Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach

An update on microcrystalline cellulose in direct compression: Functionality, critical material attributes, and co-processed excipients

Microcrystalline cellulose (MCC) is one of the most popular cellulose derivatives in the pharmaceutical industry. Thanks to its outstanding tabletability, MCC is generally included in direct compression (DC) tablet formulations containing poor-tabletability active pharmaceutical ingredients. Nowadays, numerous grades of MCC from various brands are accessible for pharmaceutical manufacturers, leading to variability in MCC properties. Hence, it seems to be worthy and urgent to evaluate the influences of MCC variability on tablet quality and to identify critical material attributes (CMAs) based on the idea of Quality by Control. Besides, MCC-based co-processed excipients can effectively combine the functions of the filler, binder, disintegrant, lubricant, glidant, or flavor, and thus have drawn extensive interest. In this review, we focused specifically on the recent advances and development of MCC on DC tableting, including the functions in tablet formulations, potential CMAs, and MCC-based co-possessed excipients, therefore providing a reference for further studies.

State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation

During the development of a pharmaceutical formulation, a powerful tool is needed to extract the key points from the complicated process parameters and material attributes. Artificial neural networks (ANNs), a promising and more flexible modeling technique, can address real intricate questions in a high parallelism and distributed pattern in the manner of biological neural networks. The data mined and analyzing based on ANNs have the ability to replace hundreds of trial and error experiments. ANNs have been used for data analysis by pharmaceutics researchers since the 1990s and it has now become a research method in pharmaceutical science. This review focuses on the latest application progress of ANNs in the prediction, characterization and optimization of pharmaceutical formulation to provide a reference for the further interdisciplinary study of pharmaceutics and ANNs.

Applications of Machine Learning in Solid Oral Dosage Form Development

This review comprehensively summarizes the application of machine learning in solid oral dosage form development over the past three decades. In both academia and industry, machine learning is increasingly applied for multiple preformulation/formulation and process development studies. Further, this review provides the authors' perspectives on how pharmaceutical scientists can use machine learning for right projects and in right ways; some key ingredients include (1) the determination of inputs, outputs, and objectives; (2) the generation of a database containing high-quality data; (3) the development of machine learning models based on dataset training and model optimization; (4) the application of trained models in making predictions for new samples. It is expected by the authors and others that machine learning will promisingly play a more important role in tomorrow's projects for solid oral dosage form development.

Multivariate analysis for optimization and validation of the industrial tablet-manufacturing process

OBJECTIVE

This study aimed initially to optimize the industrial tablet-manufacturing process using multivariate analysis, and then to validate the model obtained. The study also provides a comprehensive review of the influence of different factors on relevant biopharmaceutical parameters.

SIGNIFICANCE

This is the first time multivariate analysis has been applied to such a broad set of industrial data to investigate the influence of starting materials and the tablet-manufacturing processes on drug dissolution.

METHODS

Partial least squares regression was retrospectively applied to the data obtained from 2 years production, to study the influence of 90 factors on dissolution of tablets that contained two active pharmaceutical ingredients. The model established was verified using the worst-case approach and process validation.

RESULTS

Croscarmellose sodium had the most significant influence on drug dissolution, with the next significant factors as sodium chloride and sodium glycolate content, settling volume, particle size, suspension pH, loss on drying, and maximum temperature during drying. Loss on drying of microcrystalline cellulose and specific surface area of magnesium stearate were also essential factors. Among the process parameters, auger speed during roller compaction, compression speed, and force feeder speed during tablet compression had significant impacts on the tablet dissolution rate. The multivariate model created satisfied the process validation.

CONCLUSIONS

This multivariate analysis is a useful tool to predict and optimize critical material attributes and process parameters. The variability of the materials can be successfully compensated for using various process parameters, to ensure consistent approved drug quality, to thus provide better patient care.

Design of multi-particulate "Dome matrix" with sustained-release melatonin and delayed-release caffeine for jet lag treatment

Multi-particulate Dome matrix with sustained-release melatonin and delayed-release caffeine was designed to restore jet lag sleep-wake cycle. The polymeric pellets were produced using extrusion-spheronization technique and fluid-bed coated when applicable. The compact and Dome module were produced by compressing pellets with cushioning agent. Dome matrix was assembly of modules with pre-determined compact formulation and drug release characteristics. The physicochemical and in vivo pharmacokinetics of delivery systems were examined. Melatonin loaded alginate/chitosan-less matrix exhibited full drug release within 8 h gastrointestinal transit with low viscosity hydroxypropymethylcellulose as cushioning agent. The cushioning agent reduced burst drug release and omission of alginate-chitosan enabled full drug release. Delayed-release alginate-chitosan caffeine matrix was not attainable through polymer coating due to premature coat detachment. Admixing of cushioning agent high viscosity hydroxypropylmethylcellulose and high viscosity ethylcellulose (9:1 wt ratio) with coat-free caffeine loaded particulates introduced delayed-release response via hydroxypropylmethylcellulose swelled in early dissolution phase and ethylcellulose sustained matrix hydrophobicity at prolonged phase. The caffeine was released substantially in colonic fluid in response to matrix polymers being degraded by rat colonic content. Dome matrix with dual drug release kinetics and modulated pharmacokinetics is produced to introduce melatonin-induced sleep phase then caffeine-stimulated wake phase.

Study of the Potential of the Capsule Shell Based on Natural Polysaccharides in Targeted Delivery of the L-Phenylalanine Ammonia-Lyase Enzyme Preparation

The treatment of classical phenylketonuria is currently represented by many new methods of disease management. A promising method is the use of the enzyme L-phenylalanine ammonia-lyase (PAL) in various forms. The widespread use of enzyme preparations in therapy is limited by a lack of understanding of the mechanisms and systems of the targeted transport of PAL into certain organs and tissues as a result of the incorporation of a drug into the carrier. To ensure the stability of enzymes during the delivery process, encapsulation is preferable, which, as a rule, ensures the preservation of the qualitative characteristics of the enzymes orally applied to the environmental effects of the gastrointestinal tract (acidity, temperature, oxidation, etc.). Capsule preparations showed sufficient stability in the model gastric fluids and sustained release of the drug in the simulated intestinal fluid. Currently, there is a wide range of polymers used for encapsulation. The use of natural sources in the production technology of capsule systems improves bioavailability, controls the release, and prolongs the half-life of active substances. The advantage of this method is that the used enzyme is completely protected by the cell membranes of the capsules, which preserve its stability in the aggressive environment of the gastrointestinal tract. Capsules were obtained on the basis of compositions of hydrocolloids of plant origin. The potential of the developed capsules for targeted delivery of the enzyme preparation was studied. The degradation of the encapsulated form of the PAL enzyme preparation was studied in vitro in model bio-relevant media simulating the gastric and intestinal environment. The dynamics of the breakdown of the capsule shell allow us to expect that the release of L-phenylalanine ammonia-lyase from capsules based on plant hydrocolloids will occur no earlier than reaching the upper intestines, where the interaction with the protein components of the consumed food products to neutralize phenylalanine should occur.