A Process Analytical Technology approach to near-infrared process control of pharmaceutical powder blending. Part I: D-optimal design for characterization of powder mixing and preliminary spectral data evaluation

Designing optimal experiments in metabolomics

BACKGROUND

Metabolomics data is often complex due to the high number of metabolites, chemical diversity, and dependence on sample preparation. This makes it challenging to detect significant differences between factor levels and to obtain accurate and reliable data. To address these challenges, the use of Design of Experiments (DoE) techniques in the setup of metabolomic experiments is crucial. DoE techniques can be used to optimize the experimental design space, ensuring that the maximum amount of information is obtained from a limited sample space.

AIM OF REVIEW

This review aims at providing a baseline workflow for applying DoE when generating metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review provides insights into the theory of DoE. The review showcases the theory being put into practice by highlighting different examples DoE being applied in metabolomics throughout the literature, considering both targeted and untargeted metabolomic studies in which the data was acquired using both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry techniques. In addition, the review presents DoE concepts not currently being applied in metabolomics, highlighting these as potential future prospects.

Integrating sensors for monitoring blend content in a pharmaceutical continuous manufacturing plant

In a pharmaceutical manufacturing process, Critical Quality Attributes (CQAs) need to be monitored not only for the final product but also for intermediates. Blend uniformity of powders is one such attribute that needs to be measured to ensure the quality of the final product. Multiple in-line sensors were implemented within a Direct Compaction (DC) continuous tablet manufacturing line to monitor the blend content of the powders. In most cases, since the primary ingredient of interest is the active pharmaceutical ingredient (API), the concentration (potency) of the API was monitored/predicted over the course of manufacturing. For the calibration model building process, a unique setup involving dynamic powder spectral acquisition method was used. This setup was aimed at mimicking the powder flow characteristics within the manufacturing line, while at the same time utilizing a relatively small amount of powder. A Raman probe and a portable NIR were used concurrently at the exit of the blending process before the tableting stage. The performance of the two sensors and their respective models were evaluated in terms of accuracy, precision, operating range, measurement frequency, placement, reliability, robustness, and compared to predictions using gravimetric feed rates. Additionally, their performances were validated by off-line traditional analytical measurements.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Development of an In-Line Near-Infrared Method for Blend Content Uniformity Assessment in a Tablet Feed Frame

Process analytical technology (PAT) has shown great potential for in-line tableting process monitoring. The study focuses on the development and validation of an in-line near-infrared (NIR) spectroscopic method for the determination of content uniformity of blends in a tablet feed frame. An in-line NIR method was developed after careful evaluation of the impact of potential experimental factors on the robustness and model accuracy and precision. The NIR method was validated according to the principles outlined in International Conference on Harmonization-Q2 for validation of analytical procedures and was demonstrated to be suitable for monitoring blend content for the formulation under evaluation. Reliable measurements of blend homogeneity rely on representative sampling. To reach the appropriate scale of scrutiny for a unit dose, the study assessed factors that influence the effective sample size measured by NIR. Spectral averaging, integration time, and feed frame paddle wheel speed were found to influence the effective sample size measured by the NIR probe. The effective sampling size was also estimated by comparing the distribution of predicted values with the reference values. The development of a robust, in-line PAT method was facilitated by thorough understanding of the sensitivity of PAT sensors to factors affecting pharmaceutical processes and products.

Methods to Assess Mixing of Pharmaceutical Powders

The pharmaceutical manufacturing process consists of several steps, each of which must be monitored and controlled to ensure quality standards are met. The level of blending has an impact on the final product quality; therefore, it is important to be able to monitor blending progress and identify an end-point. Currently, the pharmaceutical industry assesses blend content and uniformity through the extraction of samples using thief probes followed by analytical methods, such as spectroscopy, to determine the sample composition. The development of process analytical technologies (PAT) can improve product monitoring with the aim of increasing efficiency, product quality and consistency, and creating a better understanding of the manufacturing process. Ideally, these are inline methods to remove issues related to extractive sampling and allow direct monitoring of the system using various sensors. Many technologies have been investigated, including spectroscopic techniques such as near-infrared spectroscopy, velocimetric techniques that may use tracers, tomographic techniques, and acoustic emissions monitoring. While some techniques have demonstrated potential, many have significant disadvantages including the need for equipment modification, specific requirements of the material, expensive equipment, extensive analysis, the location of the probes may be critical and/or invasive, and lastly, the technique may only be applicable to the development phase. Both the advantages and disadvantages of the technologies should be considered in application to a specific system.

