Quantitative structure property relationship modeling of excipient properties for prediction of formulation characteristics
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- 作者：Vinod L. Gaikwada ; vinod_gaikwad29@yahoo.com" class="auth_mail" title="E-mail the corresponding author ; Neela M. Bhatiab ; neelabhatia@yahoo.co.uk" class="auth_mail" title="E-mail the corresponding author ; Sujit A. Desaib ; sujitdesai37@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Manish S. Bhatiab ; drmsbhatia13@gmail.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：API ; active pharmaceutical ingredient ; CCS ; croscarmellose sodium ; ENM ; enalapril maleate ; HPMC ; hydroxy propyl methyl cellulose ; IPA ; isopropyl alcohol ; MCC ; microcrystalline cellulose ; MDS ; molecular design suite ; MET ; metformin hydrochloride ; MLR ; multiple linear regression ; PVP ; polyvinyl pyrrolidone ; QSPR ; quantitative structure property relationship ; SSG ; sodium starch glycolate ; USP ; United States Pharmacopeia
- 刊名：Carbohydrate Polymers
- 出版年：2016
- 出版时间：20 October 2016
- 年：2016
- 卷：151
- 期：Complete
- 页码：593-599
- 全文大小：772 K
文摘
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Corrected values of molecular descriptors for excipients structure were calculated.
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These descriptor values were then correlated with formulation characteristics.
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This leads to development of predictive QSPR models.
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QSPR models after validation could be able to predict the formulation composition.
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This could have a positive economic impact on formulation design trials.