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Different Doses of BI 1467335 Compared to Placebo in Patients With Clinical Evidence of NASH

Phase 2
Completed
Conditions
Non-alcoholic Fatty Liver Disease
Interventions
Drug: BI 1467335
Drug: Placebo
Registration Number
NCT03166735
Lead Sponsor
Boehringer Ingelheim
Brief Summary

The primary objective of this study is the proof of mechanism and support of dose finding, together with the safety evaluation in patients with clinical evidence of NASH.

To gain further insight into clinical effects of AOC3 inhibition on NASH further exploratory analyses of biomarkers related to NASH and liver fibrosis will be performed. This will include the effect of BI 1467335 on reduction of secondary biomarker endpoints (ALT, AST, AP, γ-GT and CK18 fragments). Safety will be assessed throughout the study to provide key information regarding the use of BI 1467335 in patients with NASH.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
114
Inclusion Criteria

Not provided

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Exclusion Criteria

Not provided

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Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
BI 1467335 dose 1BI 1467335-
BI 1467335 dose 2BI 1467335-
BI 1467335 dose 3BI 1467335-
BI 1467335 dose 4BI 1467335-
PlaceboPlacebo-
Primary Outcome Measures
NameTimeMethod
Plasma Amine Oxidase Copper-containing 3 (AOC3) Activity After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

The patient-specific plasma AOC3 activity at time t (24 hours after the last dose in week 12) relative to baseline in percentage was calculated as follows:

%AOC3at = \[(AOC3at - AOC3at,back) ⁄ (AOC3abase - AOC3abase,back)\]\*100

With AOC3at the AOC3 activity measured at time t, AOC3at,back the background noise at time t, AOC3abase the AOC3 activity measured at baseline and AOC3abase,back the background noise at baseline.

A dose-response relationship was analysed using a non-linear regression model to estimate the daily dosage needed to reach 10% of AOC3 activity (i.e. 90% inhibition) 12 weeks after treatment.

Secondary Outcome Measures
NameTimeMethod
Percentage of Participants With Drug-related Adverse Events (AEs)Start of treatment till end of treatment + 28 days, up to 113 days.

Percentage of participants with drug-related adverse events (AEs). Percentages are calculated using total number of patients per treatment as the denominator.

Alanine Aminotransaminase (ALT) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Alanine aminotransaminase (ALT) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%

Statistical analyses description: A Mixed effects Model for Repeated Measurements (MMRM) over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Aspartate Aminotransferase (AST) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Aspartate aminotransferase (AST) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%

Statistical analyses description: A Mixed effects Model for Repeated Measurements (MMRM) over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Alkaline Phosphatase (AP) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Alkaline phosphatase (AP) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%

Statistical analyses description: A Mixed effects Model for Repeated Measurements (MMRM) over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Gamma-glutamyltransferase (GGT) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Gamma-glutamyltransferase (GGT) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%

Statistical analyses description: A Mixed effects Model for Repeated Measurements (MMRM) over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Caspase-cleaved Cytokeratin 18 (CK-18 Caspase) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Caspase-cleaved cytokeratin 18 (CK-18 caspase) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%

Statistical analyses description: A MMRM over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Total Cytokeratin 18 (CK-18 Total) After 12 Weeks of Treatment, Relative to Baseline in PercentDay 1 (baseline), day 15, 29, 43, 57 and 85 (time t) 24 hours after the last dose of BI 1467335.

Total cytokeratin 18 (CK-18 total) after 12 weeks of treatment, relative to baseline in percent. Number analyzed lower than N in PPS if there is missing data for specific timepoints.

The unit of measure is: percentage relative to baseline = \[post baseline (time t)/baseline\]\*100%.

