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The traditional paradigm for pharmaceutical manufacturing is focused primarily upon centralized facilities that enable mass production and distribution. While this system reliably maintains high product quality and reproducibility, its rigidity imposes limitations upon new manufacturing innovations that could improve efficiency and support supply chain resiliency. Agile manufacturing methodologies, which leverage flexibility through portability and decentralization, allow manufacturers to respond to patient needs on demand and present a potential solution to enable timely access to critical medicines. Agile approaches are particularly applicable to the production of small-batch, personalized therapies, which must be customized for each individual patient close to the point-of-care. However, despite significant progress in the advancement of agile-enabling technologies across several different industries, there are substantial global regulatory challenges that encumber the adoption of agile manufacturing techniques in the pharmaceutical industry. This review provides an overview of regulatory barriers as well as emerging opportunities to facilitate the use of agile manufacturing for the production of pharmaceutical products. Future-oriented approaches for incorporating agile methodologies within the global regulatory framework are also proposed. Collaboration between regulators and manufacturers to cohesively navigate the regulatory waters is ultimately needed to best serve patients in the rapidly-changing healthcare environment.

Accurate and reliable feeding of small quantities of powder is crucial in many industries. It is particularly true in the case of pharmaceutical manufacturing. First, the exact dosage of highly potent active pharmaceutical ingredients (APIs) is essential. Second, due to the shift towards continuous manufacturing, processing agents must be supplied continuously. Last, with regard to personalized medicine products, small doses of API have to be processed with high flexibility. In all these applications, a few grams of powder or less per hour have to be fed, which makes processing very challenging. The common route of pre-blending causes additional effort in processing and quality control compared to direct continuous feeding, while material properties influence the performance of conventional feeders with conveying screw elements. In this study, a novel micro-feeding system based on active volumetric displacement is investigated and compared to commercial LIW feeders of various scales. In the micro-feeder, the powder is filled into a cylindrical cartridge and pushed towards the process by a piston in a controlled manner. Tests are carried out with a free-flowing grade of lactose and croscarmellose sodium as an example of cohesive powder. At feed rates of a few grams per hour, for the investigated materials, the system has at least the same performance as conventional feeders at significantly higher feed rates. Especially at low feed rates, less fluctuations are obvious and accuracy and precision of the micro-feeder are at the same level as for the established feeding technology at rates ten times higher. For the two types of investigated materials (free-flowing and cohesive), the micro-feeding system shows similar or better performance than conventional and commercially applied LIW feeders. The technology offers the potential for highly accurate, continuous feeding in the low-dose range.

In pharmaceutical manufacturing, dissolution test for immediate-release dosage forms is routinely performed to ensure the drug products conform to the quality standard specified in the United State...

To review the good documentation practices in the pharmaceutical industry as per the guidelines provided in the European Commission and WHO (World Health Organisation). GDocP is a systematic method of planning, evaluating, approving, issuing, documenting, preserving, and archiving records. GDocP is a must when operating in an atmosphere of existing GMP. To provide an overview of good documentation practices for those employed in the pharmaceutical and healthcare sectors. The GDocP stands for good documentation practice which can be described as an integral part of quality assurance (QA) and thus related to all aspects of GMP. There are very few articles related to the comparison of GDocP in the pharmaceutical manufacturing unit as per European and WHO guidelines hence we are trying to develop a study on the comparison of GDocP guidelines. Public and private organizations, institutions, and regulatory authorities working and cooperating and with the pharmaceutical industry are involved at the international and national level to reach a consensus on the guidelines and laws for the production of medicinal products for human. This article explains how these participants work and cooperate and set out current regulations along the lines of the European community and WHO referencing, where appropriate, the practiced guidelines, outside space regulatory action referred to above. In this way, the goal is to achieve exceptional standards of quality, protection, and efficacy in the manufacture of health products.

Biopharmaceuticals commonly require freezing to ensure the stability of the active pharmaceutical ingredients (APIs). At commercial scale, freezing is typically carried out over the course of days in pallets comprising tens of thousands of vials. The selected process conditions have to ensure both complete freezing in all vials and a satisfactory manufacturing throughput. Current process design, however, is mainly experimental, since no mechanistic understanding of pallet freezing and its underlying phenomena has been achieved so far. Within this work, we derive a mechanistic modeling framework and compare the model predictions with engineering run data from the Janssen COVID-19 vaccine. The model qualitatively reproduced all observed trends and reveals that stochastic ice nucleation governs both process duration and batch heterogeneity. Knowledge on the ice nucleation kinetics of the formulation to be frozen thus is required to identify suitable freezing process conditions. The findings of this work pave the way towards a more rational design of pallet freezing, from which a plethora of frozen drug products may benefit. For this reason, we provide open source access to the model in the form of a python package (Deck et al., 2021)., International Journal of Pharmaceutics, 625, ISSN:0378-5173, ISSN:1873-3476, ISSN:0378 -5173

Hot Melt Extrusion (HME) is a continuous pharmaceutical manufacturing process that has been extensively investigated for solubility improvement and taste masking of active pharmaceutical ingredients. Recently, it is being explored for its application in 3D printing. 3D printing of pharmaceuticals allows flexibility of dosage form design, customization of dosage form for personalized therapy and the possibility of complex designs with the inclusion of multiple actives in a single unit dosage form. Fused Deposition Modeling (FDM) is a 3D printing technique with a variety of applications in pharmaceutical dosage form development. FDM process requires a polymer filament as the starting material that can be obtained by hot melt extrusion. Recent reports suggest enormous applications of a combination of hot melt extrusion and FDM technology in 3D printing of pharmaceuticals and need to be investigated further. This review in detail describes the HME process, along with its application in 3D printing. The review also summarizes the published reports on the application of HME coupled with 3D printing technology in drug delivery.

