My Profile

Search abstracts

Lewis Sheiner


2019
Stockholm, Sweden



2018
Montreux, Switzerland

2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
Alicante, Spain

2013
Glasgow, Scotland

2012
Venice, Italy

2011
Athens, Greece

2010
Berlin, Germany

2009
St. Petersburg, Russia

2008
Marseille, France

2007
KÝbenhavn, Denmark

2006
Brugge/Bruges, Belgium

2005
Pamplona, Spain

2004
Uppsala, Sweden

2003
Verona, Italy

2002
Paris, France

2001
Basel, Switzerland

2000
Salamanca, Spain

1999
Saintes, France

1998
Wuppertal, Germany

1997
Glasgow, Scotland

1996
Sandwich, UK

1995
Frankfurt, Germany

1994
Greenford, UK

1993
Paris, France

1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 28 (2019) Abstr 9184 [www.page-meeting.org/?abstract=9184]


PDF poster/presentation:
Click to open Click to open

Oral: Drug/Disease modelling


B-18 Pascal Chanu A disease progression model for geographic atrophy

Chanu P1, Marchand M2, Vadhavkar S3, Maass K3, Gow J3, Deng R3, Jin J3, Quartino A3

1 Clinical Pharmacology, Genentech/Roche, France; 2 Certara Strategic Consulting, France; 3 Clinical Pharmacology, Genentech Inc

Objectives:

Geographic atrophy (GA) is a non-exudative form of age-related macular degeneration (AMD), also called dry AMD. Lampalizumab, an antigen-binding fragment of a humanized monoclonal antibody directed against complement Factor D, was developed to prevent activation of the alternative complement pathway and thus impede the progression of GA and vision loss. Positive results were observed with lampalizumab 10 mg administered intravitreally every month in the Mahalo study (CFD4870g) which met its primary endpoint: the mean difference in GA growth between the monthly group compared to the sham group at Month 18 was 0.595 mm2 (80% CI: 0.109, 1.081). In addition, a statistically significant relationship was found between cumulative AUC in both serum and aqueous humor and change from baseline in GA area in patients positive to complement factor I biomarker. Two Phase 3 studies of more than 900 patients each: Chroma (GX29176) and Spectri (GX29185) were run to assess the efficacy and safety of lampalizumab versus sham. Both Phase 3 studies failed to demonstrate the efficacy of lampalizumab 10 mg given monthly, the highest drug exposure tested.[1] The objective of this work was to develop and validate a disease progression model for GA using Chroma and Spectri data and propose a model-based approach to assess treatment effect in GA to aid drug candidate selection at an early stage of clinical drug development.

Methods:

Both Spectri and Chroma data were used as well as data from Omaspect (GX30191), the long-term safety extension study which patients who completed parents studies i.e. Spectri or Chroma could enrol to. GA area was assessed by at 24, 36, 48, 72 and 96 weeks in Spectri and Chroma and every 24 weeks in Omaspect up to 96 weeks. As lampalizumab development was interrupted prematurely, the longest GA area follow-up reached 3.3 years. Spectri data was used to develop the disease progression model, comprising 970 patients (including patients receiving lampalizumab), among those 411 were enrolled into Omaspect, 6755 GA areas were used. The model structure was similar to the one published by Delor et al. based on the disease onset time concept.[2] The individual GA areas at the start of Spectri ranged from 2.54 to 30.56 mm2; indeed, patients were not at the same disease stage at the time of enrolment in the study. Therefore, there was a need to accurately reconstruct the full disease progression trajectory. The disease onset time approach leverages data from each subject itself informing a portion of the trajectory. The rate of increase in GA area was modelled as the sum of a linear increase with time and a first order term adjusting for individual contribution to disease progression. A first model qualification was performed on Spectri (including Omaspect portion) data using visual and posterior predictive checks. Then, Chroma (including Omaspect portion) data was used for external validation of the model.

Results:

The disease progression model structure using the disease onset time concept enabled the reconstruction of the disease trajectory over more than 12 years. While disease progression appeared to be linear with time over the clinical trial duration of 2 years, GA seemed to progress in a non-linear way (faster than linearity with time) over 12 years. The disease progression model showed that on average patients started their disease 5.2 years before Spectri enrolment but with large inter-patient variability (1.3 to 18.5 years prior to enrolment). The GA area at study entry was a structural covariate in the model. Disease progression was faster for patients with GA area at study entry >6 mm2, in patients with multifocal lesions (+16% versus unifocal) and in patients with non-subfoveal lesions (+15% versus subfoveal). The model was qualified based on Spectri data and a successful external validation was performed versus Chroma data on 901 patients.

Conclusions:

A disease progression model for GA was developed and externally validated. It can be used to assess treatment effect for future drug candidate in GA. Indeed a model-based approach comparing the model-predicted GA area (only due to disease progression) to the corresponding observations (due to disease progression and potential treatment effect) can represent a complementary analysis to classical statistical analyses based on change from baseline and improve future drug development decisions.



References:
[1] Holz FG et al. Efficacy and Safety of Lampalizumab for Geographic Atrophy Due to Age-Related Macular Degeneration: Chroma and Spectri Phase 3 Randomized Clinical Trials. JAMA Ophthalmol.2018;136:666-677.
[2]Delor I, Charoin JE, Gieschke R, Retout S, Jacqmin P. Modeling Alzheimer’s disease progression using disease onset time and disease trajectory concepts applied to CDR-SOB scores from ADNI. CPT Pharmacometrics Syst Pharmacol. 2013;2, e78; doi:10.1038/psp.2013.54.