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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. Choices address process risks, are aligned with existing quality systems, yet allow exploration of CM agility benefits in commercial operations. We outline how operating procedures, control schemes, and release criteria from the historical batch process are adapted for CM with modified lot and yield definitions based on patient demand. We devise a hierarchy of complementary controls including real-time process interrogation, predictive residence time distribution models of tablet concentration, real-time product release testing using automated tablet NIR spectroscopy, active rejection and diversion, and throughput-based sampling. Results from lots produced under normal operational conditions confirm our CM process provides assurance of product quality. Qualification strategies to achieve lot size flexibility aims are also described. Finally, we consider CM extensions to formulations with differing risk profiles. Further analysis of results for lots produced under normal operational conditions is provided in part 2 (Rosas et al., 2023)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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. The influences of process equipment and design choices on NIR and RTD model variability, as well as the use of the PAT tools for monitoring the evolving properties understanding of CM process development, such as overcoming flow instabilities, is described. Results demonstrate that the RTD and NIR models developed and validated are robust to operating conditions and are critical for assuring steady state control of the continuous manufacturing process. Finally, the NIR and RTD model lifecycle, including procedures for necessary and normal model upgrades in a cGMP production environment, are presented., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Changes in consumer demand due to preferences for a healthier lifestyle have led to a new market offering fruit and salad products ready to eat. This affects the agro-industrial sector and the characteristic of waste streams generated having the organic fraction higher quality and representing a new opportunity of valorisation. This study experimentally evaluated the digestion of wastes derived from the fourth range product sector. It was also proposed the use of this digestate as a fermentation medium for producing plant growth-promoting cultures. Three digestion scenarios were studied: Scenario 1 considered biogas valorisation using a combined heat and power (CHP) unit. Scenario 2 featured biogas upgrading to be used as vehicle fuel. Finally, scenario 3 evaluated the transport of waste materials to the digestion plant by a network of pipes and pumps directly from the production chain. All three scenarios included the land application of a biostimulator based on the production of a plant growth-promoting culture derived from digestate. Life cycle analysis and life cycle costing were used to determine potential environmental impacts and costs over a lifetime of 25 years. The study showed that scenario 1 was the most favourable option for valorising this type of waste, although the economic assessment resulted in negative values for all three alternatives.

Fat waste discarded from butcheries was used as a cosubstrate in the anaerobic codigestion of sewage sludge (SS). The process was evaluated under mesophilic and thermophilic conditions. The codigestion was successfully attained despite some inhibitory stages initially present that had their origin in the accumulation of volatile fatty acids (VFA) and adsorption of long-chain fatty acids (LCFA). The addition of a fat waste improved digestion stability and increased biogas yields thanks to the higher organic loading rate (OLR) applied to the reactors. However, thermophilic digestion was characterized by an effluent of poor quality and high VFA content. Results from spectroscopic analysis suggested the adsorption of lipid components onto the anaerobic biomass, thus disturbing the complete degradation of substrate during the treatment. The formation of fatty aggregates in the thermophilic reactor prevented process failure by avoiding the exposure of biomass to the toxic effect of high LCFA concentrations.

