A compression behavior classification system of pharmaceutical powders for accelerating direct compression tablet formulation design

Mannitol-coated hydroxypropyl methylcellulose as an alternative directly compressible controlled release excipient

One of the most common forms of controlled release technology for oral drug delivery comprises an active ingredient dispersed in a hydrophilic matrix forming polymer such as hydroxypropyl methylcellulose (HPMC), which is tableted via direct compression. However, HPMC may pose problems in direct compression due to its poor flowability. Hence, mannitol syrup was spray-coated over fluidized HPMC particles to produce co-processed HPMC-mannitol at ratios of 20:80, 50:50, and 70:30. Particles of pure HPMC, co-processed HPMC-mannitol, and their respective physical mixtures were evaluated for powder flowability, compression profiles, and controlled release performance. It was found that co-processed HPMC-mannitol consisted of particles with improved flow compared to pure HPMC particles. Sufficiently strong tablets of >2 MPa could be produced at moderate to high compression forces of 150-200 MPa. The dissolution profile could be tuned to obtain desired release profiles by altering HPMC-mannitol ratios. Co-processed HPMC-mannitol offers an interesting addition to the formulator's toolbox in the design of controlled release formulations for direct compression.

Sample Size Requirements of a Pharmaceutical Material Library: A Case in Predicting Direct Compression Tablet Tensile Strength by Latent Variable Modeling

The material library is an emerging, new data-driven approach for developing pharmaceutical process models. How many materials or samples should be involved in a particular application scenario is unclear, and the impact of sample size on process modeling is worth discussing. In this work, the direct compression process was taken as the research object, and the effects of different sample sizes of material libraries on partial least squares (PLS) modeling in the prediction of tablet tensile strength were investigated. A primary material library comprising 45 materials was built. Then, material subsets containing 5 × i (i = 1, 2, 3, …, 8) materials were sampled from the primary material library. Each subset underwent sampling 1000 times to analyze variations in model fitting performance. Both hierarchical sampling and random sampling were employed and compared, with hierarchical sampling implemented with the help of the tabletability classification index d. For each subset, modeling data were organized, incorporating 18 physical properties and tableting pressure as the independent variables and tablet tensile strength as the dependent variable. A series of chemometric indicators was used to assess model performance and find important materials for model training. It was found that the minimum R2 and RMSE values reached their maximum, and the corresponding values were kept almost unchanged when the sample sizes varied from 20 to 45. When the sample size was smaller than 15, the hierarchical sampling method was more reliable in avoiding low-quality few-shot PLS models than the random sampling method. Two important materials were identified as useful for building an initial material library. Overall, this work demonstrated that as the number of materials increased, the model's reliability improved. It also highlighted the potential for effective few-shot modeling on a small material library by controlling its information richness.

A tabletability change classification system in supporting the tablet formulation design via the roll compaction and dry granulation process

In this paper, the material library approach was used to uncover the pattern of tabletability change and related risk for tablet formulation design under the roll compaction and dry granulation (RCDG) process. 31 materials were fully characterized using 18 physical parameters and 9 compression behavior classification system (CBCS) parameters. Then, each material was dry granulated and sieved into small granules (125-250 μm) and large granules (630-850 μm), respectively. The compression behavior of granules was characterized by the CBCS descriptors, and were compared with that of ungranulated powders. The relative change of tabletability (CoTr) index was used to establish the tabletability change classification system (TCCS), and all materials were classified into three types, i.e. loss of tabletability (LoT, Type I), unchanged tabletability (Type II) and increase of tabletability (Type III). Results showed that approximately 65% of materials presented LoT, and as the granules size increased, 84% of the materials exhibited LoT. A risk decision tree was innovatively proposed by joint application of the CBCS tabletability categories and the TCCS tabletability change types. It was found that the LoT posed little risk to the tensile strength of the final tablet, when Category 1 or 2A materials, or Category 2B materials with Type II or Type III change of tabletability were used. Formulation risk happened to Category 2C or 3 materials, or Category 2B materials with Type I change of tabletability, particularly when high proportions of these materials were involved in tablet formulation. In addition, the risk assessment results were verified in the material property design space developed from a latent variable model in prediction of tablet tensile strength. Overall, results suggested that a combinational use of CBCS and TCCS could aid the decision making in selecting materials for tablet formulation design via RCDG.

