Based on the current definition of solubility, 15 of the 18 acidic NSAIDs in this study will be classified as Class II compounds as the solubility criteria applies to the entire pH range of 1.2 to 7.4, although the low solubility criteria does not hold true over the entire pH range. Whence, of the 18 acidic drugs, 15 can be classified as Class I based on the pH 7.4 solubility alone. This finding is intriguing because these drugs exhibit Class I behavior as their absorption does not seem to be dissolution or solubility limited. It could then be argued that for acidic drugs, the boundaries for solubility are too restrictive. Solubility at pH > 5 (pH in duodenum) may be more appropriate because most compounds are mainly absorbed in the intestinal region. Consideration for an intermediate solubility classification for highly permeable ionizable compounds that reflects physiological conditions seems warranted.

This study examined the use of focused beam reflectance measurement (FBRM) for qualitative and quantitative analysis of pharmaceutical suspensions with particular application to toxicology supply preparations for use in preclinical studies. Aqueous suspensions of ibuprofen were used as prototype formulations. Initial experiments were conducted to examine the effects of operational conditions including FBRM probe angle, probe location, and mixing (method and rate of mixing) on the FBRM analysis. Once experimental conditions were optimized, the homogeneity and sedimentation-redispersion of particles in the suspensions were assessed. Ibuprofen suspension under continuous agitation was monitored using FBRM for 60 h to study particle size change over time. Another study was performed to determine if particle count rates obtained by FBRM could be correlated to suspension concentration. The location and the angle of the FBRM probe relative to the beaker contents, and the rate and the method of mixing the suspension were found to be sensitive parameters during FBRM analysis. FBRM was able to monitor the process of particle sedimentation in the suspension. The attrition of ibuprofen particles was detectable by FBRM during prolonged stirring with an increase in the number of smaller particles and decrease in the number of larger particles. A strong correlation was observed between particle count rate by FBRM and ibuprofen concentration in the suspension. Also, change in content uniformity in the suspension at different locations of the beaker was represented by FBRM particle count. Overall, FBRM has potential to be a useful tool for qualitative and quantitative analysis of pharmaceutical suspensions.

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Assessing in vivo performance to inform formulation selection and development decisions is an important aspect of drug development. Biopredictive dissolution methodologies for oral dosage forms have been developed to understand in vivo performance, assist in formulation development/optimization, and forecast the outcome of bioequivalence studies by combining them with simulation tools to predict plasma profiles in humans. However, unlike compendial dissolution methodologies, the various biopredictive methodologies have not yet been harmonized or standardized. This manuscript presents the initial phases of an effort to develop best practices and move toward standardization of the biopredictive methodologies through the Product Quality Research Institute (PQRI, https://pqri.org) entitled “The standardization of in vitro predictive dissolution methodologies and in silico bioequivalence study Working Group.” This Working Group (WG) is comprised of participants from 10 pharmaceutical companies and academic institutes. The project will be accomplished in a total of five phases including assessing the performance of dissolution protocols designed by the individual WG members, and then building “best practice” protocols based on the initial dissolution profiles. After refining the “best practice” protocols to produce equivalent dissolution profiles, those will be combined with physiologically based biopharmaceutics models (PBBM) to predict plasma profiles. In this manuscript, the first two of the five phases are reported, namely generating biopredictive dissolution profiles for ibuprofen and dipyridamole and using those dissolution profiles with PBBM to match the clinical plasma profiles. Key experimental parameters are identified, and this knowledge will be applied to build the “best practice” protocol in the next phase. Graphical Abstract