Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions.
Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on subs...
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2012
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oai:doaj.org-article:30d50f9a936c431ab6d2c59646a5fe172021-11-18T05:51:07ZLiterature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions.1553-734X1553-735810.1371/journal.pcbi.1002614https://doaj.org/article/30d50f9a936c431ab6d2c59646a5fe172012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22912565/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.Jon D DukeXu HanZhiping WangAbhinita SubhadarshiniShreyas D KarnikXiaochun LiStephen D HallYan JinJ Thomas CallaghanMarcus J OverhageDavid A FlockhartR Matthew StrotherSara K QuinneyLang LiPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 8, Iss 8, p e1002614 (2012) |
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| collection |
DOAJ |
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EN |
| topic |
Biology (General) QH301-705.5 |
| spellingShingle |
Biology (General) QH301-705.5 Jon D Duke Xu Han Zhiping Wang Abhinita Subhadarshini Shreyas D Karnik Xiaochun Li Stephen D Hall Yan Jin J Thomas Callaghan Marcus J Overhage David A Flockhart R Matthew Strother Sara K Quinney Lang Li Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| description |
Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms. |
| format |
article |
| author |
Jon D Duke Xu Han Zhiping Wang Abhinita Subhadarshini Shreyas D Karnik Xiaochun Li Stephen D Hall Yan Jin J Thomas Callaghan Marcus J Overhage David A Flockhart R Matthew Strother Sara K Quinney Lang Li |
| author_facet |
Jon D Duke Xu Han Zhiping Wang Abhinita Subhadarshini Shreyas D Karnik Xiaochun Li Stephen D Hall Yan Jin J Thomas Callaghan Marcus J Overhage David A Flockhart R Matthew Strother Sara K Quinney Lang Li |
| author_sort |
Jon D Duke |
| title |
Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| title_short |
Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| title_full |
Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| title_fullStr |
Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| title_full_unstemmed |
Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| title_sort |
literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2012 |
| url |
https://doaj.org/article/30d50f9a936c431ab6d2c59646a5fe17 |
| work_keys_str_mv |
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| _version_ |
1718424717510049792 |