Composite film-coated tablets intended for colon-specific delivery of 5-aminosalicylic acid: using deesterified pectin.

Combinations of Eudragit RS and deesterified pectin, polygalacturonic acid (PGA), or its potassium and sodium salts, when applied as a film coat, has a potential value as a colon-specific delivery system. Dispersions of PGA in Eudragit RS were used as the film former for coating of 5-aminosalicylic acid (5-ASA) tablet cores. Drug release behavior was assessed, in vitro, under simulating conditions in term of pH and time to in vivo during their transit to the colon. Negligible drug release occurred during first 5 hr where the coated tablets were in the stomach and small intestine. After that, the pectinolytic enzymes were added into the pH 6.8 medium to simulate the in vivo condition where there is the digestion of bacteria in the colon. The release of 5-ASA from the coated tablets occurred linearly as a function of time. Drug release depended on the composition of the mixed film, as well as the ratio of Eudragit RS to PGA or its salts. The highest drug release from the coated tablets of about 40% was obtained when the ratio of Eudragit RS to potassium salt of PGA was 2.5 to 1. Drug release profiles seemed to conform to the mechanism involving the osmotically driven release and formation of channels in the film caused by dissolution of PGA salts. Channel formation was, in most cases, activated by the presence of pectinolytic enzymes, showing that the PGA in the mixed film was subjected to enzymic breakdown. In conclusion, PGA could be used as an additive in Eudragit RS films to control the release of colonic delivery system.

Quantitative structure/property relationship analysis on aqueous solubility using genetic algorithm-combined partial least squares method.

The present study was initiated to generate a model of predicting aqueous solubility of substances from their molecular structure. For 211 drugs or drug-like compounds, their topological indices were calculated by Molconn-Z software. The optimal subset of the descriptors for the prediction of aqueous solubility was determined by genetic algorithm in combination with partial least squares (PLS) method. Thirty-four descriptors were selected by this method. Using 29 of the descriptors selected, of which the scaled PLS coefficient was significant, the cross-validated predictive q2 was 0.785 with 19 principal components that was the optimal and the standard error of prediction was 0.676. Thus, it is suggested that the model obtained would exhibit a good performance in predicting the aqueous solubility of compounds.