Acoustic assessment of mean grain size in pharmaceutical compacts

Smith, Carlowen Andrew; Stephens, James D.; Hancock, Bruno C.; Vahdat, Armin Saeedi; Cetinkaya, Çetin

doi:10.1016/j.ijpharm.2011.07.032

Cited by 19 publications

(8 citation statements)

References 31 publications

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“…Previously a set of a non-invasive/non-destructive, wave propagation-based techniques for the characterization of tablet properties have been introduced and reported (I. Ilgaz Akseli et al, 2009;Liu and Cetinkaya, 2010;Varghese and Cetinkaya, 2007;Smith et al, 2011;Vahdat et al, 2013). Current approach is based on the principle that the velocities of pressure (longitudinal) and shear (transverse) waves propagating in a medium depend on its elasticity (stiffness, hardness), and inertia (mass density and its spatial distribution) as well as its micro-granular structure.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to its mechanical and viscoelastic properties, the material texture of a tablet material (e.g., grain size and grain-to-grain stiffness coupling) determines the spectral dispersion of ultrasonic waves in the propagation medium material. By utilizing experimentally acquired spectral dispersion curves and fitting the parameters of a viscoelastic material model (including scattering effects), the physical-mechanical (such as mass density and distribution, material elasticity, and viscoelasticity) and micro-structural (such as internal grain size distribution and inter-granular bonding) properties could also be extracted (Smith et al, 2011;Vahdat et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Early detection of capping risk in pharmaceutical compacts

Vallabh

Hoag

et al. 2018

International Journal of Pharmaceutics

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Capping is a common mechanical defect in tablet manufacturing, exhibited during or after the compression process. Predicting tablet capping in terms of process variables (e.g. compaction pressure and speed) and formulation properties is essential in pharmaceutical industry. In current work, a nondestructive contact ultrasonic approach for detecting capping risk in the pharmaceutical compacts prepared under various compression forces and speeds is presented. It is shown that the extracted mechanical properties can be used as early indicators for invisible capping (prior to visible damage). Based on the analysis of X-ray cross-section images and a large set of waveform data, it is demonstrated that the mechanical properties and acoustic wave propagation characteristics is significantly modulated by the tablet's internal cracks and capping at higher compaction speeds and pressures. In addition, the experimentally extracted properties were correlated to the directly-measured porosity and tensile strength of compacts of Pearlitol®, Anhydrous Mannitol and LubriTose® Mannitol, produced at two compaction speeds and at three pressure levels. The effect compaction speed and pressure on the porosity and tensile strength of the resulting compacts is quantified, and related to the compact acoustic characteristics and mechanical properties. The detailed experimental approach and reported wave propagation data could find key applications in determining the bounds of manufacturing design spaces in the development phase, predicting capping during (continuous) tablet manufacturing, as well as online monitoring of tablet mechanical integrity and reducing batch-to-batch end-product quality variations. Disciplines Disciplines Pharmacy and Pharmaceutical Sciences Comments Comments

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Early detection of capping risk in pharmaceutical compacts

Vallabh

Hoag

et al. 2018

International Journal of Pharmaceutics

Self Cite

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show abstract

“…Our laboratory has previously introduced and reported a set of a non-invasive, acoustics-based techniques for the characterization of tablet properties (I. Ilgaz Akseli et al, 2009;Liu and Cetinkaya, 2010;Varghese and Cetinkaya, 2007;Smith et al, 2011;Vahdat et al, 2013)). The approach is based on the principle that the speeds of pressure and shear waves propagating in a medium depend on its elasticity (stiffness), and inertia (mass density) as well as its micro-granular structure.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, material texture (e.g., grain size and grain-to-grain mechanical coupling) and viscoelasticity affects the spectral dispersion of a composite compact material. Relating an experimentally acquired spectral dispersion relation to a visco-elastic material model with scattering effects, the mechanical (e.g., elasticity, mass density, and viscoelasticity) and geometric (e.g., grain size distribution and inter-granular elastic stiffness) properties (Smith et al, 2011;Vahdat et al, 2013) can be extracted.…”

Section: Introductionmentioning

confidence: 99%

“…The dwell time of a typical commercial compaction press is on a millisecond scale ranging from ~5ms to over 80 ms while the acoustic pulse method of acquiring the Time-of-Flight (ToF) is on the microsecond (μs) scale Leskinen et al, 2010) thus allowing many acquisitions during a single compaction event (real-time in-die monitoring). It has been previously established that, by utilizing a non-destructive off-line acoustic pulse-echo method Liu et al, 2011;Liu and Cetinkaya, 2010;Smith et al, 2011), the mechanical properties of tablets with complex geometries such as dry-coated and layered tablets can be characterized. It was also shown that not only can in-die measurements be made, but they can be done wirelessly and also in-line (out-of-die post compaction), resulting in comparative differentiation in solid dosage mechanical properties Stephens et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Correlation of solid dosage porosity and tensile strength with acoustically extracted mechanical properties

Mack

Cleland³

et al. 2018

International Journal of Pharmaceutics

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Currently, the compressed tablet and its oral administration is the most popular drug delivery modality in medicine. The accurate porosity and tensile strength characterization of a tablet design is vital for predicting its performance such as disintegration, dissolution, and drug-release efficiency upon administration as well as ensuring its mechanical integrity. In current work, a non-destructive contact ultrasonic approach and an associated testing procedure are presented and employed to quantify and relate the acoustically extracted mechanical properties of pharmaceutical compacts to direct porosity and tensile strength measurements. Based on a comprehensive set of experimental data, it is demonstrated how strongly the acoustic wave propagation is modulated and correlated to the tablet porosity and tensile strength of a compact made using spray-dried lactose and microcrystalline cellulose with varying mixture ratios. The effect of mixing ratio on the porosity and tensile strength on the resulting compacts is quantified and, with the acoustic experimental data, mixing ratio is related to the compact ultrasonic characteristics. The ultrasonic techniques provide a rapid, non-destructive means for evaluating compacts in formulation development and manufacturing. The presented approach and data could find critical applications in continuous tablet manufacturing, its real-time quality monitoring, as well as minimizing batch-to-batch quality variations.

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Prediction of grain size distribution in microstructure of polycrystalline materials using one dimensional convolutional neural network (1D-CNN)

Padhan

Rai

2023

Computational Materials Science

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Acoustic assessment of mean grain size in pharmaceutical compacts

Cited by 19 publications

References 31 publications

Early detection of capping risk in pharmaceutical compacts

Early detection of capping risk in pharmaceutical compacts

Correlation of solid dosage porosity and tensile strength with acoustically extracted mechanical properties

Prediction of grain size distribution in microstructure of polycrystalline materials using one dimensional convolutional neural network (1D-CNN)

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