Background: In outbreak settings, mass vaccination strategies could maximize health protection of military personnel. Self-administration of live attenuated influenza vaccine (LAIV) may be a means to vaccinate large numbers of people and achieve deployment readiness while sparing the use of human resources., Methods: A phase IV, open-label, randomized controlled trial evaluating the immunogenicity and acceptance of self-administered (SA) LAIV was conducted from 2012 to 2014. SA subjects were randomized to either individual self-administration or self-administration in a group setting. Control randomized subjects received healthcare worker-administered (HCWA) LAIV. Anti-hemagglutinin (HAI) antibody concentrations were measured pre- and post-vaccination. The primary endpoint was immunogenicity non-inferiority between SA and HCWA groups. Subjects were surveyed on preferred administration method., Results: A total of 1077 subjects consented and were randomized (529 SA, 548 HCWA). Subject characteristics were very similar between groups, though SA subjects were younger, more likely to be white and on active duty. The per-protocol analysis included 1024 subjects (501 SA, 523 HCWA). Post-vaccination geometric mean titers by vaccine strain and by study group (HCWA vs. SA) were: A/H1N1 (45.8 vs. 48.7, respectively; p=0.43), A/H3N2 (45.5 vs. 46.4; p=0.80), B/Yamagata (17.2 vs. 17.8; p=0.55). Seroresponses to A components were high (∼67%), while seroresponses to B components were lower (∼25%). Seroresponse did not differ by administration method. Baseline preference for administration method was similar between groups, with the majority in each group expressing no preference. At follow-up, the majority (64%) of SA subjects preferred SA vaccine., Conclusions: LAIV immunogenicity was similar for HCWA and SA vaccines. SA was well-tolerated and preferred to HCWA among those who performed SA., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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). To extract useful information of all components in the formulation from the large multivariate data-sets obtained during in-line spectroscopic monitoring, several spectral pre-processing techniques and spectral data analysis techniques such as the mean of selected wavenumbers (Mws), the correlation coefficient (CorrCoef) and principal component analysis (PCA) have been evaluated and compared. To find out whether these chemometric techniques are also able to differentiate between changes in the process settings influencing the freeze-drying process of the formulation, freeze-drying processes were performed at four different conditions. Results demonstrated that in-line measurements using NIR spectroscopy were possible in an icy environment and that a further process understanding could be obtained. Data-analysis revealed the crystallization behaviour of each of the four components. In addition, using the three pre-processing techniques allowed observe the sublimation of the solvents. Mws and CorrCoef have proven to be adequate methods for monitoring the main physicochemical changes of product during the processes; this affirmation was confirmed by observing the outputs of PCA for entire processes., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Determining homogeneity of a mixture using hyperspectral-imaging (HSI) techniques is at this moment an interesting research subject in pharmaceutical industry. A new methodology based in the macropixel analysis technique for the homogeneity assessment in powder blend mixtures has been developed. The appropriate selection of the macropixel size for evaluation of the homogeneity is a topic under discussion. We propose that the macropixel size selection would be based in a statistical criterion called "representative sample size" criterion. Moreover, it has been demonstrated that the macropixel size should be a function of the particle size and, thus, the particle size has been included in the formula to calculate the macropixel size. The proposed equations allow to accurately calculate the homogeneity index (H% Poole). By means of using simulated chemical images, a relationship between the H% Poole index and the controlled homogeneity was established. The method has been applied to determine the homogeneity of binary and ternary powder blends mixtures of different pharmaceuticals discriminating between homogeneous and non-homogeneous samples., (Copyright © 2013 Elsevier B.V. All rights reserved.)

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. The primary objective of this second part was to demonstrate that the approach developed in the first part could be successfully applied to near infrared hyperspectral images of oral pharmaceutical solid dosage forms such as coated, uncoated and effervescent tablets, as well as to powder blends. To this end, we assessed a new criterion for establishing mixing homogeneity by using four different methods based on a three-dimensional (M×N×λ) data array of hyperspectral images (spectral standard deviations and correlation coefficients) or a two-dimensional (M×N) data array (concentration maps and binary images). The four methods were used applying macropixel analysis to the Poole (M(P)) and homogeneity (H%(Poole)) indices. Both indices proved useful for assessing the degree of homogeneity of pharmaceutical samples. The results testify that the proposed approach can be effectively used in the pharmaceutical industry, in the finished products (e.g., tablets) and in mixing unit operations for example, as a process analytical technology tool for the blending monitoring (see part 1)., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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. The surface distribution of components was determined by macropixel analysis, which splits an image into non-overlapping blocks of a preset size and calculates several statistical parameters for the resulting divisional structure. Such parameters were used to compute mixing indices. In this work, we explored the potential of image processing in combination with mixing indices and H% for assessing blending end-point and component distribution on images. As a simplified test, an arrangement of binary and ternary systems of coloured particles was mixed collecting at-line multispectral (MSI) and non-invasive RGB pictures at preset intervals., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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., (Copyright © 2011 Wiley-Liss, Inc.)

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., (Copyright © 2011 Wiley-Liss, Inc.)

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations.