Online Process Control of a Pharmaceutical Intermediate in a Fluidized-Bed Drier Environment Using Near-Infrared Spectroscopy

Evaluation of Blend Uniformity and Terminal Point during Continuous Mixing in Water for Modified Double-Base Propellant Components Using a Near-Infrared Method

A near-infrared (NIR) spectrometer was used to test the double-base absorbent powder sample and to quantitatively analyze the contents of each component as well as their dispersion uniformity to establish a rapid quantitative test method for blending uniformity of modified double-base (MDB) propellant components. First, the quantitative calibration models of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) were constructed based on sample testing, and the RDX model's correlation coefficient was 0.9929. Then, during the blending process, NIR spectra were continually collected. For the original spectra of samples, the blend uniformity was assessed using the coefficient of moving block standard deviation (MBSD). After 160 min, the sample's MBSD value had reached a steady state of less than 0.003, indicating that the sample's components were distributed uniformly. The findings reveal that NIR spectroscopy can be used to verify the blending uniformity of MDB propellant components.

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.

Error propagation of partial least squares for parameters optimization in NIR modeling

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Theoretical and technical advancements of near-infrared spectroscopy and its operational impact in industry

This article provides a summary of the plenary lecture given at ICNIRS2017 at Copenhagen, Denmark. In principle, near infrared spectroscopy enjoys increasing popularity due to its possibilities for non-invasive, fast, and simultaneous analysis of chemical and physical parameters. Therefore, more frequently in laboratories, time-consuming classical methods including wet-chemical analysis, chromatography, electrophoresis, etc., get substituted by near infrared spectroscopy approaches. On the other hand, hardly any other discipline in analytical chemistry is making such fast technical and theoretical advancements. One of the major challenges is the development of portable devices based on micro-electro mechanical systems or linear variable filters. It belongs to the responsibility of the near infrared spectroscopist to critically evaluate the performance of those with benchtop instruments. For method development, design of experiment and quantum chemical calculation of spectra can give fundamental support. Finally, serious care is to be taken when methods are transferred into the industrial environment.

Near-infrared spectroscopy monitoring and control of the fluidized bed granulation and coating processes-A review

The fluidized bed granulation and pellets coating technologies are widely used in pharmaceutical industry, because the particles made in a fluidized bed have good flowability, compressibility, and the coating thickness of pellets are homogeneous. With the popularization of process analytical technology (PAT), real-time analysis for critical quality attributes (CQA) was getting more attention. Near-infrared (NIR) spectroscopy, as a PAT tool, could realize the real-time monitoring and control during the granulating and coating processes, which could optimize the manufacturing processes. This article reviewed the application of NIR spectroscopy in CQA (moisture content, particle size and tablet/pellet thickness) monitoring during fluidized bed granulation and coating processes. Through this review, we would like to provide references for realizing automated control and intelligent production in fluidized bed granulation and pellets coating of pharmaceutical industry.

Novel Molecular Spectroscopic Multimethod Approach for Monitoring Water Absorption/Desorption Kinetics of CAD/CAM Poly(Methyl Methacrylate) Prosthodontics

Water absorbed to poly(methyl methacrylate) (PMMA)-based CAD/CAM (computer-assisted design/computer-assisted manufacturing) prosthodontics can alter their properties including hardness and stability. In the present contribution, water absorption and desorption kinetics under defined experimental conditions were monitored employing several supplementary and advanced Fourier transform infrared (FT-IR) spectroscopic techniques in combination with multivariate analysis (MVA). In this synergistic vibrational spectroscopic multimethod approach, first a novel near-infrared (NIR) diffuse fiber optic probe reflection spectroscopic method was established for time-resolved analysis of water uptake within seven days under controlled conditions. Near-infrared water absorbance spectra in a wavenumber range between 5288-5100 cm^-1 (combination band) and 5424-5352 cm^-1 (second overtone) were used establishing corresponding calibration and validation models to quantify the amount of water in the milligram range. Therefore, 14 well-defined samples exposed to prior optimized experimental conditions were taken into consideration. The average daily water uptake conducting reference analysis was calculated as 22 mg/day for one week. Additionally, in this study for the first time NIR two-dimensional correlation spectroscopy (2D-COS) was conducted to monitor and interpret the spectral dynamics of water absorption on the prosthodontics in a wavenumber range of 5100-5300 cm^-1. For sensitive time-resolved recording of water desorption, a recently developed high-temperature, high-pressure FT-IR reaction cell with water-free ultra-dry in situ and operando operation was applied. The reaction cell, as well as the sample holder, was fully made of quartz glass, with no hot metal or ceramic parts in the vicinity of the high temperature zone. Applying a temperature gradient in the range of 25-150 ℃, mid-infrared (MIR) 2D-COS was successfully conducted to get insights into the dynamic behavior of O-H (1400-1800 cm^-1) absorption bands with increasing temperature over time and the release of CO₂ (2450 cm^-1) from the polymers. In addition, an ATR FT-IR imaging setup was optimized in order to investigate the surface homogeneity of the PMMA-based resins with a spatial resolution to 2 µm. From this vibrational spectroscopic multimethod approach and the collection of several analytical data, conclusions were drawn as to which degree the surface structure and/or its porosity have an impact onto the amount of water absorption.

