A perspective on Quality-by-Control (QbC) in pharmaceutical continuous manufacturing

The current state-of-the art in pharmaceutical continuous film coating - A review

In this decade, one of the major trends in the pharmaceutical industry is the adoption of continuous manufacturing. This requires the development of continuous equivalents of essential pharmaceutical processes such as film coating. The process of film coating is the last step of the processing of solid dosage forms and is critical because it determines the visual appearance of the end product, along with ensuring its stability and possibly even defining the rate of drug release. Several manufacturers advertise continuous solutions for film coating, these include semi-continuous and fully continuous appliances. State-of-the-art continuous coaters can match the throughput of continuous manufacturing lines, because largest appliances have a capacity of 1200-1500 kg/h. The paper also describes the main challenges related to continuous film coating including waste production at the beginning and end of the process and the problem caused by elastic recovery of the tablets when film coating is performed immediately after tablet compression. Lastly, we give an overview of the in-line sensors that can be used to monitor the quality of the film coated tablets, enabling real-time quality control of the process. Near-infrared and Raman spectroscopy can measure the mass gain of the tablets, while terahertz pulsed imaging and optical coherence tomography enable coating thickness measurement of individual tablets and even the characterization of intra-tablet coating thickness variability. UV imaging and machine vision can also measure coating thickness, and they are also excellent for detecting tablets with defective coating.

A multiscale hybrid modelling methodology for cell cultures enabled by enzyme-constrained dynamic metabolic flux analysis under uncertainty

Mammalian cell cultures make a significant contribution to the pharmaceutical industry. They produce many of the biopharmaceuticals obtaining FDA-approval each year. Motivated by quality-by-design principles, various modelling methodologies are frequently trialled to gain insight into these bioprocesses. However, these systems are highly complex and uncertain, involving dynamics at different scales, both in time and space, making them challenging to model in a comprehensive and fully mechanistic manner. This study develops a machine-learning-supported multiscale modelling framework of cell cultures, linking the macroscale bioprocess dynamics to the microscale metabolic flux distribution. As a relevant biopharmaceutical case study, we consider the production of Trastuzumab by Chinese Hamster Ovary (CHO) cells in batch. A macroscale hybrid model is constructed by integrating macro-kinetic and machine-learning approaches. Enzyme-constrained Dynamic Metabolic Flux Analysis (ecDMFA) is adopted to calculate flux distributions based on the dynamic predictions of the hybrid model. Uncertainty estimation of the multiscale model is conducted through bootstrapping. Judging from experimental data, our hybrid model can reduce the modelling error of the macroscale dynamics to 8.0%; a 70% reduction from the purely mechanistic model. In addition, the predicted dynamic flux distribution aligns with observations seen in literature, highlighting important metabolic changes throughout the process. Model uncertainty is maintained at a low level, demonstrating the trustworthiness of the predictions. Overall, our comprehensive modelling framework has the potential to facilitate the development of digital twins in the biopharmaceutical industry.

A two-stage mechanistic reduced-order model of pharmaceutical tablet dissolution: Population balance modeling and tablet wetting functions

We propose a two-stage reduced-order model (ROM) of pharmaceutical tablet dissolution that is comprised of (i) a mechanistic dissolution function of the active pharmaceutical ingredient (API) and (ii) a tablet wetting function. The former is derived from a population balance model, using a high-resolution finite volume algorithm for a given API crystal size distribution and dissolution rate coefficient. The latter is obtained from the mechanistic understanding of water penetration inside a porous tablet, and it estimates the rate at which the API is exposed to the buffer solution for a given formulation and the dimensions of the tablet, contact angle, and surface tension between the solid and liquid phases, liquid viscosity, and mean effective capillary radius of the pore solid structure. In turn, the two-stage model is mechanistic in nature and one-way coupled by means of convolution in time to capture the start time of the API dissolution process as water uptake, swelling, and disintegration take place. The two-stage model correlates dissolution profiles with critical process parameters (CPPs), critical material attributes (CMAs), and other crucial critical quality attributes (CQAs). We demonstrate the model's versatility and effectiveness in predicting the dissolution profiles of diverse pharmaceutical formulations. Specifically, we formulate and fabricate acetaminophen and lomustine solid tablets using different API content and size distributions, characterize their dissolution behavior, and estimate capillary radius as a function of tablet porosity. The estimations generated by the proposed models consistently match the experimental data across all cases investigated in this study.

A narrative review on problems in product quality, regulatory system constraints, and the concept of quality by design as a solution for quality assurance of African medicines

Background

The provision of medicines with confirmed quality and efficacy is critical for maintaining the public health and building confidence in the healthcare systems. However, the presence of poor-quality medicines still presents a significant challenge in the pharmaceutical landscape across the African regions. This is further exacerbated by the lack of consistency or discrepancy in the current regulatory framework. As a consequence, given the current constraints, a robust regulatory structure that can guarantee the supply chains attainment of the intended medicinal product requirements are required.

Objective

The review aimed to provide a detailed analysis of the quality issues in the pharmaceutical supply in Africa, highlighting the challenges and proposing potential solutions for its mitigation.

