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Fast tablet tensile strength prediction based on non-invasive analytics.

ABSTRACT: In this paper, linkages between tablet surface roughness, tablet compression forces, material properties, and the tensile strength of tablets were studied. Pure sodium halides (NaF, NaBr, NaCl, and NaI) were chosen as model substances because of their simple and similar structure. Based on the data available in the literature and our own measurements, various models were made to predict the tensile strength of the tablets. It appeared that only three parameters-surface roughness, upper punch force, and the true density of material-were needed to predict the tensile strength of a tablet. Rather surprising was that the surface roughness alone was capable in the prediction. The used new 3D imaging method (Flash sizer) was roughly a thousand times quicker in determining tablet surface roughness than traditionally used laser profilometer. Both methods gave practically analogous results. It is finally suggested that the rapid 3D imaging can be a potential in-line PAT tool to predict mechanical properties of tablets in production.

SUBMITTER: Halenius A

PROVIDER: S-EPMC4037483 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Fast tablet tensile strength prediction based on non-invasive analytics.

Halenius Anna A Lakio Satu S Antikainen Osmo O Hatara Juha J Yliruusi Jouko J

AAPS PharmSciTech 20140318 3

In this paper, linkages between tablet surface roughness, tablet compression forces, material properties, and the tensile strength of tablets were studied. Pure sodium halides (NaF, NaBr, NaCl, and NaI) were chosen as model substances because of their simple and similar structure. Based on the data available in the literature and our own measurements, various models were made to predict the tensile strength of the tablets. It appeared that only three parameters-surface roughness, upper punch for ...[more]

PMID: 24638870

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Fast tablet tensile strength prediction based on non-invasive analytics.

Publications

Fast tablet tensile strength prediction based on non-invasive analytics.

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