Quantification of lubrication and particle size distribution effects on tensile strength and stiffness of tablets

Lactose in tablets: Functionality, critical material attributes, applications, modifications and co-processed excipients

Lactose is one of the most widespread excipients used in the pharmaceutical industry. Because of its water solubility and acceptable flowability, lactose is generally added into tablet formulation to improve wettability and undesirable flowability. Based on Quality by Design, a better understanding of the critical material attributes (CMAs) of raw materials is beneficial in guiding the improvement of tablet quality and the development of lactose. Additionally, the modifications and co-processing of lactose can introduce more-desirable characteristics to the resulting particles. This review focuses on the functionality, CMAs, applications, modifications and co-processing of lactose in tablets.

Direct Tableting on a Continuous Manufacturing Line-Impact of Mixing Parameters, Material Densities, and Drug Load on Subsequent Process Parameters and Tablet Quality

The continuous manufacturing (CM) of solid oral dosage forms has received increased attention in recent years and has become a leading technology in the pharmaceutical industry. A model has been developed based on process data from two design of experiments (DoEs), where the impact of the mixer process parameters, throughput (THR), hold up mass (HUM), impeller speed (IMP), and the input raw material bulk density (BD_i), on the continuous process and the resulting drug product has been investigated. These statistical models revealed equations, describing process parameter interactions for optimization purposes. For the exit valve opening width (EV) at the bottom of the continuous mixer (CMT), the combination of high throughput (30 kg/h) and low impeller speed (300 rpm) resulted in optimal process conditions. Apparent bulk density of the blend (BD) within the process, fill depth (FD), and tensile strength (TS) were mainly impacted by input bulk density (BD_i) of the tableting mixture, emphasizing the role of material attributes on the continuous manufacturing process. The apparent bulk density itself was, other than from the input bulk density, equally dependent from THR and IMP in opposite deflections. However, process parameters (THR and IMP) revealed a minor impact on the apparent BD compared to the input bulk density. FD was impacted mainly by THR ahead of IMP and the TS by IMP and THR to a similar extend, in opposite deflections. A simplified linear model to estimate the input bulk density revealed satisfactory prediction quality when included in the derived statistical model equations.

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.

UV/VIS imaging-based PAT tool for drug particle size inspection in intact tablets supported by pattern recognition neural networks

The potential of machine vision systems has not currently been exploited for pharmaceutical applications, although expected to provide revolutionary solutions for in-process and final product testing. The presented paper aimed to analyze the particle size of meloxicam, a yellow model active pharmaceutical ingredient, in intact tablets by a digital UV/VIS imaging-based machine vision system. Two image processing algorithms were developed and coupled with pattern recognition neural networks for UV and VIS images for particle size-based classification of the prepared tablets. The developed method can identify tablets containing finer or larger particles than the target with more than 97% accuracy. Two algorithms were developed for UV and VIS images for particle size analysis of the prepared tablets. According to the applied statistical tests, the obtained particle size distributions were similar to the results of the laser diffraction-based reference method. Digital UV/VIS imaging combined with multivariate data analysis can provide a new non-destructive, rapid, in-line tool for particle size analysis in tablets.

Impact of Vertical Blender Unit Parameters on Subsequent Process Parameters and Tablet Properties in a Continuous Direct Compression Line

The continuous manufacturing of solid oral-dosage forms represents an emerging technology among the pharmaceutical industry, where several process steps are combined in one production line. As all mixture components, including the lubricant (magnesium stearate), are passing simultaneously through one blender, an impact on the subsequent process steps and critical product properties, such as content uniformity and tablet tensile strength, is to be expected. A design of experiment (DoE) was performed to investigate the impact of the blender variables hold-up mass (HUM), impeller speed (IMP) and throughput (THR) on the mixing step and the subsequent continuous manufacturing process steps. Significant impacts on the mixing parameters (exit valve opening width (EV), exit valve opening width standard deviation (EV SD), torque of lower impeller (T_L), torque of lower impeller SD (T_L SD), HUM SD and blend potency SD), material attributes of the blend (conditioned bulk density (CBD), flow rate index (FRI) and particle size (d₁₀ values)), tableting parameters (fill depth (FD), bottom main compression height (BCH) and ejection force (EF)) and tablet properties (tablet thickness (TT), tablet weight (TW) and tensile strength (TS)) could be found. Furthermore, relations between these process parameters were evaluated to define which process states were caused by which input variables. For example, the mixing parameters were mainly impacted by impeller speed, and material attributes, FD and TS were mainly influenced by variations in total blade passes (TBP). The current work presents a rational methodology to minimize process variability based on the main blender variables hold-up mass, impeller speed and throughput. Moreover, the results facilitated a knowledge-based optimization of the process parameters for optimum product properties.

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).

