Hydrogels are of great interest in delivering drugs through their polymeric network. Hydrogels of macroporous copolymer 2-hydroxy ethyl methacrylate (HEMA) with acrylic acid (AA) were prepared in the presence of N,N 0 -methylene-bis-acrylamide as crosslinker and benzoyl peroxide as initiator. The structure of the copolymer, hydrogel character, and biodegradability have already been discussed in our previous article (Mohapatra et al., Polym Polym Compos 2005, 13, 807) entitled P(HEMA-co-AA) as Novel Biodegradable Macroporous Hydrogel. The current study involves the in vitro and in vivo release of alfuzosin hydrochloride at pH 7.0 and 9.2, taking different concentrations of drug and hydrogel. The percentage of drug entrapment study was done and the stability study was also performed according to I.C.H. guidelines for a period of 6 months giving satisfactory results.

Hydrogels of macroporous copolymer, 2-hydroxyl ethyl methacrylate with acrylic acid, were prepared in the presence of N,N'-methylene-bis-acrylamide as crosslinker and benzoyl peroxide as initiator. The structure of the copolymer was characterized by FT-IR, H1-NMR and scanning electron microscopy and the thermal stability by thermogravimetric analysis. Its hydrogel character was observed by studying the swelling of the copolymers simply by measuring weight gain and weight loss. The swelling was determined in distilled water, saline solution and buffers of pH, 4 and 9.2, was found to increase with increasing pH, attaining a maximum at pH 9.2. The biodegradability of the copolymers was studied by introducing microbes to the culture media along with the prepared sample and it was verified by examining the surface morphology by SEM. The rate of biodegradation was monitored by the CO2 release method.

In this paper a generalized class of finite population variance is suggested and its large sample bias and mean square error are derived. Further some special cases of this class are considered along with a numerical example to compute and compare their biases and mean square errors.

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