On-line monitoring of vacuum drying of theophylline using NIR spectroscopy: solid-state transitions, water content and semi-empirical modeling

The aim of this work was to monitor in-line and at a real time, the solid-state forms during pharmaceuticals manufacturing. It concerns the dehydration behavior and the solid-state transitions of theophylline in an agitated vacuum contact dryer. First, a near infrared spectroscopy (NIRS) method was performed using a reflectance diffuse probe to measure the in-line and in-situ exact composition of the mixture of different forms of theophylline and water content during drying. A multivariate modeling has been investigated to build a robust model which can predict four components at the same time during drying process. The XRPD analysis was used as a reference method in the process of calibration of NIRS. The indicators of the accuracy in quantitative spectral analysis confirm the robustness of the model and the efficiency of the method of calibration. Second, the kinetics of solid state transformations were investigated. It was shown that the dehydration advanced first by the formation of the metastable anhydrate and after a lag time of the stable one. Once the stable form appeared, formation of the metastable form came to an end. The temperature was found out to be the main factor controlling the overall process rate but also the final contents of the stable and metastable anhydrates for the considered dryer and operating conditions range. Finally, a semi-empirical drying model was proposed and significant quantitative differences were found, particularly at the product temperature which was probably caused by the excessive simplicity of the model.

Optimization of Parameter Selection for Partial Least Squares Model Development

In multivariate calibration using a spectral dataset, it is difficult to optimize nonsystematic parameters in a quantitative model, i.e., spectral pretreatment, latent factors and variable selection. In this study, we describe a novel and systematic approach that uses a processing trajectory to select three parameters including different spectral pretreatments, variable importance in the projection (VIP) for variable selection and latent factors in the Partial Least-Square (PLS) model. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the ratio of standard error of prediction to standard deviation (RPD), and the determination coefficient of calibration (Rcal(2)) and validation (Rpre(2)) were simultaneously assessed to optimize the best modeling path. We used three different near-infrared (NIR) datasets, which illustrated that there was more than one modeling path to ensure good modeling. The PLS model optimizes modeling parameters step-by-step, but the robust model described here demonstrates better efficiency than other published papers.

Discriminant analysis of Chinese patent medicines based on near-infrared spectroscopy and principal component discriminant transformation

Principal component discriminant transformation was applied for discrimination of different Chinese patent medicines based on near-infrared (NIR) spectroscopy. In the method, an optimal set of orthogonal discriminant vectors, which highlight the differences between the NIR spectra of different classes, is designed by maximizing Fisher's discriminant function. Therefore, a model for discriminating a class and the others can be obtained with the tiny differences between the NIR spectra of different classes. Furthermore, because NIR spectra contain a large amount of redundant information, principal component analysis (PCA) is employed to reduce the dimension. On the other hand, continuous wavelet transform (CWT) is taken as the pretreatment method to remove the variant background. For identifying the method, different medicines and the same medicine from different manufactures were studied. The results show that all the models can provide 100% discrimination.

