WFRF:(Alzghoul Ahmad)
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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03583naa a2200373 4500 | |
| 001 | oai:DiVA.org:uu-232174 | |
| 003 | SwePub | |
| 008 | 140915s2014 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-2321742 URI |
| 024 | 7 | a https://doi.org/10.1021/mp500303a2 DOI |
| 040 | a (SwePub)uu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a art2 swepub-publicationtype |
| 100 | 1 | a Alhalaweh, Amjadu Uppsala universitet,Institutionen för farmaci4 aut0 (Swepub:uu)amjal166 |
| 245 | 1 0 | a Computational predictions of glass-forming ability and crystallization tendency of drug molecules |
| 264 | c 2014-07-30 | |
| 264 | 1 | b American Chemical Society (ACS),c 2014 |
| 338 | a print2 rdacarrier | |
| 520 | a 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. | |
| 650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Medicinska och farmaceutiska grundvetenskaperx Farmaceutiska vetenskaper0 (SwePub)301012 hsv//swe |
| 650 | 7 | a MEDICAL AND HEALTH SCIENCESx Basic Medicinex Pharmaceutical Sciences0 (SwePub)301012 hsv//eng |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
| 700 | 1 | a Alzghoul, Ahmadu Uppsala universitet,Datalogi,Uppsala Database Laboratory4 aut0 (Swepub:uu)ahmal479 |
| 700 | 1 | a Kaialy, Waseem4 aut |
| 700 | 1 | a Mahlin, Dennyu Uppsala universitet,Institutionen för farmaci4 aut0 (Swepub:uu)dma10394 |
| 700 | 1 | a Bergström, Christel A. S.u Uppsala universitet,Institutionen för farmaci4 aut0 (Swepub:uu)cjo29958 |
| 710 | 2 | a Uppsala universitetb Institutionen för farmaci4 org |
| 773 | 0 | t Molecular Pharmaceuticsd : American Chemical Society (ACS)g 11:9, s. 3123-3132q 11:9<3123-3132x 1543-8384x 1543-8392 |
| 856 | 4 | u https://doi.org/10.1021/mp500303a |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-232174 |
| 856 | 4 8 | u https://doi.org/10.1021/mp500303a |
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