Methods

The review was conducted from May 2023 to April 2024. This narrative review examined poor-quality medicines, regulatory challenges, and mitigation strategies in the African pharmaceutical industry. The review utilized databases such as Google Scholar, PubMed, and Web of Science. The search strategy was customized to include open-access articles published in peer-reviewed scientific journals in English and focused exclusively on studies conducted in African countries.

Results

The review portrays the prevalence of poor-quality medicinal products in various regions of Africa. Among various categories of findings, 42% of the reports on poor-quality medicinal products come from the African region, as per the WHO report. Furthermore, separate findings on substandard medicinal products from many African countries were encountered. The presence of problems in the regulatory system, such as the absence of any pharmacopeia belonging to any African country and variation/inconsistency in each country's regulatory set-up, was indicated. Other factors for the inability to enforce regulatory law, such as insufficient skilled and committed human resources, the presence of corruption, as well as financial resource scarcity, were revealed in the review. From the situational analysis, the possibility of building a robust quality assurance system in the near future through a quality by design approach under existing resource limitations was discussed.

Conclusion

The pharmaceutical sector in Africa faces significant challenges, including the prevalence of poor-quality medicines and weak regulatory enforcement. Tackling these challenges are vital for enhancing health outcomes throughout the continent through the provision of high-quality medicines. Trending toward quality by design in the quality assurance system under prevailing financial scarcity can be very beneficial.

UV/VIS-imaging of white caffeine tablets for prediction of CQAs: API content, crushing strength, friability, disintegration time and dissolution profile

The paper provides a demonstration of how UV/VIS imaging can be employed to evaluate the crushing strength, friability, disintegration time and dissolution profile of tablets comprised of solely white components. The samples were produced using different levels of compression force and API content of anhydrous caffeine. Images were acquired from both sides of the samples using UV illumination for the API content prediction, while the other parameters were assessed using VIS illumination. Based on the color histograms of the UV images, API content was predicted with 5.6 % relative error. Textural analysis of the VIS images yielded crushing strength predictions under 10 % relative error. Regarding friability, three groups were established according to the weight loss of the samples. Likewise, the evaluation of disintegration time led to the identification of three groups: <10 s, 11-35 s, and over 36 s. Successful classification of the samples was achieved with machine learning algorithms. Finally, immediate release dissolution profiles were accurately predicted under 5 % of RMSE with an artificial neural network. The 50 ms exposition time during image acquisition and the resulting outcomes underscore the practicality of machine vision for real-time quality control in solid dosage forms, regardless of the color of the API.

Rational Function-Based Approach for Integrating Tableting Reduced-Order Models with Upstream Unit Operations: Dry Granulation Case Study

We present a systematic and automatic approach for integrating tableting reduced-order models with upstream unit operations. The approach not only identifies the upstream critical material attributes and process parameters that describe the coupling to the first order and, possibly, the second order, but it also selects the mathematical form of such coupling and estimates its parameters. Specifically, we propose that the coupling can be generally described by normalized bivariate rational functions. We demonstrate this approach for dry granulation, a unit operation commonly used to enhance the flowability of pharmaceutical powders by increasing granule size distribution, which, inevitably, negatively impacts tabletability by reducing the particle porosity and imparting plastic work. Granules of different densities and size distributions are made with a 10% w/w acetaminophen and 90% w/w microcrystalline cellulose formulation, and tablets with a wide range of relative densities are fabricated. This approach is based on product and process understanding, and, in turn, it is not only essential to enabling the end-to-end integration, control, and optimization of dry granulation and tableting processes, but it also offers insight into the granule properties that have a dominant effect on each of the four stages of powder compaction, namely die filling, compaction, unloading, and ejection.

Process analytical technology in Downstream-Processing of Drug Substances- A review

Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.

Application of quality by design in optimization of nanoformulations: Principle, perspectives and practices

Nanoparticulate drug delivery systems (NDDS) based nanoformulations have emerged as promising drug delivery systems. Various NDDS-based formulations have been reported such as polymeric nanoparticles (NPs), nanoliposomes, solid lipid NPs, nanocapsules, liposomes, self-nano emulsifying drug delivery systems, pro liposomes, nanospheres, microemulsion, nanoemulsion, gold NPs, silver NPs and nanostructured lipid carrier. They have shown numerous advantages such as enhanced bioavailability, aqueous solubility, permeability, controlled release profile, and blood-brain barrier (BBB) permeability. This advantage of NDDS can help to deliver pure drugs to the target site. However, the formulation of nanoparticles is a complex process that requires optimization to ensure product quality and efficacy. Quality by Design (QbD) is a systemic approach that has been implemented in the pharmaceutical industry to improve the quality and reliability of drug products. QbD involves the optimization of different parameters like zeta potential (ZP), particle size (PS), entrapment efficiency (EE), polydispersity index (PDI), and drug release using statistical experimental design. The present article discussed the detailed role of QbD in optimizing nanoformulations and their advantages, advancement, and applications from the industrial perspective. Various case studies of QbD in the optimization of nanoformulations are also discussed.