The crystallization of peptides offers a sustainable and inexpensive alternative to the purification process. In this study, diglycine was crystallised in porous silica, showing the porous templates’ positive yet discriminating effect. The diglycine induction time was reduced by five-fold and three-fold upon crystallising in the presence of silica with pore sizes of 6 nm and 10 nm, respectively. The diglycine induction time had a direct relationship with the silica pore size. The stable form (α-form) of diglycine was crystallised in the presence of porous silica, with the diglycine crystals obtained associated with the silica particles. Further, we studied the mechanical properties of diglycine tablets for their tabletability, compactability, and compressibility. The mechanical properties of the diglycine tablets were similar to those of pure MCC, even with the presence of diglycine crystals in the tablets. The diffusion studies of the tablets using the dialysis membrane presented an extended release of diglycine through the dialysis membrane, confirming that the peptide crystal can be used for oral formulation. Hence, the crystallization of peptides preserved their mechanical and pharmacological properties. More data on different peptides can help us produce oral formulation peptides faster than usual.

Objectives The aim of this study was to couple fused deposition modelling 3D printing with melt extrusion technology to produce core–shell-structured controlled-release tablets with dual-mechanism drug-release performance in a simulated intestinal fluid medium. Coupling abovementioned technologies for personalized drug delivery can improve access to complex dosage formulations at a reasonable cost. Compared with traditional pharmaceutical manufacturing, this should facilitate the following: (1) the ability to manipulate drug release by adjusting structures, (2) enhanced solubility and bioavailability of poorly water-soluble drugs and (3) on-demand production of more complex structured dosages for personalized treatment. Methods Acetaminophen was the model drug and the extrusion process was evaluated by a series of physicochemical characterizations. The geometries, morphologies, and in vitro drug-release performances were compared between directly compressed and 3D-printed tablets. Key findings Initially, 3D-printed tablets released acetaminophen more rapidly than directly compressed tablets. Drug release became constant and steady after a pre-determined time. Thus, rapid effectiveness was ensured by an initially fast acetaminophen release and an extended therapeutic effect was achieved by stabilizing drug release. Conclusions The favourable drug-release profiles of 3D-printed tablets demonstrated the advantage of coupling HME with 3D printing technology to produce personalized dosage formulations.

Optimized physical properties (e.g., bulk, surface/interfacial, and mechanical properties) of active pharmaceutical ingredients (APIs) are key to the successful integration of drug substance and drug product manufacturing, robust drug product manufacturing operations, and ultimately to attaining consistent drug product critical quality attributes. However, an appreciable number of APIs have physical properties that cannot be managed via routes such as form selection, adjustments to the crystallization process parameters, or milling. Approaches to control physical properties in innovative ways offer the possibility of providing additional and unique opportunities to control API physical properties for both batch and continuous drug product manufacturing, ultimately resulting in simplified and more robust pharmaceutical manufacturing processes. Specifically, diverse opportunities to significantly enhance API physical properties are created if allowances are made for generating co-processed APIs by introducing nonactive components (e.g., excipients, additives, carriers) during drug substance manufacturing. The addition of a nonactive coformer during drug substance manufacturing is currently an accepted approach for cocrystals, and it would be beneficial if a similar allowance could be made for other nonactive components with the ability to modify the physical properties of the API. In many cases, co-processed APIs could enable continuous direct compression for small molecules, and longer term, this approach could be leveraged to simplify continuous end-to-end drug substance to drug product manufacturing processes for both small and large molecules. As with any novel technology, the regulatory expectations for co-processed APIs are not yet clearly defined, and this creates challenges for commercial implementation of these technologies by the pharmaceutical industry. The intent of this paper is to highlight the opportunities and growing interest in realizing the benefits of co-processed APIs, exemplified by a body of academic research and industrial examples. This work will highlight reasons why co-processed APIs would best be considered as drug substances from a regulatory perspective and emphasize the areas where regulatory strategies need to be established to allow for commercialization of innovative approaches in this area.

Individualized therapy with pharmaceutical products aims to elicit predictable and optimized treatment responses from specific patients. Doing so requires production platforms and technology capable of tailoring products to individual patient needs. However, despite recent manufacturing innovations and key technologies on the rise, e.g. continuous manufacturing and additive manufacturing (3D printing), the prevailing production paradigm employed in the pharmaceutical industry is mass production. Although mass production is efficient and cost-effective, it is typically based on a 'one-size-fits-all' product concept and lacks the flexibility and agility required to fully meet the needs of the individual patient. Indeed, we present data that confirm a suspected major imbalance between the recent medical evolution underpinning personalized/precision medicine and the recent advances in the associated manufacturing technologies. In this context we target the needs of the individual as a main driver for pharmaceutical products which support individualized therapy. We particularly address that a wider integration of critical patient dimensions into the manufacture and provision of pharmaceutical products is pivotal for enabling a patient-centric and efficient mass customization-based production paradigm. Here, we present a critical review of the area and its inherent challenges which aims to clarify key design requirements for establishing mass customization opportunities. Through primary sources of scientific information for individualized therapies, patient needs are captured, analysed, and conceptualized. This summarized set of key drivers provides the basis for a proposed patient-centric framework of requirements for use in design of product and production platforms for mass customization. The extent to which emerging pharmaceutical manufacturing technologies satisfy key individual patient needs is explored through a high-level assessment against the proposed patient-centric framework, with special attention paid to oral dosage forms. Altogether this holistic review and position paper, with its constituent steps, reveals major gaps in the evolution of Product-Process-Production approaches and solutions required for producing affordable individualized/personalized pharmaceuticals that respond to the needs and demands of the individual patient. Lastly, in a brief commentary and outlook, we suggest key research directions for closing gaps and addressing manufacturing technology challenges. We also articulate the importance of tackling them in a holistic, integrated way, together with challenges in product individualization and personalization.

