Literature DB >> 19177064

Data-driven methods to discover molecular determinants of serious adverse drug events.

A P Chiang1, A J Butte.   

Abstract

The dangers of serious adverse drug reactions (SADRs) are well known to clinicians, pharmacologists, and the lay public. Efforts to elucidate the molecular mechanisms behind SADRs have made significant progress through genetics and gene expression measurements. However, as the field of pharmacology adopts the same novel higher-density measurement modalities that have proven successful in other areas of biology, one wonders whether there can be more ways to benefit from the explosion of data created by these tools. The development of analytic tools and algorithms to interpret these biological data to create tools for medicine is central to the field of translational bioinformatics. In this review we introduce some of the types of SADR predictors that are required, and we discuss several databases that are publicly available for the study of SADRs, ranging from clinical to molecular measurements. We also describe recent examples of how bioinformatics methods coupled with data repositories can advance the science of SADRs.

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Year:  2009        PMID: 19177064      PMCID: PMC2726746          DOI: 10.1038/clpt.2008.274

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  77 in total

1.  Molecular basis of the human dihydropyrimidine dehydrogenase deficiency and 5-fluorouracil toxicity.

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Journal:  J Clin Invest       Date:  1996-08-01       Impact factor: 14.808

2.  FDA is incapable of protecting US "against another Vioxx".

Authors:  Jeanne Lenzer
Journal:  BMJ       Date:  2004-11-27

3.  Biological spectra analysis: Linking biological activity profiles to molecular structure.

Authors:  Anton F Fliri; William T Loging; Peter F Thadeio; Robert A Volkmann
Journal:  Proc Natl Acad Sci U S A       Date:  2004-12-29       Impact factor: 11.205

4.  Accessing genetic information with high-density DNA arrays.

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Journal:  Science       Date:  1996-10-25       Impact factor: 47.728

5.  Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies.

Authors:  J Lazarou; B H Pomeranz; P N Corey
Journal:  JAMA       Date:  1998-04-15       Impact factor: 56.272

6.  Genetic predisposition to the metabolism of irinotecan (CPT-11). Role of uridine diphosphate glucuronosyltransferase isoform 1A1 in the glucuronidation of its active metabolite (SN-38) in human liver microsomes.

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Journal:  J Clin Invest       Date:  1998-02-15       Impact factor: 14.808

7.  Phase II study of weekly intravenous recombinant humanized anti-p185HER2 monoclonal antibody in patients with HER2/neu-overexpressing metastatic breast cancer.

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Journal:  J Clin Oncol       Date:  1996-03       Impact factor: 44.544

8.  An information-intensive approach to the molecular pharmacology of cancer.

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Journal:  Science       Date:  1997-01-17       Impact factor: 47.728

9.  Use of a cDNA microarray to analyse gene expression patterns in human cancer.

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Journal:  Nat Genet       Date:  1996-12       Impact factor: 38.330

10.  Cyclosporine A-induced decrease in calbindin-D 28 kDa in rat kidney but not in cerebral cortex and cerebellum.

Authors:  M C Varela; A Arce; B Greiner; M Schwald; L Aicher; D Wahl; O Grenet; S Steiner
Journal:  Biochem Pharmacol       Date:  1998-06-15       Impact factor: 5.858

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  19 in total

1.  S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.

Authors:  Helena F Deus; Miriã C Correa; Romesh Stanislaus; Maria Miragaia; Wolfgang Maass; Hermínia de Lencastre; Ronan Fox; Jonas S Almeida
Journal:  BMC Bioinformatics       Date:  2011-07-14       Impact factor: 3.169

2.  Higher plasma bilirubin predicts veno-occlusive disease in early childhood undergoing hematopoietic stem cell transplantation with cyclosporine.

Authors:  Kwi Suk Kim; Aree Moon; Hyoung Jin Kang; Hee Young Shin; Young Hee Choi; Hyang Sook Kim; Sang Geon Kim
Journal:  World J Transplant       Date:  2016-06-24

Review 3.  Novel opportunities for computational biology and sociology in drug discovery.

Authors:  Lixia Yao; James A Evans; Andrey Rzhetsky
Journal:  Trends Biotechnol       Date:  2010-04       Impact factor: 19.536

4.  A semi-supervised approach to extract pharmacogenomics-specific drug-gene pairs from biomedical literature for personalized medicine.

Authors:  Rong Xu; Quanqiu Wang
Journal:  J Biomed Inform       Date:  2013-04-06       Impact factor: 6.317

5.  Predicting adverse drug reactions using publicly available PubChem BioAssay data.

Authors:  Y Pouliot; A P Chiang; A J Butte
Journal:  Clin Pharmacol Ther       Date:  2011-05-25       Impact factor: 6.875

6.  Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.

Authors:  Mei Liu; Ruichu Cai; Yong Hu; Michael E Matheny; Jingchun Sun; Jun Hu; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2013-12-11       Impact factor: 4.497

7.  Discovery and preclinical validation of drug indications using compendia of public gene expression data.

Authors:  Marina Sirota; Joel T Dudley; Jeewon Kim; Annie P Chiang; Alex A Morgan; Alejandro Sweet-Cordero; Julien Sage; Atul J Butte
Journal:  Sci Transl Med       Date:  2011-08-17       Impact factor: 17.956

Review 8.  Novel data-mining methodologies for adverse drug event discovery and analysis.

Authors:  R Harpaz; W DuMouchel; N H Shah; D Madigan; P Ryan; C Friedman
Journal:  Clin Pharmacol Ther       Date:  2012-06       Impact factor: 6.875

9.  Molecular therapy drives patient-centric health care paradigms.

Authors:  Scott A Waldman; Andre Terzic
Journal:  Clin Transl Sci       Date:  2010-08       Impact factor: 4.689

Review 10.  Novel opportunities for computational biology and sociology in drug discovery.

Authors:  Lixia Yao; James A Evans; Andrey Rzhetsky
Journal:  Trends Biotechnol       Date:  2009-08-10       Impact factor: 19.536

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