Biomedical subjects

Siavoush Dastmalchi

Publications and source records attributed to Siavoush Dastmalchi.

4 recordsLinked to original sources

PubMed2007

Kinetic analysis of chlorpropamide dissolution from solid dispersions.

Solid dispersions (SDs) of chlorpropamide were prepared by the solvent deposition technique using two grades of microcrystalline cellulose as carrier materials with different ratios of drug to carrier. The dissolution rate of chlorpropmide from the SDs was carried out at two physiological pH values of 1.1 and 7.25 simulating gastric and intestinal environments. The dissolution was dependent on the grade, the ratio of drug to carrier and pH. The higher dissolution was observed for more hydrophilic grade of the carrier as well as the higher ratio of carrier to drug. At the higher pH the drug dissolved much faster than the lower pH. X-ray diffraction showed some reduced drug crystallinity in SDs whereas infrared spectroscopy revealed no drug interactions with solvent and the carriers. The enhanced dissolution was attributed to the reduced drug crystallinity, decreased particle size, increased wettability and reduced aggregation of the hydrophobic drug particles. A novel model denoted as reciprocal powered time model with its theoretical justification was employed to analyze the dissolution data and proved to be superior to commonly used models for the analysis of the data. There was a quantitative relation between the model parameter and the ratio of carrier to drug which could be of value in dissolution rate prediction.

Chlorpropamide↗

PubMed2006

QSPR models for the prediction of apparent volume of distribution.

An estimate of volume of distribution (V(d)) is of paramount importance both in drug choice as well as maintenance and loading dose calculations in therapeutics. It can also be used in the prediction of drug biological half life. This study employs quantitative structure-pharmacokinetic relationship (QSPR) techniques for the prediction of volume of distribution. Values of V(d) for 129 drugs were collated from the literature. Structural descriptors consisted of partitioning, quantum mechanical, molecular mechanical, and connectivity parameters calculated by specialized software and pK(a) values obtained from ACD labs/log D database. Genetic algorithm and stepwise regression analyses were used for variable selection and model development. Models were validated using a leave-many-out procedure. QSPR analyses resulted in a number of significant models for acidic and basic drugs separately, and for all the drugs. Validation studies showed that mean fold error of predictions for the selected models were between 1.79 and 2.17. Although separate QSPR models for acids and bases resulted in lower prediction errors than models for all the drugs, the external validation study showed a limited applicability for the equation obtained for acids. Therefore, the universal model that requires only calculated structural descriptors was recommended. The QSPR model is able to predict the volume of distribution of drugs belonging to different chemical classes with a prediction error similar to that of the other more complicated prediction methods including the commonly practiced interspecies scaling. The structural descriptors in the model can be interpreted based on the known mechanisms of distribution and the molecular structures of the drugs.

Algorithms↗

PubMed2005

Enhancing dissolution, serum concentrations and hypoglycemic effect of glibenclamide using solvent deposition technique.

PURPOSE: Glibenclamide is practically insoluble in water and its GI absorption is limited by its dissolution rate. Therefore, to enhance the drug dissolution, serum concentrations and its hypoglycemic effects, it was formulated as solid dispersions and evaluated the relevant in vitro and in vivo parameters. METHODS: The drug solid dispersions were prepared by solvent deposition technique using microcrystalline cellulose as the carrier in different ratios and their dissolution rates were compared to those of pure drug and its physical mixture with carrier. Drug serum concentrations and hypoglycemic effects in rabbits of pure drug, a physical mixture and the corresponding solid dispersion were investigated. In order to elucidate the observed in vitro and in vivo differences, IR spectroscopy and x-ray diffraction patterns of the formulations were studied. RESULTS: The solid dispersion with the drug to carrier ratio of 1:19 showed the highest dissolution rate with the dissolution efficiency (DE) of 44.42 in comparison to pure drug (DE = 3.82), physical mixture (DE = 4.91) and other solid dispersions (DE between 13.85-39.94) and also produced higher drug serum concentrations (more than 4 times at 6th hour post dose) as well as enhanced hypoglycemic effects relative to pure drug and its corresponding physical mixture. CONCLUSIONS: Solvent deposition technique was proved an effective tool of increasing dissolution probably due to enhanced wettability and reduced drug particle size, which in turn led to enhance drug serum concentrations and its hypoglycemic effects. Strong quantitative correlations were established between dissolution parameter and parameters related to serum concentrations as well as hypoglycemic effects.

Animals↗

PubMed2004

Presence of transient helical segments in the galanin-like peptide evident from (1)H NMR, circular dichroism, and prediction studies.

Galanin and its newly discovered relative galanin-like peptide (GALP) are neuropeptides that are implicated in the neuroendocrine regulation of body weight and reproduction. GALP encompasses within its sequence the first 13 residues of galanin, known to be crucial to binding and activation of galanin receptor (GalR) subtypes. Using 2D-NMR and circular dichroism spectroscopy we demonstrated that GALP does not adopt a preferred conformation in pure water alone. However, it shows characteristics of transient turn-like structures in two distinct regions of its sequence, 11-23 and 41-49. These transient ordered structures, nascent helices, probably form stable helical structures upon addition of the helix-inducing solvent, trifluoroethanol, as determined by circular dichroism studies. Secondary structure prediction methods also predict the presence of two helical regions in the sequence of GALP overlapping reasonably with those regions identified as nascent helical structures by experimental methods.

Animals↗