Salbutamol Reversibility

Treatment effect (FF/UMEC/VI, FF/VI+UMEC; FF/VI; UMEC/VI)

Study effect (200812, CTT116853, CTT116855)

Smoking Status at Screening (Current or Former smoker)

4.6. Data Handling Conventions

4.6.1. Missing covariates

FF Analysis Dataset

Percent predicted FEV1 at baseline was missing in 18 subjects, post albuterol/salbutamol reversibility at screening was missing in 6 subjects and baseline/screening CrCL value was missing in 3 subjects. This represented between 0.4 and 2.5% of the 714 subjects included in the FF analysis dataset. Each of these covariates was included in the graphical exploration of potential covariate-parameter relationships.

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UMEC Analysis Dataset

Percent predicted FEV1 at baseline was missing in 18 subjects, post albuterol/salbutamol reversibility at screening was missing in 6 subjects and baseline/screening CrCL value was missing in 3 subjects. This represented between 0.5 and 2.9% of the 622 subjects included in the UMEC analysis dataset. Each of these covariates was included in the graphical exploration of potential covariate-parameter relationships.

VI Analysis Dataset

Percent predicted FEV1 at baseline was missing in 18 subjects, post albuterol/salbutamol reversibility at screening was missing in 6 subjects and baseline/screening CrCL value was missing in 3 subjects. This represented between 0.4 and 2.5% of the 817 subjects included in the VI analysis dataset. Each of these covariates was included in the graphical exploration of potential covariate-parameter relationships.

4.6.2. Missing concentrations (dependent variable)

The lower limit of quantification (LLQ) for FF, UMEC and VI was 10 pg/mL. All analyzed samples determined to be below the LLQ were kept in the dataset and denoted as samples below quantification limit (BQL). Table 5, Table 6 and Table 7 list the percentage of samples determined to be BQL along with actual sample numbers analyzed across the PK sampling windows for FF, UMEC and VI, respectively. Samples taken outside of the sampling windows were not included in these summaries. These BQLsamples were analyzed as censored data during the population PK analysis [Ahn, 2008].

Table 5 Summary of FF BQL Samples Included in FF Analysis Dataset

Time % FF BQL Samples(Samples Reported as BQL/Total Samples Analyzed)

200812 CTT116853 CTT116855Pre-dose 171/214 (80%) 57/72 (79%) 323/399 (81%)5 – 15 min 100/370 (27%) 43/134 (32%) 274/781 (35%)45 – 90 min 28/215 (13%) 7/71 (10%) 73/387 (19%)2.5 – 4 h 12/64 (19%) 2/10 (20%)6 – 8 h 28/64 (44%) 4/10 (40%)10 – 12 h 36/63 (57%) 7/10 (70%)23-24 h 39/64 (61%) 8/10 (80%)Total Samples by Study 414/1054 (39%) 128/317 (40%) 670/1567 (43%)Total Samples for FF 1212/2938 (41%)Data Source: Table 5.2, Table 5.4, Table 5.6: Samples taken outside planned sampling windows were excluded from summaries. The total number of FF concentration samples included in the FF analysis dataset was 2948.

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Table 6 Summary of UMEC BQL Samples Included in UMEC Analysis Dataset

Time % UMEC BQL Samples(Samples Reported as BQL/Total Samples Analyzed)

200812 CTT116853 CTT116855Pre-dose 82/216 (38%) 31/72 (43%) 86/310 (28%)5 – 15 min 17/368 (5%) 9/134 (7%) 12/600 (2%)45 – 90 min 11/215 (5%) 5/71 (7%) 10/297 (3%)2.5 – 4 h 12/64 (19%) 0/9 (0%)6 – 8 h 20/64 (31%) 1/9 (11%)10 – 12 h 21/63 (33%) 1/10 (10%)23 – 24h 21/64 (33%) 2/10 (20%)Total Samples by Study 184/1054 (17%) 49/315 (16%) 108/1207 (9%)Total Samples for UMEC 341/2576 (13%)Data Source: Table 5.8, Table 5.10, Table 5.12: Samples taken outside planned sampling windows were excluded from summaries. The total number of UMEC concentration samples included in the UMEC analysis dataset was 2589.

Table 7 Summary of VI BQL Samples Included in VI Analysis Dataset

Time % VI BQL Samples(Samples Reported as BQL/Total Samples Analyzed)

200812 CTT116853 CTT116855Pre-dose 125/216 (58%) 47/72 (65%) 325/500 (65%)5 – 15 min 19/368 (5%) 12/134 (9%) 58/971 (6%)45 – 90 min 14/214 (7%) 5/69 (7%) 17/479 (4%)2.5 – 4 h 4/64 (6%) 0/10 (0%)6 – 8 h 14/63 (22%) 2/10 (20%)10 – 12 h 24/63 (38%) 5/10 (50%)23 – 24h 29/64 (45%) 4/9 (44%)Total Samples by Study 229/1052 (22%) 75/314 (24%) 400/1950 (21%)Total Samples for VI 704/3316 (21%)Data Source: Table 5.14, Table 5.16, Table 5.18: Samples taken outside planned sampling windows were excluded from summaries. The total number of UMEC concentration samples included in the UMEC analysis dataset was 3331.

4.6.3. Missing dosing times

For Study CTT116855, for Subject the date/time of dose prior to first PK sample at Visit 4 was missing and therefore, Visit 4 data for this subject was excluded from the analyses.

4.6.4. Missing PK sampling times

There were no missing PK sampling times from any of the three studies included in the present analyses.

4.7. PK Outliers

For all three analytes (FF, UMEC and VI), there were unexpectedly high concentrations associated with some PK samples taken more than 20 hours after the last dose. In some

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cases, these concentrations were higher than the 0-15 min post-dose sample in the same subject.

