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.

Integrated sensing and processing (ISP) encompasses the use of optical computing and adapted excitation signals to physically implement chemometric calculations in spectroscopic sensors for imaging. As data sets become larger and more complex with each emerging generation of hyperspectral imagers, the 'pixel-to-pupil' ratio increases at a rate faster than computing power can accommodate. In response to the need for faster and more efficient methods of processing, many analog solutions to the problem of high data dimensionality have emerged. The successful development of ISP has strong implications for military imaging, biosensing, spectroscopic imaging, and pharmaceutical process analytical technology (PAT). ISP developments in spectroscopy and PAT have emerged as alternatives to conventional Fourier transform infrared (FT-IR), near-infrared (NIR), IR, UV-visible, fluorescence, Raman, and acoustic-resonance spectrometry (ARS). Flourishing applications of ISP have demonstrated predictive ability equivalent to conventional approaches for sample differentiation and analyte quantification, in only a fraction of the time required for traditional spectrometric measurements.

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).

This research introduces a novel process analytical technique, integrated sensing and processing acoustic resonance spectrometry (ISP-ARS), and compares ISP-ARS with conventional full-spectrum ARS for the characterization of solid fuel premixes used in a new pill safe designed to protect narcotics. In ISP-ARS, the acoustic excitation waveform is the analog implementation of the chemometric weight function, encoded for this work on an MP3 player and used to distinguish between fuel samples, sparing post-collection multivariate computation. In effect, the detector directly outputs the sample identity. Repeated measurements of batches of similar fuel mixtures over time produce an automatic projection of similar spectra into corresponding three-dimensional probability density contours, thus, forming the analyte classification directly. For the characterization of ten different fuel mixtures, full spectral ARS resulted in a median intermixture distance in multidimensional standard deviations (MSDs) of 185.1, while ISP-ARS resulted in a median MSD distance of 81.3. The median cross-validation MSD was 1.41 for the ARS and 1.58 for the ISP-ARS. Distances in MSDs greater than three are considered separable, and MSDs less than three are indistinguishable. The classification procedure correctly identified all samples for both analytical techniques. ISP-ARS is an effective, simpler, and more rapid alternative to full spectrum ARS that can be implemented with a commercial MP3 player and used as an inexpensive spectrometric sensor for dynamic data-driven application simulations (DDDAS) and process analytical applications.

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.