A novel mixing rule model to predict the flowability of directly compressed pharmaceutical blends

In the pharmaceutical industry, powder flowability is an essential manufacturability attribute to consider when selecting the suitable manufacturing route and formulation. The selection of the formulation is usually based on the physical and chemical properties of the Active Pharmaceutical Ingredient (API) under consideration. Current industrial practice heavily relies on experimental work, which often results in significant labor and API consumption that results in higher costs. In this study we describe the development of a mixing rule to predict powder blend flowability from the flow properties of the individual components for industrial formulations manufactured via Direct Compression (DC). The mixing rule assumes that the granular solids' interactions are dominated by cohesive forces but are pragmatic to calibrate from the perspective of the typical data collated in an industrial environment. The proposed model was validated using a range of different APIs and the results show that the model can effectively predict the flowability properties of any formulation across the space of DC-relevant formulation compositions. Finally, a connection between the model and APIs properties (shape and size) was investigated via a linear correlation between the API particle properties and interparticle forces.

Validation of model-based design of experiments for continuous wet granulation and drying

This paper presents an application case of model-based design of experiments for the continuous twin-screw wet granulation and fluid-bed drying sequence. The proposed framework consists of three previously developed models. Here, we are testing the applicability of previously published unit operation models in this specific part of the production line to a new active pharmaceutical ingredient. Firstly, a T-shaped partial least squares regression model predicts d-values of granules after wet granulation with different process settings. Then, a high-resolution full granule size distribution is computed by a hybrid population balance and partial least squares regression model. Lastly, a mechanistic model of fluid-bed drying simulates drying time and energy efficiency, using the outputs of the first two models as a part of the inputs. In the application case, good operating conditions were calculated based on material and formulation properties as well as the developed process models. The framework was validated by comparing the simulation results with three experimental results. Overall, the proposed framework enables a process designer to find appropriate process settings with a less experimental workload. The framework combined with process knowledge reduced 73.2% of material consumption and 72.3% of time, especially in the early process development phase.

Leveraging a multivariate approach towards enhanced development of direct compression extended release tablets

Extended release formulations play a crucial role in the pharmaceutical industry by maintaining steady plasma levels, reducing side effects, and improving therapeutic efficiency and compliance. One commonly used method to develop extended release formulations is direct compression, which offers several advantages, such as simplicity, time savings, and cost-effectiveness. However, successful direct compression-based extended release formulations require careful assessment and an understanding of the excipients' attributes. The scope of this work is the characterization of the compaction behavior of some matrix-forming agents and diluents for the development of extended release tablets. Fifteen excipients commonly used in extended release formulations were evaluated for physical, compaction and tablet properties. Powder properties (e.g., particle size, flow properties, bulk density) were evaluated and linked to the tablet's mechanical properties in a fully integrated approach, and data were analyzed by constructing a principal component analysis (PCA). Significant variability was observed among the various excipients. The present work successfully demonstrates the applicability of PCA as an effective tool for comparative analysis, pattern and clustering recognition and correlations between excipients and their properties, facilitating the development and manufacturing of direct compressible extended release formulations.

Computer numerical control (CNC) carving as an on-demand point-of-care manufacturing of solid dosage form: A digital alternative method for 3D printing

