ABSTRACT-PURPOSE.Comparative drug release kinetics from nanoparticles was carried out using conventional and our novel models with the aim of finding a general model applicable to multi mechanistic release. Theoretical justification for the two best general models was also provided for the first time. METHODS. Ten conventional models and three models developed in our laboratory were applied to release data of 32 drugs from 106 nanoparticle formulations collected from literature. The accuracy of the models was assessed employing mean percent error (E) of each data set, overall mean percent error (OE) and number of Es less than 10 percent. RESULTS. Among the models the novel reciprocal powered time (RPT), Weibull (W) and log-probability (LP) ones produced OE values of 6.47, 6.39 and 6.77, respectively. The OEs of other models were higher than 10%. Also the number of errors less than 10% for the models was 84.9, 80.2 and 78.3 percents of total number of data sets. CONCLUSIONS. Considering the accuracy criteria the reciprocal powered time model could be suggested as a general model for analysis of multi mechanistic drug release from nanoparticles. Also W and LP models were the closest to the suggested model RPT.

Introduction: Oral drug delivery is the most favored route of drug administration. However, poor oral bioavailability is one of the leading reasons for insufficient clinical efficacy. Improving oral absorption of drugs with low water solubility and/or low intestinal membrane permeability is an active field of research. Cocrystallization of drugs with appropriate coformers is a promising approach for enhancing oral bioavailability. Methods: In the present review, we have focused on recent advances that have been made in improving oral absorption through cocrystallization. The covered areas include supersaturation and its importance on oral absorption of cocrystals, permeability of cocrystals through membranes, drug-coformer pharmacokinetic (PK) interactions, conducting in vivo-in vitro correlations for cocrystals. Additionally, a discussion has been made on the integration of nanocrystal technology with supramolecular design. Marketed cocrystal products and PK studies in human subjects are also reported. Results: Considering supersaturation and consequent precipitation properties is necessary when evaluating dissolution and bioavailability of cocrystals. Appropriate excipients should be included to control precipitation kinetics and to capture solubility advantage of cocrystals. Beside to solubility, cocrystals may modify membrane permeability of drugs. Therefore, cocrystals can find applications in improving oral bioavailability of poorly permeable drugs. It has been shown that cocrystals may interrupt cellular integrity of cellular monolayers which can raise toxicity concerns. Some of coformers may interact with intestinal absorption of drugs through changing intestinal blood flow, metabolism and inhibiting efflux pumps. Therefore, caution should be taken into account when conducting bioavailability studies. Nanosized cocrystals have shown a high potential towards improving absorption of poorly soluble drugs. Conclusions: Cocrystals have found their way from the proof-of-principle stage to the clinic. Up to now, at least two cocrystal products have gained approval from regulatory bodies. However, there are remaining challenges on safety, predicting in vivo behavior and revealing real potential of cocrystals in the human.

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Experimental solubilities of three benzodiazepines (chlordiazepoxide, diazepam, and lorazepam) in ethanol + water mixtures at 303.2 K are reported. The solubility of drugs was increased with the addition of ethanol and reached the maximum value of a volume fraction of 90 % of ethanol. The Jouyban-Acree model was used to fit the experimental data, and the solubilities were reproduced using previously trained version of the Jouyban-Acree model and the solubility data in monosolvents in which the overall mean relative deviations (OMRDs) of the models were 8.6 %, 21.9 % and 19.3 %, respectively, for the fitted model, the trained version for ethanol + water mixtures and generally trained version for various organic solvents + water mixtures.