Industrial Applications of Online Monitoring of Drying Processes of Drug Substances Using NIR

Process analytical technology in Downstream-Processing of Drug Substances- A review

Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.

Monitoring of the residual moisture content in finished textiles during converting by NIR hyperspectral imaging

Hyperspectral imaging was used for large-scale monitoring of the residual moisture in wide textile webs at the end of the drying process that follows their washing or finishing by impregnation in aqueous solutions or dispersions. Such data are essential for optimizing the energy efficiency and the precise control of the drying process. Quantitative analysis of the recorded spectral data was carried out with multivariate regression methods such as the partial least squares (PLS) algorithm. Reference data for calibration of the prediction models were determined by gravimetry. The drying of textile materials from both natural or synthetic fibers possessing different water absorption capacities (cotton, polyamide, polyester), which were partially finished with an optical brightener, was investigated. Moisture contents in the range from 0 to about 12 wt% were considered in the calibration models. For all systems, the root mean square error of prediction (RMSEP) for the residual moisture was found to be about 0.5 wt%, that is, about 1 g/m². In addition to the quantitative determination of the water content, hyperspectral imaging provides detailed information about its spatial distribution across the textile web, which may help to improve the control of the drying process. In particular, it was demonstrated that the developed methods were capable of detecting and visualizing inhomogeneous moisture distributions. Averaging of the individual values of the moisture content predicted from all spectra across the surface of the textile samples resulted in a very close correlation with the corresponding gravimetric reference values. Due to the averaging process, the difference between both values is generally lower than RMSEP even in case of samples with inhomogeneous distribution of the moisture. The high precision and the broad capabilities of the developed analytic methods for in-line monitoring of the moisture content hold the potential for an efficient process control in technical textile converting processes.

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor

PURPOSE

The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry-Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control.

METHODS

Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance.

RESULTS

The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13 % ) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection.

CONCLUSIONS

The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate.

PAT-Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets

Current endeavor was aimed towards monitoring percent weight build-up during functional coating process on drug-layered pellets. Near-infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15-Kg cellulosic coating material during Wurster coating process of drug-loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm^-1, 7515.24 to 7108.33 cm^-1, and 5257.00 to 5098.87 cm^-1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm^-1was found to be specific to drug. The final model gave superb correlation co-efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at-line prediction of functional coat value and can be used for monitoring the Wurster coating process.

Classification of Ciprofloxacin Tablets Using Near-Infrared Spectroscopy and Chemometric Modeling

Exposure to unknown, mislabeled, and counterfeit pharmaceutical products is a worldwide problem that presents a serious risk to public health. Near-infrared (NIR) spectroscopy can serve as a useful tool for screening pharmaceuticals in a rapid and cost-effective manner to ensure that drug products are safe and effective. By applying chemometric techniques to NIR spectra from finished products in tablet form, minor spectral differences are discoverable, even in instances where the tablets being evaluated contain the same active pharmaceutical ingredients (APIs). Differences in NIR spectra can occur as a result of various factors including the types and quantities of pharmaceutical excipients used to generate the product and associated manufacturing site process variables. In this study, variability in the NIR spectra of intact tablets with the same API was evaluated using an unsupervised chemometric technique in the form of hierarchical cluster analysis (HCA) on a data set consisting of NIR spectra from more than 800 ciprofloxacin tablets from six manufacturers. Results obtained from HCA and squared Euclidean distance measurements indicate the largest dissimilarities in NIR spectra occur between manufacturers. Based on these findings, a quadratic discriminant analysis (QDA) model was built following dimensionality reduction by principal component analysis for the purpose of predicting the origin of ciprofloxacin tablets. Using QDA, we were able to correctly classify a collection of 907 tablets with greater than 96% accuracy. Chemometric models such as the one developed here could ultimately be employed as part of a large, diversified drug surveillance program.

Automated measurement and monitoring of bioprocesses: key elements of the M(3)C strategy

The state-of-routine monitoring items established in the bioprocess industry as well as some important state-of-the-art methods are briefly described and the potential pitfalls discussed. Among those are physical and chemical variables such as temperature, pressure, weight, volume, mass and volumetric flow rates, pH, redox potential, gas partial pressures in the liquid and molar fractions in the gas phase, infrared spectral analysis of the liquid phase, and calorimetry over an entire reactor. Classical as well as new optical versions are addressed. Biomass and bio-activity monitoring (as opposed to "measurement") via turbidity, permittivity, in situ microscopy, and fluorescence are critically analyzed. Some new(er) instrumental analytical tools, interfaced to bioprocesses, are explained. Among those are chromatographic methods, mass spectrometry, flow and sequential injection analyses, field flow fractionation, capillary electrophoresis, and flow cytometry. This chapter surveys the principles of monitoring rather than compiling instruments.

An insight into water of crystallization during processing using vibrational spectroscopy

Many organic molecules used as drugs can incorporate water into their crystal lattice. These compounds are also prone to processing-induced transformations (PITs) because processing often exposes the compounds to moisture, heat and mechanical stress. The aim of this review is to provide an overview of the possibilities for following and understanding hydrate/anhydrate transformations using vibrational spectroscopy (mid-infrared, near-infrared, Raman and terahertz). The review begins with a general section on hydrates, followed by considerations on the impact of these on drug products and a description of transformation mechanisms of hydrates. Moreover, a general introduction is given for the spectroscopic techniques together with a discussion of critical issues for quantification models. Unit operations that may induce transformations in hydrate systems are discussed with focus on the published work on the use of spectroscopy to derive information from these processes. Finally, the effect of excipients on PITs is discussed.