Influence of drug load on dissolution behavior of tablets containing a poorly water-soluble drug: estimation of the percolation threshold

Application of shadowgraph imaging (SGI) particle characterisation data to interpret the impact of varying test conditions on powder dissolution and to develop an automated agglomeration identification method (AIM) in the USP flow-through apparatus

The aims of this work were 1) to explore the application of shadowgraph imaging (SGI) as a real time monitoring tool to characterize ibuprofen particle behaviour during dissolution testing under various conditions in the USP 4 flow-through apparatus and 2) to investigate the potential to develop an SGI-based automated agglomeration identification method (AIM) for real time agglomerate detection during dissolution testing. The effect of surfactant addition, changes in the drug mass and flow rate, the use of sieved and un-sieved powder fractions, and the use of different drug crystal habits were investigated. Videos at every sampling time point during dissolution were taken and analysed by SGI. The AIM was developed to characterize agglomerates based on two criteria - size and solidity. All detections were confirmed by manual video observation and a reference agglomerate data set. The method was validated under new dissolution conditions with un-sieved particles. Characterisation of particle dispersion behaviour by SGI enabled interpretation of the impact of dissolution test conditions. Higher numbers of early detections reflected greater dissolution rates with increased surfactant concentration, using sieved fraction or plate-shaped crystals, but was impacted by drug mass tested. An AIM was successfully developed and applied to detect agglomerates during dissolution, suggesting potential, with appropriate method development, for application in quality control.

Empirical Model Variability: Developing a new global optimisation approach to populate compression and compaction mixture rules

This study systematically evaluated the predictive accuracy of common empirical models for pharmaceutical powder compaction. A dataset of nine placebo and twelve active pharmaceutical ingredient (API) loaded blend formulations (four APIs at three drug loadings) was fitted to the widely used empirical tablet compression (Gurnham, Heckel, and Kawakita) and compaction (Ryshkewitch-Duckworth and Leuenberger) models. At low API loadings (<20w/w%), all models achieved R2 above 90 % and RRMSE (relative root mean squared error) below 0.1. However, as API loads increased, overall model performance decreased, notably in the Heckel model. A parameter variability analysis identified multiple parameter pairs achieving acceptable fits. Consequently, a novel global optimization approach was developed populating arithmetic, geometric, and harmonic mixture rules for empirical tuning parameters. This method outperformed the traditional line of best fit approach. A cross validation study revealed that this method is capable of predicting tuning parameters which achieve an acceptable Goodness of Fit for new blends. Finally, with the restriction of maintaining consistent parameters for the placebo blend, the proposed method could substantially reduce the experimental requirements and API consumption for the exploration of new blends.

Specific surface area of mannitol rather than particle size dominant the dissolution rate of poorly water-soluble drug tablets: A study of binary mixture

The dissolution behavior of tablets, particularly those containing poorly water-soluble drugs, is a critical factor in determining their absorption and therapeutic efficacy. Traditionally, the particle size of excipients has been considered a key property affecting tablet dissolution. However, lurasidone hydrochloride (LH) tablets prepared by similar particle size mannitol, namely M200 (D90 = 209.68 ± 1.42 μm) and 160C (D90 = 195.38 ± 6.87 μm), exhibiting significant differences in their dissolution behavior. In order to find the fundamental influential factors of mannitol influencing the dissolution of LH tablets, the properties (particle size, water content, true density, bulk density, tapped density, specific surface area, circularity, surface free energy, mechanical properties and flowability) of five grades mannitol including M200 and 160C were investigated. Principal component analysis (PCA) was used to establish a relationship between mannitol properties and the dissolution behavior of LH. The results demonstrated that specific surface area (SSA) emerged as the key property influencing the dissolution of LH tablets. Moreover, our investigation based on the percolation theory provided further insights that the SSA of mannitol influences the probability of LH-LH bonding and LH infinite cluster formation, resulting in the different percolation threshold states, then led to different dissolution behaviors. Importantly, it is worth noting that these findings do not invalidate previous conclusions, as reducing particle size generally increases SSA, thereby affecting the percolation threshold and dissolution behavior of LH. Instead, this study provides a deeper understanding of the underlying role played by excipient SSA in the dissolution of drug tablets. This study provides valuable guidance for the development of novel excipients aimed at improving drug dissolution functionality.

Ten years of the manufacturing classification system: a review of literature applications and an extension of the framework to continuous manufacture

The MCS initiative was first introduced in 2013. Since then, two MCS papers have been published: the first proposing a structured approach to consider the impact of drug substance physical properties on manufacturability and the second outlining real world examples of MCS principles. By 2023, both publications had been extensively cited by over 240 publications. This article firstly reviews this citing work and considers how the MCS concepts have been received and are being applied. Secondly, we will extend the MCS framework to continuous manufacture. The review structure follows the flow of drug product development focussing first on optimisation of API properties. The exploitation of links between API particle properties and manufacturability using large datasets seems particularly promising. Subsequently, applications of the MCS for formulation design include a detailed look at the impact of percolation threshold, the role of excipients and how other classification systems can be of assistance. The final review section focusses on manufacturing process development, covering the impact of strain rate sensitivity and modelling applications. The second part of the paper focuses on continuous processing proposing a parallel MCS framework alongside the existing batch manufacturing guidance. Specifically, we propose that continuous direct compression can accommodate a wider range of API properties compared to its batch equivalent.