Critical review on the role of excipient properties in pharmaceutical powder-to-tablet continuous manufacturing

INTRODUCTION

The pharmaceutical industry is gradually changing batch-wise manufacturing processes to continuous manufacturing processes, due to the advantages it has to offer. The final product quality and process efficiency of continuous manufacturing processes is among others impacted by the properties of the raw materials. Existing knowledge on the role of raw material properties in batch processing is however not directly transferable to continuous processes, due to the inherent differences between batch and continuous processes.

AREAS COVERED

A review is performed to evaluate the role of excipient properties for different unit operations used in continuous manufacturing processes. Unit operations that will be discussed include feeding, blending, granulation, final blending, and compression.

EXPERT OPINION

Although the potency of continuous manufacturing is widely recognized, full utilization still requires a number of challenges to be addressed effectively. An expert opinion will be provided that discusses those challenges and potential solutions to overcome those challenges. The provided overview can serve as a framework for the pharmaceutical industry to push ahead process optimization and formulation development for continuous manufacturing processes.

Continuous direct compression of a commercially batch-manufactured tablet formulation with two different processing lines

The transfer from batch-based to continuous tablet manufacturing increases the quality and efficiency of processes. Nonetheless, as in the development of a batch process, the continuous process design requires optimization studies to ensure a robust process. In this study, processing of a commercially batch-manufactured tablet product was tested with two continuous direct compression lines while keeping the original formulation composition and tablet quality requirements. Tableting runs were conducted with different values of process parameters. Changes in parameter settings were found to cause differences in tablet properties. Most of these quality properties could be controlled and maintained within the set limits effortlessly already at this stage of studies. However, the API content and content uniformity seemed to require more investigation. The observed content uniformity challenges were traced to individual tablets with a high amount of API. This was suspected to be caused by API micro-agglomerates since tablet weight variability did not explain the issue. This could be solved by adding a mill between two blenders in the process line. Overall, this case study produced promising results with both tested manufacturing lines since many tablet properties complied with the test result limits without optimization of process parameter settings.

Development and Application of Control Concepts for Twin-Screw Wet Granulation in the ConsiGmaTM-25: Part 1 Granule Composition

Continuous manufacturing of pharmaceuticals offers several benefits, such as increased production efficiency, enhanced product quality control, and lower environmental footprint. To fully exploit these benefits, standard operation mode (production processes with no or minimal disturbance mitigation measures) should be supported by adopting novel quality-by-control (QbC) methodologies. The paper at hand is the first part of a study focused on developing QbC algorithms for optimizing twin-screw wet granulation in the industrial manufacturing line ConsiGmaTM-25, specifically addressing granule composition. This work relies on previously established process-analytical-technology (PAT) equipment for real-time monitoring of the granule composition, i.e., the active pharmaceutical ingredient (API) and liquid content in wet granules. The developed control platform integrates model-based process control algorithms that aim to keep the API- and liquid content at target values through real-time adjustments of the process parameters. Furthermore, the platform integrates a digital operator assistant, which aims to detect and classify granulation disturbances and provides messages and instructions for the plant operator. The present manuscript systematically outlines all design steps from the development phase in the simulation environment to the final real system application and validation. The control platform's performance is demonstrated through selected test scenarios on the ConsiGmaTM-25 manufacturing line. The obtained results indicate improved disturbance robustness and an increase in intermediate/final product quality (compared to conventional operating modes): The process control algorithms successfully maintained the API- and liquid content at target values despite process disturbances. Furthermore, realistic disturbances (feeder, pump, and material) were accurately detected and classified by the digital assistant algorithm. The information was provided through a user interface, offering real-time support for plant personnel.

Development and Application of Control Concepts for Twin-Screw Wet Granulation in the ConsiGmaTM-25: Part 2 Granule Size

Traditional operation modes, such as running the production processes at constant process settings or within a narrow design space, do not fully exploit the advantages of continuous pharmaceutical manufacturing. Integrating Quality by Control (QbC) algorithms as a standard component of production processes can mitigate the effect of diverse process disturbances and enhance process efficiency, particularly in terms of production costs and environmental footprint. This paper explores the potential of QbC algorithms for optimizing twin-screw wet granulation in the ConsiGmaTM-25 manufacturing line, specifically addressing granule size. It represents the second part of a study (Celikovic et al. (2024)) focused on granule composition. The concepts proposed in this work rely on process analytical technology (PAT) equipment for real-time monitoring of the granulation CQAs and a dynamic process model linking the granulation process parameters and the monitored CQAs. The granule size model identified via the local-linear-model-tree (LoLiMoT) algorithm is used to develop both a model predictive controller (MPC) and a granule size soft sensor. The MPC employs this model as a core component for selecting optimal granulation parameters to ensure the production of granules with target size. A digital operator assistant is developed to address disturbances that cannot be mitigated via MPC but can be eliminated by the plant operators. This study systematically outlines a workflow, starting from conceptualization, moving through simulation development, and finally ending with real-world application on a production line. In this final step, all proposed concepts are transferred to the ConsiGmaTM-25 manufacturing line, where their performance is validated through selected disturbance scenarios.

Hot-Melt Extrusion: from Theory to Application in Pharmaceutical Formulation-Where Are We Now?