Understanding and predicting the flow of bulk pharmaceutical materials could be key in enabling pharmaceutical manufacturing by continuous direct compression (CDC). This study examines whether, by taking powder and bulk measurements, and using statistical modelling, it would be possible to predict the flow of a range of materials likely to be used in CDC. More than 100 materials were selected for study, from four pharmaceutical companies. Particle properties were measured by static image analysis, powder surface area and surface energy techniques, and flow by shear cell measurements. The data was then analysed, and a range of statistical modelling techniques were used to build predictive models for flow. Using the results from static image analysis, a model could be built which allowed the prediction of likely flow in a shear cell, which can be related to performance in a CDC system. Only a small amount of powder was required for the image analysis. Surface area did not add to the precision of the model, and the available surface energy technique did not correlate with flow. A small sample of powder can be examined by static image analysis, and this data can be used to give an early read on likely flow of a material in a CDC system or other pharmaceutical process, allowing early intervention (if necessary) to improve the characteristics of a material, early in development.

Quality by Design (QbD) was originated in the broad domain of Quality Management and was recently adapted and formalized in specific terms for assisting pharmaceutical companies efforts towards market and operational excellence. However, despite some impressive success stories, the pharmaceutical industry have not yet fully embraced QbD, particularly in routine commercial manufacturing (Rantanen and Khinast, 2015; Puñal Peces et al., 2016). In this review, we aim to analyse the current state of implementation of QbD methodologies and tools in the pharmaceutical industry, extracting patterns and trends and identifying gaps and opportunities that may be considered to improve QbD adoption. For this purpose, a critical analysis of 60 research papers was performed, whose contents were classified, compared and summarized at different abstraction levels. Our analysis reveals the following tools as the frequently adopted for conducting each activity: Risk Assessment (RA) - Ishikawa Diagram, Failure Mode and Effects Analysis (FMEA) and Risk Estimation Matrix (REM); Screening Design of Experiments (DoE) - 2-level Full and Fractional Factorial Designs; Optimisation DoE - Central Composite Design (CCD). Emerging trends include the growing interest in quantifying and managing the impact of raw materials' attributes variability on process and product, as well as the development of Retrospective QbD approaches (rQbD) in complement to standard QbD.

Choosing the optimal lot size in drug manufacturing has critical implications for process scheduling and economic performance. There are no rigorous models addressing drug product manufacturing. This work offers a lot-sizing model to avoid empirical decisions for lot resizing at various drug lifecycle phases or for grassroot design of injectable drug product manufacturing. An economic lot-sizing model for manufacturing injectables that included process-specific risks and aspects such as rates of defective products, quality control, and changeover operations was developed. Change-control costs for revalidation required by regulatory authorities in case of lot resizing were also considered. A sensitivity analysis was carried out to determine influential model parameters. Two case studies representing different drug profiles demonstrated the use of the method: (i) an inexpensive injectable filled in an ampule after patent expiry; (ii) a new, expensive injectable product filled in vials. Depending on the drug profile, the controlling factors were found to be different, e.g., overtime production scheduling in case (i) and defective product rates in case (ii). This work highlighted the usefulness of model-based approaches for determining influential parameters, design tradeoffs, and improvement potential. The approach was demonstrated for retrofit and grassroot design cases in pharmaceutical manufacturing.

Since entering graduate school 43 years ago, I have been studying physical pharmaceutics with a focus on the effects of environmental factors on pharmaceutical properties of solid oral dosage forms during the manufacturing process. I have reported on changes in the characteristics of pharmaceutical products during manufacturing processes, such as grinding, mixing, granulation, and tableting owing to complicated phenomena based on chemical reactions or the crystalline polymorphic transitions of bulk drugs and excipients. To develop modern pharmaceutical manufacturing processes based on process analysis technology (PAT) as a next generation good manufacturing practice, real-time monitoring was introduced in these processes using a non-destructive analytical method, such as the near-infrared spectroscopy combined with chemometrics. Many case studies related to the mixing, granulation, tableting, and coating processes involving PAT have been reported. In those studies, I focused on clarifying the physical and chemical mechanism through "design space" representation. Additionally, non-destructive analytical methods, including X-ray computed tomography, audible acoustic emission, Raman spectroscopy, terahertz spectroscopy, and infrared thermal imaging analysis were applied as novel candidate analytical methods to the pharmaceutical process to monitor critical quality attributes. To achieve this purpose in various pharmaceutical dosage forms, I have been attempting the assembly of a modern manufacturing process managed through a "design space" paradigm involving in-line monitoring using novel analytical methods, multivariate analyses, and feed-back systems.

PURPOSE: The International Council for Harmonization (ICH) “Q10 Pharmaceutical Quality Systems” (ICH Q10) guidance was introduced to address the growing gap between current good manufacturing practices and pharmaceutical manufacturing quality systems. This study evaluated the impact of the ICH Q10 guidance on the PQS of pharmaceutical manufacturers. MATERIALS AND METHODS: Data were obtained from the enabler questionnaire from pharmaceutical manufacturers surveyed by the St. Gallen OPEX Benchmarking Program. These results represent the degree of implementation for enabler-focused questions based on a 5-point Likert scale self-assessment. Data analysis included a comparison of means and medians before and after the release of the ICH Q10 guidance and annual changes. RESULTS AND DISCUSSION: There was a statistically significant difference for enabler implementation as a whole (p-value < 0.0000), before and after the release of ICH Q10 Furthermore, statistically significant differences were observed for four of the five enabler categories (p-values

While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA’s support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015 ). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations ( Vanhoorne, 2020 , Rogers and Ierapetritou, 2015 , Tezyk et al., 2015 ) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications ( Kruisz, 2017 , Martinetz, 2018 , Tian, 2021 ). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections – 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.

