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Sökning: onr:"swepub:oai:DiVA.org:su-135045" > Cheminformatics-aid...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004584naa a2200541 4500
001oai:DiVA.org:su-135045
003SwePub
008161031s2016 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-1350452 URI
0247 a https://doi.org/10.1093/jamia/ocv1272 DOI
040 a (SwePub)su
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Low, Yen S.4 aut
2451 0a Cheminformatics-aided pharmacovigilance :b application to Stevens-Johnson Syndrome
264 c 2015-10-24
264 1b Oxford University Press (OUP),c 2016
338 a print2 rdacarrier
520 a Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%-81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations.
650 7a NATURVETENSKAPx Data- och informationsvetenskap0 (SwePub)1022 hsv//swe
650 7a NATURAL SCIENCESx Computer and Information Sciences0 (SwePub)1022 hsv//eng
650 7a SAMHÄLLSVETENSKAPx Medie- och kommunikationsvetenskap0 (SwePub)5082 hsv//swe
650 7a SOCIAL SCIENCESx Media and Communications0 (SwePub)5082 hsv//eng
650 7a MEDICIN OCH HÄLSOVETENSKAPx Medicinska och farmaceutiska grundvetenskaperx Samhällsfarmaci och klinisk farmaci0 (SwePub)301042 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Basic Medicinex Social and Clinical Pharmacy0 (SwePub)301042 hsv//eng
650 7a NATURVETENSKAPx Biologix Bioinformatik och systembiologi0 (SwePub)106102 hsv//swe
650 7a NATURAL SCIENCESx Biological Sciencesx Bioinformatics and Systems Biology0 (SwePub)106102 hsv//eng
653 a pharmacovigilance
653 a cheminformatics
653 a QSAR
653 a Stevens-Johnson Syndrome
653 a adverse drug reactions
7001 a Caster, Olau Stockholms universitet,Institutionen för data- och systemvetenskap,Uppsala Monitoring Center, Sweden4 aut0 (Swepub:su)olca0104
7001 a Bergvall, Tomas4 aut
7001 a Fourches, Denis4 aut
7001 a Zang, Xiaoling4 aut
7001 a Norén, G. Niklasu Stockholms universitet,Matematiska institutionen,Uppsala Monitoring Center, Sweden4 aut
7001 a Rusyn, Ivan4 aut
7001 a Edwards, Ralph4 aut
7001 a Tropsha, Alexander4 aut
7102 a Stockholms universitetb Institutionen för data- och systemvetenskap4 org
7730 t JAMIA Journal of the American Medical Informatics Associationd : Oxford University Press (OUP)g 23:5, s. 968-978q 23:5<968-978x 1067-5027x 1527-974X
8564 u https://doi.org/10.1093/jamia/ocv127y Fulltext
8564 u https://academic.oup.com/jamia/article-pdf/23/5/968/7050239/ocv127.pdf
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-135045
8564 8u https://doi.org/10.1093/jamia/ocv127

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