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Artificial intelligence for solving solubility problems in drug development

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Artificial intelligence for solving solubility problems in drug development

Journal of Pharmacy and Pharmacology

First published:  4 December 2017
DOI: 
10.1111/jphp.12850

Safa Damiati, Norman Smith, Maria Herrero-Zazo, Luigi Martini, Jane Lawrence and David Barlow

Objective: The aim of the work reported here was to use artificial intelligence to model the apparent increase in aqueous solubility of poorly water-soluble drugs afforded by the use of hydrotropes, and thereby to gain a better understanding of the mechanism(s) underlying this phenomenon.

Methods: For the non-steroidal anti-inflammatory drugs (NSAIDs), indomethacin, ibuprofen and mefenamic acid, the solubilising effects of a set of 11 potential hydrotropes were determined experimentally using UV/HPLC. These solubility data, together with 19 molecular descriptors relating to the drugs and hydrotropes, were used to train an ANN.

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