No abstract

The Haas -Drenth -Wilson (HDW) (Haas et al., 1999) theoretical model was used to correlate osmotic second virial coefficient (B) values with solubility (S) values for equine serum albumin (ESA) and ovalbumin for corresponding solution conditions. The best fit from the theoretical model was compared to experimental S versus B data. B values were experimentally measured using static light scattering. Solubilities of ESA were estimated using a sitting drop method. When the experimental data for S versus B were plotted, an excellent fit for ESA was obtained according to the HDW model. The results showed that the coordination number (z) in the crystal lattice was 6, and the adjustable parameter (A) was 0.072. For ovalbumin, previously reported solubility data in aqueous ammonium sulfate solutions were utilized. The solubility data for ovalbumin were correlated with the measured B values obtained in our laboratory. The resulting best fit from the HDW model showed that z = 6 and A = 0.084.

In conventional fluorescence spectroscopy, fluorescence intensity at high fluorophore concentration is oRen not proportional to fluorophore concentration, owing to primary and secondary absorption (inner-filter effects). In this paper, fluorescence calibration curves for anthracene solutions were obtained using a conventional right angle cell, a frontal reflection cell, a short pass cell, and a total internal reflection fluorescence (TIRF) cell for comparing the observed primary inner-filter effects. Measurements were also made of a two-component mixture using the nonfluorescent 94trofluorene with anthracene for comparing primary and secondary inner-filter effects. A conventional right angle cell exhibited the widest linear dynamic range and lowest detectable anthracene concentration, whereas the TIRF cell provided the best linearity at high concentrations. The TIRF cell was determined to have significant potential for quantitative analysis of hghly concentrated and/or turbid solutions.

No abstract

Quality control dissolution testing represents a key product performance test for solid oral dosage forms and is the most likely QC test to result in laboratory investigations because of the relatively complex relationship between the dissolution performance, the drug product properties, and the systems necessary to measure the quality attribute. The Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) has pooled our collective knowledge to outline some common ways that dissolution methods can fail. Examples and case studies are given to highlight errors related to equipment, method, materials, measurement, people, and the environment. Best practices for building method understanding and avoiding the exemplified issues are discussed. Case studies highlight the importance of buffer preparation, potential impact of contamination of the dissolution medium, additive-induced degradation, risks in the use of automation, differences between dissolution systems, and the effect of filter selection. Investing in analyst training programs, understanding the capabilities of your equipment portfolio, and using well-designed studies for robustness and ruggedness will reduce dissolution method investigations and improve compliance and productivity during the method lifecycle.