Investigation on the impact of different proportions of components in formulations on stability of a moisture sensitive drug

Physicochemical and mechanical properties of tablets are largely dictated by formulation compositions. Different excipients possess different tableting and moisture sorption behaviors. Therefore, this study was designed to elucidate the relative influence of the proportion of components in formulations on tablet properties. Acetylsalicylic acid (ASA) tablets containing different proportions of starch, microcrystalline cellulose (MCC) and calcium hydrogen phosphate dihydrate (DCP) were prepared. The excipients were evaluated for their moisture sorption properties. Mechanical strength of the tablets was determined alongside with ASA stability, by storing the tablets at 75% RH, 25 °C. The stability study showed the importance of drug loading level on its stability. For a fixed ASA proportion, formulations with more starch were able to absorb more moisture and possessed larger areas of hysteresis loop in their moisture sorption isotherms. The presence of starch contributed positively to ASA stability although increasing proportions of starch compromised the tablet mechanical properties. Contrastingly, MCC produced mechanically stronger tablets as its plastically deforming and fibrous properties contributed to a good structural network. The findings provide a deeper understanding of the dichotomous effect by the proportion of components in formulations containing a moisture sensitive drug on drug stability and mechanical strength of the resultant tablets.

Effect of excipient particle size distribution variability on compact tensile strength; and its in-line prediction by force-displacement and force-time profiling

BACKGROUND

Direct compression is potentially sensitive to particle size distribution (PSD) variability in pharmaceutical grade excipients. Yet, the impact is insufficiently studied. Furthermore, the use of force sensor as a process analytical technology (PAT) platform, to monitor the effect of PSD variations on compact tensile strength, is a readily available but underutilized strategy.

METHODS

To address these shortfalls, the effect of PSD variability on compaction was investigated. Low (4% w/w drug) and high (15% w/w drug) dose blends comprising chlorpheniramine, microcrystalline cellulose and spray-agglomerated lactose were tableted. The PSD of spray-agglomerated lactose was varied by adding ungranulated fines to simulate commercially-relevant variability. Tensile strength and disintegration time were determined. The use of force sensor, to generate force-displacement and force-time profiles, for in-line tensile strength prediction was evaluated.

RESULTS

Increasing proportion of ungranulated fines (≥ 16%) reduced tensile strength by 10% and 4% in low and high dose formulations (p < 0.02). Increased friction during compaction hindered particle movement and reduced the energy available for bonding. Nevertheless, disintegration performances were equally acceptable for immediate drug release (≈ 30 s). Modelling of tensile strength with force-displacement and force-time profiles yielded ≥ 98% accuracy for in-line prediction (relative root mean square error of prediction = 3.7% and 4.8%).

CONCLUSION

A better understanding of the relationship between PSD variability and direct compression was attained; and force-displacement and force-time profiling are pragmatic and elegant PAT strategies. Significantly, with further refinements, the force sensor in the rotary tablet press can be repurposed for process monitoring and quality inspection. This unlocks opportunities for process understanding and control, without additional investments in PAT platforms.

A Multi-variate Mathematical Model for Simulating the Granule Size Distribution in Roller Compaction-Milling Process

Granule size distribution (GSD) is one of the critical quality attributes in the roller compaction (RC) process. Determination of GSD for newly developed pharmaceutical compounds with unknown ribbon breakage behaviors at the RC milling step requires a quantitative insight into process parameters and ribbon attributes. Despite its pivotal role in mapping the process operating conditions to achieve desired granule size, limited work has been presented in literature with a focus on RC-milling modeling. In this study, a multi-variate mathematical model is presented to simulate the full size-distribution of granulated ribbons as a function of ribbon mechanical properties. Experimental data with a lab-scale oscillating milling apparatus were generated using ribbons made of various powder compositions. Model parameters were determined by fitting it to experimental data sets. Parameters obtained from the first step were correlated to ribbon Young's modulus. The model was validated by predicting GSD of data that were excluded in model development step. Predictive capabilities of the developed model were further explored by simulating GSD profiles of a granulated pharmaceutical excipient obtained at three different conditions of a real-scale Gerteis RC system. While maintaining the milling operating conditions similar to the lab-scale apparatus (i.e., screen size and spacing, and low rotor speed), the proposed modeling approach successfully predicted the GSD of roller compacted MCC powder as the model compound. This model can be alternatively utilized in conjunction with an RC model in order to facilitate the process understanding to obtain granule attributes as part of Quality-by-Design paradigm.

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.

Influence of the formula on the properties of a fast dispersible fruit tablet made from mango, Chlorella, and cactus powder

Tableting of fruit powders is gaining popularity because of the advantages it brings in, such as ease of storage, transportation, and use, and effervescent tablets could be a good alternative to accomplish fast dissolving. The present study provides a specific effervescent tablet formulation that is appropriate for the delivery of mango, cactus, and Chlorella fruit powder. The direct compression method was employed. A series of disintegration time, tensile strength, and moisture content tests were performed on the different formulations at each stage. The effects of effervescent agents' ratio, fruit powder proportion, acid and alkali content, and mannitol and lactose content on tablet properties were investigated. The results indicated that the tablet properties were highly influenced by formulation, especially the ratios of effervescent agents, fruit powders, acid to alkali ratio, as well as mannitol to lactose ratio. The best performing formulation was as follows, 45% effervescent agents (citric acid monohydrate:sodium bicarbonate = 1.3:1), 35% adhesives (mannitol:lactose = 1:8), and 20% mixed fruit powders (mango:cactus:Chlorella fruit powders = 14:5:1). With this formula, the moisture content was 3.62% and the disintegration time was 154 s, as well as a sufficient tensile strength of 2.32 MPa. Our study presented useful findings regarding the specific effects of changing ingredient ratios on tablet strength and other properties and provided a basis for the potential of using mango, cactus and microalgae powders as novel functional ingredients for fruit powder effervescent tablets. This may be used as a basis for further research on tableting.