Fast time-resolved micro-CT imaging of pharmaceutical tablets: Insights into water uptake and disintegration.

We use dynamic micro-computed tomography (micro-CT) with a high temporal resolution to visualize water penetration through the porous network of immediate-release pharmaceutical solid tablets and characterize dynamic swelling and disintegration mechanisms. We process the micro-CT images using two theoretical scenarios that reflect different paths of pore structure evolution: a scenario where tablet porosity remains constant during the swelling process and a scenario where the tablet porosity progressively diminishes and eventually closes during the swelling process. We calculate the time evolution of the volume of water absorbed by the tablet and, specifically, absorbed by the excipients and the pore structure, as well as the formation and evolution of cracks. In turn, the three-dimensional disintegration pattern of the tablets is reconstructed. Restricting attention to the limiting scenario where tablet porosity is assumed fixed during the swelling process, we couple liquid penetration due to capillary pressure described by the Lucas-Washburn theory with the first-order swelling kinetics of the excipients to provide a physical interpretation of the experimental observations. We estimate model parameters that are in agreement with values reported in the literature, and we demonstrate that water penetration is dominated by intra-particle porosity rather than inter-particle porosity.

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.

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.

An Integrated Nanocomposite Proximity Sensor: Machine Learning-Based Optimization, Simulation, and Experiment.

This paper utilizes multi-objective optimization for efficient fabrication of a novel Carbon Nanotube (CNT) based nanocomposite proximity sensor. A previously developed model is utilized to generate a large data set required for optimization which included dimensions of the film sensor, applied excitation frequency, medium permittivity, and resistivity of sensor dielectric, to maximize sensor sensitivity and minimize the cost of the material used. To decrease the runtime of the original model, an artificial neural network (ANN) is implemented by generating a one-thousand samples data set to create and train a black-box model. This model is used as the fitness function of a genetic algorithm (GA) model for dual-objective optimization. We also represented the 2D Pareto Frontier of optimum solutions and scatters of distribution. A parametric study is also performed to discern the effects of the various device parameters. The results provide a wide range of geometrical data leading to the maximum sensitivity at the minimum cost of conductive nanoparticles. The innovative contribution of this research is the combination of GA and ANN, which results in a fast and accurate optimization scheme.

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.

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).

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.

Infertilidad, una mirada desde la Atención Primaria de Salud / Infertility, a look since the Primary Health Care

Introducción: El problema de la infertilidad cobra mayor dimensión y trascendencia a nivel mundial, soncada vez más frecuentes las consultas de parejas infértiles en la atención primaria de salud.Objetivo: Caracterizar el comportamiento de la infertilidad, desde la Atención Primaria de Salud.Métodos: Se realizó un estudio observacional, descriptivo, longitudinal retrospectivo, en parejas infértiles, pertenecientes a la consulta municipal de infertilidad del Policlínico Docente Noelio Capote del municipio Jaruco, provincia Mayabeque, desde el mes de septiembre delaño 2017 hasta septiembre del 2019. El universo de estudio estuvo constituido por 113 parejas infértiles. Las variables estudiadas fueron: la edad, la tenencia de hijos anteriores; eltipo de infertilidad, el tiempo de infertilidad previa a la consulta y los factores de riesgos asociados.Resultados: Predominaron en las parejas infértiles las edades entre 30 a 39 años con un 37.2 por ciento, las mujeres tenían en mayor número de hijos anteriores 39.82 por ciento, la infertilidad primaria fue la más frecuente con un 60.17 por ciento, de 2 a 5 años fue el tiempo de infertilidad de las parejas previa a la consulta con un 37.17 por ciento, el tabaquismo y la obesidad eran los factores de riesgos que prevalecieron con 53.98 por ciento y 42.48 por ciento.Conclusiones: La infertilidad se reconoce como un problema de salud, con un importante impacto médicosocial de la pareja, existe un elevada resolutividad en la Atención Primaria de Salud.(AU)

Introduction: The problem of infertility takes a higher dimension and transcendence at world level, every time the consultations of infertile couples are more frequent in Primary Health Care.Objective: To characterize the behavior of infertility since Primary Health Care.Methods: An observational, descriptive, longitudinal retrospective study was carried out, in infertile couples, from the municipal infertility consultation at ¨Noelio Capote¨ teaching Policlinic in Jaruco, Mayabeque, from September, 2017 to September, 2019. The study universe wasformed by 113 infertile couples. The studied variables were: age, the tenancy of previous children; type of infertility, previous time of infertility of the consultation associated risk factors.Results: The infertile couples from 30 to 39 years old prevailed with a 37.2 per cent, women with previouschildren 39.82 per cent, primary infertility was the most frequent with a 60.17 per cent, from 2 to 5 yearswas the infertility time of the couples previous the consultaion with a 37.17 per cent, smoking habitand obesity were the risk factors that prevailed with a 98 % 42.48 per cent.Conclusions: Infertility is recognized as a health problem, with an important medical-social impact of thecouple, there is a high possibility of solution Primary Health Care.(AU)

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.

