PubMed · 5411642
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
E A Parker. 1970. Staphcillin injection.. https://pubmed.ncbi.nlm.nih.gov/5411642/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Roller compaction (RC) is an important dry granulation technique. Since pilot and commercial scale roller compactors, which operate continuously on a large scale, usually require kilograms of material per run, formulation and process development directly on such roller compactors is not practical. In contrast, a compaction simulator (CS) can produce ribblets, also known as "slugs", using only a few grams of material with sinusoidal displacement profile replicating the motion of a specific point on the roll surface. Thus, it is possible to develop RC formulation and process in laboratory using a CS-based material-sparing approach. However, because of the inherently different configurations for applying pressure between die compression and roll compression, translating uniaxial pressure from CS experiments to roll pressure during RC is often unreliable, leading to significant uncertainties in the critical quality attributes of ribbons, such as ribbon solid fraction (or porosity) and mechanical strength. The objective of this study was to identify a correction factor (Kp = uniaxial die compression pressure/roll pressure), by correlating the compressibility profiles from CS and a roller compactor of interest, to enable more reliable process translation from CS to roller compactor. In this study, a Kp value of 0.5 was determined for Alexanderwerk WP120 and validated for Gerteis Mini-Pactor and Bepex Pharmapactor. This value may serve as a starting point for translating the optimal compaction pressure identified based on CS investigation to common roller compactors, requiring only minor adjustments to attain optimal RC process parameters (i.e., roll force and roll gap) for a chosen roller compactor.
Data mining, computer-aided molecular modeling, descriptor calculation and multiple linear regression techniques were utilized to produce statistically significant and predictive models for O/W and W/O microemulsions. The literature was scanned over the last 20 years, subsequently, 68 phase diagrams from eight different references were collected. Molecular modeling techniques were then applied on the components of the microemulsion systems to generate plausible 3-D structures. Subsequently, various physicochemical descriptors were calculated based on the resulting 3-D structures. The generated descriptors were correlated with microemulsion existence areas utilizing multiple linear regression analysis (MLR). The generated models were statistically cross-validated and were found to be of significant predictive power. Furthermore, the resulting models allowed better understanding of the process of microemulsion formation.
Unexpected poor flowability during commercial production of a direct compression tablet formulation initiated an investigation of the flow properties of the powder mixture and its components by means of a uniaxial tester. The failure function--a curve describing the strength of the powder bed as a junction of the maximum main stress that has consolidated the bed--of the powder mixture and its components was determined. The drug was more cohesive than the filler, which was somewhat more cohesive than the powder mixture. Three excipients--a hinder, a glidant and a lubricant constituting 3.5 w/w% of the formulation improved the flowability of the mixture of active ingredient and filler. The failure function discriminated powder mixtures with poor flow from mixtures with medium or good flow. However, it was not possible to discriminate medium from good flow by means of the failure function. Attempts to correlate univariately the flow property parameters of the powder mixtures with particle size data or flow property data of included active ingredient and filler batches failed. Therefore a multivariate approach was tested. Principal component analysis (PCA) and projection to latent structures by means of partial least squares (PLS) were employed. An excellent PCA model was obtained with the flow properties of the powder mixture. A good PCA model of tableting performance--based on tablet weight variation and tablet machine speed-was obtained.