Near-Infrared Spectroscopy for the In-Line Characterization of Powder Voiding Part II: Quantification of Enhanced Flow Properties of Surface Modified Active Pharmaceutical Ingredients

Method transfer of a near-infrared spectroscopic method for blend uniformity in a poorly flowing and hygroscopic blend

The challenges in transferring and executing a near-infrared (NIR) spectroscopic method for croscarmellose (disintegrant) in binary blends for a continuous manufacturing (CM) process are presented. This work demonstrates the development of a NIR calibration model and its use to determine the blending parameters needed for binary blends at a development plant and later used to predict CM process blends. The calibration models were developed with laboratory scale powder blends ranging from 4.32%-64.77 (%w/w) of croscarmellose and evaluated using independent test blends. The selected model was then transferred to the continuous manufacturing development site to determine the croscarmellose concentration for spectra collected in real-time. A total of 18 development plant runs were monitored using an in-line NIR spectrometer, however, these spectra showed high baseline variations. The baseline variations were caused by the poor flow of the material within the system. An inconsistent bias which varied from 2.51 to 14.95 (%w/w) was observed in the predictions of croscarmellose. High baseline spectra were eliminated and the bias was significantly reduced by 42-51%. Experiments at lower flow rate speeds did not show significant changes in baseline and bias values showed more consistency. The calibration model was then transferred to two NIR spectrometers installed at-line at the commercial site, where powder samples were collected at the beginning middle and end of each CM plant run. The NIR calibration model predicted disintegrant concentration from the powder samples. Results showed the bias values for the NIR (1) varied from 0.74 to 2.21 (%w/w) and NIR (2) from 0.28 to 3.39 (%w/w). Average concentration values for both equipments were very close to the reference concentration values of 43.18 and 50.98 (%w/w). The study showed the model was able to identify flow issues, identified as baseline shifts, that could be used to alert to problems in the powder bed that may warrant diversion from a production line. These powder flow problems such as air gaps and inconsistent powder bed height affected the NIR spectra collected at the development plant and provided results with high bias. A lower bias was obtained in samples collected at line after blending.

A sampling system for flowing powders based on the theory of sampling

An innovative chute and stream sampler system for flowing powders has been developed and tested. The system is designed for representative sampling based on the principles of the Theory of Sampling (TOS). The sampling system was used in combination with near infrared (NIR) spectroscopy to determine the drug concentration of flowing powders. The system is comprised of three parts: a chute, a stream sampler and a sample collection port. The NIR spectra were obtained at the chute, before entering the sampler, and as the powder flowed through the stream sampler. Samples were also collected from the sample collection port to be analyzed using an ultraviolet-visible (UV-Vis) reference method to determine drug content. A total of eight pharmaceutical powder blends, ranging in concentration from 10.5(%w/w) to 19.5(%w/w) of caffeine, were used to test the sampling system. Materials were characterized before blends were made to provide information on flow properties. The throughput of the system was between 30 and 35 kg/h based on the flow properties of the blend. Drug concentration was effectively determined at the chute and stream sampler. The NIR calibration models showed low root mean squared errors of prediction, 0.65(%w/w) and 0.51(%w/w), for the chute and stream sampler respectively. The NIR calibration models also showed low bias values -0.36(%w/w) at the chute and 0.057(%w/w) at the stream sampler. Significant agreement was obtained between the results from the nondestructive NIR versus the destructive UV-Vis method. Variographic analysis was performed to estimate the analytical and sampling errors when determining the drug concentration at the chute and stream sampler respectively. The variographic analysis showed low analytical errors, 0.103(%w/w)² and 0.181(%w/w)² at the chute and stream sampler respectively. The analysis also showed that the minimum practical error (MPE) was around 0.2(%w/w)² at both chute and stream sampler.

Surface modification of acetaminophen particles by atomic layer deposition

Active pharmaceutical ingredients (APIs) are predominantly organic solid powders. Due to their bulk properties many APIs require processing to improve pharmaceutical formulation and manufacturing in the preparation for various drug dosage forms. Improved powder flow and protection of the APIs are often anticipated characteristics in pharmaceutical manufacturing. In this work, we have modified acetaminophen particles with atomic layer deposition (ALD) by conformal nanometer scale coatings in a one-step coating process. According to the results, ALD, utilizing common chemistries for Al₂O₃, TiO₂ and ZnO, is shown to be a promising coating method for solid pharmaceutical powders. Acetaminophen does not undergo degradation during the ALD coating process and maintains its stable polymorphic structure. Acetaminophen with nanometer scale ALD coatings shows slowed drug release. ALD TiO₂ coated acetaminophen particles show cytocompatibility whereas those coated with thicker ZnO coatings exhibit the most cytotoxicity among the ALD materials under study when assessed in vitro by their effect on intestinal Caco-2 cells.

Near Infrared Spectroscopy: From Feasibility to Implementation in the Pharmaceutical Industry

Near infrared (NIR) spectroscopy will play an increasingly important role in pharmaceutical processes as the quality of pharmaceutical products is progressively defined on the basis of their performance and pharmaceutical quality control is transformed to meet this challenge. This new quality control will require a thorough understanding of the sources of error in NIR methods, an understanding that starts with fundamentals such as the physics of diffuse reflectance and the Theory of Sampling, and progresses to working with pharmaceutical engineers to implement online predictions and control of pharmaceutical operations. This article outlines the research areas that need to be integrated to advance the implementation of NIR spectroscopy in the pharmaceutical industry.