Data reconciliation in the Quality-by-Design (QbD) implementation of pharmaceutical continuous tablet manufacturing

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.

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.

Surface Modifiers on Composite Particles for Direct Compaction

Direct compaction (DC) is considered to be the most effective method of tablet production. However, only a small number of the active pharmaceutical ingredients (APIs) can be successfully manufactured into tablets using DC since most APIs lack adequate functional properties to meet DC requirements. The use of suitable modifiers and appropriate co-processing technologies can provide a promising approach for the preparation of composite particles with high functional properties. The purpose of this review is to provide an overview and classification of different modifiers and their multiple combinations that may improve API tableting properties or prepare composite excipients with appropriate co-processed technology, as well as discuss the corresponding modification mechanism. Moreover, it provides solutions for selecting appropriate modifiers and co-processing technologies to prepare composite particles with improved properties.

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.

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.

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.

A hybrid model for multipoint real time potency observation in continuous direct compression manufacturing operations

The ongoing transition from batch to continuous manufacturing offers both challenges and opportunities in the field of oral solid dosage form production. In turn, Process Analytical Technology (PAT) offers a path towards the successful deployment of continuous tablet manufacturing in rotary tablet presses. One promising PAT tool for this endeavour is the NIR-derived potency measurement. However, the high degree of noise in the data may hamper the extraction of useful information. For this reason, this work focused on the implementation of an adaptive Kalman filter algorithm that incorporates and reconciles the potency prediction given by one or more NIR probes with those of a semi-mechanistic compartmental model developed for the application at hand. This approach allowed for more robust concentration estimations. Furthermore, it was observed that potency levels in multiple locations in the studied tablet press (including those in the finished tablets) could be appropriately inferred using a single in-line measurement data stream. This methodology thus opens the door to advanced process control applications.

Estimation of Feeding Composition of Industrial Process Based on Data Reconciliation

For an industrial process, the estimation of feeding composition is important for analyzing production status and making control decisions. However, random errors or even gross ones inevitably contaminate the actual measurements. Feeding composition is conventionally obtained via discrete and low-rate artificial testing. To address these problems, a feeding composition estimation approach based on data reconciliation procedure is developed. To improve the variable accuracy, a novel robust M-estimator is first proposed. Then, an iterative robust hierarchical data reconciliation and estimation strategy is applied to estimate the feeding composition. The feasibility and effectiveness of the estimation approach are verified on a fluidized bed roaster. The proposed M-estimator showed better overall performance.

Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects.

Design of condition-based maintenance framework for process operations management in pharmaceutical continuous manufacturing

Continuous manufacturing, an emerging technology in the pharmaceutical industry, has the potential to increase the efficiency, and agility of pharmaceutical manufacturing processes. To realize these potential benefits of continuous operations, effectively managing materials, equipment, analyzers, and data is vital. Developments for continuous pharmaceutical manufacturing have led to novel technologies and methods for processing material, designing and configuring individual equipment and process analyzers, as well as implementing strategies for active process control. However, limited work has been reported on managing abnormal conditions during operations to prevent unplanned deviations and downtime and sustain system capabilities. Moreover, although the sourcing, analysis, and management of real-time data have received growing attention, limited discussion exists on the continued verification of the infrastructure for ensuring reliable operations. Hence, this work introduces condition-based maintenance (CBM) as a general strategy for continually verifying and sustaining advanced pharmaceutical manufacturing systems, with a focus on the continuous manufacture of oral solid drug products (OSD-CM). Frameworks, such as CBM, benefit unified efforts towards continued verification and operational excellence by leveraging process knowledge and the availability of real-time data. A vital implementation consideration for manufacturing operations management applications, such as CBM, is a systems architecture and an enabling infrastructure. This work outlines the systems architecture design for CBM in OSD-CM and highlights sample fault scenarios involving equipment and process analyzers. For illustrative purposes, this work also describes the infrastructure implemented on an OSD-CM testbed, which uses commercially available automation systems and leverages enterprise architecture standards. With the increasing digitalization of manufacturing operations in the pharmaceutical industry, proactively using process data towards modernizing maintenance practices is relevant to a single unit operation as well as to a series of physically integrated unit operations.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.