For FF, of the 759 PK samples taken 20 hours post-dose or later, 79% were BQL. Of the 161 quantifiable concentrations taken 20 hours post-dose, FF concentrations ranged from 10.1 to 54.7 pg/mL. These quantifiable concentrations represented 5.5% of the total number of observations in the FF dataset.

For UMEC, of the 673 PK samples taken 20 hours post-dose or later, 33% were BQL. Of the 451 quantifiable concentrations taken 20 hours post-dose, UMEC concentrations ranged from 10.0 to 162 pg/mL. These quantifiable concentrations represented 17.4% of the total number of observations in the UMEC dataset.

For UMEC, of the 862 PK samples taken 20 hours post-dose or later, 62% were BQL. Of the 331 quantifiable concentrations taken 20 hours post-dose, VI concentrations ranged from 10.0 to 124 pg/mL. These quantifiable concentrations represented 9.9% of the total number of observations in the VI dataset.

A preliminary exploration of these unexpectedly high trough concentrations did not identify a common factor, such as study centre, that might explain these data. As these unexpectedly high trough concentrations represented a relatively small percentage of the overall data for each analyte, they were not expected to unduly influence the estimate of the model parameters and were, therefore, retained in the final analyses. In the previous UMEC/VI analysis, a similar phenomenon was observed in relation to a few study centers (Goyal, 2014). A sensitivity analysis (population PK) including and excludingsamples from those centers indicated < 5% difference in the estimated parameters and therefore all samples were retained in the previous UMEC/VI analysis. Using this historical evidence, a decision was made not to exclude high trough concentration samples in the current analysis.

4.8. Modelling Procedure

Population non-linear mixed effects modelling was performed using the approach described in the Reporting and Analysis Plan

Nonlinear mixed effect modeling approach was used to estimate FF, UMEC and VI PK parameters based on the available data and the regulatory guidance documents [FDA, 1999; EMA, 2007].

4.8.1. Population PK Analysis

For each study, PK samples were collected as described in Table 2. Actual sampling times were used in the analysis. Approximately 41, 13 and 21% of concentrations in the FF, UMEC and VI PK were BQL. The R code to derive the proportion of BQL observations in each of the datasets is presented in Table 5.22. The full likelihood methods implemented in NONMEM were used to analyze such BQL data [Ahn, 2008]. The Stochastic Approximation Expectation Maximization (SAEM) with interaction was the method used in NONMEM for the FF, UMEC and VI population PK analyses. Under this method, the BQL data was considered to be censored. The F_FLAG method in

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NONMEM was used to estimate the likelihood for BQL data while simultaneously fitting and estimating the model parameters using the data above LLQ.

4.8.2. Exploratory Data Analysis

Exploratory data analysis was performed to understand the informational content of the analysis datasets with respect to the anticipated models, to search for extreme values and/or potential outliers, to examine the correlation between covariates and to assess possible trends in the data.

In addition, Monte Carlo simulations using the previously reported population PK models for FF, UMEC and VI were undertaken to confirm that the data from studies 200812, CTT116853 and CTT116855 were consistent with previous studies. The observed concentration versus time data were overlaid onto the 90% prediction intervals (PI) to assess the ability of these models to describe the observed data from Studies 200812, CTT116853 and CTT116855.

4.8.3. Structural Model Development

A model-based estimation approach was undertaken whereby the plasma concentration-time data from FF, UMEC and VI from Studies 200812, CTT116853 and CTT116855 were combined.

The previously developed population PK base models (i.e., no covariates included) for inhaled FF, UMEC and VI [GlaxoSmithKline Document Number 2011N122282_00, GlaxoSmithKline Document Number 2012N137814_00] served as the starting point for the structural model development.

4.8.4. FF Structural Model

The previous population PK model for FF in subjects with COPD [GlaxoSmithKline Document Number 2011N122282_00; Siederer, 2016] was used as a starting point for this analysis. The PK of FF were well described by a two-compartment model with first-order absorption and first-order elimination. The only covariate found to be statistically significant was race on inhaled clearance (CL/F) but no dose adjustment was warranted based on the predicted systemic FF exposures. More details on the model output (Run 52; dmp6688-1.0) can be found in GlaxoSmithKline Document Number2011N122282_00.

4.8.5. UMEC Structural Model

The previous population PK model for UMEC in subjects with COPD [GlaxoSmithKline Document Number 2012N137814_00; Goyal, 2014] was used as a starting point for this analysis. The PK of UMEC were well described by a two-compartment model with first-order absorption and first-order elimination. Weight, age and baseline creatinine clearance (calculated by Cockcroft-Gault equation) were found to be significant covariates on CL/F and weight was also a significant covariate on the apparent volume of distribution (V/F). However, no dose adjustment was warranted for these covariatesbased on the predicted systemic UMEC exposures. More details on the model output

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(umpop27_ka, dmp 10706) can be found in GlaxoSmithKline Document Number2012N137814_00.

4.8.6. VI Structural Model

Two population PK models in subjects with COPD for VI were available to support the present analysis.

The VI population PK model from the UMEC/VI program [GlaxoSmithKline Document Number 2012N137814_00; Goyal, 2014] was a two-compartment model with first-order absorption and first-order elimination. Weight and age were found to be significant covariates on CL/F. However, no dose adjustment was warranted for these covariatesbased on the predicted systemic VI exposures. More details on the model output (vipop39, dmp 10681) can be found in GlaxoSmithKline Document Number2012N137814_00.

The VI population PK model from the FF/VI program [GlaxoSmithKline Document Number 2011N122282_00; Siederer, 2016] was a three-compartment model wi

*complete removal of patient data listings may …...figure 2.5 final ff pharmacokinetic model...

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