Computer numerical control (CNC) carving is a widely used method of industrial subtractive manufacturing of wood, plastics, and metal products. However, there have been no previous reports of applying this approach to manufacture medicines. In this work, the novel method of tablet production using CNC carving is introduced for the first time. This report provides a proof-of-concept for applying subtractive manufacturing as an alternative to formative (powder compression) and additive (3D printing) manufacturing for the on-demand production of solid dosage forms. This exemplar manufacturing approach was employed to produce patient-specific hydrocortisone (HC) tablets for the treatment of children with congenital adrenal hyperplasia. A specially made drug-polymer cast based on polyethene glycol (PEG 6,000) and hydroxypropyl cellulose was produced using thermal casting. The cast was used as a workpiece and digitally carved using a small-scale 3-dimensional (3D) CNC carving. To establish the ability of this new approach to provide an accurate dose of HC, four different sizes of CNC carved tablet were manufactured to achieve HC doses of 2.5, 5, 7.5 and 10 mg with a relative standard deviation of the tablet weight in the range of 3.69-4.79%. In addition, batches of 2.5 and 5 mg HC tablets met the British Pharmacopeia standards for weight uniformity. Thermal analysis and X-ray powder diffraction indicated that the model drug was in amorphous form. In addition, HPLC analysis indicated a level of purity of 96.5 ± 1.1% of HC. In addition, the process yielded mechanically strong cylindrical tablets with tensile strength ranging from 0.49 to 1.6 MPa and friability values of <1%, whilst maintaining an aesthetic look. In vitro, HC release from the CNC-carved tablets was slower with larger tablet sizes and higher binder contents. This is the first report on applying CNC carving in the pharmaceutical context of producing solid dosage forms. The work showed the potential of this technology as an alternative method for the on-demand manufacturing of patient-specific dosage forms.

Attribute transmission and effects of diluents and granulation liquids on granule properties and tablet quality for high shear wet granulation and tableting process

This study aims to examine (i) the effect of diluent types (lactose monohydrate, corn starch, and microcrystalline cellulose) and granulation liquids (20% polyvinylpyrrolidone-k30, 65% alcohol, and dispersion containing 40% model drug- Pithecellobium clypearia Benth extracted powder) on granule properties and tablet quality for high shear wet granulation and tableting (HSWG-T) and, more importantly, (ii) the attribute transmission in the process. In general, the impact of diluents on granule properties and tablet quality was more dominant than that of granulation liquids. Attribute transmission patterns were revealed as follows. The granules' ISO. Roundness and density correlated with raw material (i.e., model drug, diluent, and/or granulation liquid) properties such as density and viscosity. The granules' compressibility parameter a correlated with the granules' Span, and parameter y₀ correlated with the granules' flowability and friability. Compactibility parameters k_a and k_b correlated mainly with granule flowability and density, and parameter b correlated significantly and positively with tablet tensile strength. The compressibility correlated negatively with tablet solid fraction (SF) and friability, while the compactibility correlated positively with tablet disintegration time. Moreover, the rearrangement and elasticity of granules correlated positively with SF and friability, respectively. Overall, this study provides some guides for achieving high-quality tablets via HSWG-T.

Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales

The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and data were collected according to the design of experiments at different scales. In total, 38 different tablets were prepared, and the tensile strength (TS) and dissolution rate after 10 min (DS10) were measured. In addition, 15 material attributes (MAs) related to particle size distribution, bulk density, elasticity, plasticity, surface properties, and moisture content of granules were evaluated. By using unsupervised learning including principal component analysis and hierarchical cluster analysis, the regions of tablets produced at each scale were visualized. Subsequently, supervised learning with feature selection including partial least squares regression with variable importance in projection and elastic net were applied. The constructed models could predict the TS and DS10 from the MAs and the compression force with high accuracy (R²= 0.777 and 0.748, respectively), independent of scale. In addition, important factors were successfully identified. ML can be used for better understanding of similarity/dissimilarity between scales, for constructing predictive models of critical quality attributes, and for determining critical factors.

Multivariate data analysis to evaluate commonly used compression descriptors

Numerous studies elucidated material behavior based on compression analyses. Especially compressibility, compactibility and tabletability were in the focus of these investigations. In the present study, a comprehensive multivariate data analysis was performed using principal component analysis method. Twelve pharmaceutically used excipients were selected for direct compression tableting and subsequent evaluation of several compression analyses. Material properties, tablet properties, tableting parameters and parameters from compression analyses were used as input variables. The materials could successfully be grouped using principal component analysis. Of the tableting parameters, the compression pressure showed the greatest influence on the results. The tabletability was found to be the most important compression analysis in the material characterization. Compressibility and compactibility only played a minor role in the evaluation. Some important insights have been gained for a deeper understanding of the tableting process using the multivariate approach to evaluate the variety of compression data.