At-line determination of pharmaceuticals small molecule's blending end point using chemometric modeling combined with Fourier transform near infrared spectroscopy

This article summarizes the development and validation of a Fourier transform near infrared spectroscopy (FT-NIR) method for the rapid at-line prediction of active pharmaceutical ingredient (API) in a powder blend to optimize small molecule formulations. The method was used to determine the blend uniformity end-point for a pharmaceutical solid dosage formulation containing a range of API concentrations. A set of calibration spectra from samples with concentrations ranging from 1% to 15% of API (w/w) were collected at-line from 4000 to 12,500cm^-1. The ability of the FT-NIR method to predict API concentration in the blend samples was validated against a reference high performance liquid chromatography (HPLC) method. The prediction efficiency of four different types of multivariate data modeling methods such as partial least-squares 1 (PLS1), partial least-squares 2 (PLS2), principal component regression (PCR) and artificial neural network (ANN), were compared using relevant multivariate figures of merit. The prediction ability of the regression models were cross validated against results generated with the reference HPLC method. PLS1 and ANN showed excellent and superior prediction abilities when compared to PLS2 and PCR. Based upon these results and because of its decreased complexity compared to ANN, PLS1 was selected as the best chemometric method to predict blend uniformity at-line. The FT-NIR measurement and the associated chemometric analysis were implemented in the production environment for rapid at-line determination of the end-point of the small molecule blending operation.

Blend uniformity evaluation during continuous mixing in a twin screw granulator by in-line NIR using a moving F-test

This study focuses on the twin screw granulator of a continuous from-powder-to-tablet production line. Whereas powder dosing into the granulation unit is possible from a container of preblended material, a truly continuous process uses several feeders (each one dosing an individual ingredient) and relies on a continuous blending step prior to granulation. The aim of the current study was to investigate the in-line blending capacity of this twin screw granulator, equipped with conveying elements only. The feasibility of in-line NIR (SentroPAT, Sentronic GmbH, Dresden, Germany) spectroscopy for evaluating the blend uniformity of powders after the granulator was tested. Anhydrous theophylline was used as a tracer molecule and was blended with lactose monohydrate. Theophylline and lactose were both fed from a different feeder into the twin screw granulator barrel. Both homogeneous mixtures and mixing experiments with induced errors were investigated. The in-line spectroscopic analyses showed that the twin screw granulator is a useful tool for in-line blending in different conditions. The blend homogeneity was evaluated by means of a novel statistical method being the moving F-test method in which the variance between two blocks of collected NIR spectra is evaluated. The α- and β-error of the moving F-test are controlled by using the appropriate block size of spectra. The moving F-test method showed to be an appropriate calibration and maintenance free method for blend homogeneity evaluation during continuous mixing.

Use of in-die powder densification parameters in the implementation of process analytical technologies for tablet production on industrial scale

The use of process analytical technologies (PAT) to ensure final product quality is by now a well established practice in pharmaceutical industry. To date, most of the efforts in this field have focused on development of analytical methods using spectroscopic techniques (i.e., NIR, Raman, etc.). This work evaluated the possibility of using the parameters derived from the processing of in-line raw compaction data (the forces and displacement of the punches) as a PAT tool for controlling the tableting process. To reach this goal, two commercially available formulations were used, changing the quantitative composition and compressing them on a fully instrumented rotary pressing machine. The Heckel yield pressure and the compaction energies, together with the tablets hardness and compaction pressure, were selected and evaluated as discriminating parameters in all the prepared formulations. The apparent yield pressure, as shown in the obtained results, has the necessary sensitivity to be effectively included in a PAT strategy to monitor the tableting process. Additional investigations were performed to understand the criticalities and the mechanisms beyond this performing parameter and the associated implications. Specifically, it was discovered that the efficiency of the apparent yield pressure depends on the nominal drug title, the drug densification mechanism and the error in pycnometric density. In this study, the potential of using some parameters derived from the compaction raw data has been demonstrated to be an attractive alternative and complementary method to the well established spectroscopic techniques to monitor and control the tableting process. The compaction data monitoring method is also easy to set up and very cost effective.

Identification of anisodamine tablets by Raman and near-infrared spectroscopy with chemometrics

Vibrational spectroscopy including Raman and near-infrared (NIR) spectroscopy has become an attractive tool for pharmaceutical analysis. In this study, effective calibration models for the identification of anisodamine tablet and its counterfeit and the distinguishment of manufacturing plants, based on Raman and NIR spectroscopy, were built, respectively. Anisodamine counterfeit tablets were identified by Raman spectroscopy with correlation coefficient method, and the results showed that the predictive accuracy was 100%. The genuine anisodamine tablets from 5 different manufacturing plants were distinguished by NIR spectroscopy using partial least squares discriminant analysis (PLS-DA) models based on interval principal component analysis (iPCA) method. And the results showed the recognition rate and rejection rate were 100% respectively. In conclusion, Raman spectroscopy and NIR spectroscopy combined with chemometrics are feasible and potential tools for rapid pharmaceutical tablet discrimination.

