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Computational predi...
Computational predictions of glass-forming ability and crystallization tendency of drug molecules
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- Alhalaweh, Amjad (author)
- Uppsala universitet,Institutionen för farmaci
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- Alzghoul, Ahmad (author)
- Uppsala universitet,Datalogi,Uppsala Database Laboratory
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Kaialy, Waseem (author)
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- Mahlin, Denny (author)
- Uppsala universitet,Institutionen för farmaci
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- Bergström, Christel A. S. (author)
- Uppsala universitet,Institutionen för farmaci
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(creator_code:org_t)
- 2014-07-30
- 2014
- English.
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In: Molecular Pharmaceutics. - : American Chemical Society (ACS). - 1543-8384 .- 1543-8392. ; 11:9, s. 3123-3132
- Related links:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
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- Amorphization is an attractive formulation technique for drugs suffering from poor aqueous solubility as a result of their high lattice energy. Computational models that can predict the material properties associated with amorphization, such as glass-forming ability (GFA) and crystallization behavior in the dry state, would be a time-saving, cost-effective, and material-sparing approach compared to traditional experimental procedures. This article presents predictive models of these properties developed using support vector machine (SVM) algorithm. The GFA and crystallization tendency were investigated by melt-quenching 131 drug molecules in situ using differential scanning calorimetry. The SVM algorithm was used to develop computational models based on calculated molecular descriptors. The analyses confirmed the previously suggested cutoff molecular weight (MW) of 300 for glass-formers, and also clarified the extent to which MW can be used to predict the GFA of compounds with MW < 300. The topological equivalent of Grav3_3D, which is related to molecular size and shape, was a better descriptor than MW for GFA; it was able to accurately predict 86% of the data set regardless of MW. The potential for crystallization was predicted using molecular descriptors reflecting Hückel pi atomic charges and the number of hydrogen bond acceptors. The models developed could be used in the early drug development stage to indicate whether amorphization would be a suitable formulation strategy for improving the dissolution and/or apparent solubility of poorly soluble compounds.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Publication and Content Type
- ref (subject category)
- art (subject category)
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