Daniel I. Lewis, Josh Carter, Rob Johnson, & David A. Lewis
Oz-UK Ltd, Unit 15a, Lansdowne Court, Bumpers Way, Chippenham, Wiltshire, SN14 6RZ, UK.
Summary
Metered Dose Inhalers (MDIs) are commonly used for treating respiratory conditions, but suspension formulations are prone to sedimentation or creaming, requiring consistent shaking for uniform drug delivery [1]. Manual testing introduces variability and operator fatigue, impacting comprehensive through-can-use life characterization.
To overcome this, the novel automated in-vitro drug delivery characterization system, Rockstar (Lewis Jonsen Limited), was developed. Its novelty lies in providing precise digital control and visual feedback over the kinematic parameters applied to the MDI during shaking.
Rockstar enables precise control over critical MDI actuation parameters, including diverse shake methodologies (e.g., 90°, 180°, up/down) and the temporal profiles of rotational speed (i.e., acceleration and deceleration during the shake and return movement). The system provides real-time visualization of shake metrics, enabling researchers to adjust, simulate, and correlate manual operator shaking characteristics with the automated process. Furthermore, it provides exact control of shake number, shake-to-fire delay, and actuation duration. Importantly, it rigorously fires all doses (including waste shots) under consistent conditions to maintain representative in-canister drug homogeneity throughout the MDI’s use-life.
In this study, Rockstar systematically fired all 200 doses from three generic salbutamol sulphate MDIs (>600 total actuations, including priming doses), with drug delivery quantified for a subset of 10 doses per MDI at Beginning, Middle, and End of Life using a Dosage Unit Sampling Apparatus (DUSA) and validated HPLC assay.
Results demonstrated high consistency in delivered dose across individual MDIs and through their lifecycle; the overall delivered salbutamol dose observed was 99 ± 5 µg. This highly reproducible, USP-compliant data confirms Rockstar’s capability to provide reliable MDI performance measurements. Its automation advances high-throughput testing, significantly reduces human variability, and offers a critical tool for characterizing current and next-generation MDI products.