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Rapid, non-destructive inspection and classification of inhalation blisters using low-energy x-ray imaging

Rao, Raj, Ament, Brian, Richard, Parmee, J, Cameron and Martin, Mayo (2018) Rapid, non-destructive inspection and classification of inhalation blisters using low-energy x-ray imaging. Journal of pharmaceutical innovation. ISSN 1939-8042; 1872-5120


X-ray imaging has gained increased acceptance as a useful analytical technique for pharmaceutical capsules and tablets, typically with masses on the order of ~100 mg. Here, an x-ray imaging technique was investigated for dry powder inhaler (DPI) blisters having a relatively low powder fill mass of 2 mg. Filling bulk formulated powder into inhalation blisters involves compressing the powder, increasing it’s density by a factor of ~3. Sealed blisters are conditioned by ultrasonic vibration to break up the compacted powder within, so that it may be readily dispersed to a respirable aerosol when actuated with an inhaler device. Currently, the presence of any residual powder consolidation within the blister is assessed manually by cutting open blisters and visually examining the contents, a slow and destructive process, unsuitable for high throughput manufacturing. Low-energy x-ray imaging was investigated as a rapid, non-destructive inspection method for low fill-mass (2 mg) blisters having a tare weight of ~75 mg per dose. The measurement principle relies on denser, consolidated powder appearing as darker regions in the recorded image. Proof-of-concept experiments were performed using empty blister strips, and blister strips filled with 2 mg of placebo powder, half of which were subjected to ultrasonic conditioning. The tests demonstrated that digital processing of x-ray images combined with multivariate data analysis reliably distinguished between the three types of blisters tested, i.e. empty blisters, conditioned and un-conditioned blisters of 2 mg fill mass. Using independent training and validation sets of 948 images each, a classification accuracy ≥99.8% was demonstrated.

Item Type: Article
Keywords: x-ray, image analysis, multivariate data analysis, dry powder inhaler, blister
Date Deposited: 22 May 2018 00:45
Last Modified: 22 May 2018 00:45


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