A process analytical technology approach based on near infrared spectroscopy: tablet hardness, content uniformity, and dissolution test measurements of intact tablets.

Near infrared spectroscopy (NIRS) is a nondestructive analytical technique that enables simultaneous measurements of chemical composition (viz. the content in active pharmaceutical ingredient, API) and various physical properties (viz. tablet hardness and dissolution profile) in pharmaceutical tablets. In this work, partial least squares (PLS) calibration models and discriminant partial least squares (DPLS) classification models were constructed by using calibration sets consisting of laboratory samples alone. The laboratory samples were mixtures of the API and excipients that were pressed into tablets. API content, tablet hardness, and dissolution measurements of intact tablets were made by using three different calibration models that are fast--results can be obtained within a few seconds--, simple and robust--they involve minimal analyst intervention--, and clean--they use no toxic reagent and produce no toxic waste. Based on the results, the proposed NIR method is an effective alternative to current reference methods for the intended purpose. The advantages provided by NIR spectroscopy in this context confirm its potential for inclusion in process analytical technologies in the pharmaceutical industry.

Real-time determination of critical quality attributes using near-infrared spectroscopy: a contribution for Process Analytical Technology (PAT).

Process Analytical Technology (PAT) is playing a central role in current regulations on pharmaceutical production processes. Proper understanding of all operations and variables connecting the raw materials to end products is one of the keys to ensuring quality of the products and continuous improvement in their production. Near infrared spectroscopy (NIRS) has been successfully used to develop faster and non-invasive quantitative methods for real-time predicting critical quality attributes (CQA) of pharmaceutical granulates (API content, pH, moisture, flowability, angle of repose and particle size). NIR spectra have been acquired from the bin blender after granulation process in a non-classified area without the need of sample withdrawal. The methodology used for data acquisition, calibration modelling and method application in this context is relatively inexpensive and can be easily implemented by most pharmaceutical laboratories. For this purpose, Partial Least-Squares (PLS) algorithm was used to calculate multivariate calibration models, that provided acceptable Root Mean Square Error of Predictions (RMSEP) values (RMSEP(API)=1.0 mg/g; RMSEP(pH)=0.1; RMSEP(Moisture)=0.1%; RMSEP(Flowability)=0.6 g/s; RMSEP(Angle of repose)=1.7° and RMSEP(Particle size)=2.5%) that allowed the application for routine analyses of production batches. The proposed method affords quality assessment of end products and the determination of important parameters with a view to understanding production processes used by the pharmaceutical industry. As shown here, the NIRS technique is a highly suitable tool for Process Analytical Technologies.

Quality by design approach of a pharmaceutical gel manufacturing process, part 1: determination of the design space.

This work was conducted in the framework of a quality by design project involving the production of a pharmaceutical gel. Preliminary work included the identification of the quality target product profiles (QTPPs) from historical values for previously manufactured batches, as well as the critical quality attributes for the process (viscosity and pH), which were used to construct a D-optimal experimental design. The experimental design comprised 13 gel batches, three of which were replicates at the domain center intended to assess the reproducibility of the target process. The viscosity and pH models established exhibited very high linearity and negligible lack of fit (LOF). Thus, R(2) was 0.996 for viscosity and 0.975 for pH, and LOF was 0.53 for the former parameter and 0.84 for the latter. The process proved reproducible at the domain center. Water content and temperature were the most influential factors for viscosity, and water content and acid neutralized fraction were the most influential factors for pH. A desirability function was used to find the best compromise to optimize the QTPPs. The body of information was used to identify and define the design space for the process. A model capable of combining the two response variables into a single one was constructed to facilitate monitoring of the process.

Quality by design approach of a pharmaceutical gel manufacturing process, part 2: near infrared monitoring of composition and physical parameters.

We applied the principles of quality by design to the production process of a pharmaceutical gel by using the near infrared spectroscopy (NIRS) technique in combination with multivariate chemometric tools. For this purpose, we constructed a D-optimal experimental design having normal operational condition (NOC) batches as central point. The primary aim here was to develop an expeditious NIRS method for determining the composition of a pharmaceutical gel and assess the temporal changes in major physical factors affecting the quality of the product (specifically, viscosity and pH). Gel components were quantified by using partial least squares (PLS) calibration models of the PLS1 type. The study was completed by using the batch statistical process control method to compare product batches included in the experimental design with NOC batches. Similarities and differences between the two types of batches were identified by using control charts for residuals (Q-statistic) and Hotteling's T2 (D-statistic). The ensuing models, which were subject to errors less than 5%, allowed the gel production process to be effectively monitored. As shown in this work, the NIRS technique is a highly suitable tool for process analytical technology.

On-line monitoring of a granulation process by NIR spectroscopy.

Near infrared (NIR) spectroscopy has been used in a noninvasively mode to develop qualitative and quantitative methods for the monitoring of a wet granulation process. The formulation contained API (10%w/w) and microcrystalline cellulose and maize starch as main excipients. NIR spectra have been acquired through the glass window of the fluidizer in reflectance mode without causing interference to neither the process nor the formulation. The spectral data has been used to develop a qualitative multivariate model based on principal component analysis (PCA). This qualitative model allows the monitoring of different steps during the granulation process only using the spectral data. Also, a quantitative calibration model based on partial least squares (PLS) methodology has been obtained to predict relevant parameters of the process, such as the moisture content, particle size distribution, and bulk density. The methodology for data acquisition, calibration modeling and method application is relatively low-cost and can be easily performed on most of the pharmaceutical sites. Based on the results, the proposed strategy provides excellent results for the monitoring of granulation processes in the pharmaceutical industry.