Pharmacometric Analysis of the Relationship Between Absolute Lymphocyte Count and Expanded Disability Status Scale and Relapse Rate, Efficacy End Points, in Multiple Sclerosis Trials. (10th May 2018)

• Record Type: Journal Article
• Authors: Novakovic, A.M.; Thorsted, A.; Schindler, E.; Jönsson, S.; Munafo, A.; Karlsson, M.O.
• Is Part Of: Journal of clinical pharmacology. Volume 58:Number 10(2018)
• Page Start: 1284
• Page End: 1294
• Publication Date: 2018-05-10
• Subjects: EDSS -- lymphocytes -- multiple sclerosis -- pharmacometrics -- relapses; Pharmacology -- Periodicals; Pharmacology -- Periodicals; Pharmacology, Clinical -- Periodicals; 615.1
• DOI: 10.1002/jcph.1136
• Languages: English
• ISSNs: 0091-2700

Abstract

Abstract: The aim of this work was to assess the relationship between the absolute lymphocyte count (ALC), and disability (as measured by the Expanded Disability Status Scale [EDSS]) and occurrence of relapses, 2 efficacy endpoints, respectively, in patients with remitting‐relasping multiple sclerosis. Data for ALC, EDSS, and relapse rate were available from 1319 patients receiving placebo and/or cladribine tablets. Pharmacodynamic models were developed to characterize the time course of the endpoints. ALC‐related measures were then evaluated as predictors of the efficacy endpoints. EDSS data were best fitted by a model where the logit‐linear disease progression is affected by the dynamics of ALC change from baseline. Relapse rate data were best described by the Weibull hazard function, and the ALC change from baseline was also found to be a significant predictor of time to relapse. Presented models have shown that once cladribine exposure driven ALC‐derived measures are included in the model, the need for drug effect components is of less importance (EDSS) or disappears (relapse rate). This simplifies the models and theoretically makes them mechanism specific rather than drug specific. Having a reliable mechanism‐specific model would allow leveraging historical data across compounds, to support decision making in drug development and possibly shorten the time to market.