The aim of the study is to develop modified, branched versions of the Noyes-Whitney and the Weibull equations, including explicitly the solubility/dose parameter, for the analysis of dissolution data, which reach the plateau either at infinite or finite time. The modified Weibull function is applied to the analysis of experimental and literature dissolution data. To demonstrate the usefulness of the mathematical models, two model drugs are used: one highly soluble, metoprolol, and one relatively insoluble, ibuprofen. The models were fitted successfully to the data performing better compared with their classic versions. The advantages of the use of the models presented are several. They fit better to a large range of datasets, especially for fast dissolution curves that reach complete dissolution at a finite time. Also, the modified Weibull presented can be derived from differential equations, and it has a physical meaning as opposed to the purely empirical character of the original Weibull equation. The exponent of the Weibull equation can be attributed to the heterogeneity of the process and can be explained by fractal kinetics concepts. Also, the solubility/dose ratio is present explicitly as a parameter and allows to obtain estimates of the solubility even when the dissolution data do not reach the solubility level. The use of the developed branched equations gives better fittings and specific physical meaning to the dissolution parameters. Also, the findings underline the fact that even in the simplest, first-order case, the speed of the dissolution process depends on the dose, a fact of great importance in biopharmaceutic classification for regulatory purposes.

The competitive binding of diflunisal and three well-known uraemic toxins (3-indoxyl sulfate, indole-3-acetic acid and hippuric acid) to bovine serum albumin (BSA), human serum albumin (HSA) and human plasma was studied by direct potentiometry. The method used the potentiometric drug ion-probe technique with a home-made ion sensor (electrode) selective to the drug anion. The site-oriented Scatchard model was used to describe the binding of diflunisal to BSA, HSA and human plasma, while the general competitive binding model was used to calculate the binding parameters of the three uraemic toxins to BSA. Diflunisal binding parameters, number of binding sites, n(i) and association constants for each class of binding site, K-i, were calculated in the absence and presence of uraemic toxins. Although diflunisal exhibits high binding affinity for site I of HSA and the three uraemic toxins bind primarily to site II, strong interaction was observed between the drug and the three toxins, which were found to affect the binding of diflunisal on its primary class of binding sites on both BSA and HSA molecules and on human plasma. These results are strong evidence that the decreased binding of diflunisal that occurs in uraemic plasma may not be solely attributed to the lower albumin concentration observed in many patients with renal failure. The uraemic toxins that accumulate in uraemic plasma may displace the drug from its specific binding sites on plasma proteins, resulting in increased free drug plasma concentration in uraemic patients.

Purpose: (1) To develop novel scaled bioequivalence (BE) limits with levelling-off properties based solely on variability considerations and (2) to evaluate their performance in comparison to the classic unscaled BE limits 0.80-1.25, the expanded BE limits 0.75-1.33 and the recently proposed Geometric Mean Ratio (GMR)-dependent scaled BE limits BELscW (Karalis et al., Eur. J. Pharm. Sci., 26:54-61, 2005). Materials and Methods: Two model functions were used to ensure the gradual change of the BE limits from a starting value towards a predefined plateau value. Plots of the new BE limits and extreme GMR values ensuring BE as a function of the coefficient of variation (CV) were constructed. Two-period crossover BE studies with 12, 24, or 36 subjects were simulated assuming CV values from 10 to 60%. Power curves were constructed by recording the percentage of accepted BE studies as the true GMR was raised from 1.00 to 1.50. The percentage of the true GMR within the simulated BE limits vs. true GMR was used to evaluate the estimation accuracy of the scaled methods. Results: Depending on the parameters' values of the model functions, the scaled BE limits exhibit different performance. Four new scaled BE limits, showing favourable performance for the evaluation of average BE are presented. At low variability levels two of the novel BE limits show similar performance to the 0.80-1.25 criterion, while the other two (as expected from their design) appear to be less permissive. At high CV values (30, 40%) all new BE limits exhibit much higher statistical power than the 0.80-1.25 criterion. They show almost identical behavior with the expanded 0.75-1.33 limits and appear to be less permissive than BELscW. Finally, the percentage of the true GMR within the simulated BE limits vs. true GMR shows a sharp decline. Due to the absence of the GMR factor in the model functions a more accurate estimation of the new scaled BE limits, compared to BELscW, is observed. Conclusions: The new scaled BE limits appear to be highly effective at all levels of variation investigated and present satisfactory estimation accuracy.

Dissolution research started to develop about 100 years ago as a field of physical chemistry and since then important progress has been made. However, explicit interest in drug related dissolution has grown only since the realisation that dissolution is an important factor of drug bioavailability in the 1950s. This review attempts to account the most important developments in the field, from a historical point of view. It is structured in a chronological order, from the theoretical foundations of dissolution, developed in the first half of the 20th century, and the development of a relationship between dissolution and bioavailability in the 1950s, going to the more recent developments in the framework of the Biopharmaceutics Classification System (BCS). Research on relevant fields of pharmaceutical technology, like sustained release formulations, where drug dissolution plays an important role, is reviewed. The review concludes with the modem trends on drug dissolution research and their regulatory implications. (c) 2006 Elsevier B.V. All rights reserved.

Previous findings from our group based on Monte Carlo simulations indicated that Fickian drug release from Euclidian or fractal matrices can be described with the Weibull function. In this study, the entire drug release kinetics of various published data and experimental data from commercial or prepared controlled release formulations of diltiazem and diclofenac are analyzed using the Weibull function. The exponent of time b of the Weibull function is linearly related to the exponent n of the power law derived from the analysis of the first 60% of the release curves. The value of the exponent b is an indicator of the mechanism of transport of a drug through the polymer matrix. Estimates for b < 0.75 indicate Fickian diffusion in either fractal or Euclidian spaces while a combined mechanism (Fickian diffusion and Case 11 transport) is associated with b values in the range 0.75 < b < 1. For values of b higher than 1, the drug transport follows a complex release mechanism. (c) 2005 Elsevier B.V. All rights reserved.