3D printing is a new emerging technology in the pharmaceutical manufacturing landscape. Its potential advantages for personalized medicine have been widely explored and commented on in the literature over recent years. More recently, the selective laser sintering (SLS) technique has been investigated for oral drug-delivery applications. Thus, this article reviews the work that has been conducted on SLS 3D printing for the preparation of solid oral forms (SOFs) from 2017 to 2020 and discusses the opportunities and challenges for this state-of-the-art technology in precision medicine. Overall, the 14 research articles reviewed report the use of SLS printers equipped with a blue diode laser (445–450 nm). The review highlights that the printability of pharmaceutical materials, although an important aspect for understanding the sintering process has only been properly explored in one article. The modulation of the porosity of printed materials appears to be the most interesting outcome of this technology for pharmaceutical applications. Generally, SLS shows great potential to improve compliance within fragile populations. The inclusion of “Quality by Design” tools in studies could facilitate the deployment of SLS in clinical practice, particularly where Good Manufacturing Practices (GMPs) for 3D-printing processes do not currently exist. Nevertheless, drug stability and powder recycling remain particularly challenging in SLS. These hurdles could be overcome by collaboration between pharmaceutical industries and compounding pharmacies.

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

Process Analytical Technology (PAT) instruments include analyzers capable of measuring physical and chemical process parameters and key attributes with the goal of optimizing process controls. PAT in the form of a probe or sensor is designed to integrate within the pharmaceutical manufacturing line and is coupled with computing equipment to perform chemometric modeling for result interpretation and multilayer statistical control of processes. PAT solutions are intended for understanding bioprocesses with a goal to control quality at all stages of product manufacturing and achieve quality by design (QbD). The goal of PAT implementation is to promote real-time release of products to decrease the cycle time and cost of production. This review focuses on the applications of PAT solutions at different stages of the manufacturing process for vaccine production, the advantages, challenges at present state, and the vision of the future development of biopharmaceutical industries.

It is important to identify, assess, and address current barriers to implementation of post-approval changes that are intended to ensure continued (uninterrupted) operations and drive innovation and continual improvement in a maximally efficient, agile, and flexible pharmaceutical manufacturing sector. Leveraging the International Conference for Harmonisation Quality Guideline Q10 provides regulatory relief when it comes to addressing changes related to excipients, specifically excipient supplier's name and address changes, which will ensure a sustainable, reliable global supply and the availability of high quality product to patients through the entire commercial lifecycle of a product without extensive regulatory oversight.

Three dimensional printing technologies are widely used in medical applications, reflecting the ease of customization and personalization. Hence, applications of 3D printing in pharmaceutical manufacturing may provide variety and complexity of pharmaceutical dosage forms that conventional methods do not. 3D printing can be used to produce individualized drug and dosage forms for future therapeutic application. Herein, we developed a pharmaceutical formulation in the form of a floating controlled drug-release tablet loaded with a metronidazole core using 3D printing. The floating shell or tablet housing was prepared from polyvinylalcohol. Initially, shapes of tablet floating housings were designed and printed in cylinder, sphere and cone shapes. Metronidazole tablet cores were then prepared by direct compression and were assembled into the printed tablet housing. We then examined the effects of shapes of the floating tablet housing, pole sizes for drug release and air volumes for floating. Cylindrical floating tablet housings floated stably at the surface of water. These tablets also floated immediately and for more than 4 h, and drug release was more than 88% after 8 h. Floating tablets with a pore sizes of 2.0 mm and air volumes of 132 mm3 provided zero-order drug release in kinetic investigations, with an r2 value of 0.9661.

There is a current trend in pharmaceutical manufacturing to shift from traditional batch manufacture to continuous manufacturing. The purpose of this study was to test the ability of an integrated continuous direct compression (CDC) line, in relation to batch processing, to achieve consistent tablet quality over long processing periods for formulations with poor flow properties or with a tendency to segregate. The study design included four industrially relevant formulations with different segregation indices and flow properties induced through different grades of the Active Pharmaceutical Ingredient (API), paracetamol, and major filler as well as varying the amount of API. The performance metrics investigated were content, uniformity of content, tablet weight, and tablet strength. The overall process stability over time was significantly improved with the CDC line as compared to the batch process. For all the formulations with a high API content, the CDC line provided better or equal uniformity of content and tablet weight as compared to batch. The CDC line was especially efficient in providing a stable content and tablet weight for poorly flowing formulations containing the standard, cohesive, grade of API. The only formulation that performed better in the batch process was the formulation with a low API content. Thus, for this formulation, the batch process achieved lower variation in tablet content since maintaining a low feed rate for the API proved challenging in the CDC line. In addition, some of the API became stuck in the CDC line between feeding and tableting, most likely at the funnel in the mixer inlet, highlighting the need for properly designed interfaces between units. The insensitivity of the CDC line towards poor flow indicates that one could use direct compression at high drug load compositions of poorly flowing powder blends that could not be processed via batch manufacturing.

In pharmaceutical industries, the quality assessment of emulsions is typically based on subjective examination of these samples under the microscope by trained analysts. The major drawbacks of such manual quality assessment include inter-observer variability, intra-observer variability, lack of speed and poor accuracy. In order to address these challenges, an automated approach, based on machine vision and machine learning, is investigated in this study. Micrographs, obtained during an emulsification process, are classified into four quality-based categories named TAMU (target, acceptable, marginal and unacceptable). A machine learning approach using principal component–based discriminant analysis is employed in this study for the classification. This approach is compared with manual classification results obtained for the same set of micrographs using attribute agreement analysis, which is a methodology of assessing the accuracy and precision of an evaluation system. The automated approach is demonstrated to be repeatable, 40% more accurate compared to the least performing analyst and 10% more accurate than the best performing analyst. The results show that the automated classification is superior to manual classification of micrographs with respect to speed (180 times faster), greater accuracy and repeatability. The automated approach, implemented as a soft sensor, integrated with real-time image acquisition can be applied for in situ process monitoring of emulsions. The real-time approach can be used to predict the instantaneous product quality as well as optimum process time required to achieve the desirable droplet characteristics, which will avoid over-processing and wastage of resources in pharmaceutical industries.