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

Data provided by in situ sensors is always affected by some level of impreciseness as well as uncertainty in the measurements due to process operation disturbance or material property variance. In-process data precision and reliability should be considered when implementing active product quality control and real-time process decision making in pharmaceutical continuous manufacturing. Data reconciliation is an important strategy to address such imperfections effectively, and to exploit the data redundancy and data correlation based on process understanding. In this study, a correlation between tablet weight and main compression force in a rotary tablet press was characterized by the classical Kawakita equation. A load cell, situated at the exit of the tablet press chute, was also designed to measure the tablet production rate as well as the tablet weight. A novel data reconciliation strategy was proposed to reconcile the tablet weight measurement subject to the correlation between tablet weight and main compression force, in such, the imperfect tablet weight measurement can be reconciled with the much more precise main compression force measurement. Special features of the Welsch robust estimator to reject the measurement gross errors and the Kawakita model parameter estimation to monitor the material property variance were also discussed. The proposed data reconciliation strategy was first evaluated with process control open-loop and closed-loop experimental data and then integrated into the process control system in a continuous tablet manufacturing line. Specifically, the real-time reconciled tablet weight measurements were independently verified with an at-line Sotax Auto Test 4 tablet weight measurements every five minutes. Promising and reliable performance of the reconciled tablet weight measurement was demonstrated in achieving process automation and quality control of tablet weight in pilot production runs.

Sensor Network Robustness Using Model-Based Data Reconciliation for Continuous Tablet Manufacturing.

Advances in continuous manufacturing in the pharmaceutical industry necessitate reliable process monitoring systems that are capable of handling measurement errors inherent in all sensor technologies and detecting measurement outliers to ensure operational reliability. The purpose of this work was to demonstrate data reconciliation (DR) and gross error detection methods as real-time process management tools to accomplish robust process monitoring. DR mitigates the effects of random measurement errors, while gross error detection identifies nonrandom sensor malfunctions. DR is an established methodology in other industries (i.e., oil and gas) and was recently investigated for use in drug product continuous manufacturing. This work demonstrates the development and implementation of model-based steady-state data reconciliation on 2 different end-to-end continuous tableting lines: direct compression and dry granulation. These tableting lines involve different equipment and sensor configurations, with sensor network redundancy achieved using equipment-embedded sensors and in-line process analytical technology tools for the critical process parameters and critical quality attributes. The nonlinearity of the process poses additional challenges to solve the steady-state data reconciliation optimization problem in real time. At-line and off-line measurements were used to validate the framework results.

A Quality-by-Control Approach in Pharmaceutical Continuous Manufacturing of Oral Solid Dosage via Direct Compaction.

The pharmaceutical industry has been undergoing a paradigm shift towards continuous manufacturing, under which novel approaches to real-time product quality assurance have been investigated. A new perspective, entitled Quality-by-Control (QbC), has recently been proposed as an important extension and complementary approach to enable comprehensive Quality-by-Design (QbD) implementation. In this study, a QbC approach was demonstrated for a commercial scale tablet press in a continuous direct compaction process. First, the necessary understanding of the compressibility of a model formulation was obtained under QbD guidance using a pilot scale tablet press, Natoli BLP-16. Second, a data reconciliation strategy was used to reconcile the tablet weight measurement based on this understanding on a commercial scale tablet press, Natoli NP-400. Parameter estimation to monitor and update the material property variance was also considered. Third, a hierarchical three-level control strategy, which addressed the fast process dynamics of the commercial scale tablet press was designed. The strategy consisted of the Level 0 built-in machine control, Level 1 decoupled Proportional Integral Derivative (PID) control loops for tablet weight, pre-compression force, main compression force, and production rate control, and Level 2 data reconciliation of sensor measurements. The effective and reliable performance, which could be demonstrated on the rotary tablet press, confirmed that a QbC approach, based on product and process knowledge and advanced model-based techniques, can ensure robustness and efficiency in pharmaceutical continuous manufacturing.

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

The Quality-by-Design (QbD) guidance issued by the US Food and Drug Administration (FDA) has catalyzed the modernization of pharmaceutical manufacturing practices including the adoption of continuous manufacturing. Active process control was highlighted recently as a means to improve the QbD implementation. This advance has since been evolving into the concept of Quality-by-Control (QbC). In this study, the concept of QbC is discussed, including a definition of QbC, a review of the recent developments towards the QbC, and a perspective on the challenges of QbC implementation in continuous manufacturing. The QbC concept is demonstrated using a rotary tablet press, integrated into a pilot scale continuous direct compaction process. The results conclusively showed that active process control, based on product and process knowledge and advanced model-based techniques, including data reconciliation, model predictive control (MPC), and risk analysis, is indispensable to comprehensive QbC implementation, and ensures robustness and efficiency.

