Determination of the scale of segregation of low dose tablets using hyperspectral imaging

Ely, David R.; Carvajal, Micaela

doi:10.1016/j.ijpharm.2011.05.027

Cited by 12 publications

(7 citation statements)

References 7 publications

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“…As the size of the QDs increases, the renal clearance significantly drops. 20 The QDs used in this study had a diameter of 20 nm. This can explain the negligible renal accumulation of free QDs.…”

Section: 15mentioning

confidence: 99%

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Theranostic liposomes loaded with quantum dots and apomorphine for brain targeting and bioimaging

Wen¹,

Zhang²,

Al‐Suwayeh³

et al. 2012

IJN

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Quantum dots (QDs) and apomorphine were incorporated into liposomes to eliminate uptake by the liver and enhance brain targeting. We describe the preparation, physicochemical characterization, in vivo bioimaging, and brain endothelial cell uptake of the theranostic liposomes. QDs and the drug were mainly located in the bilayer membrane and inner core of the liposomes, respectively. Spherical vesicles with a mean diameter of ∼140 nm were formed. QDs were completely encapsulated by the vesicles. Nearly 80% encapsulation percentage was achieved for apomorphine. A greater fluorescence intensity was observed in mouse brains treated with liposomes compared to free QDs. This result was further confirmed by ex vivo imaging of the organs. QD uptake by the heart and liver was reduced by liposomal incorporation. Apomorphine accumulation in the brain increased by 2.4-fold after this incorporation. According to a hyperspectral imaging analysis, multifunctional liposomes but not the aqueous solution carried QDs into the brain. Liposomes were observed to have been efficiently endocytosed into bEND3 cells. The mechanisms involved in the cellular uptake were clathrin-and caveolamediated endocytosis, which were energy-dependent. To the best of our knowledge, our group is the first to develop liposomes with a QD-drug hybrid for the aim of imaging and treating brain disorders.

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Section: 15mentioning

confidence: 99%

“…The technique is useful for quality control assessments of pharmaceutical products. 20,21 Hyperspectral images showed that the liposomes had permeated through the BBB as intact vesicles. The QDs were entrapped in the liposomes and did not show leakage after 1 hour of incubation in the brain.…”

Section: 15mentioning

confidence: 99%

Theranostic liposomes loaded with quantum dots and apomorphine for brain targeting and bioimaging

Wen¹,

Zhang²,

Al‐Suwayeh³

et al. 2012

IJN

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“…The characterisation of pharmaceutical solid dosage forms (SDFs) using near infrared spectroscopy coupled with chemical imaging (NIR-CI) is extended to a wide range of applications related to quality control of end-products, e.g. active pharmaceutical ingredients (APIs) and excipient blending, [1][2][3][4][5][6][7] polymorphism, 8,9 counterfeit identification 10,11 and coatings. 12 NIR-CI and other hyperspectral imaging techniques based on vibration spectroscopy, like mid-IR, Raman and terahertz, are relevant due to the fast and non-invasive extraction of chemical information about the distribution of constituents in solid samples.…”

Section: Introductionmentioning

confidence: 99%

Classical Least Squares Combined with Spectral Interval Selection Using Genetic Algorithm for Prediction of Constituents in Pharmaceutical Solid Dosage Forms from near Infrared Chemical Imaging Data

Alexandrino

Breitkreitz

Poppi

2016

Journal of Near Infrared Spectroscopy

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A new algorithm that combines spectral interval selection using genetic algorithm and classical least squares (GA-iCLS) is presented for the prediction of the active pharmaceutical ingredients and excipients in various pharmaceutical solid dosage forms from near infrared chemical imaging data. The algorithm is based on the CLS approach, selecting the best wavenumber intervals in the unfolded hypercube of each sample (D), and in pure-compound reference spectra (S), wherein the pixel-to-pixel prediction capability of the compounds, obtained by C = DS T (SS T) −1 , is optimised for the samples. The wavelength intervals were selected (GA optimisation) while minimising the error between the mean concentrations of the ith compound predicted in the pixels and the nominal concentration in the corresponding sample (known a priori). The excluded wavenumber intervals from D (and S), for each sample, were interpreted based on systematic deviations from D = CS T + E (CLS approach) due to the scattering effects and/or intermolecular interactions in mixtures of the pure compounds. The comparison of the chemical images generated from the predictions performed using the GA-iCLS algorithms with similar images obtained without spectral interval selection, using direct CLS and multivariate curve resolution-alternating least squares, revealed the potential applicability of the proposed algorithm for analytical purposes for pharmaceuticals using chemical imaging data.

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“…The high selectivity of vibrational spectroscopy for functional groups means that the concentration and distribution of ingredients can be examined. Thus, even though pharmaceutical formulations and their processes involve multiple component systems, API particle size and its distribution (uniformity) in the excipient matrix are specifically assessed using spectroscopy and chemical imaging (14,25,27,28). …”

Section: Introductionmentioning

confidence: 99%

Assessment of Active Pharmaceutical Ingredient Particle Size in Tablets by Raman Chemical Imaging Validated using Polystyrene Microsphere Size Standards

Kuriyama

Ozaki

2014

AAPS PharmSciTech

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Particle size is a critical parameter for controlling pharmaceutical quality. The aim of this study was to assess the size of the micrometer-scale active pharmaceutical ingredients (API) in tablets using Raman chemical imaging and to understand the effects of formulation on particle size. Model tablets containing National Institute of Standards and Technology traceable polystyrene microsphere size standards were developed to determine the binarization threshold value of Raman chemical images for API particle sizing in specific formulations and processes. Three sets of model tablets containing 5, 10, and 15 μm polystyrene microspheres, used to mimic API, were prepared using a commercial tablet formulation (Ebastel tablets, mean API particle size was about 5 μm). Raman mapping with a 50× objective (NA, 0.75) was applied to tablet cross-sections, and particle size of polystyrene microspheres was estimated from binary images using several binarization thresholds. Mean particle size for three sets of polystyrene microspheres showed good agreement between pre- and postformulation (the slope = 1.024, R = 1.000) at the specific threshold value ((mean + 0.5σ) of the polystyrene-specific peak intensity histogram), regardless of particle agglomeration, tablet surface roughness, and laser penetration depth. The binarization threshold value showed good applicability to Ebastel tablets, where the API-specific peak intensity histogram showed a pattern similar to that of polystyrene microspheres in model tablets. The model tablets enabled determination of an appropriate binarization threshold for assessing the mean particle size of micrometer-scale API in tablets by utilizing the unique physicochemical properties of polystyrene microspheres.

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Determination of the scale of segregation of low dose tablets using hyperspectral imaging

Cited by 12 publications

References 7 publications

Theranostic liposomes loaded with quantum dots and apomorphine for brain targeting and bioimaging

Theranostic liposomes loaded with quantum dots and apomorphine for brain targeting and bioimaging

Classical Least Squares Combined with Spectral Interval Selection Using Genetic Algorithm for Prediction of Constituents in Pharmaceutical Solid Dosage Forms from near Infrared Chemical Imaging Data

Assessment of Active Pharmaceutical Ingredient Particle Size in Tablets by Raman Chemical Imaging Validated using Polystyrene Microsphere Size Standards

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