Our findings provide a basis for designing methods to prevent the antibody reduction during the manufacturing process. Biotechnol. Bioeng. 2010;107: 622-632. (C) 2010 Wiley Periodicals, Inc.”
“To understand in situ drug thermodynamic activity when embedded in a supramolecular structured hydrophilic matrix that simultaneously self-assembled during drug supersaturation.\n\nA propylene glycol (PG)/water, hydroxypropyl methyl cellulose matrix containing ethanol was used to support diclofenac supersaturation. Phase behaviour, thermodynamics and drug transport were assessed through the determination of evaporation

kinetics, supersaturation kinetics and transmembrane penetration.\n\nInitial ethanol evaporation from the drug loaded matrix (2.9 +/- 0.4 mg.min(-1).cm(-2)) was comparable to that of the pure solvent (ca. 3 mg.min(-1).cm(-2)). this website When 25% w/w of the total ethanol from the applied phase was lost (ethanol/water/PG molar ratio of 7:5:1.2), an inflection point in the evaporation

profile and a sudden decrease in drug GW3965 solubility demonstrated that a defined supramolecular structure was formed. The 55-fold decrease in drug solubility observed over the subsequent 8 h drove in situ supersaturation, the rate of which was a function of the drug load in the matrix (y = 0.0078x, R-2 < 0.99).\n\nThe self-assembling supramolecular matrix prevented drug re-crystallisation for > 24 h, but did not hinder mobility and this allowed the thermodynamic activity of the drug to be directly translated into highly efficient transmembrane penetration.”
“Due to impressive achievements JQ1 in genomic research, the number of genome sequences has risen quickly, followed by an increasing number of genes with unknown or hypothetical function. This strongly calls for development of high-throughput methods in the fields of transcriptomics, proteomics and metabolomics. Of these platforms, metabolic profiling has the strongest correlation with the phenotype. We previously published a high-throughput metabolic profiling method for C. glutamicum as well as the automatic GC/MS

processing software MetaboliteDetector. Here, we added a high-throughput transposon insertion determination for our C. glutamicum mutant library. The combination of these methods allows the parallel analysis of genotype/phenotype correlations for a large number of mutants. In a pilot project we analyzed the insertion points of 722 transposon mutants and found that 36% of the affected genes have unknown functions. This underlines the need for further information gathered by high-throughput techniques. We therefore measured the metabolic profiles of 258 randomly chosen mutants. The MetaboliteDetector software processed this large amount of GC/MS data within a few hours with a low relative error of 11.5% for technical replicates.