Publications by authors named "Juan G Rosas"

We implement a fully integrated continuous manufacturing (CM) line for direct compression and coating of a pharmaceutical oral solid dosage form in a commercial production facility. In this first paper of a two-part series, we describe process design and operational choices made to introduce CM using infrastructure originally intended for batch operations. Consistent with lean manufacturing principles, we select equipment, facilities, and novel process analytical technologies that meet production agility goals alongside an existing batch process.

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This is the second of two articles detailing the continuous manufacturing (CM) development and implementation activities for an marketed product which have been realized in novel, qualified equipment, using validated control strategy elements to enable manufacture of batches under current good manufacturing practices (cGMP) and compliant with data integrity principles. Here, the application of process analytical technologies (PAT) and automation tools on batches produced under normal operational conditions is reviewed. The results from residence time distribution (RTD) models for predicting API concentration, in-line near infrared (NIR) testing of blend uniformity (BU) and at-line NIR spectroscopy analysis of core tablet concentration and tablet identity for real-time release testing (RTRT) are discussed.

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Freeze drying is a complex, time consuming and thus expensive process, hence creating a need for understanding the material behaviour in the process environment and for process optimization. Near-infrared (NIR) spectroscopy offers the opportunity to monitor physicochemical changes of the formulation during freeze-drying. The aim of this work was to examine whether NIR spectroscopy allows in-line monitoring of all components during the entire freeze-drying process of a multi-component pharmaceutical formulation (a solution of fenofibrate and mannitol in a mixture of tertiary-butyl alcohol, and water).

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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).

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This article is the second of a series of two articles detailing the application of mixing index to assess homogeneity distribution in oral pharmaceutical solid dosage forms by image analysis. Chemical imaging (CI) is an emerging technique integrating conventional imaging and spectroscopic techniques with a view to obtaining spatial and spectral information from a sample. Near infrared chemical imaging (NIR-CI) has proved an excellent analytical tool for extracting high-quality information from sample surfaces.

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The Process Analytical Technologies (PAT) initiative of the US Food and Drug Administration (US FDA) has established a framework for the development of imaging techniques to determine the real-time distribution of mixture components during the production of solid dosage forms. This study, which is the first in a series of two parts, uses existing mixing indices and a new criterion called the "percentage of homogeneity" (H%) to assess image homogeneity. Image analysis techniques use feature extraction procedures to extract information from images subjected to treatments including colour segmentation and binarization.

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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.

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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).

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