Multivariate approaches for the development of quality control in-situ fiber optics dissolution methods for fixed-dose combination tablets.

The purpose of this research was to develop a fiber optic (FO) dissolution method for quantification of multiple actives in combination pharmaceutical tablets. FO dissolution allows direct API quantification in the vessel, obviating the need for error-prone facets of traditional dissolution methods. However, FO dissolution is potentially challenged by overlapping UV spectra, matrix effects, UV-active excipients, API interactions with excipients and media, and undissolved components attenuating the UV signal. These obstacles might render FO dissolution method development more complex than LC-end dissolution. The case study in this manuscript has the added complexity of a triple combination product (Midol), where acetaminophen, caffeine, and pyrilamine maleate exhibit similar release kinetics, share largely overlapping UV spectra and span an order of magnitude difference in concentration. Single-wavelength quantification required unique features for the actives of interest, which were not available for the formulation of interest without preprocessing. The methods employed for the quantification of actives were a partial least squares multivariate calibration and a peak area calibration, both using prepared mixtures as reference data. The selected combination tablet demonstrated collinear API release; therefore, individual quantification required a design of experiments for mixture design. The advantages of FO dissolution will be discussed in the context of the formulation under investigation. Additionally, some general guidelines will be suggested for the development of other FO methods.

Development and beyond: Strategy for long-term maintenance of an online laser diffraction particle size method in a spray drying manufacturing process.

The purpose of this manuscript is to present the intended use and long-term maintenance strategy of an online laser diffraction particle size method used for process control in a spray drying process. A Malvern Insitec was used for online particle size measurements and a Malvern Mastersizer was used for offline particle size measurements. The two methods were developed in parallel with the Mastersizer serving as the reference method. Despite extensive method development across a range of particle sizes, the two instruments demonstrated different sensitivities to material and process changes over the product lifecycle. This paper will describe the procedure used to ensure consistent alignment of the two methods, thus allowing for continued use of online real-time laser diffraction as a surrogate for the offline system over the product lifecycle.

A uHPLC-MS mathematical modeling approach to dry powder inhaler single agglomerate analysis.

Demonstration of content uniformity (CU) is critical toward the successful development of dry powder inhalers (DPIs). Methods for unit dose CU determination for DPI products are well-established within the field of respiratory science. Recent advances in the area include a uHPLC-MS method for high-throughput uniformity analysis, which allows for a greater understanding of blending operations as the industry transitions to a quality-by-design approach to development. Further enhancements to this uHPLC-MS method now enable it to determine CU and sample weight at the single agglomerate level, which is roughly 50× smaller than a unit dose. When coupled with optical microscopy-based agglomerate sizing, the enhanced uHPLC-MS method can also predict the density and porosity of individual agglomerates. Expanding analytical capabilities to the single agglomerate level provides greater insights and confidence in the DPI manufacturing process.

Raman spectroscopy for the process analysis of the manufacturing of a suspension metered dose inhaler.

The purpose of this research was to demonstrate the utility of Raman spectroscopy for process analysis of a suspension metered dose inhaler manufacturing process. Chemometric models were constructed for the quantification of ethanol and active pharmaceutical ingredient such that both could be monitored in real-time during the compounding and filling operations via tank measurements and recirculation line flow-cell measurements. Different spectral preprocessing techniques were used to delineate the effects of mixing speed and temperature changes from actual concentration effects. Raman spectroscopy offers advantages in time savings and quality of information over the standard methods of analysis for respiratory formulations, such as a drug content assay via HPLC and ethanol testing via GC. The successful implementation of this work will allow formulation scientists to quantitatively assess both the formulation (e.g., the concentration of active pharmaceutical ingredient (API) and ethanol), as well as the manufacturing process (e.g., determination of mixing endpoints) in real-time.

Development of a high-throughput UHPLC-MS-based content uniformity method as a tool for assessing dry powder inhalers.

BACKGROUND: Dry powder inhaler (DPI) product manufacturing requires the assessment of uniformity at various stages of the manufacturing process. RESULTS: To efficiently and precisely determine the uniformity of the small doses inherent to DPI technology, an ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS)-based content uniformity method was developed. Using mathematical modeling and proper selection of bracketing standards, a volumetric approximation of sample weight was utilized, eliminating the need for accurate sample weights and reducing sample preparation time. CONCLUSION: UHPLC-MS coupled with mathematical modeling makes high-throughput CU testing of DPI drug products possible which allows for an enhanced understanding of the manufacturing process.