Using a Material Library to Understand the Change of Tabletability by High Shear Wet Granulation

Understanding the tabletability change of materials after granulation is critical for the formulation and process design in tablet development. In this paper, a material library consisting of 30 pharmaceutical materials was used to summarize the pattern of change of tabletability during high shear wet granulation and tableting (HSWGT). Each powdered material and the corresponding granules were characterized by 19 physical properties and nine compression behavior classification system (CBCS) parameters. Principal component analysis (PCA) was used to compare the physical properties and compression behaviors of ungranulated powders and granules. A new index, namely the relative change of tabletability (CoT_r), was proposed to quantify the tabletability change, and its advantages over the reworking potential were demonstrated. On the basis of CoT_r values, the tabletability change classification system (TCCS) was established. It was found that approximately 40% of materials in the material library presented a loss of tabletability (i.e., Type I), 50% of materials had nearly unchanged tabletability (i.e., Type II), and 10% of materials suffered from increased tabletability (i.e., Type III). With the help of tensile strength (TS) vs. compression pressure curves implemented on both powders and granules, a data fusion method and the PLS2 algorithm were further applied to identify the differences in material properties requirements for direct compression (DC) and HSWGT. Results indicated that increasing the plasticity or porosity of the starting materials was beneficial to acquiring high TS of tablets made by HSWGT. In conclusion, the presented TCCS provided a means for the initial risk assessment of materials in tablet formulation design and the data modeling method helped to predict the impact of formulation ingredients on the strength of compacts.

Hydrochlorothiazide/Losartan Potassium Tablet Prepared by Direct Compression

Hydrochlorothiazide (HCTZ)/losartan potassium (LOS-K) was used as a model drug to prepare compound tablets through the investigation of the compression and mechanical properties of mixed powders to determine the formulation and preparation factors, followed by D-optimal mixture experimental design to optimize the final parameters. The type and amount of lactose monohydrate (SuperTab®14SD, 19.53−26.91%), microcrystalline cellulose (MCC PH102, 32.86−43.31%), pre-gelatinized starch (Starch-1500, 10.96−15.91%), and magnesium stearate (0.7%) were determined according to the compressive work, stress relaxation curves, and Py value. Then, the compression mechanism of the mixed powder was investigated by the Kawakita equation, Shapiro equation, and Heckel analysis, and the mixed powder was classified as a Class-II powder. The compaction pressure (150−300 MPa) and tableting speed (1200−2400 Tab/h) were recommended. A D-optimal mixture experimental design was utilized to select the optimal formulation (No 1, 26.027% lactose monohydrate, 32.811% MCC PH102, and 15.462% pregelatinized starch) according to the drug dissolution rate, using Hyzaar® tablets as a control. Following oral administration in beagle dogs, there were no significant differences in bioavailability between the No. 1 tablet and the Hyzaar® tablet in HCTZ, losartan carboxylic acid (E-3174), and LOS-K (F < F0.05). Thus, formulation and preparation factors were determined according to the combination of the compression and mechanical properties of the mixed powder and quality of tablets, which was demonstrated to be a feasible method in direct powder compression.