Verification of model development technique for NIR-based real-time monitoring of ingredient concentration during blending

There has been a considerable research on the process analytical technology (PAT) and real-time monitoring based on NIR, but the model development is still an important issue and persons in charge have difficulty in building good models. In this study, to realize efficient NIR-based real-time monitoring of ingredient concentration and establish a model development method, we investigated the effect of a calibration set, spectral preprocessing, wavelengths, and other factors on the prediction error through pilot and commercial scale blending experiments. The results confirmed that the small prediction error was realized by a calibration set, including dynamic measurement spectra acquired with the target blender. In addition, the results demonstrated that locally weighted partial least squares (LW-PLS) achieved the smaller prediction error than conventional PLS. The present study has also clarified that spectral preprocessing methods and wavelengths selected to build a model affect the prediction error of ingredient concentration interactively. A wide wavelength range should be selected when the spectral preprocessing does not lessen the effect of baseline variation, while a narrow wavelength range should be selected when it strongly decreases the effect.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed.

Effect of experimental design on the prediction performance of calibration models based on near-infrared spectroscopy for pharmaceutical applications

Near-infrared spectroscopy (NIRS) is a valuable tool in the pharmaceutical industry, presenting opportunities for online analyses to achieve real-time assessment of intermediates and finished dosage forms. The purpose of this work was to investigate the effect of experimental designs on prediction performance of quantitative models based on NIRS using a five-component formulation as a model system. The following experimental designs were evaluated: five-level, full factorial (5-L FF); three-level, full factorial (3-L FF); central composite; I-optimal; and D-optimal. The factors for all designs were acetaminophen content and the ratio of microcrystalline cellulose to lactose monohydrate. Other constituents included croscarmellose sodium and magnesium stearate (content remained constant). Partial least squares-based models were generated using data from individual experimental designs that related acetaminophen content to spectral data. The effect of each experimental design was evaluated by determining the statistical significance of the difference in bias and standard error of the prediction for that model's prediction performance. The calibration model derived from the I-optimal design had similar prediction performance as did the model derived from the 5-L FF design, despite containing 16 fewer design points. It also outperformed all other models estimated from designs with similar or fewer numbers of samples. This suggested that experimental-design selection for calibration-model development is critical, and optimum performance can be achieved with efficient experimental designs (i.e., optimal designs).

Application of quality by design to formulation and processing of protein liposomes

Quality by design (QbD) principles were explored in the current study to gain a comprehensive understanding of the preparation of superoxide dismutase (SOD) containing liposome formulations prepared using freeze-and-thaw unilamellar vesicles (FAT-ULV). Risk analysis and D-optimal statistical design were performed. Of all the variables investigated, lipid concentration, cholesterol mol%, main lipid type and protein concentration were identified as critical parameters affecting SOD encapsulation efficiency, while the main lipid type was the only factor influencing liposome particle size. Using a model generated by the D-optimal design, a series of three-dimensional response spaces for SOD liposome encapsulation efficiency were established. The maximum values observed in the response surfaces indirectly confirmed the existence of a specific SOD-lipid interaction, which took place in the lipid bilayer under the following optimal conditions: (1) appropriate membrane thickness and curvature (DPPC liposomes); and (2) optimal "pocket size" generated by cholesterol content. With respect to storage stability, the prepared SOD liposomes remained stable for at least 6 months in aqueous dispersion state at 4°C. This research highlights the level of understanding that can be accomplished through a well-designed study based on the philosophy of QbD.

Lactose characteristics and the generation of the aerosol

The delivery efficiency of dry-powder products for inhalation is dependent upon the drug formulation, the inhaler device, and the inhalation technique. Dry powder formulations are generally produced by mixing the micronised drug particles with larger carrier particles. These carrier particles are commonly lactose. The aerosol performance of a powder is highly dependent on the lactose characteristics, such as particle size distribution and shape and surface properties. Because lactose is the main component in these formulations, its selection is a crucial determinant of drug deposition into the lung, as interparticle forces may be affected by the carrier-particle properties. Therefore, the purpose of this article is to review the various grades of lactose, their production, and the methods of their characterisation. The origin of their adhesive and cohesive forces and their influence on aerosol generation are described, and the impact of the physicochemical properties of lactose on carrier-drug dispersion is discussed in detail.

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.