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Apr 25, 2020

Population Pharmacokinetic and Pharmacokinetic / Pharmacodynamic Modeling of Weight‐Based Intravenous Reslizumab Dosing

Abstract

Reslizumab 3.0 mg/kg has demonstrated efficacy in clinical studies of patients with eosinophilic asthma and a history of exacerbations. A population pharmacokinetic (PK) model was developed to determine whether 3.0 mg/kg weight‐based dosing is appropriate to obtain consistent reslizumab exposures in all patients. PK data in healthy volunteers and patients ≥12 years with moderate to severe asthma, eosinophilic asthma, or nasal polyposis were analyzed from 4 phase 1, 2 phase 2, and 2 phase 3 studies of intravenous (IV) reslizumab (N = 804). Covariates evaluated included age, race, sex, baseline weight, renal and liver function, concomitant medications, and antidrug antibody status. Exposure‐response models were developed to characterize key efficacy (blood eosinophil levels, forced expiratory volume in 1 second [FEV1], Asthma Control Questionnaire [ACQ‐7] scores), and safety end points (muscle disorder adverse events [AEs]). Vial‐based dosing was evaluated as an alternative to weight‐based dosing. IV reslizumab PK was accurately described by a 2‐compartment PK model with 0‐order input and first‐order elimination. Body weight was the only covariate that significantly influenced PK parameters. However, with weight‐based dosing, comparable steady‐state exposures were observed across high and low body weights. Greater eosinophil lowering and longer response duration were observed with increasing dose; exposure‐related effects on FEV1 and ACQ‐7 were also seen, demonstrating the clinical importance of a dosing regimen to optimize reslizumab exposure. The probability of a muscle disorder AE appeared to increase with increasing exposure. Steady‐state exposure measures were similar for both dosing regimens, showing vial‐based dosing as an alternative method of achieving the benefits of weight‐based dosing.

By Julie Passarell, David Jaworowicz, Elizabeth Ludwig, Laura Rabinovich‐Guilatt, Donna S. Cox, Micha Levi, Margaret Garin, Jill Fiedler‐Kelly, Mary Bond

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