Hot-melt extrusion (HME) is a globally recognized, robust, effective technology that enhances the bioavailability of poorly soluble active pharmaceutical ingredients and offers an efficient continuous manufacturing process. The twin-screw extruder (TSE) offers an extremely resourceful customizable mixer that is used for continuous compounding and granulation by using different combinations of conveying elements, kneading elements (forward and reverse configuration), and distributive mixing elements. TSE is thus efficiently utilized for dry, wet, or melt granulation not only to manufacture dosage forms such as tablets, capsules, or granule-filled sachets, but also for designing novel formulations such as dry powder inhalers, drying units for granules, nanoextrusion, 3D printing, complexation, and amorphous solid dispersions. Over the past decades, combined academic and pharmaceutical industry collaborations have driven novel innovations for HME technology, which has resulted in a substantial increase in published articles and patents. This article summarizes the challenges and models for executing HME scale-up. Additionally, it covers the benefits of continuous manufacturing, process analytical technology (PAT) considerations, and regulatory requirements. In summary, this well-designed review builds upon our earlier publication, probing deeper into the potential of twin-screw extruders (TSE) for various new applications.

Identification of critical process parameters for expansion of clinical grade human Wharton's jelly-derived mesenchymal stromal cells in stirred-tank bioreactors

Cell therapies based on multipotent mesenchymal stromal cells (MSCs) are traditionally produced using 2D culture systems and platelet lysate- or serum-containing media (SCM). Although cost-effective for single-dose autologous treatments, this approach is not suitable for larger scale manufacturing (e.g., multiple-dose autologous or allogeneic therapies with banked MSCs); automated, scalable and Good Manufacturing Practices (GMP)-compliant platforms are urgently needed. The feasibility of transitioning was evaluated from an established Wharton's jelly MSCs (WJ-MSCs) 2D production strategy to a new one with stirred-tank bioreactors (STRs). Experimental conditions included four GMP-compliant xeno- and serum-free media (XSFM) screened in 2D conditions and two GMP-grade microcarriers assessed in 0.25 L-STRs using SCM. From the screening, a XSFM was selected and compared against SCM using the best-performing microcarrier. It was observed that SCM outperformed the 2D-selected medium in STRs, reinforcing the importance of 2D-to-3D transition studies before translation into clinical production settings. It was also found that attachment efficiency and microcarrier colonization were essential to attain higher fold expansions, and were therefore defined as critical process parameters. Nevertheless, WJ-MSCs were readily expanded in STRs with both media, preserving critical quality attributes in terms of identity, viability and differentiation potency, and yielding up to 1.47 × 109 cells in a real-scale 2.4-L batch.

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Impact of GAMP 5, data integrity and QbD on quality assurance in the pharmaceutical industry: How obvious is it?

In the pharmaceutical industry, it is essential to ensure the safety and efficacy of medicinal products. Therefore a robust quality assurance framework is needed. This manuscript examines the impact of GAMP 5 and data integrity (DI) on quality assurance, while also highlighting the role of quality by design (QbD) principles. GAMP 5 is a widely used framework for validating automated systems that establishes quality assurance practices. DI guarantees the reliability of data collected throughout various stages of drug development. The integration of QbD principles promotes a systematic approach to development that emphasizes a deep understanding of critical quality attributes, risk management, and continuous improvement. With their implementation, organizations are able to meet regulatory requirements and provide safe medications to patients worldwide.

Terahertz time-domain spectroscopy for the investigation of tablets prepared from roller compacted granules

Roller compaction before tableting is a common unit operation to increase the processability of powders. Terahertz time-domain spectroscopy (THz-TDS) has recently been introduced as a potential process analytical technology (PAT) for measuring tablet porosity based on the refractive index of the tablet. Tablet porosity is a governing parameter for tablet disintegration and dissolution. The first aim of this study was to investigate tablets prepared from roller-compacted materials with THz-TDS to explore its usefulness for particle size evaluation of granules in tablets. Secondly, the impact of roller compaction and granule size before tablet compression on the established THz-TDS based measurement of tablet porosity was investigated. Microcrystalline cellulose and α-lactose monohydrate were roller compacted separately at five specific compaction forces (2, 4, 8, 12, and 16 kN cm-1) and fractionated into three size fractions. Tablets were prepared from the fractionated and unfractionated granules at twelve tableting pressures and subjected to THz-TDS transmission measurements. It was possible to use the scattering behaviour of the tablets at terahertz frequencies to describe the granulated materials' particle size changes during tableting. At the same time, prediction of porosity was impaired due to the deviation of the refractive index in strongly scattering samples. A correction method was introduced in which the porosity error was corrected based on the tablet's scattering behaviour, resulting in an improved prediction of tablet porosity. In conclusion, THz-TDS is considered a promising technique for the process monitoring of tableting based on its sensitivity to porosity and particle size changes within the tablet non-destructively, with a possible application as part of an in-process control strategy of the tableting of granulated or non-granulated materials.