Advanced pharmaceutical manufacturing technologies have the potential to make substantial contributions toward reducing waste, cost, and cycle time. However, the steady introduction of advanced man...

Scholars often associate Operational Excellence (OPEX) enablers with high operational performance. Several studies have concluded that advancing OPEX enablers helps improve organizational performance. This paper aims to better understand the relation between OPEX enablers and a robust quality control lab. Integral to pharmaceutical quality systems, robust quality control labs ensure effective drug provision to patients. We examine how implementing OPEX enablers in quality control labs contributes to strengthening quality effectiveness a pharmaceutical manufacturing organization. The analysis was based on a database of the University of St.Gallen comprising 53 pharmaceutical quality control labs. An independent t-test and multiple linear regressions were used to study the relation between OPEX enablers and quality control lab effectiveness. The results show that highly effective quality control labs exhibit significantly higher OPEX enabler implementation. Thirty-five percent of the variance in lab performance can be explained by enabler implementation. High OPEX enabler implementation contributes to robust quality control labs achieving high-level quality and service. Organizations thus attain effective and efficient drug release.

Semi-solid extrusion (SSE) 3D printing is an innovative and promising method that is suitable for the fabrication of personalized dosage forms of tablets. The aim of this study is to develop and evaluate the effectiveness of SSE 3D printed tablets with novel internal structures. Twelve types of 3D printed tablets with pre-designed structures were developed. Glipizide was selected as the model drug and three different concentrations of the HPMC K100LV polymer were used in the 3D printing process as the hydrophilic matrix. All of the printed tablets had satisfactory physical properties and structural integrity indicating the suitability of SSE 3D printing for the fabrication of personalized medicines with complex structures. The dissolution profiles of the printed tablets revealed the relationship between novel structures and drug release behavior. Tailored drug release may be easily achieved without changing the prescription by adjusting printing parameters such as outline value, grid width and printing pattern. All results of this paper clearly reveal the feasibility and capability of SSE 3D printing technology as a novel pharmaceutical manufacturing technique to fabricate personalized medicines and modulate drug dissolution profiles.

In this study, easy and robust RP-HPLC method was developed and validated to determine acceptable residual limit of citalopram hydrobromide for cleaning procedures. The United States, Food and Drug Administration has mentioned that the acceptable limit for residues present in the equipment during processing or manufacturing should be based on logical criteria. In present study, acceptable residual limit for cleaning procedure of citalopram hydrobromide was calculated by using three approaches including therapeutic dose method, 10 ppm criteria and visual limit of inspection. The value by erapeutic dose approach was less among three calculated values hence, selected as acceptable residual limit (10.66 µg/25 cm2 ) for analytical method development and validation for the detection of this drug residues on the surfaces of manufacturing equipment. A RP-HPLC assay method was developed using C18 column and mobile phase containing mixture of methanol and ammonium acetate buffer (pH4.6) (70:30) with flow rate of 1.6 ml/min. System suitability parameters like theoretical plates and tailing factor were calculated for the validation of the developed method as per ICH Q2B guidelines. After analyzing recovery study data, it was found that stainless steel plate has minimum recovery (88.87%) and pre-analyzed tablet solution has maximum recovery (99.29%)

Three-dimensional printing (3DP) by fused deposition modeling (FDM) has gained momentum as a promising pharmaceutical manufacturing method due to encouraging forward-looking perspectives in personalized medicine preparation. The current challenges the technology has for applicability in the fabrication of solid dosage forms include the limited range of suitable pharmaceutical grade thermoplastic materials. Hence, it is important to investigate the implications of variable properties of the polymeric carrier on the preparation steps and the final output, as versatile products could be obtained by using the same material. In this study, we highlighted the influence of polyvinyl alcohol (PVA) particle size on the residence time of the mixtures in the extruder during the drug-loaded filament preparation step and the consequent impact on drug release from the 3D printed dosage form. We enhanced filament printability by exploiting the plasticizing potential of the active pharmaceutical ingredient (API) and we explored a channeled tablet model as a design strategy for dissolution facilitating purposes. Our findings disclosed a new perspective regarding material considerations for the preparation of PVA-based solid dosage forms by coupling hot melt extrusion (HME) and FDM-3DP.

Microfluidics (MF) is the science dealing with the behavior, precise control, and manipulation of fluids as well as particles on the scale of tens to hundreds of micrometers. It is also utilized for chemical and biological applications, usually called micro–Total Analysis Systems (mTAS) or Lab-on-a-chip (LOC). MF is a fascinating and capable technology with various superior benefits compared to conventional macro-scale platforms, such as the lesser requirement of sample and reagent volumes, higher sensitivity, low cost, portability, faster processing of samples and potential to be automated and highly integrated to reduce human errors. The concept of transformation of meso to nanoliters using MF technology has shown its potential in the healthcare system for early diagnosis, and personalized medicine. The integrated multifunctional system with parallelization provides a better and faster process control. Minimization of the consumption of fluid makes the technology safer in every aspect of the development process, analysis, and storage. The impressive improvement in patient care and monitoring has led to the commercial motivation of the pharmaceutical industry to develop new drugs and modify existing products with better efficacy and safety in a cost-effective manner using MF technologies. Hence, the present review briefs on the applications of MF technology in the key issues of the drug discovery process, overcoming the limitations of development of analytical procedures and prosperous pharmaceutical manufacturing for novel controlled and targeted release dosage forms to fabricate quality products.