Nanocrystals in cosmetics and cosmeceuticals by topical delivery

The main issues with local delivery of cosmetics are their high sensitivity and limited drug loading of active pharmaceutical ingredient. Nanocrystal technology offers consumers cutting-edge and effective products and exhibits enormous development potential in the beauty business as a new delivery method to address the issue of low solubility and low permeability of sensitive chemicals. In this review, we described the processes for making NCs, along with the impacts of loading and the uses of different carriers. Among them, nanocrystalline loaded gel and emulsion are widely used and may further improve the stability of the system. Then, we introduced the beauty efficacy of drug NCs from five aspects: anti-inflammation and acne, anti-bacterial, lightening and freckle removal, anti-aging as well as UV protection. Following that, we presented the current scenario about stability and safety. Finally, the challenges and vacancy were discussed along with the potential uses of NCs in the cosmetics industry. This review serves as a resource for the advancement of nanocrystal technology in the cosmetics sector.

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.

The role of excipient molecular weight in drug release by fibrous dosage forms with close packing and high drug loading

In this work, the role of excipient molecular weight in drug release by close-packed, highly drug-loaded fibrous dosage forms is investigated. Three dosage forms with 87 wt% ibuprofen drug, and 13 wt% hydroxypropyl methylcellulose (HPMC) excipient of molecular weights 10, 26, and 86 kg/mol were prepared by wet 3D-patterning and drying. Upon immersion in a dissolution fluid, the dosage form with 10 kg/mol excipient fragmented and dissolved within 10 minutes. The dosage form with 26 kg/mol excipient fragmented slower, and dissolved in 60 minutes. The dosage form with 86 kg/mol excipient, however, did not fragment at all. Instead, a thick, highly viscous mass was formed that eroded slowly, in 500 minutes. Theoretical models suggest that the dissolution fluid rapidly percolates the inter-fiber void space, and a capillary pressure develops in the pores of the fibers. The fluid then diffuses into the fiber walls, and they transition to a viscous suspension. If the molecular weight of the excipient is small (~10 kg/mol), the viscosity is low and the suspension fragments and dissolves rapidly. If the molecular weight is moderate (~30 kg/mol), the fragmentation and dissolution rates are slower. If the molecular weight is large (~100 kg/mol), a thick, highly viscous mass is formed from which drug release is very slow. Thus, by appropriate choice of the molecular weight of the excipient, a wide range of drug release rates by close-packed, highly drug-loaded fibrous dosage forms can be realized.

Application of percolation threshold to disintegration and dissolution of ibuprofen tablets with different microcrystalline cellulose grades

The study presented was conducted to determine whether a percolation threshold value, previously determined for ibuprofen/microcrystalline cellulose (MCC) blends using percolation theory and compression data (Queiroz et al., 2019), could translate to tablet disintegration and dissolution data. The influence of MCC grade (air stream dried versus spray dried) on tablet disintegration and dissolution was also investigated. Complementary to conventional disintegration and dissolution testing, Raman imaging determined drug distribution within tablets, and in-line particle video microscopy (PVM) and focused-beam reflectance measurement (FBRM) monitored tablet disintegration. Tablets were prepared containing 0-30% w/w ibuprofen. Raman imaging confirmed the percolation threshold by quantifying the number and equivalent circular diameters of ibuprofen domains on tablet surfaces. Across the percolation threshold, a step change in dissolution behaviour occurred, and tablets containing air stream dried MCC showed slower disintegration rates compared to tablets containing spray dried MCC. Dissolution measurements confirmed experimentally a percolation threshold in agreement with that determined using percolation theory and compression data. An increase in drug domains, due to cluster formation, and less efficient tablet disintegration contributed to slower ibuprofen dissolution above the percolation threshold. Slower dissolution was measured for tablets containing air stream dried compared to spray dried MCC.

Solvent-free sonochemistry as a route to pharmaceutical co-crystals

We describe the synthesis of pharmaceutically relevant co-crystals by solvent-free sonochemistry starting from solid reagents. Employing a standard ultrasonic cleaning bath, quantitative conversions occurred within 20-60 minutes to give co-crystals of paracetamol and aspirin with a range of co-formers. As well as the utility of the method, the work raises interesting mechanistic questions regarding acoustic cavitation with no liquid phase being present.

Manufacturing classification system in the real world: factors influencing manufacturing process choices for filed commercial oral solid dosage formulations, case studies from industry and considerations for continuous processing

Following the first Manufacturing Classification System (MCS) paper, the team conducted surveys to establish which active pharmaceutical ingredient (API) properties were important when selecting or modifying materials to enable an efficient and robust pharmaceutical manufacturing process. The most commonly identified factors were (1) API particle size: small particle sizes are known to increase risk of processing issues; (2) Drug loading in the formulation: high drug loadings allow less opportunity to mitigate poor API properties through the use of excipients. The next step was to establish linkages with process decisions by identifying publicly-available proxies for these important parameters: dose (in place of drug loading) and BCS class (in place of particle size). Poorly-soluble API were seen as more likely to have controlled (smaller) particle size than more highly soluble API. Analysis of 435 regulatory filings revealed that higher doses and more poorly-soluble API was associated with more complex processing routes. Replacing the proxy factors with the original parameters should give the opportunity to demonstrate stronger trends. This assumption was tested by accessing a dataset relating to commercial tablet products. This showed that, for dry processes, a larger particle size was associated with higher achievable drug loading as determined by percolation threshold.