Search

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.

In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effect) framework to characterize the disease progression in MS (as measured by EDSS). Data were collected from a 96-week Phase III clinical study, involving 104206 item-level observations from 1319 patients with relapsing-remitting MS, treated with placebo or cladribine. Observed scores for each EDSS item were modelled describing the probability of a given score as a function of patients’ (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time and the model was then extended to cladribine arms in order to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. IRT model was able to describe baseline and longitudinal EDSS data on item and total level. Final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of 8 items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modelling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in Phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner., CLINICAL PHARMACOKINETICS, Volume: 58, Issue: 3, Pages: 401-401, DOI: 10.1007/s40262-018-0706-x

The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.

In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effect) framework to characterize the disease progression in MS (as measured by EDSS). Data were collected from a 96-week Phase III clinical study, involving 104206 item-level observations from 1319 patients with relapsing-remitting MS, treated with placebo or cladribine. Observed scores for each EDSS item were modelled describing the probability of a given score as a function of patients’ (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time and the model was then extended to cladribine arms in order to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. IRT model was able to describe baseline and longitudinal EDSS data on item and total level. Final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of 8 items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modelling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in Phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner., CLINICAL PHARMACOKINETICS, Volume: 58, Issue: 3, Pages: 401-401, DOI: 10.1007/s40262-018-0706-x

In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effect) framework to characterize the disease progression in MS (as measured by EDSS). Data were collected from a 96-week Phase III clinical study, involving 104206 item-level observations from 1319 patients with relapsing-remitting MS, treated with placebo or cladribine. Observed scores for each EDSS item were modelled describing the probability of a given score as a function of patients’ (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time and the model was then extended to cladribine arms in order to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. IRT model was able to describe baseline and longitudinal EDSS data on item and total level. Final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of 8 items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modelling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in Phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner., CLINICAL PHARMACOKINETICS, Volume: 58, Issue: 3, Pages: 401-401, DOI: 10.1007/s40262-018-0706-x

The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.

The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.

In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effect) framework to characterize the disease progression in MS (as measured by EDSS). Data were collected from a 96-week Phase III clinical study, involving 104206 item-level observations from 1319 patients with relapsing-remitting MS, treated with placebo or cladribine. Observed scores for each EDSS item were modelled describing the probability of a given score as a function of patients’ (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time and the model was then extended to cladribine arms in order to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. IRT model was able to describe baseline and longitudinal EDSS data on item and total level. Final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of 8 items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modelling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in Phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner., CLINICAL PHARMACOKINETICS, Volume: 58, Issue: 3, Pages: 401-401, DOI: 10.1007/s40262-018-0706-x

The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.

In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effect) framework to characterize the disease progression in MS (as measured by EDSS). Data were collected from a 96-week Phase III clinical study, involving 104206 item-level observations from 1319 patients with relapsing-remitting MS, treated with placebo or cladribine. Observed scores for each EDSS item were modelled describing the probability of a given score as a function of patients’ (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time and the model was then extended to cladribine arms in order to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. IRT model was able to describe baseline and longitudinal EDSS data on item and total level. Final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of 8 items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modelling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in Phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner., CLINICAL PHARMACOKINETICS, Volume: 58, Issue: 3, Pages: 401-401, DOI: 10.1007/s40262-018-0706-x

The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.