Linked experimental and modelling approaches for tablet property predictions

Recent years have seen the advent of Quality-by-Design (QbD) as a philosophy to ensure the quality, safety, and efficiency of pharmaceutical production. The key pharmaceutical processing methodology of Direct Compression to produce tablets is also the focus of some research. The traditional Design-of-Experiments and purely experimental approach to achieve such quality and process development goals can have significant time and resource requirements. The present work evaluates potential for using combined modelling and experimental approach, which may reduce this burden by predicting the properties of multicomponent tablets from pure component compression and compaction model parameters. Additionally, it evaluates the use of extrapolation from binary tablet data to determine theoretical pure component model parameters for materials that cannot be compacted in the pure form. It was found that extrapolation using binary tablet data - where one known component can be compacted in pure form and the other is a challenging material which cannot be - is possible. Various mixing rules have been evaluated to assess which are suitable for multicomponent tablet property prediction, and in the present work linear averaging using pre-compression volume fractions has been found to be the most suitable for compression model parameters, while for compaction it has been found that averaging using a power law equation form produced the best agreement with experimental data. Different approaches for estimating component volume fractions have also been evaluated, and using estimations based on theoretical relative rates of compression of the pure components has been found to perform slightly better than using constant volume fractions (that assume a fully compressed mixture). The approach presented in this work (extrapolation of, where necessary, binary tablet data combined with mixing rules using volume fractions) provides a framework and path for predictions for multicomponent tablets without the need for any additional fitting based on the multicomponent formulation composition. It allows the knowledge space of the tablet to be rapidly evaluated, and key regions of interest to be identified for follow-up, targeted experiments that that could lead to an establishment of a design and control space and forgo a laborious initial Design-of-Experiments.

A Multivariate Formulation and Process Development Platform for Direct Compression

The efficient development of robust tableting processes is challenging due to the lack of mechanistic understanding on the impact of raw material properties and process parameters on tablet quality. The experimental determination of the effect of process and formulation parameters on tablet properties and subsequent optimization is labor-intensive, expensive and time-consuming. The combined use of an extensive raw material property database, process simulation tools and multivariate modeling allows more efficient and more optimized development of the direct compression (DC) process. In this study, key material attributes and in-process mechanical properties with a potential effect on tablet processability and tablet properties were identified. In a first step, an extensive characterization of 55 raw materials (over 100 material descriptors) (Van Snick et al., 2018) and 26 formulation blends (31 material descriptors) (Dhondt et al., 2022) was performed. These blends were subsequently compacted on a compaction simulator under multiple process conditions through a design of experiments (DoE) approach. A T-shaped partial least squares (T-PLS) model was established which correlates tablet quality attributes with process settings, raw material properties and blend ratios. During future development of the DC formulation and process for a new active pharmaceutical ingredient (API), this model can then be used to provide a preliminary formulation and compaction process settings as starting point to be further optimized during development trials based on well-defined raw material characteristics and compaction tests. This study hence contributes to a better understanding on the impact of raw material properties and process settings on a DC process and final properties of the produced tablets; and provides a platform allowing a more efficient and more optimized development of a robust tableting process.

A new direct compression mechanism of structural transition in Poria cocos extract composite particles

The structural transition to generate amorphous translucent grains in Poria cocos dry extract (PCE) composite particles was found and studied as a new direct compression mechanism. The pressure and displacement sensing techniques were used to obtained stress-strain profiles during compression. The Exponential function, Kawakita model, Shapiro model and Heckel model were used to analysis mechanical properties of powders. 12 parameters derived from compression models and powder physical properties were applied to partial least squares method (PLS) for analyzing powder compression mechanism. It was found that only the oven-dried PCE composite particles undergoes the structural transition and generate translucent grains scattered and embedded in tablet, and these tablets have excellent mechanical stability. The structural transition in plant dry extract as the PCE composite particles could be exploited to improve powder compression and tabletability.

Improvements on multiple direct compaction properties of three powders prepared from Puerariae Lobatae Radix using surface and texture modification: comparison of microcrystalline cellulose and two nano-silicas

It has been reported that hydrophilic nano-silica (N) markedly improved direct compaction (DC) properties of Zingiberis Rhizoma alcoholic extract. This study aims to examine the broader scope and generality of the previous work by investigating (i) three powders, i.e., the directly pulverized product, ethanol extract, and water extract prepared from the same medicinal herb-Puerariae Lobatae Radix (named DP, EE, and WE) and (ii) the effects on their DC properties of co-processing with N, hydrophobic nano-silica (BN), or microcrystalline cellulose (C). Unexpectedly, C provided the best improvement on tabletability for WE, while N for both DP and EE. More importantly, only N could move all parent powders to a regime suitable for DC, and BN rather than C enabled parent WE to be directly compressed. Typically, 6/9 N-modified powders simultaneously met the requirements of DC on bulk density, flowability, and tablet tensile strength (σ_t). Principal component analysis indicated that DC properties were mainly governed by flowability and texture properties. The partial least-squares regression model revealed that flowability, texture parameters, and deformation behavior of powders were dominating factors impacting tablet σ_t and solid fraction. Overall, the findings are promising for the manufacture of high drug loading tablets of herbs by DC.

