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Quantitative Structure-Property Relationship Modeling for Prediction of Hydrophilic Drug Entrapment in Liposomes for Lung Targeted Delivery

Abstract

Targeted delivery to lung tissues play a vital role in asthma patients since the biological barriers like trachea, bronchi, bronchioles, and alveoli restrict the passage of a drug across it. Various cysteinyl leukotriene receptors such as LTC4, LTD4, and LTE4 present at lung site (especially bronchi), whereby release of leukotrienes contribute bronchoconstriction that leads to asthma and other lung disorders. Therefore, leukotriene receptor antagonists like Montelukast sodium (hydrophilic and potent LTC4 antagonist) are preferred in the treatment of asthma. Database of phospholipids used in liposomal formulations for the hydrophilic drug was screened for development of quantitative structure-property relationship (QSPR) model. Further, by using partial least square and principal component analysis methods, the best set of descriptors (SlogP_VSA2, TPSA, vsa_other, PEOE_VSA_PPOS) out of 115 were selected depending on % drug entrapment. Based on best descriptors, phosphatidylcholine was selected as an independent variable along with cholesterol for implementation of the factorial design in the preparation of liposomal batches. The optimized batch showed 84% entrapment efficiency, which was further studied by considering critical attributes in process analytical technique (PAT) study. The optimized batch was lyophilized which showed 76% drug release tested by dialysis method. The ex-vivo drug diffusion studied across bronchial smooth muscle cells showed 11% diffusion (90 min) attributed to the binding of maximum drug amount to cysteinyl leukotriene receptors. Developed liposomal formulation have achieved the desired objective of targeted delivery by application of QSPR and PAT methodologies.

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Publication details

The article was received on 30 Dec 2017, accepted on 07 Feb 2018 and first published on 08 Feb 2018


Article type: Paper
DOI: 10.1039/C7NJ05190E
Citation: New J. Chem., 2018, Accepted Manuscript
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    Quantitative Structure-Property Relationship Modeling for Prediction of Hydrophilic Drug Entrapment in Liposomes for Lung Targeted Delivery

    N. M. Bhatia, V. L. Gaikwad, R. V. Mane, R. P. Dhavale and M. S. Bhatia, New J. Chem., 2018, Accepted Manuscript , DOI: 10.1039/C7NJ05190E

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