Near infrared spectrometry for the quantification of human dermal absorption of econazole nitrate and estradiol.

PURPOSE: The purpose of this study was to demonstrate the use of near-infrared (NIR) spectrometry for the in vitro quantification of econazole nitrate (EN) and estradiol (EST) in human skin. METHODS: NIR spectra were collected from EN and EST powders to verify the presence of NIR chromophores. One percent EN cream, a saturated solution of EN, or 0.25% EST solution was applied to human skin. NIR spectra were collected and one-point net analyte signal (NAS) multivariate calibration was used to predict the drug concentrations. NIR results were validated against known skin concentrations measured by high-pressure liquid chromatography (HPLC) analysis of solvent extracts. RESULTS: NIR spectroscopy measured dermal absorption from saturated solutions of EN on human skin with an r2=0.990, standard error of estimation (SEE)=2.46%, and a standard error of performance (SEP)=3.55%, EN cream on skin with an r2=0.987, SEE=2.30%, and SEP=2.66%, and 0.25% solutions of EST on skin with an r2=0.987, SEE=3.30%, and SEP=5.66%. Despite low permeation amounts of both drugs through the stratum corneum into human tissue, the NIR signal-to-noise ratio was greater than three, even for the lowest concentrations. CONCLUSION: NIR analyses paralleled the results obtained from HPLC, and thus could serve as a viable alternative for measuring the topical bioavailability/bioequivalence of different EN and EST formulations. Because these experiments were conducted in human tissue, this research suggests an all-optical in vivo method of measurement for dermal absorption could be developed.

Acoustic-resonance spectrometry as a process analytical technology for the quantification of active pharmaceutical ingredient in semi-solids.

The purpose of this study was to demonstrate acoustic resonance spectrometry (ARS) as an alternative process analytical technology to near infrared (NIR) spectroscopy for the quantification of active pharmaceutical ingredient (API) in semi-solids such as creams, gels, ointments, and lotions. The ARS used for this research was an inexpensive instrument constructed from readily available parts. Acoustic-resonance spectra were collected with a frequency spectrum from 0 to 22.05 KHz. NIR data were collected from 1100 to 2500 nm. Using 1-point net analyte signal (NAS) calibration, NIR for the API (colloidal oatmeal [CO]) gave an r2 prediction accuracy of 0.971, and a standard error of performance (SEP) of 0.517%CO. ARS for the API resulted in an r2 of 0.983 and SEP of 0.317%CO. NAS calibration is compared with principal component regression. This research demonstrates that ARS can sometimes outperform NIR spectrometry and can be an effective analytical method for the quantification of API in semi-solids. ARS requires no sample preparation, provides larger penetration depths into lotions than optical techniques, and measures API concentrations faster and more accurately. These results suggest that ARS is a useful process analytical technology (PAT).

Acoustic-resonance spectrometry as a process analytical technology for rapid and accurate tablet identification.

This research was performed to test the hypothesis that acoustic-resonance spectrometry (ARS) is able to rapidly and accurately differentiate tablets of similar size and shape. The US Food and Drug Administration frequently orders recalls of tablets because of labeling problems (eg, the wrong tablet appears in a bottle). A high-throughput, nondestructive method of online analysis and label comparison before shipping could obviate the need for recall or disposal of a batch of mislabeled drugs, thus saving a company considerable expense and preventing a major safety risk. ARS is accurate and precise as well as inexpensive and nondestructive, and the sensor is constructed from readily available parts, suggesting utility as a process analytical technology (PAT). To test the classification ability of ARS, 5 common household tablets of similar size and shape were chosen for analysis (aspirin, ibuprofen, acetaminophen, vitamin C, and vitamin B12). The measures of successful tablet identification were intertablet distances in nonparametric multidimensional standard deviations (MSDs) greater than 3 and intratablet MSDs less than 3, as calculated from an extended bootstrap error-adjusted single sample technique. The average intertablet MSD was 65.64, while the average intratablet MSD from cross-validation was 1.91. Tablet mass (r (2) = 0.977), thickness (r (2) = 0.977), and density (r (2) = 0.900) were measured very accurately from the AR spectra, each with less than 10% error. Tablets were identified correctly with only 250 ms data collection time. These results demonstrate that ARS effectively identified and characterized the 5 types of tablets and could potentially serve as a rapid high-throughput online pharmaceutical sensor.

