Population Pharmacodynamics of Cladribine Tablets Therapy in Patients with Multiple Sclerosis: Relationship between Magnetic Resonance Imaging and Clinical Outcomes
R. Savic (1), A. Munafo (2), M.O. Karlsson (1)
(1) Dept of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden (2) Modelling and Simulation, Merck Serono S.A. – Geneva, Geneva, Switzerland
Objectives: We previously developed NLME models to characterize the effect of cladribine tablets on clinical outcomes in patients with relapsing-remitting multiple sclerosis.[1-3] These models allow predictions of relapse rate dynamics and disability progression based on an individual's disease activity, baseline characteristics, renal clearance and cladribine dose. Here, we integrate key MRI readouts into models relating cladribine exposure to clinical efficacy, and delineate the poorly-understood relationship between MRI and clinical markers of MS progression.
Methods: Our database included 2-year data from 1319 patients from the CLARITY study, with an additional 287 patients from the placebo arms of two sc interferon beta-1a studies for the Expanded Disability Status Scale (EDSS) model. To examine the relationship between MRI readouts and clinical endpoints, we tested the effect of MRI burden of disease (BOD) on EDSS score and MRI combined unique (CU) lesion count on relapse rate (RR). First, the MRI data were modelled using a count data approach, with MRI time profiles explained by indirect response model and inhibition of kin with cladribine in an exposure-dependent fashion. Then, MRI models were linked with the exposure-clinical endpoints models, where both simultaneous and sequential approaches were tested. Technical challenges included simultaneous modelling of repeated time-to-event and count data (CU-RR model), as well as handling categorical variable (EDSS) using approaches for continuous bound data.
Results: Predictions from a BOD model were linked to EDSS score. The final model consisted of positive relationships with log-transformed BOD and EDSS score at baseline. CU lesions and RR data were fitted simultaneously. In the final model, RR hazard was linearly related to the model-predicted CU lesion count. In both models, the coefficient of the linear relationship was well estimated from the data. The integrated models resulted in a significant model fit improvement and also showed that part of the variability in response was explained by integrated MRI readouts.
Conclusions: Despite major technical challenges and poor mechanistic understanding about MRI-clinical marker relationships, links between MRI lesion dynamics and clinical endpoints were established. The proposed exposure-biomarker-clinical endpoints models integrate a significant amount of knowledge and data, representing a useful platform for quantitative understanding of the MS time course.
Disclosures/Acknowledgements: This study was funded by Merck Serono S.A. - Geneva, Switzerland, an affiliate of Merck KGaA, Darmstadt, Germany. R. Savic and MO. Karlsson are paid consultants for Merck Serono S.A.; A. Munafo are employees of Merck Serono S.A.
References:
[1] Giovannoni G, et al. A placebo-controlled trial of oral cladribine for relapsing multiple sclerosis. N Engl J Med 2010;362(5):416-26.
[2] Savic R, Munafo A, Karlsson M. The effect of cladribine tablets on disease progression in multiple sclerosis: a non-linear mixed effect analysis. Poster P477 presented at: 26th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), 13-16 October 2010, Gothenburg, Sweden
[3] Disease progression model for multiple sclerosis and effect of cladribine tablets therapy on clinical endpoints. Poster presented at the American Conference on Pharmacometrics (ACoP), 3-6 April 2011, San Diego, USA