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. In this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

Techno-economic analysis of dynamic, end-to-end optimal pharmaceutical campaign manufacturing using PharmaPy

Increased interest in the pharmaceutical industry to transition from batch to continuouos manufacturing motivates the use of digital frameworks that allow systematic comparison of candidate process configurations. This paper evaluates the technical and economic feasibility of different end-to-end optimal process configurations, viz. batch, hybrid and continuous, for small-scale manufacturing of an active pharmaceutical ingredient. Production campaigns were analyzed for those configurations containing continuous equipment, where significant start-up effects are expected given the relatively short campaign times considered. Hybrid operating mode was found to be the most attractive process configuration at intermediate and large annual production targets, which stems from combining continuous reactors and semi-batch vaporization equipment. Continuous operation was found to be more costly, due to long stabilization times of continuous crystallization, and thermodynamic limitations of flash vaporization. Our work reveals the benefits of systematic digital evaluation of process configurations that operate under feasible conditions and compliant product quality attributes.

Comparing Integrated Continuous Process "LaVortex®" and Conventional Batch Processes for the Pharmaceutical Manufacturing of Acetaminophen Oral Dosage Formulations: Challenges and Pharmaceutical Properties of the Granular and Tableted Products

LaVortex® was developed as a novel free-flow continuous granulation/drying (CGD) system. In this study, we compared the advantages and disadvantages of granules prepared by continuous and batchwise manufacturing systems. Granules containing 30 % acetaminophen were manufactured under various operating conditions using CGD system, with comparison granules manufactured using conventional batch systems that involve a combination of fluid bed granulation (FG), agitation granulation (AG), continuous drying, fluid bed drying, and/or shelf drying, after which the pharmaceutical properties of each type of manufactured granule were evaluated. Cumulative particle-size distributions were determined by sieving, powder flowabilities were determined by angle of repose measurements, and scanning electron microscopy was employed to examine granule morphologies. The CGD system produced fine-to-large spherical or ellipsoidal granules that exhibited excellent powder fluidities and tabletabilities that are almost identical to those of AG granules. Moreover, the CGD granules exhibited better powder flowability than the FG granules. The addition of water promoted CGD-granule growth and improved significantly powder flowability, and did a little in tabletability. Small spherical granules with good fluidity suitable for fine-particle-coating core materials, or large granules with excellent fluidity and tabletability, were prepared by adjusting the values of the elemental parameters of the CGD process.

Machine learning in additive manufacturing & Microfluidics for smarter and safer drug delivery systems

A new technological passage has emerged in the pharmaceutical field, concerning the management, application, and transfer of knowledge from humans to machines, as well as the implementation of advanced manufacturing and product optimisation processes. Machine Learning (ML) methods have been introduced to Additive Manufacturing (AM) and Microfluidics (MFs) to predict and generate learning patterns for precise fabrication of tailor-made pharmaceutical treatments. Moreover, regarding the diversity and complexity of personalised medicine, ML has been part of quality by design strategy, targeting towards the development of safe and effective drug delivery systems. The utilisation of different and novel ML techniques along with Internet of Things sensors in AM and MFs, have shown promising aspects regarding the development of well-defined automated procedures towards the production of sustainable and quality-based therapeutic systems. Thus, the effective data utilisation, prospects on a flexible and broader production of "on demand" treatments. In this study, a thorough overview has been achieved, concerning scientific achievements of the past decade, which aims to trigger the research interest on incorporating different types of ML in AM and MFs, as essential techniques for the enhancement of quality standards of customised medicinal applications, as well as the reduction of variability potency, throughout a pharmaceutical process.

Modelling the effect of L/S ratio and granule moisture content on the compaction properties in continuous manufacturing

The pharmaceutical field is currently moving towards continuous manufacturing pursuing reduced waste, consistency, and automation. During continuous manufacturing, it is important to understand how both operating conditions and material properties throughout the process affect the final properties of the product to optimise and control production. In this study of a continuous wet granulation line, the liquid to solid ratio (L/S) and drying times were varied to investigate the effect of the final granule moisture content and the liquid to solid ratio on the properties of the granules during tabletting and the final tensile strength of the tablets. Both variables (L/S and granule moisture) affected the tablet tensile strength with the moisture content having a larger impact. Further analysis using a compaction model, showed that the compactability of the granules was largely unaffected by both L/S and moisture content while the compressibility was influenced by these variables, leading to a difference in the final tablet strength and porosity. The granule porosity was linked to the L/S ratio and used instead for the model fitting. The effect of moisture content and granule porosity was added to the model using a 3d plane relationship between the compressibility constant, the moisture content and porosity of the granules. The tablet tensile strength model, considering the effect of moisture and granule porosity, performed well averaging a root mean squared error across the different conditions of 0.17 MPa.

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors (Sampat et al., 2022), this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. The results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

Semi-mechanistic reduced order model of pharmaceutical tablet dissolution for enabling Industry 4.0 manufacturing systems

We propose a generalization of the Weibull dissolution model, referred to as generalized Weibull dissolution model, that seamlessly captures all three fractional dissolution rates experimentally observed in pharmaceutical solid tablets, namely decreasing, increasing, and non-monotonic rates. This is in contrast to traditional reduced order models, which capture at most two fractional dissolution rates and, thus, are not suitable for a wide range of product formulations hindering, for example, the adoption of knowledge management in the context of Industry 4.0. We extend the generalized Weibull dissolution model further to capture the relationship between critical process parameters (CPPs), critical materials attributes (CMAs), and dissolution profile to, in turn, facilitate real-time release testing (RTRT) and quality-by-control (QbC) strategies. Specifically, we endow the model with multivariate rational polynomials that interpolate the mechanistic limiting behavior of tablet dissolution as CPPs and CMAs approach certain values of physical significance (such as the upper and lower bounds of tablet porosity or lubrication conditions), thus the semi-mechanistic nature of the reduced order model. Restricting attention to direct compaction and using various case studies from the literature, we demonstrate the versatility and the capability of the semi-mechanistic ROM to estimate changes in dissolution due to process disturbances in tablet weight, porosity, lubrication conditions (i.e., the total amount of shear strain imparted during blending), and moisture content in the powder blend. In all of the cases considered in this work, the estimations of the model are in remarkable agreement with experimental data.