In-Depth Understanding of Granule Compression Behavior under Variable Raw Material and Processing Conditions

Tablet manufacturing involves the processing of raw materials through several unit operations. Thus, the mitigation of input-induced variability should also consider the downstream processability of intermediary products. The objective of the present work was to study the effect of variable raw materials and processing conditions on the compression properties of granules containing two active pharmaceutical ingredients (APIs) and microcrystalline cellulose. Differences in compressibility and tabletability of granules were highlighted in function of the initial particle size of the first API, granule polydispersity and fragmentation. Moreover, interactions were underlined with the atomizing pressure. Changing the supplier of the second API was efficiently controlled by adapting the binder addition rate and atomizing pressure during granulation, considering the starting crystal size. By fitting mathematical models on the available compression data, the influence of diluent source on granule compactibility and tabletability was identified. These differences resumed to the ease of compaction, tableting capacity and pressure sensitivity index due to variable water binding capacity of microcrystalline cellulose. Building the design space enabled the identification of suitable API types and the appropriate processing conditions (spray rate, atomizing pressure, compression force) required to ensure the desired tableting performance.

Mathematical approaches for powders and multiparticulate units processability characterization in pharmaceutical development

An understanding of material properties and processing effects on solid dosage forms performance is required within the Quality-by-design approach to pharmaceutical development. Several research groups have developed mathematical approaches aiming to facilitate the selection of formulation composition and the manufacturing technology. These approaches are based on material particulate, bulk and compression-related properties. This paper provides theoretical assumptions and a critical review of different mathematical approaches for processability characterization of powders and multiparticulate units. Mathematical approaches have mainly been developed for directly compressible materials, but sometimes other manufacturing technologies, such as roller compaction and wet granulation, are also considered. The obtained compact tensile strength has been implemented in the majority of approaches, as an important characteristic describing compact mechanical properties. Flowability should be also evaluated, since it affects sample processability. Additionally, particle size and shape, material density and compressibility, compactibility and tabletability profiles have been also distinguished as relevant properties for solid dosage form development. The application of mathematical approaches may contribute to the mechanistic understanding of critical material attributes and facilitate dosage form development and optimization. However, it is essential to select the appropriate one, based on the intended dosage form characteristics, in order to ensure that all relevant powder/multiparticulate units characteristics are implemented and critically evaluated.

Application of machine learning to a material library for modeling of relationships between material properties and tablet properties

This study investigates the usefulness of machine learning for modeling complex relationships in a material library. We tested 81 types of active pharmaceutical ingredients (APIs) and their tablets to construct the library, which included the following variables: 20 types of API material properties, one type of process parameter (three levels of compression pressure), and two types of tablet properties (tensile strength (TS) and disintegration time (DT)). The machine learning algorithms boosted tree (BT) and random forest (RF) were applied to analysis of our material library to model the relationships between input variables (material properties and compression pressure) and output variables (TS and DT). The calculated BT and RF models achieved higher performance statistics compared with a conventional modeling method (i.e., partial least squares regression), and revealed the material properties that strongly influence TS and DT. For TS, true density, the tenth percentile of the cumulative percentage size distribution, loss on drying, and compression pressure were of high relative importance. For DT, total surface energy, water absorption rate, polar surface energy, and hygroscopicity had significant effects. Thus, we demonstrate that BT and RF can be used to model complex relationships and clarify important material properties in a material library.

