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The objective of this work was to prepare and optimize the fast-dissolving film of salbutamol sulphate, which can be useful in an acute attack of asthma. The film was prepared using a solvent evaporation technique and is taken through the sublingual route. The film contains polyvinyl alcohol as a polymer, glycerol as a plasticizer, and mannitol as filler. A 33 full factorial design was utilized for the optimization of the effect of independent variables such as amount of polyvinyl alcohol, amount of glycerol, amount of mannitol on the mechanical properties, and % drug release of film. The multiple regression analysis of the results led to equations that adequately describe the influence of the independent variables on the selected responses. Polynomial regression equations and contour plots were used to relate the dependent and independent variables. The experimental results indicated that polymer concentration, plasticizer concentration, and filler concentration had complex effects on film mechanical behavior and % drug release. Furthermore, the desirability function was employed in order to determine the best batch out of all 27 batches of the factorial design. The % relative error was calculated, which showed that observed responses were in close agreement with the predicted values calculated from the generated regression equations. It was found that the optimum values of the responses for fast release film could be obtained at medium levels of polyvinyl alcohol and glycerol, and a high level of mannitol. The prepared film was clear, transparent, and had a smooth surface. The concept of similarity factors Sd was used to prove similarity of dissolution between distilled water and simulated saliva (pH 6.8) or simulated gastric fluid (pH 1.2).

This work examines the influence of various process parameters (like sodium alginate concentration, calcium chloride concentration, and hardening time) on papain entrapped in ionotropically cross-linked alginate beads for stability improvement and site-specific delivery to the small intestine using neural network modeling. A 3(3) full-factorial design and feed-forward neural network with multilayer perceptron was used to investigate the effect of process variables on percentage of entrapment, time required for 50% and 90% of the enzyme release, particle size, and angle of repose. Topographical characterization was conducted by scanning electron microscopy, and entrapment was confirmed by Fourier transform infrared spectroscopy and differential scanning calorimetry. Times required for 50% (T(50)) and 90% (T(90)) of enzyme release were increased in all 3 of the process variables. Percentage entrapment and particle size were found to be directly proportional to sodium alginate concentration and inversely proportional to calcium chloride concentration and hardening time, whereas angle of repose and degree of cross-linking showed exactly opposite proportionality. Beads with >90% entrapment and T(50) of <10 minutes could be obtained at the low levels of all 3 of the process variables. The inability of beads to dissolve in acidic environment, with complete dissolution in buffer of pH >or=6.8, showed the suitability of beads to release papain into the small intestine. The shelf-life of the capsules prepared using the papain-loaded alginate beads was found to be 3.60 years compared with 1.01 years of the marketed formulation. It can be inferred from the above results that the proposed methodology can be used to prepare papain-loaded alginate beads for stability improvement and site-specific delivery.

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