Accuracy Improvement of In-line Near-Infrared Spectroscopic Moisture Monitoring in a Fluidized Bed Drying Process

Quantitative analysis of moisture content and particle size in a fluidized bed granulation process using near infrared spectroscopy and acoustic emission combined with data fusion strategies

Monitoring granule property is essential for fluidization maintenance and product quality control in fluidized bed granulation (FBG). In this study, two non-invasive techniques, near-infrared (NIR) spectroscopy and acoustic emission (AE), were applied for quantitative analysis of moisture content (MC) and median particle size (D50) in a FBG process, combined with chemometrics and data fusion strategies. Partial least squares (PLS) and support vector machine (SVM) regression models were established based on NIR and AE spectral data. The optimal quantitative models were identified considering the effect of spectra preprocessing and variable selection. In the comparison study, the best separate models for MC and D50 quantification were based on NIR and AE, respectively. The NIR model exhibited the better prediction ability with the determination coefficient of validation set (R2v) of 0.9815, root mean square error of validation set (RMSEv) of 0.2226 %, and residual predictive deviation (RPD) of 7.4674 for MC. Meanwhile, the AE model presented the better prediction performance with R2v of 0.9710, RMSEv of 18.2643 μm, and RPD of 5.9740 for D50. Furthermore, among three data fusion strategies, the high-level fusion model achieved the best overall performance on D50 quantification with R2v of 0.9863, RMSEv of 12.5707 μm, and RPD of 8.6798. The results indicated that both NIR and AE are effective monitoring tools for MC and D50 analysis in fluidized bed granulation process. In addition, a more accurate and reliable analysis of particle size can be achieved by combining NIR and AE technology with high-level data fusion.

In-Line Detection of Bed Fluidity in Gas-Solid Fluidized Beds Using Near-Infrared Spectroscopy

A novel approach was developed to detect bed fluidity in gas-solid fluidized beds using diffuse reflectance near-infrared (NIR) spectroscopy. Because the flow dynamics of gas and solid phases are closely associated with the fluidization state, the fluidization quality can be evaluated through hydrodynamic characterization. In this study, the baseline level of NIR spectra was used to quantify the voidage of the fluidized bed. Two indicators derived from the NIR baseline fluctuation profiles were investigated to characterize bed fluidity, named bubble proportion and skewness. To establish a robust fluidity evaluation method, the relationships between the indicators and bed fluidity were investigated under different conditions firstly, including static bed height and average particle size. Then, a generalized threshold was identified to distinguish poor and good bed fluidity, ensuring that the probability of the α- and β-errors was less than 15% regardless of material conditions. The results show that both indicators were sensitive to changes in bed fluidity under the investigated conditions. The indicator of skewness was qualified to detect bed fluidity under varied conditions with a robust threshold of 1.20. Furthermore, the developed NIR method was successfully applied to monitor bed fluidity and for early warning of defluidization in a laboratory-scale fluidized bed granulation process.

Nonlinearity parameter in the pathlength dimension to improve the scattering in the transmission spectra

In spectrochemical quantitative analysis of solutions containing scattering components, the spectral nonlinearity caused by scattering seriously affects the prediction accuracy, robustness, and even feasibility of the models. Unlike the traditional methods (modeling with the spectra data of single pathlength) of approximating the nonlinear spectral line to linear to reduce the nonlinear features of scattering, a new method is proposed to reduce the effect of scattering by taking advantage of the nonlinear characteristics of spectral lines. First, the logarithmic function is used to fit the attenuation of multiple pathlengths, then the regression coefficient of the function is taken as the characteristic parameter of scattering, and the wavelengths with smaller characteristic parameter are selected as the modeling wavelengths. The model is robust and insensitive to the effect of scattering. The experiment involving a variety of scattering cases containing intralipids and ink was taken to verify the method. An F-test of the experimental results was significant at the 0.05 level. The root mean square error of prediction of the new method was 1.94%, and the prediction accuracy was 75.5% higher than that of the traditional model. The new method provides a novel approach toward describing the spectral nonlinearity with a function.