A review of emerging technologies enabling improved solid oral dosage form manufacturing and processing

Tablets are the most widely utilized solid oral dosage forms because of the advantages of self-administration, stability, ease of handling, transportation, and good patient compliance. Over time, extensive advances have been made in tableting technology. This review aims to provide an insight about the advances in tablet excipients, manufacturing, analytical techniques and deployment of Quality by Design (QbD). Various excipients offering novel functionalities such as solubility enhancement, super-disintegration, taste masking and drug release modifications have been developed. Furthermore, co-processed multifunctional ready-to-use excipients, particularly for tablet dosage forms, have benefitted manufacturing with shorter processing times. Advances in granulation methods, including moist, thermal adhesion, steam, melt, freeze, foam, reverse wet and pneumatic dry granulation, have been proposed to improve product and process performance. Furthermore, methods for particle engineering including hot melt extrusion, extrusion-spheronization, injection molding, spray drying / congealing, co-precipitation and nanotechnology-based approaches have been employed to produce robust tablet formulations. A wide range of tableting technologies including rapidly disintegrating, matrix, tablet-in-tablet, tablet-in-capsule, multilayer tablets and multiparticulate systems have been developed to achieve customized formulation performance. In addition to conventional invasive characterization methods, novel techniques based on laser, tomography, fluorescence, spectroscopy and acoustic approaches have been developed to assess the physical-mechanical attributes of tablet formulations in a non- or minimally invasive manner. Conventional UV-Visible spectroscopy method has been improved (e.g. fiber-optic probes and UV imaging-based approaches) to efficiently record the dissolution profile of tablet formulations. Numerous modifications in tableting presses have also been made to aid machine product changeover, cleaning, and enhance efficiency and productivity. Various process analytical technologies have been employed to track the formulation properties and critical process parameters. These advances will contribute to a strategy for robust tablet dosage forms with excellent performance attributes.

Monitoring of high-load dose formulations based on co-processed and non co-processed excipients

This work presents the evaluation of a co-processed material for high-load dose formulations and its real-time monitoring by near-infrared (NIR) spectroscopy at the tablet press feed frame. The powder and tableting properties of co-processed material blends were evaluated and compared to the blend of the individual excipients. The formulations with the co-processed material showed excellent flow properties and were superior to the physical blend of individual excipients. Two NIR spectroscopic methods were developed to monitor ibuprofen concentration between 40.0 and 60.0% w/w, one method using a co-processed material as the main excipient and the other using the blend of the individual excipients. The NIR spectra were obtained while the powder blends flowed within a three-chamber feed frame from a Fette 3090 tablet press. The NIR spectroscopic method with the co-processed material presented better performance with significantly lower prediction error. Variographic analysis demonstrated that using the co-processed material considerably reduces the sampling and analytical errors in the in-line determination of ibuprofen. The authors understand that this is the first study where the sampling errors are evaluated as a function of the excipients used in the pharmaceutical formulation. This study demonstrated that selecting a suitable excipient for the formulation helps optimize the manufacturing process, reducing the magnitude of the total measurement error.

Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale

Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part of pharmaceutical quality by design (QbD). It identifies combinations of material and processing parameters ensuring that processing conditions achieve a targeted CQA. Optimum processing conditions are formulation and equipment-dependent. Therefore, it is challenging to translate a process design between formulations, pilot-scale and production-scale equipment. In this study, an empirical model was developed to determine optimum processing conditions for direct compression formulations with varying flow properties, across pilot- and production-scale tablet presses. The CQA of interest was tablet weight variability, expressed as percentage relative standard deviation. An experimental design was executed for three model placebo blends with varying flow properties. These blends were compacted on one pilot-scale and two production-scale presses. The process model developed enabled the optimization of processing parameters for each formulation, on each press, with respect to a target tablet weight variability of <1%RSD. The model developed was successfully validated using data for additional placebo and active formulations. Validation formulations were benchmarked to formulations used for model development, employing permeability index values to indicate blend flow.

