In-line fluorescence spectroscopy for quantification of low amount of active pharmaceutical ingredient

The pharmaceutical industry is currently implementing new manufacturing principles and modernizing the related processing solutions. A key element in this development is implementation of process analytical technologies (PAT) for measuring product quality in a real-time mode, ideally for a continuously operating processing line. Near-infrared (NIR) spectroscopy is widely used for this purpose, but has limited use for low concentration formulations, due to its inherent detection limit. Light-induced fluorescence (LIF) spectroscopy is a PAT tool that can be used to quantify low concentrations of active pharmaceutical ingredient, and recent development of instrumentation has made it available for in-line applications. In this study, the content of tryptophan in a dynamic powder flow could be measured as low as 0.10 w/w % with LIF spectroscopy with good accuracy of RMSEP = 0.008 w/w %. Both partial least squares regression and support vector machines (SVM) were investigated, but we found SVM to be the better option due to non-linearities between the calibration test and the in-line measurements. With the use of SVM, LIF spectroscopy is a promising candidate for low concentration applications where NIR is not suitable.

Employing Multivariate Statistics and Latent Variable Models to Identify and Quantify Complex Relationships in Typical Compression Studies

The effect of storage condition (% RH) on flufenamic acid:nicotinamide (FFA:NIC) cocrystal compressibility, compactibility, and tabletability profiles was not observed after visual evaluation or linear regression analysis. However, multivariate statistical analysis showed that storage condition had a significant effect on each compressional profile. Shapiro and Heckel equations were used to determine the compression parameters: porosity, Shapiro's compression parameter (f), densification factor (Da), plastic yield pressure (YPpl), and elastic yield pressure (YPel). Latent variable models such as exploratory factor analysis, principal component analysis, and principal component regression were employed to decode complex hidden main, interaction, and quadratic effects of % RH and the compression parameters on FFA:NIC tablet mechanical strength (TMS). Statistically significant correlations between f and Da, f and YPpl, and Da and YPel supported the idea that both rearrangement and fragmentation, and plastic deformation are important to FFA:NIC TMS. To the authors knowledge, this is the first time that simultaneously operating dual mechanisms of fragmentation and plastic deformation in low and midrange compression, and midrange plastic deformation have been identified and reported. A quantitative PCR model showed that f, Da, and YPel had statistically significant main effects along with a significant antagonist storage condition-porosity "conditional interaction effect". f exhibited a 2.35 times greater impact on TMS compared to Da. The model root-mean-square error at calibration and prediction stages were 0.04 MPa and 0.08 MPa, respectively. The R² values at the calibration stage and at the prediction stage were 0.9005 and 0.7539, respectively. This research demonstrated the need for caution when interpreting the results of bivariate compression data because complex latent inter-relationships may be hidden from visual assessment and linear regression analysis, and result in false data interpretation as illustrated in this report.

Effect of Percent Relative Humidity, Moisture Content, and Compression Force on Light-Induced Fluorescence (LIF) Response as a Process Analytical Tool

The effect of percent relative humidity (16-84% RH), moisture content (4.2-6.5% w/w MC), and compression force (4.9-44.1 kN CF) on the light-induced fluorescence (LIF) response of 10% w/w active pharmaceutical ingredient (API) compacts is reported. The fluorescent response was evaluated using two separate central composite designs of experiments. The effect of % RH and CF on the LIF signal was highly significant with an adjusted R (2)  = 0.9436 and p < 0.0001. Percent relative humidity (p = 0.0022), CF (p < 0.0001), and % RH(2) (p = 0.0237) were statistically significant factors affecting the LIF response. The effects of MC and CF on LIF response were also statistically significant with a p value <0.0001 and adjusted R (2) value of 0.9874. The LIF response was highly impacted by MC (p < 0.0001), CF (p < 0.0001), and MC(2) (p = 0022). At 10% w/w API, increased % RH, MC, and CF led to a nonlinear decrease in LIF response. The derived quadratic model equations explained more than 94% of the data. Awareness of these effects on LIF response is critical when implementing LIF as a process analytical tool.

Granulation of Y2O3 powders by a vibration method for the preparation of transparent ceramics

A modified vibrating screen method was employed to prepare granulated Y₂O₃ powders, which were used to fabricate transparent ceramics.