Developing a Virtual Flowability Sensor for Monitoring a Pharmaceutical Dry Granulation Line

Current technologies to measure granule flowability involve at-line methods that can take hours to perform. This is problematic for a continuous dry granulation tableting line, where the quality assurance and control of the final tablet products depend on real-time monitoring and control of powder flowability. Hence, a real-time alternative is needed for measuring the flowability of the granular products coming out of the roller compactor, which is the unit operation immediately preceding the tablet press. Since particle analyzers have the potential to take inline measurements of the size and shape of granules, they can potentially serve as real-time flowability sensors, given that the size and shape measurements can be used to reliably predict flowability measurements. This paper reports on the use of Partial Least Squares (PLS) regression to utilize distributions of size and shape measurements in predicting the output of three different types of flowability measurements: rotary drum flow, orifice flow, and tapped density analysis. The prediction performance of PLS had a coefficient of determination ranging from 0.80 to 0.97, which is the best reported performance in the literature. This is attributed to the ability of PLS to handle high collinearity in the datasets and the inclusion of multiple shape characteristics-eccentricity, form factor, and elliptical form factor-into the model. The latter calls for a change in industry perspective, which normally dismisses the importance of shape in favor of size; and the former suggests the use of PLS as a better way to reduce the dimensionality of distribution datasets, instead of the widely used practice of pre-selecting distribution percentiles.

Comparison Between Pure Component Modeling Approaches for Monitoring Pharmaceutical Powder Blends with Near-Infrared Spectroscopy in Continuous Manufacturing Schemes

Near-infrared (NIR) spectroscopy has become an important process analytical technology (PAT) for monitoring and implementing control in continuous manufacturing (CM) schemes. However, NIR requires complex multivariate models to properly extract the relevant information and the traditional model of choice, partial least squares, can be unfavorable on account of its high material and time investments for generating calibrations. To account for this, pure component-based approaches have been gaining attention due to their higher flexibility and ease of development. In the present study, the application of two pure component approaches, classical least squares (CLS) models and iterative optimization technology (IOT) algorithms, to pharmaceutical powder blends in a continuous feed frame was considered. The approaches were compared from both a model performance and practical implementation perspective. IOT were found to demonstrate superior performance in predicting drug content compared to CLS. The practical implementation of each modelling approach was also given consideration.

A benchmark simulator for quality-by-design and quality-by-control studies in continuous pharmaceutical manufacturing - Intensified filtration-drying of crystallization slurries

This article introduces ContCarSim, a benchmark simulator for the development and testing of quality-by-design and quality-by-control strategies in the continuous intensified filtration-drying of paracetamol/ethanol slurries on a novel carousel technology, developed by Alconbury Weston Ltd (United Kingdom). The simulator is based on a detailed mechanistic mathematical modeling framework, and has been validated with filtration and drying experiments on a prototype equipment. A set of design- and control-relevant challenges to be addressed through ContCarSim are proposed. A case study is developed, to demonstrate the features of the simulator and its suitability to design, test and optimize the unit operation. ContCarSim is expected to promote the transition to end-to-end continuous pharmaceutical manufacturing and the adoption of closed-loop quality control by the pharmaceutical industry. The simulator can also be employed as a benchmark for data analytics and process monitoring studies.

Quality by Design: A Suitable Methodology in Industrial Pharmacy for Costa Rican Universities

This review aims to present the Quality by Design (QbD) model as a suitable methodology to perform research in the academic Costa Rican institutions that teach Pharmacy. Pubmed, Science Direct, and Google Scholar databases were screened for original research papers and review papers published not more than ten years ago. Institutional repositories from the different universities were reviewed as well. The QbD model stands out as a great methodology for carrying out research projects regarding Pharmaceutical Sciences, but especially for Industrial Pharmacy, where it has contributed in terms of formulation development, manufacturing, and quality control. Academic research based on this model enables the training and development of practical, scientific, and leadership skills in Industrial Pharmacy students. The generated knowledge can be shared in classrooms, which represents an ideal environment to communicate research results and to foster collaborative work between researchers, professors, and students. Moreover, research performed through a QbD approach increases the confidence shown by the industrial sector and health regulatory authorities in the quality of the research, products, and knowledge that are developed and created in an Academy. As a result, the implementation of the model has allowed the creation, transfer, and materialization of knowledge from the Costa Rican Academy to different local pharmaceutical industries.

A review on the modernization of pharmaceutical development and manufacturing - Trends, perspectives, and the role of mathematical modeling

Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.

