ABSTRACT
Ionotropic gelation is a low-cost, easy and green microencapsulation technique. However, the encapsulation of highly soluble compounds is challenging because of the wide loss of material into the external water phase by passive diffusion and the consequent low encapsulation efficiency. In this work an important increase of encapsulation efficiency for Thymus vulgaris L. aqueous extract in alginate-based microparticles has been obtained. A formulation with the proper thyme extract/alginate ratio (30:70) was used as reference and then optimized by adding different co-carrier excipients. Microparticles obtained by dropping a solution containing thyme extract and alginate into a chitosan/calcium-chloride/acid acetic solution lead to a high encapsulation efficiency (70.43 ± 5.28 %). After drying, microparticles had a particle size of 1096 ± 72 µm, 20.087 ± 1.487 % of extract content, 6.2 % of residual water, and showed a complete release of thyme extract within one hour. Combining alginate and chitosan as polymeric co-carrier was a valuable option for efficiently encapsulating an aqueous extract by ionotropic gelation.
Subject(s)
Alginates , Chitosan , Particle Size , Plant Extracts , Thymus Plant , Chitosan/chemistry , Alginates/chemistry , Thymus Plant/chemistry , Plant Extracts/chemistry , Microspheres , Water/chemistry , Drug Compounding/methods , Drug Carriers/chemistryABSTRACT
Spray congealing technique was exploited to produce solid lipid microparticles (SLMp) loaded with a highly water-soluble drug (metoclopramide hydrochloride) dissolved in the aqueous phase of a water in oil (W/O) emulsion. The use of an emulsion as starting material for a spray congealing treatment is not so frequent. Moreover, for this application, a W/O emulsion with a drug dissolved in water is a totally novel path. A ternary diagram was built to optimize the emulsion composition, a factorial design was used to identify the factors affecting the properties of the microparticles and a Design of Experiment strategy was applied to define the impact of process conditions and formulation variables on the SLMp properties. SLMp were characterized by particle size distribution, morphology, residual moisture, drug content, release behavior, FT-IR analysis and XRPD. The obtained microparticles presented a spherical shape, particle size distribution between 54-98 µm depending on atomizing pressure used during the production step and 2-5% residual moisture 4 days after the preparation. XRPD analysis revealed that lipid polymorphic transition alfa-beta occurs depending on the presence of water. In vitro drug release tests highlighted that all the formulations had a reduced release rate compared to the drug alone. These results suggest that spray congealing of a W/O emulsion could be proposed as a good strategy to obtain SLMp with a high loading of a hydrophilic drug and able to control its release rate.
ABSTRACT
The use of design space (DS) is a key milestone in the quality by design (QbD) of pharmaceutical processes. It should be considered from early laboratory development to industrial production, in order to support scientists with making decisions at each step of the product's development life. Presently, there are no available data or methodologies for developing models for the implementation of design space (DS) on laboratory-scale spray dryers. Therefore, in this work, a comparison between two different modeling approaches, thermodynamics and computational fluid dynamics (CFD), to a laboratory spray dryer model have been evaluated. The models computed the outlet temperature (Tout) of the process with a new modeling strategy that includes machine learning to improve the model prediction. The model metrics calculated indicate how the thermodynamic model fits Tout data better than CFD; indeed, the error of the CFD model increases towards higher values of Tout and feed rate (FR), with a final mean absolute error of 10.43 K, compared to the 1.74 K error of the thermodynamic model. Successively, a DS of the studied spray dryer equipment has been implemented, showing how Tout is strongly affected by FR variation, which accounts for about 40 times more than the gas flow rate (Gin) in the DS. The thermodynamic model, combined with the machine learning approach here proposed, could be used as a valid tool in the QbD development of spray-dried pharmaceutical products, starting from their early laboratory stages, replacing traditional trial-and-error methodologies, preventing process errors, and helping scientists with the following scale-up.
ABSTRACT
Sericin is a protein extracted from Bombyx mori silk cocoons. Over the last decade, this wastewater product of the textile industry has shown many interesting biological properties. This protein is widely used in the cosmetic and biomedical fields. In this study, sericin has been obtained via a High-Temperature High-Pressure degumming process, and was dried using the freeze-drying (fd) and spray-drying (sd) techniques. Proteins tend to collapse during drying, hence, sericin has been dried in the presence of two selected carrier agents: methyl-ß-cyclodextrin and trehalose. The obtained powders have been analyzed using thermal investigation, microscopy (optical, SEM), and granulometric and spectroscopic analyses. Moreover, the percentage yield of the spray-drying process has been calculated. Both the agents were able to significantly improve the drying process, without altering the physico-chemical properties of the protein. In particular, the co-spray-drying of sericin with methyl-ß-cyclodextrin and trehalose gave good process yields and furnished a powder with low moisture content and handling properties that are better than those of the other studied dried products. These characteristics seem to be appropriate and fruitful for the manufacturing of cosmetic raw materials.