Due to the trend of continuous pharmaceutical manufacturing, twin screw wet granulation (TSWG), a continuous process, has gained increased research interest as a potential substitution of traditional batch granulation processes. Despite the complex nature of TSWG, its mechanisms have been gradually unveiled with the aid of innovative research strategies. This review synthesizes these recent findings to provide a comprehensive and mechanistic understanding of TSWG. We explain the impact of screw profiles (i.e. conveying, kneading, turbine mixing, and screw mixing elements) and process conditions (i.e. screw speed, feed rate, and liquid-to-solid ratio) on TSWG mixing performance and granule growth along the barrel, both of which ultimately affect critical granule attributes such as content uniformity, size distribution, strength, and compaction properties.

In this study, the novel high-speed tablet film coating process in the continuous manufacturing was investigated. The influence of key process variables (inlet air flow rate, inlet air temperature, and suspension spray rate) were investigated using a Box-Behnken experimental design method. Statistical regression models were developed to predict the outlet air temperature and relative humidity, the coating efficiency, the tablet moisture content, and coating uniformity. The effects of the three key process variables were comprehensively investigated based on mathematical analysis, contour plots, and interaction plots. The results indicate that all the process responses are affected by changing the inlet air flow rate, temperature, and suspension spray rate. A design space (DS) in terms of failure probability was determined based on specifications for tablet moisture content (

Three-dimensional (3D) printing is an innovative additive manufacturing technology, capable of fabricating unique structures s in a layer-by-layer manner. Semi-solid extrusion (SSE) is a subset of material extrusion 3D printing, and through the sequential deposition of layers of gel or paste creates objects of any desired size and shape. In comparison to other extrusion-based technologies, SSE 3D printing employs low printing temperatures which makes it suitable for drug delivery and biomedical applications, and the use of disposable syringes provides benefits in meeting critical quality requirements for pharmaceutical use. Besides pharmaceutical manufacturing, SSE 3D printing has attracted increasing attention in the field of bioelectronics, particularly in the manufacture of biosensors capable of measuring physiological parameters or as a means to trigger drug release from medical devices. This review begins by highlighting the major printing process parameters and material properties that influence the feasibility of transforming a 3D design into a 3D object, and follows with a discussion on the current SSE 3D printing developments and their applications in the fields of pharmaceutics, bioprinting and bioelectronics. Finally, the advantages and limitations of this technology are explored, before focusing on its potential clinical applications and suitability for preparing personalised medicines.

The goal of this paper is to give an introduction to analysis of images acquired by a digital camera with visible illumination and to review its applications as a Process Analytical Technology (PAT) which has great potential in pharmaceutical manufacturing. By utilizing in-line analytical techniques, it is possible to monitor the quality of all the material leaving a processing unit and to create models capable to predict product quality attributes, which are otherwise measured by cumbersome off-line techniques. The rapidly developing machine vision has proven its versatility in numerous applications and it has great potential as an in-line analytical tool. The ongoing conversion of the pharmaceutical industry from batch to continuous manufacturing accelerated the development of digital image analysis methods in the last decade. Among numerous other benefits, continuous technologies, equipped with digital image analysis, enable detecting disturbances in the material flow, and analyzing the products comprehensively. The purpose of this work is to give an insight into the currently available image analysis methods in the characterization of powders, crystallization, granulation, milling, mixing, tableting, film coating, in vitro dissolution testing, and residence time distribution measurements by highlighting some of the most relevant examples of application.

Pharmaceutical manufacturing is facing the greatest ideological revolution since industrial drug manufacturing. Drugs have been traditionally manufactured in batch mode, but now, continuous manufacturing has started to gain serious interest in the pharmaceutical industry. [...]

Lyophilization modeling is well documented in academic circles but has not yet been widely adopted by pharmaceutical manufacturing companies. To facilitate wider adoption and implementation, an accessible ExcelTM-based tool is provided, presenting several fresh examples as a practical introduction to the process of modeling the primary drying phase. Case studies are presented of the tool's application during process development and scale up which highlight business benefits that have been realized by using the model. The authors and contributors are members of the BioPhorum's Lyophilization Workstream and represent several pharmaceutical companies. The current manuscript is intended to serve as a pathway to not only share the collective knowledge on the topic but also accelerate its adoption in the industry.

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.

During pharmaceutical manufacturing, line-scan hyperspectral imaging enables us to collect several electromagnetic spectra at each pixel in a two-dimensional plane for each tablet. The present study quantitatively determines two independent values of the active pharmaceutical ingredient (API) content in a tablet and the amount of coating on a surface of the same tablet simultaneously; the process is visualized by means of a near-infrared hyperspectral imaging (NIR-HSI) system combined with multivariate data analysis at a typical manufacturing speed of 4,000 tablets per minute. The API content and the amount of coating were controlled to be in the range 80–120% and 0–7 mg, respectively. The results of the cross validation of regression models demonstrated a coefficient of determination (R2) of 0.942, a root-mean-square error of cross validation (RMSECV) of 3.48% for the API content, an R2 of 0.939, and an RMSECV of 0.46 mg for the amount of coating. These results demonstrated that the API content in a tablet as well as the amount of coating on the surface of the same tablet can be simultaneously determined with sufficient accuracy. This technique is practically applicable to process analytical technology in pharmaceutical manufacturing.

The 3D printing is considered as an emerging digitized technology that could act as a key driving factor for the future advancement and precise manufacturing of personalized dosage forms, regenerative medicine, prosthesis and implantable medical devices. Tailoring the size, shape and drug release profile from various drug delivery systems can be beneficial for special populations such as paediatrics, pregnant women and geriatrics with unique or changing medical needs. This review summarizes various types of 3D printing technologies with advantages and limitations particularly in the area of pharmaceutical research. The applications of 3D printing in tablets, films, liquids, gastroretentive, colon, transdermal and intrauterine drug delivery systems as well as medical devices have been briefed. Due to the novelty and distinct features, 3D printing has the inherent capacity to solve many formulation and drug delivery challenges, which are frequently associated with poorly aqueous soluble drugs. Recent approval of Spritam® and publication of USFDA technical guidance on additive manufacturing related to medical devices has led to an extensive research in various field of drug delivery systems and bioengineering. The 3D printing technology could be successfully implemented from pre-clinical phase to first-in-human trials as well as on-site production of customized formulation at the point of care having excellent dose flexibility. Advent of innovative 3D printing machineries with built-in flexibility and quality with the introduction of new regulatory guidelines would rapidly integrate and revolutionize conventional pharmaceutical manufacturing sector.