Big data collection in pharmaceutical manufacturing and its use forproduct quality predictions

Advances in data science and digitalization are transforming the world, and the pharmaceutical industry is no exception. Multiple sensor-equipped manufacturing processes and laboratory analysis are the main sources of primary data, which have been utilized for the presented dataset of 1005 actual production batches of selected medicine. This dataset includes incoming raw material quality results, compression process time series and final product quality results for the selected product. The data is highly valuable for it provides an insight into every 10 seconds of the process trajectory for 1005 actual production batches along with product quality collected over several years. It therefore offers an opportunity to develop advanced analysis models and procedures which would lead to the omission of current conventional and time consuming laboratory testing. Benefits for both the industry and patient are obvious: reducing product lead times and costs of manufacture.

Investigating the Trade-Off between Design and Operational Flexibility in Continuous Manufacturing of Pharmaceutical Tablets: A Case Study of the Fluid Bed Dryer

Market globalisation, shortened patent lifetimes and the ongoing shift towards personalised medicines exert unprecedented pressure on the pharmaceutical industry. In the push for continuous pharmaceutical manufacturing, processes need to be shown to be agile and robust enough to handle variations with respect to product demands and operating conditions. In this paper we examine the use of operational envelopes to study the trade-off between the design and operational flexibility of the fluid bed dryer at the heart of a tablet manufacturing process. The operating flexibility of this unit is key to the flexibility of the full process and its supply chain. The methodology shows that for the fluid bed dryer case study there is significant effect on flexibility of the process at different drying times with the optimal obtained at 700s. The flexibility is not affected by the change in volumetric flowrate, but only by the change in temperature. Here the method used a black box model to show how it could be done without access to the full model equation set, as this often needs to be the case in commercial settings.

In-line particle size measurement based on image analysis in a fully continuous granule manufacturing line for rapid process understanding and development

The present paper serves as a demonstration how an in-line PAT tool can be used for rapid and efficient process development in a fully continuous powder to granule line consisting of an interconnected twin-screw wet granulator, vibrational fluid bed dryer, and a regranulating mill. A new method was investigated for the periodic in-line particle size measurement of high mass flow materials to obtain real-time particle size data of the regranulated product. The system utilises a vibratory feeder with periodically altered feeding intensity in order to temporarily reduce the mass flow of the material passing in front of the camera. This results in the drastic reduction of particle overlapping in the images, making image analysis a viable tool for the in-line particle size measurement of high mass-flow materials. To evaluate the performance of the imaging system, the effect of several milling settings and the liquid-to-solid ratio was investigated on the product's particle size in the span of a few hours. The particle sizes measured with the in-line system were in accordance with the expected trends as well as with the results of the off-line reference particle size measurements. Based on the results, the in-line imaging system can serve as a PAT tool to obtain valuable real-time information for rapid process development or quality assurance.

Real-Time Monitoring of Powder Mass Flowrates for Plant-Wide Control of a Continuous Direct Compaction Tablet Manufacturing Process

While measurement and monitoring of powder/particulate mass flow rate are not essential to the execution of traditional batch pharmaceutical tablet manufacturing, in continuous operation, it is an important additional critical process parameter. It has a key role both in establishing that the process is in a state of control, and as a controlled variable in process control system design. In current continuous tableting line operations, the pharmaceutical community relies on loss-in-weight feeders to monitor and understand upstream powder flow dynamics. However, due to the absence of established sensing technologies for measuring particulate flow rates, the downstream flow of the feeders is monitored and controlled using various indirect strategies. For example, the hopper level of the tablet press is maintained as a controlled process output by adjusting the turret speed of the tablet press, which indirectly controlling the flow rate. This gap in monitoring and control of the critical process flow motivates our investigation of a novel PAT tool, a capacitance-based sensor (ECVT), and its effective integration into the plant-wide control of a direct compaction process. First, the results of stand-alone experimental studies are reported, which confirm that the ECVT sensor can provide real-time measurements of mass flow rate with measurement error within -1.8 ~ 3.3% and with RMSE of 0.1 kg/h over the range of flow rates from 2 to 10 kg/h. The key caveat is that the powder flowability has to be good enough to avoid powder fouling on the transfer line walls. Next, simulation case studies are carried out using a dynamic flowsheet model of a continuous direct compression line implemented in Matlab/Simulink to demonstrate the potential structural and performance advantages in plant-wide process control enabled by mass flow sensing. Finally, experimental studies are performed on a direct compaction pilot plant in which the ECVT sensor is located at the exit of the blender, to confirm that the powder flow can be monitored instantaneously and controlled effectively at the specified setpoint within a plant-wide feedback controller system.

Perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes

Pharmaceutical continuous manufacturing, especially under the context of COVID-19 pandemic, is regarded as an emerging technology that can guarantee the adequate quality assurance and mitigate process risk while guaranteeing the desirable economic performance. Flexibility analysis is one approach to quantitively assess the capability of chemical process to guarantee feasible operation in face of variations on uncertain parameters. The aim of this paper is to provide the perspectives on the flexibility analysis for continuous pharmaceutical manufacturing processes. State-of-the-art and progress in the flexibility analysis for chemical processes including concept evolution, mathematical model formulations, solution strategies, and applications are systematically overviewed. Recent achievements on the flexibility/feasibility analysis of the downstream dosage form manufacturing process are also touched upon. Further challenges and developments in the field of flexibility analysis for novel continuous manufacturing processes of active pharmaceutical ingredients along with the integrated continuous manufacturing processes are identified.