Sensor Network for Continuous Tablet Manufacturing.

The progress in the mechanistic understanding of the unit operations and the availability of multiple sensor technologies enable the inline implementation of data reconciliation and gross error detection methods in continuous pharmaceutical manufacturing. In this work, we demonstrate the benefits of accurate real-time monitoring of the process state in a continuous tableting process, with case studies representative of common situations in pilot-plant or manufacturing line implementation.

Variation and Risk Analysis in Tablet Press Control for Continuous Manufacturing of Solid Dosage via Direct Compaction.

A continuous rotary tablet press is a multi-stage process with many punch stations running in parallel, in which each punch undergoes the following steps: die filling and metering, pre-compaction, main-compaction, tablet ejection, and tablet take-off from lower punch. Process uncertainties or disturbances within a punch station or among stations in the tablet press are a major source of variation in final product quality attributes, e.g., hardness, weight, etc., which in turn imposes challenges for the real-time release in pharmaceutical continuous manufacturing of solid dosage. In this study, the direct compression line at Purdue University was investigated and a Natoli BLP-16 tablet press was used to characterize powder compressibility, system dynamics and variation, as well as the interaction effects on process control development. The compressibility of tablets made from a blend of Acetaminophen (API), Avicel Microcrystalline Cellulose PH-200 (excipient), and SiO2 (lubricant) was found to be largely independent of tableting speed. By contrast, filling depth or dosing level, turret speed, feed-frame speed, and compression force were interacting and significantly affected the die-filling process and the final product quality attributes. Thus, the design of the process control structure plays an important role in reducing process and product quality variations. A hierarchical three-level control design was proposed and evaluated, consisting of Level 0 Natoli built-in control, Level 1 decoupled Proportional Integral Derivative (PID) cascaded control loops for tablet weight and production rate control, and Level 2 advanced model predictive control. Process variations, e.g., in powder bulk density changes, during continuous steady-state operation were also investigated. Finally, a risk analysis of the effects of the process dynamics on variation on the product quality control was briefly discussed and summarized.

Effective Thermal Expansion Property of Consolidated Granular Materials.

Thermally-assisted compaction of granular materials is of keen interest in many engineering applications. A proper estimation of the material behavior of compacted granular materials is contingent upon the knowledge of microstructure formation, which is highly dependent on the bulk material properties and processing conditions, during the deformation stage. Originating from the pair interactions between particles, the macroscopic properties are obtained using various homogenization techniques and postulating continuum constitutive laws. While pioneers in this field have laid fundamental groundwork regarding effective medium descriptions, there exists a discrepancy between discrete and continuum level solutions. In our previous work, we elaborated a Particle Mechanics Approach (PMA) that integrates thermal contact and Hertzian deformation models to understand the thermo-mechanically-coupled consolidation problem. We also considered the analogous problem from the perspective of the conventional Continuum Mechanics Approach (CMA). In this study, following the multi-scale modeling framework, we propose an effective thermal expansion coefficient for the thermally-assisted compaction of granular materials.

General and mechanistic optimal relationships for tensile strength of doubly convex tablets under diametrical compression.

We propose a general framework for determining optimal relationships for tensile strength of doubly convex tablets under diametrical compression. This approach is based on the observation that tensile strength is directly proportional to the breaking force and inversely proportional to a non-linear function of geometric parameters and materials properties. This generalization reduces to the analytical expression commonly used for flat faced tablets, i.e., Hertz solution, and to the empirical relationship currently used in the pharmaceutical industry for convex-faced tablets, i.e., Pitt's equation. Under proper parametrization, optimal tensile strength relationship can be determined from experimental results by minimizing a figure of merit of choice. This optimization is performed under the first-order approximation that a flat faced tablet and a doubly curved tablet have the same tensile strength if they have the same relative density and are made of the same powder, under equivalent manufacturing conditions. Furthermore, we provide a set of recommendations and best practices for assessing the performance of optimal tensile strength relationships in general. Based on these guidelines, we identify two new models, namely the general and mechanistic models, which are effective and predictive alternatives to the tensile strength relationship currently used in the pharmaceutical industry.

Mesoscopic approach to granular crystal dynamics.

We present a mesoscopic approach to granular crystal dynamics, which comprises a three-dimensional finite-element model and a one-dimensional regularized contact model. The approach investigates the role of vibrational-energy trapping effects in the dynamic behavior of one-dimensional chains of particles in contact (i.e., granular crystals), under small to moderate impact velocities. The only inputs of the models are the geometry and the elastic material properties of the individual particles that form the system. We present detailed verification results and validate the model comparing its predictions with experimental data. This approach provides a physically sound, first-principles description of dissipative losses in granular systems.