In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.

DISCLOSURES: No funding supported the writing of this article. The author has nothing to disclosed.

Nanomedicine is a rapidly emerging field with several breakthroughs in the therapeutic drug delivery application. The unique properties of the nanoscale delivery systems offer huge advantages to their payload such as solubilization, increased bioavailability, and improved pharmacokinetics with an overall goal of enhanced therapeutic index. Nanomedicine has the potential for integrating and enabling new therapeutic modalities. Several nanoparticle-based drug delivery systems have been granted approval for clinical use based on their outstanding clinical outcomes. Nanomedicine faces several challenges that hinder the realization of its full potential. In this review, we discuss the critical formulation- and biological-related quality features that significantly influence the performance of nanoparticulate systems in vivo. We also discuss the quality-by-design approach in the pharmaceutical manufacturing and its implementation in the nanomedicine. A deep understanding of these nanomedicine quality checkpoints and a systematic design that takes them into consideration will hopefully expedite the clinical translation process. Graphical abstract.

Progress in continuous flow chemistry over the past two decades has facilitated significant developments in the flow synthesis of a wide variety of Active Pharmaceutical Ingredients (APIs), the foundation of Continuous Pharmaceutical Manufacturing (CPM), which has gained interest for its potential to reduce material usage, energy and costs and the ability to access novel processing windows that would be otherwise hazardous if operated via traditional batch techniques. Design space investigation of manufacturing processes is a useful task in elucidating attainable regions of process performance and product quality attributes that can allow insight into process design and optimization prior to costly experimental campaigns and pilot plant studies. This study discusses recent demonstrations from the literature on design space investigation and visualization for continuous API production and highlights attainable regions of recoveries, material efficiencies, flowsheet complexity and cost components for upstream (reaction + separation) via modeling, simulation and nonlinear optimization, providing insight into optimal CPM operation.

The present paper reports the first monitoring and control of ultra-low dose powder feeding using a camera image-based mass flow measurement system. Caffeine was fed via a single-screw microfeeder as a model active pharmaceutical ingredient (API). The mass, mass flow and sizes of the particles were successfully monitored in real-time by the developed videometric system consisting of a high-speed process camera coupled with an image analysis software. The system was also tested in feedback control mode to automatically reach the desired mass flow values by adjusting the feeder speed based on the mass flow measured by the image analysis system. Based on these features, the developed videometric system can serve as a multi-purpose PAT-tool and can provide valuable real-time information about the process which is indispensable for modern continuous pharmaceutical manufacturing.

Three dimensional (3D) printing as an advanced manufacturing technology is progressing to be established in the pharmaceutical industry to overcome the traditional manufacturing regime of 'one size fits for all'. Using 3D printing, it is possible to design and develop complex dosage forms that can be suitable for tuning drug release. Polymers are the key materials that are necessary for 3D printing. Among all 3D printing processes, extrusion-based (both fused deposition modeling (FDM) and pressure-assisted microsyringe (PAM)) 3D printing is well researched for pharmaceutical manufacturing. It is important to understand which polymers are suitable for extrusion-based 3D printing of pharmaceuticals and how their properties, as well as the behavior of polymer−active pharmaceutical ingredient (API) combinations, impact the printing process. Especially, understanding the rheology of the polymer and API−polymer mixtures is necessary for successful 3D printing of dosage forms or printed structures. This review has summarized a holistic materials−process perspective for polymers on extrusion-based 3D printing. The main focus herein will be both FDM and PAM 3D printing processes. It elaborates the discussion on the comparison of 3D printing with the traditional direct compression process, the necessity of rheology, and the characterization techniques required for the printed structure, drug, and excipients. The current technological challenges, regulatory aspects, and the direction toward which the technology is moving, especially for personalized pharmaceuticals and multi-drug printing, are also briefly discussed.

For continuous pharmaceutical manufacturing of oral solid dosages, it is essential that product quality is measured inline. In this application, a continuous rotary tablet press is used. The goal is a model-based assessment of the quality of the blend in the feed frame to determine whether the concentration of the active pharmaceutical ingredient (API) will be within the prescribed limits. This is to achieve a better quality assurance than by offline testing of a small sample of tablets. In this way, product quality for real-time release (RTR) could be implemented. With a near-infrared (NIR) probe, the concentration of the API in the feed chute and the feed-frame were measured, as well as the API concentration of the tablets by an offline NIR measurement. These different data sets are connected and used for the residence time distribution characterization of the mixing dynamic of the tablet press. A residence time distribution model is fitted to the data, and is further used to compute the lead-lag time. This yields information on how long it takes for a quantity of product to go from being measured in the feed frame until ending up in tablets. Further, it gives information on the occurrence of mixing in the feed-frame itself. These models allow making accurate predictions of whether tablets fall within specified concentration range in real-time. The real-time prediction can be used in combination with a control system both to maintain the quality of the blend as well as to know which tablets to discard. This real-time quality assurance will lead to less material waste and fewer declined batches of tablets.

