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

Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of κ-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.

Study of Immediate Release Spherical Microparticles Containing Clarithromycin using a Hot-melt Fluid Bed Technique.

The aim of the study was to evaluate a hot-melt technique for preparation of immediate release spherical microparticles containing clarithromycin with acceptable characteristics and process yield. A modified fluid bed apparatus with rotor insert was used to prepare spherical microparticles in the size range of 125-355 µm. Poloxamer 188, PEG-32 glyceryl laurate (Gelucire 44/14) and a mixture of polyethylene glycol (PEG) 4000 with PEG 400 were used as meltable binders. Key process parameters were identified and optimized and their influence on process yield and microparticles characteristics was determined. Microparticles with poloxamer 188 and PEG exhibited relatively good mechanical properties. Process yield was around 70% and 60% in the case of PEG and poloxamer 188 respectively. Microparticles prepared with PEG-32 glyceryl laurate exhibited poor mechanical properties and process yield compared to other microparticles. The process was shown to be limited by the bed temperature, exhibiting the best process stability with poloxamer 188 followed by PEG and PEG-32 glyceryl laurate. Dissolution rate and equilibrium concentration of clarithromycin released from prepared microparticles was improved compared to similar particles prepared by wet granulation.