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Published on: June 3, 2014
Prediction and elucidation of factors affecting solubilisation of imatinib mesylate in lipids
Karthik Siram1, Selvaraj Divakar2, Chellan Vijaya Raghavan3
1Department of Pharmaceutics, PSG College of Pharmacy, Peelamedu, Coimbatore, India.
The physico-chemical properties of lipids influencing the solubilisation of imatinib mesylate (IM) in lipid matrix were evaluated and a statistical model to predict the same has been derived in the present study. After experimental quantification of IM solubility in various lipids, Hansen Hildebrand's total solubility parameters were calculated in order to study the role of various forces connected to lipid-drug interaction. To develop a relationship between the various descriptors of the lipids and experimental solubility of IM in lipids (% w/w), quantitative structure-solubility relationship (QSSR) was used. To generate equations that can predict the solubility of IM in lipids (%w/w), multiple linear regression was used. Amongst the various lipids tested, glyceryl monostearate and behenic acid solubilised the highest (6.19 ± 0.22%) and lowest (0.01 ± 0.01%) amounts of IM respectively. Our results suggested that alkyl chain length, polarity of the lipids, index of cohesive interaction in solids, estimated number of hydrogen bonds that would be accepted by the solute from water molecules in an aqueous solution, estimated number of hydrogen bonds that would be donated by the solute to water molecules in an aqueous solution and solvent accessible surface area collectively play a significant role in solubilising IM in the lipids. The equation developed could predict the solubility of IM in lipids with good accuracy (R2pred = 0.912).
The physico-chemical properties of lipids influencing the solubilisation of imatinib mesylate (IM) in lipid matrix were evaluated and a statistical model to predict the same has been derived in the present study. After experimental quantification of IM solubility in various lipids, Hansen Hildebrand's total solubility parameters were calculated in order to study the role of various forces connected to lipid-drug interaction. To develop a relationship between the various descriptors of the lipids and experimental solubility of IM in lipids (% w/w), quantitative structure-solubility relationship (QSSR) was used. To generate equations that can predict the solubility of IM in lipids (%w/w), multiple linear regression was used. Amongst the various lipids tested, glyceryl monostearate and behenic acid solubilised the highest (6.19 ± 0.22%) and lowest (0.01 ± 0.01%) amounts of IM respectively. Our results suggested that alkyl chain length, polarity of the lipids, index of cohesive interaction in solids, estimated number of hydrogen bonds that would be accepted by the solute from water molecules in an aqueous solution, estimated number of hydrogen bonds that would be donated by the solute to water molecules in an aqueous solution and solvent accessible surface area collectively play a significant role in solubilising IM in the lipids. The equation developed could predict the solubility of IM in lipids with good accuracy (R2pred = 0.912).
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