The implementation of continuous processing technologies for pharmaceutical manufacturing has increased due to its potential to enhance supply chain flexibility, reduce the footprint of the manufacturing facility, and deliver more consistent quality. Additionally, it facilitates extensive, real-time monitoring by sensors and process analytical technology (PAT) tools without perturbing the process. In the presented case study, the use of multivariate tools for the real-time monitoring and retrospective review of a continuous active pharmaceutical ingredient (API) synthesis was evaluated from process development through to commercialization. A multivariate statistical process monitoring (MSPM) approach summarizing variability in both quality critical (controlled flow rates, temperatures) and non-quality critical parameters (pressures, pump speeds, conductivity) was used to monitor three telescoped chemistry stages of a continuous API synthesis. Four different modeling strategies were presented addressing specific monitoring and analysis requirements during the pharmaceutical development lifecycle. During development (R&D and commercial facility), the implemented multivariate monitoring resulted in the identification of potential failure modes, a deeper understanding of the natural process variability and accelerated root cause analysis for a recurrent reagent blockage. During manufacturing (commercial facility), the multivariate tool confirmed potential for predictive maintenance and early fault detection. While the implemented control strategy based on parametric control and offline analytical testing provided the required quality assurance, the multivariate trends provided additional information on process performance. More specifically, they enabled more detailed process understanding during the development of the continuous API synthesis following quality by design (QbD) principles and demonstrated the potential for enhanced process performance during commercial manufacturing.

During continuous manufacturing, there may be some out of specification tablets that need to be diverted in real time, in order to ensure the quality of the final product. Specifically, the content uniformity of each tablet must be guaranteed before it can be released to market. However, currently, no methods or tools are available that can assure the content uniformity and divert the non-confirming products in real time. The aim of this work is to develop and evaluate a strategy to divert the non-confirming tablets in real time and thereby assure drug concentration of final tablets. This work has been conducted in silico using a combination of MATLAB and Simulink. A methodology to implement a residence time distribution (RTD)-based control system for drug concentration-based tablet diversion which uses the convolution integral was developed and implemented in MATLAB. Comparisons between the performance of “fixed window” and “RTD-based” approaches for diversion have also been presented and used to assess optimal usability. In this work, two novel strategies namely, “fixed window approach” and “RTD-based approach” have been developed and evaluated for real-time diversion of non-confirming tablets. The RTD-based control system was designed, developed, and implemented in silico. A framework for its implementation in a real-time system has also been elaborated on. This methodology was compared to an alternative fixed window approach. The proposed control system is analyzed for various manufacturing scenarios, systems, and disturbances. A comparison of the two proposed strategies suggests that the “RTD-based control system” is more efficient in every simulated scenario. The relative performance is best when the disturbances in the system are characterized by short pulse-like changes.

Continuous manufacturing offers shorter processing times and increased product quality assurance, among several other advantages. This makes it an ever-growing interest among pharmaceutical companies. A suitable efficient control system is however desired for continuous pharmaceutical manufacturing to achieve a consistent predefined end product quality. In order to control product quality more accurately, the effects of input disturbances need to be proactively mitigated. Therefore, it is desired that a combined feedforward/feedback control system integrated with suitable process analytical technology (PAT) be implemented over a traditional feedback-only control system. The feedforward controller measures and takes corrective actions for disturbances proactively before they affect the process and thereby product quality. The feedback controller considers the real-time deviation of control variable from a pre-specified set point and keeps it at a minimum possible value. The deviation of a control variable from the set point could be due to both measurable and unmeasurable disturbances. In this work, a combined control strategy has been developed for a continuous twin screw wet granulation (WG) process. An integrated flowsheet model was developed and simulated in order to evaluate the effect of control loops on critical quality attributes (CQAs). Different strategies of manipulation were evaluated and the best strategy was identified. In silico study on the combined feedforward/feedback control strategy and feedback-only control strategy demonstrates that the combined loop results in diminished variability of the CQAs.

An extrusion-based 3D printer was used to fabricate paracetamol tablets with different geometries (mesh, ring and solid) from a single paste-based formulation formed from standard pharmaceutical ingredients. The tablets demonstrate that tunable drug release profiles can be achieved from this single formulation even with high drug loading (> 80% w/w). The tablets were evaluated for drug release using a USP dissolution testing type I apparatus. The tablets showed well-defined release profiles (from immediate to sustained release) controlled by their different geometries. The dissolution results showed dependency of drug release on the surface area/volume (SA/V) ratio and the SA of the different tablets. The tablets with larger SA/V ratios and SA had faster drug release. The 3D printed tablets were also evaluated for physical and mechanical properties including tablet dimension, drug content, weight variation and breaking force and were within acceptable range as defined by the international standards stated in the US Pharmacopoeia. X-ray powder diffraction, differential scanning calorimetry and attenuated total reflectance Fourier transform infrared spectroscopy were used to identify the physical form of the active and to assess possible drug-excipient interactions. These data again showed that the tablets meet USP requirement. These results clearly demonstrate the potential of 3D printing to create unique pharmaceutical manufacturing, and potentially clinical, opportunities. The ability to use a single unmodified formulation to achieve defined release profiles could allow, for example, relatively straightforward personalization of medicines for individuals with different metabolism rates for certain drugs and hence could offer significant development and clinical opportunities.

In order to establish a pharmaceutical manufacturing process control system based on a Quality-by-Design concept, the pharmaceutical properties of tablets during the tablet-coating process were monitored in real time and predicted using values recorded by in-line near-infrared (NIR) spectroscopy. Coating amount (C%), thickness (L), tablet hardness (HT), and tablet dissolution parameters with elution times (T0, T50, and T80) were measured using individual pharmaceutical tests. Tablet coating was performed by spraying F-A (25 w/w%) or F-B (17.8 w/w%) containing EUDRAGIT® L 30 D-55, and monitored using an in-line NIR spectroscopy instrument. Calibration models to predict tablet properties (C%, L, HT, T0, T50, and T80) were obtained based on NIR spectroscopy using a partial least-squares regression (PLS). Chemometric parameters were found to be sufficiently accurate. Correlations between the predicted and measured values of each tablet property showed satisfactory linear relationships. Therefore, the pharmaceutical properties (C%, L, HT, T0, T50, and T80) of tablets may be monitored in real time during the coating process with an in-line NIR spectroscopy method.