Statistical significance of polymeric physicochemical properties in the development of formulations containing a drug from neutral class

• Published in: Arabian journal of chemistry Vol. 9; no. S2; pp. S1915 - S1927
• Main Authors: Gaikwad, Vinod L., Bhatia, Manish S., Singhvi, Indrajeet
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2016; Elsevier
• Subjects: Mathematical model; Neutral drug release; Polymer system; QSPR; Transportability profile; QSPR; Neutral drug release; Mathematical model; Polymer system; Transportability profile
• ISSN: 1878-5352; 1878-5379
• DOI: 10.1016/j.arabjc.2015.06.022

The main objective of the present study was to develop quantitative-structure property relationship (QSPR) models with predictability for release, transportability and related properties of formulation containing a neutral drug (glimepiride) based on polymeric properties. Such physicochemical properties are measure of polymers’ behavior in deciding release, transportability and bioavailability of drug. Therefore comprehensive study of properties could help in deciding proper polymer composite for formulation with required characteristics. A total of nine glimepiride (GLMP) tablet batches were prepared using three polymers representing extended, moderate and immediate release categories. Molecular descriptors were calculated from polymeric structures and correlated with formulation characteristics. This leads to generation of predictive models. Compatibility between drug-excipients was confirmed. Weight uniformity, drug content, hardness and friability tests showed acceptable results. In vitro dissolution kinetics exhibited Korsmeyer-peppas model as best fit. Best correlation coefficient and validation of developed QSPRs showed powerful predictability for properties. Transportability was influenced by release rate together with molecular size, pKa, logP and water solubility of GLMP. Generated models were found to significantly predict the release, transportability and related formulation properties. QSPR models were developed with enough prediction potential for the properties of formulation containing any neutral drug and could also help to decide the formulation composition for required characteristics together with pharmacoeconomic impact with respect to time, cost and material.