Determination of quality markers for quality control of Zanthoxylum nitidum using ultra-performance liquid chromatography coupled with near infrared spectroscopy

With the increasing demand for quality control in the traditional Chinese medicine industry, there is a need for the development of quality markers and a quick, non-destructive technique for the discrimination of related species. In our previous study, ultra-performance liquid chromatography (UPLC) was used for the simultaneous determination of five compounds, including three alkaloids (nitidine chloride, chelerythrine, and magnoflorine), one flavonoid (aurantiamarin), and one lignan (sesamin). In this study, the simultaneous quantification of the above-mentioned compounds could be used to discriminate the powders of roots from those of stems. To further test the reliability of the five compounds, seventy-two batches of wild and seventy-five batches of cultivated Zanthoxylum nitidum samples collected from Guangdong, Guangxi, and Fujian provinces in China were analyzed by UPLC and near-infrared spectroscopy (NIRS). In general, the quantitative results of UPLC were consistent with those of NIRS, and cultivated Z. nitidum has similar major bioactive compounds as the wild one, as supported by principal component analysis. Consequently, these five major bioactive compounds are suggested as potential quality markers. In addition, the NIRS method with discriminant analysis successfully differentiated Z. nitidum from three related species (Z. avicennae, Z. scandens and Toddalia asiatica) of the Rutaceae family. In summary, this study provides a method for the rapid identification of Z. nitidum and discrimination of root and stem powders, and suggests five compounds as quality markers for the evaluation of Z. nitidum.

Developing Multisensory Approach to the Optical Spectral Analysis

This article presents an overview of research aimed at developing a scientific approach to creating multisensor optical systems for chemical analysis. The review is mainly based on the author's works accomplished over the recent 10 years at Samara State Technical University with broad international cooperation. It consists of an introduction and five sections that describe state of the art in the field of optical sensing, suggested development methodology of optical multisensor systems, related aspects of experimental design and process analytical technology followed by a collection of practical examples in different application fields: food and pharmaceutical production, medical diagnostics, and ecological monitoring. The conclusion summarizes trends and prospects of the multisensory approach to optical spectral analysis.

Unveiling non-linear water effects in near infrared spectroscopy: A study on organic wastes during drying using chemometrics

In the context of organic waste management, near infrared spectroscopy (NIRS) is being used to offer a fast, non-destructive, and cost-effective characterization system. However, cumbersome freeze-drying steps of the samples are required to avoid water's interference on near infrared spectra. In order to better understand these effects, spectral variations induced by dry matter content variations were obtained for a wide variety of organic substrates. This was made possible by the development of a customized near infrared acquisition system with dynamic highly-resolved simultaneous scanning of near infrared spectra and estimation of dry matter content during a drying process at ambient temperature. Using principal components analysis, the complex water effects on near infrared spectra are detailed. Water effects are shown to be a combination of both physical and chemical effects, and depend on both the characteristics of the samples (biochemical type and physical structure) and the moisture content level. This results in a non-linear relationship between the measured signal and the analytical characteristic of interest. A typology of substrates with respect to these water effects is provided and could further be efficiently used as a basis for the development of local quantitative calibration models and correction methods accounting for these water effects.

Process Control of Drug Product Continuous Manufacturing Operations—a Study in Operational Simplification and Continuous Improvement

Purpose

The purpose of this manuscript is to demonstrate that implementation of gravimetric measurements provides the same assurance of product quality and process control as spectroscopic measurements (1) for control of drug content in a fixed-dose combination (FDC) tablet and (2) for identification of non-conforming material.

Methods

A wet granulation continuous tableting line was used to make the FDC drug product batches. Comparative data was generated for ten batches using near-infrared (NIR) spectroscopy for core tablets, and gravimetric in-process control measurements (IPCs) applied to the ratio control of intra- and extra-granular blend (IG and EG). HPLC reference data were collected to further demonstrate uniformity at each stage of the production process, including IG, final blend, and core tablets. All possible sources of variation not directly detectable by the gravimetric measurements were considered and quantified.

Results

The two IPC measurement techniques showed excellent agreement where both were within 2% of the target drug concentrations and within 2% of each other for the ten comparative batches. The NIR was more sensitive to material and process variations than the gravimetric IPCs; thus, it was more variable within and across batches. Gravimetric IPCs were demonstrated as an effective replacement for spectroscopic measurements for continuous tableting operations, capable of ensuring on target manufacturing and detection of non-conforming material.

Conclusions

As pharmaceutical companies continue to push toward operational simplicity and sustainable manufacturing processes, soft-sensor and gravimetric controls as alternatives to their spectroscopic counterparts will be applied more broadly for process monitoring and control.