Preparation of Co-Processed Excipients for Controlled-Release of Drugs Assembled with Solid Lipid Nanoparticles and Direct Compression Materials

The purpose of the study was to develop a novel, directly compressible, co-processed excipient capable of providing a controlled-release drug system for the pharmaceutical industry. A co-processed powder was formed by adsorption of solid lipid nanoparticles (SLN) as a controlled-release film onto a functional excipient, in this case, dicalcium phosphate dihydrate (DPD), for direct compression (Di-Tab®). The co-processed excipient has advantages: easy to implement; solvent-free; industrial scaling-up; good rheological and compressibility properties; and the capability to form an inert platform. Six different batches of Di-Tab®:SLN weight ratios were prepared (4:0.6, 3:0.6, 2:0.6, 1:0.6, 0.5:0.6, and 0.25:0.6). BCS class III ranitidine hydrochloride was selected as a drug model to evaluate the mixture's controlled-release capabilities. The co-processed excipients were characterized in terms of powder rheology and dissolution rate. The best Di-Tab®:SLN ratio proved to be 2:0.6, as it showed high functionality with good flow and compressibility properties (Carr Index = 16 ± 1, Hausner Index = 1.19 ± 0.04). This ratio could control release for up to 8 h, so it fits the ideal profile calculated based on biopharmaceutical data. The compressed systems obtained using this powder mixture behave as a matrix platform in which Fickian diffusion governs the release. The Higuchi model can explain their behavior.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Tabletability Flip - Role of Bonding Area and Bonding Strength Interplay

Predicting tableting performance of mixtures from that of individual components is of practical importance for achieving efficient and robust tablet design. It has been commonly assumed that a solid form exhibiting better tabletability will result in better tabletability when formulated. However, we show that the rank order of tabletability between two powders can flip when mixed with another powder, a phenomenon termed tabletability flip. Using three examples, we show that the tabletability flip upon mixing with microcrystalline cellulose is activated by the switch of the dominating factor in the bonding area (BA) and bonding strength (BS) interplay that determines tablet tensile strength. A mechanistic understanding of this phenomenon can significantly improve the accuracy of predicted tableting performance of mixtures from that of individual powders.

Preparation and evaluation of captopril loaded gastro-retentive zein based porous floating tablets

In this study, gastro-retentive porous floating tablets of captopril based on zein are reported using l-menthol as a porogen. Tablets were prepared by the direct compression method. Removing of l-menthol through sublimation process generated pores in tablets, which decreased the density to promote floating over gastric fluid. Prepared tablets showed no floating lag time and prolong total floating time (>24 h). Drug release was found dependent upon porosity of tablets, an increase in porosity of tablets resulted in increased drug release, so it can be tuned by varying concentration of l-menthol. In addition to floating and sustained release properties, porous tablets showed robust mechanical behavior in wet conditions, which can enable them to withstand real gastric environment stress. In vivo studies using New Zealand rabbits also confirmed the prolonged gastric retention (24 h) and plasma drug concentration-time profile showed sustained release of captopril with higher T_max and MRT as compared to marketed immediate-release tablets. Overall, it was concluded that effective gastric retention can be achieved using porous zein tablets using l-menthol as a porogen.

Using a Material Library to Understand the Impacts of Raw Material Properties on Ribbon Quality in Roll Compaction

The purpose of this study is to use a material library to investigate the effect of raw material properties on ribbon tensile strength (TS) and solid fraction (SF) in the roll compaction (RC) process. A total of 81 pharmaceutical materials, including 53 excipients and 28 natural product powders (NPPs), were characterized by 22 material descriptors and were compacted under five different hydraulic pressures. The transversal and longitudinal splitting behaviors of the ribbons were summarized. The TS-porosity and TS-pressure relationships were used to explain the roll compaction behavior of powdered materials. Through defining the target ribbon quality (i.e., 0.6 ≤ SF ≤ 0.8 and TS ≥ 1 MPa), the roll compaction behavior classification system (RCBCS) was built and 81 materials were classified into three categories. A total of 24 excipients and five NPPs were classified as Category I materials, which fulfilled the target ribbon quality and had less occurrence of transversal splitting. Moreover, the multivariate relationships between raw material descriptors, the hydraulic pressure and ribbon quality attributes were obtained by PLS regression. Four density-related material descriptors and the cohesion index were identified as critical material attributes (CMAs). The multi-objective design space summarizing the feasible material properties and operational region for the RC process were visualized. The RCBCS presented in this paper enables a formulator to perform the initial risk assessment of any new materials, and the data modeling method helps to predict the impact of formulation ingredients on strength and porosity of compacts.