Literature DB >> 29313964

The Next Generation of Drug Safety Science: Coupling Detection, Corroboration, and Validation to Discover Novel Drug Effects and Drug-Drug Interactions.

Nicholas P Tatonetti1,2,3,4.   

Abstract

Rare adverse drug reactions and drug-drug interactions (DDIs) are difficult to detect in randomized trials and impossible to prove using observational studies. We must ascribe to a new way of conducting research that has the efficiency of a retrospective analysis and the rigor of a prospective trial. This can be achieved by integrating observational data from humans with laboratory experiments in model systems. The former establishes clinical significance and the latter supports causality.
© 2017 American Society for Clinical Pharmacology and Therapeutics.

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Year:  2018        PMID: 29313964      PMCID: PMC6005687          DOI: 10.1002/cpt.949

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


  10 in total

1.  A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions.

Authors:  Eugène P van Puijenbroek; Andrew Bate; Hubert G M Leufkens; Marie Lindquist; Roland Orre; Antoine C G Egberts
Journal:  Pharmacoepidemiol Drug Saf       Date:  2002 Jan-Feb       Impact factor: 2.890

Review 2.  Connecting the dots: applications of network medicine in pharmacology and disease.

Authors:  A Jacunski; N P Tatonetti
Journal:  Clin Pharmacol Ther       Date:  2013-08-29       Impact factor: 6.875

3.  Co-medication of pravastatin and paroxetine-a categorical study.

Authors:  Li An; Priyadarshini P Ravindran; Swetha Renukunta; Srinivas Denduluri
Journal:  J Clin Pharmacol       Date:  2013-08-13       Impact factor: 3.126

4.  Combination Therapy With Ceftriaxone and Lansoprazole, Acquired Long QT Syndrome, and Torsades de Pointes Risk.

Authors:  Pietro Enea Lazzerini; Iacopo Bertolozzi; Marco Rossi; Pier Leopoldo Capecchi; Franco Laghi-Pasini
Journal:  J Am Coll Cardiol       Date:  2017-04-11       Impact factor: 24.094

5.  Coupling Data Mining and Laboratory Experiments to Discover Drug Interactions Causing QT Prolongation.

Authors:  Tal Lorberbaum; Kevin J Sampson; Jeremy B Chang; Vivek Iyer; Raymond L Woosley; Robert S Kass; Nicholas P Tatonetti
Journal:  J Am Coll Cardiol       Date:  2016-10-18       Impact factor: 24.094

6.  Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels.

Authors:  N P Tatonetti; J C Denny; S N Murphy; G H Fernald; G Krishnan; V Castro; P Yue; P S Tsao; P S Tsau; I Kohane; D M Roden; R B Altman
Journal:  Clin Pharmacol Ther       Date:  2011-05-25       Impact factor: 6.875

7.  Co-administration of paroxetine and pravastatin causes deregulation of glucose homeostasis in diabetic rats via enhanced paroxetine exposure.

Authors:  Feng Li; Mian Zhang; Dan Xu; Can Liu; Ze-Yu Zhong; Ling-Ling Jia; Meng-Yue Hu; Yang Yang; Li Liu; Xiao-Dong Liu
Journal:  Acta Pharmacol Sin       Date:  2014-06       Impact factor: 6.150

8.  Systems pharmacology augments drug safety surveillance.

Authors:  T Lorberbaum; M Nasir; M J Keiser; S Vilar; G Hripcsak; N P Tatonetti
Journal:  Clin Pharmacol Ther       Date:  2014-12-20       Impact factor: 6.875

9.  An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval.

Authors:  Tal Lorberbaum; Kevin J Sampson; Raymond L Woosley; Robert S Kass; Nicholas P Tatonetti
Journal:  Drug Saf       Date:  2016-05       Impact factor: 5.606

10.  Next-generation phenotyping of electronic health records.

Authors:  George Hripcsak; David J Albers
Journal:  J Am Med Inform Assoc       Date:  2012-09-06       Impact factor: 4.497

  10 in total
  4 in total

1.  Measuring the impact of pharmacovigilance activities, challenging but important.

Authors:  Florence van Hunsel; Helga Gardarsdottir; Anthonius de Boer; Agnes Kant
Journal:  Br J Clin Pharmacol       Date:  2019-07-31       Impact factor: 4.335

2.  Prevalence of potential drug - drug interactions in the cardiothoracic intensive care unit patients in a Chinese tertiary care teaching hospital.

Authors:  Haitao Wang; Haitao Shi; Na Wang; Yan Wang; Li Zhang; Yujie Zhao; Jiao Xie
Journal:  BMC Pharmacol Toxicol       Date:  2022-06-14       Impact factor: 2.605

3.  Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning.

Authors:  Andrej Kastrin; Polonca Ferk; Brane Leskošek
Journal:  PLoS One       Date:  2018-05-08       Impact factor: 3.240

Review 4.  No population left behind: Improving paediatric drug safety using informatics and systems biology.

Authors:  Nicholas P Giangreco; Jonathan E Elias; Nicholas P Tatonetti
Journal:  Br J Clin Pharmacol       Date:  2021-01-19       Impact factor: 3.716

  4 in total

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