Application of MHE-based NMPC on a Rotary Tablet Press under Plant-Model Mismatch

Active control strategies play a vital role in modern pharmaceutical manufacturing. Automation and digitalization are revolutionizing the pharmaceutical industry and are particularly important in the shift from batch operations to continuous operation. Active control strategies provide real-time corrective actions when departures from quality targets are detected or even predicted. Under the concept of Quality-by-Control (QbC), a three-level hierarchical control structure can be applied to achieve effective setpoint tracking and disturbance rejection in the tablet manufacturing process through the development and implementation of a moving horizon estimation-based nonlinear model predictive control (MHE-NMPC) framework. When MHE is coupled with NMPC, historical data in the past time window together with real-time data from the sensor network enable model parameter updating and control. The adaptive model in the NMPC strategy compensates for process uncertainties, further reducing plant-model mismatch effects. The frequency and constraints of parameter updating in the MHE window should be determined cautiously to maintain control robustness when sensor measurements are degraded or unavailable. The practical applicability of the proposed MHE-NMPC framework is demonstrated via using a commercial scale tablet press, Natoli NP-400, to control tablet properties, where the nonlinear mechanistic models used in the framework can predict the essential powder properties and provide physical interpretations.

A Comprehensive Framework for the Modular Development of Condition Monitoring Systems for a Continuous Dry Granulation Line

The development of condition monitoring systems often follows a modular scheme where some systems are already embedded in certain equipment by their manufacturers, and some are distributed across various equipment and instruments. This work introduces a framework for guiding the modular development of monitoring systems and integrating them into a comprehensive model that can handle uncertainty of predictions from the constituent modules. Furthermore, this framework improves the robustness of the modular condition monitoring systems as it provides a methodology for maintaining quality assurance and preventing unnecessary shutdowns in the event of some modules going off-line due to condition-based maintenance interventions.

A Hierarchical Approach to Monitoring Control Performance and Plant-Model Mismatch

Controllers are often tuned during plant commissioning, with a fixed process model. However, over time degradation can occur in the process, the process model and the controller, making it necessary to either re-tune the controller or re-identify the process model. Authors have proposed a variety of approaches to identify plant-model mismatch (PMM) and control performance degradation (CPD). While each approach may have its own advantages and disadvantages, they are generally designed to function on different timescales. The differing timescales result in the need for a multi-level hierarchical approach to monitor, detect, and manage PMM and CPD, as illustrated through a continuous pharmaceutical manufacturing application, i.e., a direct compression tablet manufacturing process. This work also highlights the requirement for index-based metrics, that enable the impact of PMM and CPD to be quantified and assessed from a control performance monitoring perspective, to aid fault diagnosis through root cause analysis to guide maintenance decisions for continuous manufacturing applications.

Development of mechanistic reduced order models (ROMs)for glidant and lubricant effects in continuous manufacturing of pharmaceutical solid-dosage forms

As the pharmaceutical industry transitions from batch to continuous manufacturing, real-time monitoring, and mechanistic model-based control are essential to conform to FDA quality standards. Glidants and lubricants are known to affect the Critical Quality Attributes (CQAs) of a tablet such as tensile strength, tablet porosity, and dissolution profile (Razavi et al., 2018; Apeji and Olowosulu, 2020). Quantitative models for predicting these effects are essential for enabling centralized control strategies of lubricant and glidant feeding and blending in direct compression tableting lines. This work presents the development of mechanistic reduced order models to capture the effects of lubricant (magnesium stearate) and glidant (silica) on CQAs and Critical Process Parameters (CPPs). A Latin Hypercube experimental campaign with thirty different mixing conditions of silica with MCC (Avicel PH200) and APAP (Acetaminophen) was carried out using a Natoli NP400 tablet press and a SOTAX AT4 tablet tester. Experiments show that the tensile strength and blend bulk density are significantly affected by the mixing conditions of silica. Similarly, adding magnesium stearate (MgSt) changes the bulk density of the blend, compaction force required to form a tablet, and tensile strength of the tablet, depending on the lubrication conditions (Mehrotra et al., 2007; Razavi et al., 2018).

PAT implementation for advanced process control in solid dosage manufacturing - A practical guide

The implementation of continuous pharmaceutical manufacturing requires advanced control strategies rather than traditional end product testing or an operation within a small range of controlled parameters. A high level of automation based on process models and hierarchical control concepts is desired. The relevant tools that have been developed and successfully tested in academic and industrial environments in recent years are now ready for utilization on the commercial scale. To date, the focus in Process Analytical Technology (PAT) has mainly been on achieving process understanding and quality control with the ultimate goal of real-time release testing (RTRT). This work describes the workflow for the development of an in-line monitoring strategy to support PAT-based real-time control actions and its integration into solid dosage manufacturing. All stages are discussed in this paper, from process analysis and definition of the monitoring task to technology assessment and selection, its process integration and the development of data acquisition.