Near-infrared spectrometry for the quantification of dermal absorption of econazole nitrate and 4-cyanophenol.

PURPOSE: The purpose of this study was to demonstrate the utility of near-infrared (NIR) spectroscopy for the in vitro quantification of econazole nitrate (EN) and 4-cyanophenol (4-CP) in hairless guinea pig skin. METHODS: NIR spectra were collected from each of the following: EN and 4-CP powders, EN and 4-CP in solution, and skin samples following topical exposure to either 4-CP in water or EN in propylene glycol and topical creams. To predict drug concentration from NIR spectra, principal component regression (PCR), interval PCR, and uninformative variable elimination PCR were each used with a leave-one-out cross-validation, and results were compared. NIR results were validated against known skin concentrations measured by high-pressure liquid chromatography (HPLC) analysis of solvent extracts. RESULTS: NIR results matched the HPLC results for the quantification of 4-CP and EN in skin exposed to saturated solutions and topical creams with an r2 > 0.90, a standard error of estimation < 7.0%, and a standard error of performance < 8.0%. CONCLUSION: This experiment demonstrated that NIR closely parallels results obtained from tissue extraction and HPLC analysis, proving its potential utility for the rapid and noninvasive determination of topical bioavailability/bioequivalence of EN and quantification of the model chemical 4-CP. Investigation of drugs in human skin is now justified.

Acoustic-resonance spectrometry as a process analytical technology for the quantification of active pharmaceutical ingredient in semi-solids.

The purpose of this study was to demonstrate acoustic resonance spectrometry (ARS) as an alternative process analytical technology to near infrared (NIR) spectroscopy for the quantification of active pharmaceutical ingradient (API) in semi-solids such as creams, gels, ointments, and lotions. The ARS used for this research was an inexpensive instrument constructed from readily available parts. Acoustic-resonance spectra were collected with a frequency spectrum from 0 to 22.05 KHz. NIR data were collected from 1100 to 2500 nm. Using 1-point net analyte signal (NAS) calibration, NIR for the API (colloidal oatmeal [CO]) gave anr 2 prediction accuracy of 0.971, and a standard error of performance (SEP) of 0.517%CO. ARS for the API resulted in anr 2 of 0.983 and SEP of 0.317%CO. NAS calibration is compared with principal component regression. This research demonstrates that ARS can sometimes outperform NIR spectrometry and can be an effective analytical method for the quantification of API in semi-solids. ARS requires no sample preparation, provides larger penetration depths into lotions than optical techniques, and measures API concentrations faster and more accurately. These results suggest that ARS is a useful process analytical technology (PAT).

Acoustic-resonance spectrometry as a process analytical technology for rapid and accurate tablet identification.

This research was performed to test the hypothesis that acoustic-resonance spectrometry (ARS) is able to rapidly and accurately differentiate tablets of similar size and shape. The US Food and Drug Administration frequently orders recalls of tablets because of labeling problems (eg, the wrong tablet appears in a bottle). A high-throughput, nondestructive method of online analysis and label comparison before shipping could obviate the need for recall or disposal of a batch of mislabeled drugs, thus saving a company considerable expense and preventing a major safety risk. ARS is accurate and precise as well as inexpensive and nondestructive, and the sensor, is constructed from readily available parts, suggesting utility as a process analytical technology (PAT). To test the classification ability of ARS, 5 common household tablets of similar size and shape were chosen for analysis (aspirin, ibuprofen, acetaminophen, vitamin C, and vitamin B12). The measures of successful tablet identification were intertablet distances in nonparametric multidimensional standard deviations (MSDs) greater than, 3 and intratablet MSDs less than 3, as calculated from an extended bootstrap erroradjusted single sample technique. The average intertablet MSD was 65.64, while the average intratablet MSD from cross-validation was 1.91. Tablet mass (r2=0.977), thickness (r2=0.977), and density (r2=0.900) were measured very accurately from the AR spectra, each with less than 10% error. Tablets were identified correctly with only 250 ms data collection time. These results demonstrate that ARS effectively identified and characterized the 5 types of tablets and could potentially serve as a rapid high-throughput online pharmaceutical sensor.