Statistical analyses description: A Mixed effects Model for Repeated Measurements (MMRM) over time including fixed effects for 'base', 'treatment', 'time', 'base\*time' interaction, and 'treatment\*time' interaction was performed. The MMRM estimates for the treatment effects at Week 12 and the corresponding covariance matrix were used to analyse the dose-response relationship using the Multiple contrast test (MCPMod). A test for non-flat dose-response relationship was first performed. If this relationship could be shown, the best fitting model out of a set of candidate models (Sigmoidal Emax, Logistic, Quadratic, Linear, Exponential, Linear logistic, Emax and Betamod) was to be selected and fitted.

Trial Locations

Locations (43)

Toronto Liver Centre

🇨🇦

Toronto, Ontario, Canada

Radboud Universitair Medisch Centrum

🇳🇱

Nijmegen, Netherlands

National Research Institute

🇺🇸

Los Angeles, California, United States

The University of North Carolina at Chapel Hill

🇺🇸

Chapel Hill, North Carolina, United States

American Research Corporation at the Texas Liver Institute

🇺🇸

San Antonio, Texas, United States

Amsterdam UMC, Locatie AMC

🇳🇱

Amsterdam, Netherlands

Maastricht Universitair Medisch Centrum

🇳🇱

Maastricht, Netherlands

AZ Maria Middelares

🇧🇪

Gent, Belgium

Universitätsklinikum Leipzig

🇩🇪

Leipzig, Germany

Manchester Royal Infirmary

🇬🇧

Manchester, United Kingdom

Aintree University Hospital

🇬🇧

Liverpool, United Kingdom

eStudySite

🇺🇸

La Mesa, California, United States

Southern California Research Center

🇺🇸

Coronado, California, United States

University of California San Diego

🇺🇸

La Jolla, California, United States

Florida Research Institute

🇺🇸

Lakewood Ranch, Florida, United States

Quest Clinical Research

🇺🇸

San Francisco, California, United States

Genoma Research Group, Inc

🇺🇸

Miami, Florida, United States

Edegem - UNIV UZ Antwerpen

🇧🇪

Edegem, Belgium

Pinnacle Clinical Research

🇺🇸

Live Oak, Texas, United States

Duke University Medical Center

🇺🇸

Durham, North Carolina, United States

Dallas Diabetes and Endocrine Center

🇺🇸

Dallas, Texas, United States

Diabetes and Endocrinology Consultants, PC

🇺🇸

Morehead City, North Carolina, United States

Virginia Commonwealth University

🇺🇸

Richmond, Virginia, United States

HOP La Pitié Salpêtrière

🇫🇷

Paris, France

Universitätsklinikum Aachen, AöR

🇩🇪

Aachen, Germany

Universitätsmedizin der Johannes Gutenberg-Universität Mainz

🇩🇪

Mainz, Germany

Universitätsklinikum Frankfurt

🇩🇪

Frankfurt am Main, Germany

Universitätsklinikum Köln (AöR)

🇩🇪

Köln, Germany

St James's Hospital

🇮🇪

Dublin, Ireland

Universitätsklinikum Würzburg

🇩🇪

Würzburg, Germany

Hospital Virgen de la Victoria

🇪🇸

Malaga, Spain

Hospital Universitario Marqués de Valdecilla

🇪🇸

Santander, Spain

Hospital Vall d'Hebron

🇪🇸

Barcelona, Spain

Queen Elizabeth Hospital

🇬🇧

Birmingham, United Kingdom

Hospital Virgen del Rocío

🇪🇸

Sevilla, Spain

Hospital General Universitario de Valencia

🇪🇸

Valencia, Spain

Royal Stoke University Hospital

🇬🇧

Stoke on Trent, United Kingdom

Rutgers Robert Wood Johnson Medical School

🇺🇸

New Brunswick, New Jersey, United States

HOP Claude Huriez

🇫🇷

Lille, France

Northwell Health

🇺🇸

Manhasset, New York, United States

University of Calgary

🇨🇦

Calgary, Alberta, Canada

UZ Leuven

🇧🇪

Leuven, Belgium

Centre Hospitalier Universitaire de Liège

🇧🇪

Liège, Belgium

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