Fiber Bragg grating with polyimide-silica hybrid membrane for accurately monitoring cell growth and temperature in a photobioreactor

A microstructured fiber Bragg grating (MSFBG) was created to accurately and simultaneously monitor the cell growth of photosynthetic bacteria (PSB) Rhodopseudomonas palustris CQK 01 and the temperature in a photobioreactor. The proposed sensor was made from an FBG unit that was separated into three regions, an unperturbed region, and two etched regions with smooth surfaces. The unperturbed grating region was employed to monitor the temperature. To eliminate the effects of the liquid concentration and temperature on the biomass, a polyimide-silica hybrid membrane was created and coated on an etched grating region to separate the liquids from the PSB; that is, this thinned region was developed to analyze the liquid concentration and temperature. Another etched grating region with a smaller diameter was used to determine the response to the temperature, biomass, and liquid concentration. In addition, two models were also presented to demonstrate accurate simultaneous measurement of the biomass and temperature. We discovered that the MSFBG sensor can rapidly and accurately determine the difference in the Bragg wavelength shifts caused by changes in the temperature, biomass, and liquid-phase concentration. The measured biomass is highly correlated with the real cell growth, with a correlation of 0.9438; the hydrogen production rate and temperature difference from metabolic heat production reached 1.97 mmol/L/h and 2.8 °C, respectively, in the PSB culture.

On-line application of near-infrared spectroscopy for monitoring water levels in parts per million in a manufacturing-scale distillation process

An on-line analytical method based on transmission near-infrared spectroscopy (NIRS) for the quantitative determination of water concentrations (in parts per million) was developed and applied to the manufacture of a pharmaceutical intermediate. Calibration models for water analysis, built at the development site and applied at the manufacturing site, were successfully demonstrated during six manufacturing runs at a 250-gallon scale. The water measurements will be used as a forward-processing control point following distillation of a toluene product solution prior to use in a Grignard reaction. The most significant impact of using this NIRS-based process analytical technology (PAT) to replace off-line measurements is the significant reduction in the risk of operator exposure through the elimination of sampling of a severely lachrymatory and mutagenic compound. The work described in this report illustrates the development effort from proof-of-concept phase to manufacturing implementation.

Advances of vibrational spectroscopic methods in phytomics and bioanalysis

During the last couple of years great advances in vibrational spectroscopy including near-infrared (NIR), mid-infrared (MIR), attenuated total reflection (ATR) and imaging and also mapping techniques could be achieved. On the other hand spectral treatment features have improved dramatically allowing filtering out relevant information from spectral data much more efficiently and providing new insights into the biochemical composition. These advances offer new possible quality control strategies in phytomics and enable to get deeper insights into biochemical background in terms of medicinal relevant questions. It is the aim of the present article pointing out the technical and methodological advancements in the NIR and MIR field and to demonstrate the individual methods efficiency by discussing distinct selected applications.

In-line monitoring of the thickness of printed layers by near-infrared (NIR) spectroscopy at a printing press

In this work, it is demonstrated that the coating weight of printed layers can be determined in-line in a running printing press by near-infrared (NIR) reflection spectroscopy assisted by chemometric methods. Three different unpigmented lacquer systems, i.e., a conventional oil-based printing lacquer, an ultraviolet (UV)-curable formulation, and a water-based dispersion varnish, were printed on paper with coating weights between about 0.5 and 7 g m(-2). NIR spectra for calibration were recorded with a special metal reflector simulating the mounting conditions of the probe head at the printing press. Calibration models were developed on the basis of the partial least squares (PLS) algorithm and evaluated by independent test samples. The prediction performance of the developed models was examined at a sheet-fed offset printing press at line speeds between 90 and 180 m min(-1). Results show an excellent correlation of data predicted in-line from the NIR spectra with reference values obtained off-line by gravimetry. The prediction errors were found to be ≤ 0.2 g m(-2), which confirms the suitability of the developed spectroscopic method for process control in technical printing processes.

Near infrared and Raman spectroscopy for the in-process monitoring of pharmaceutical production processes

Within the Process Analytical Technology (PAT) framework, it is of utmost importance to obtain critical process and formulation information during pharmaceutical processing. Process analyzers are the essential PAT tools for real-time process monitoring and control as they supply the data from which relevant process and product information and conclusions are to be extracted. Since the last decade, near infrared (NIR) and Raman spectroscopy have been increasingly used for real-time measurements of critical process and product attributes, as these techniques allow rapid and nondestructive measurements without sample preparations. Furthermore, both techniques provide chemical and physical information leading to increased process understanding. Probes coupled to the spectrometers by fiber optic cables can be implemented directly into the process streams allowing continuous in-process measurements. This paper aims at reviewing the use of Raman and NIR spectroscopy in the PAT setting, i.e., during processing, with special emphasis in pharmaceutics and dosage forms.