Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation

Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation Publisher

Safdari R¹ ; Ferdousi R^{1, 2} ; Aziziheris K³ ; Niakankalhori SR¹ ; Omidi Y²

Show Affiliations

1. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2. Research Center for Pharmaceutical Nanotechnology, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
3. Department of Mathematical Sciences, University of Tabriz, Tabriz, Iran

Source: BioImpacts Published:2016

Abstract

Introduction: Health care industry also patients penalized by medical errors that are inevitable but highly preventable. Vast majority of medical errors are related to adverse drug reactions, while drug-drug interactions (DDIs) are the main cause of adverse drug reactions (ADRs). DDIs and ADRs have mainly been reported by haphazard case studies. Experimental in vivo and in vitro researches also reveals DDI pairs. Laboratory and experimental researches are valuable but also expensive and in some cases researchers may suffer from limitations. Methods: In the current investigation, the latest published works were studied to analyze the trend and pattern of the DDI modelling and the impacts of machine learning methods. Applications of computerized techniques were also investigated for the prediction and interpretation of DDIs. Results: Computerized data-mining in pharmaceutical sciences and related databases provide new key transformative paradigms that can revolutionize the treatment of diseases and hence medical care. Given that various aspects of drug discovery and pharmacotherapy are closely related to the clinical and molecular/biological information, the scientifically sound databases (e.g., DDIs, ADRs) can be of importance for the success of pharmacotherapy modalities. Conclusion: A better understanding of DDIs not only provides a robust means for designing more effective medicines but also grantees patient safety. © 2016 The Author(s).

Related Docs

1. Computational Prediction of Drug-Drug Interactions Based on Drugs Functional Similarities, Journal of Biomedical Informatics (2017)

2. Radiolabeled Theranostics: Magnetic and Gold Nanoparticles, BioImpacts (2016)

3. Clinical Decision Support Systems-Based Interventions to Improve Medication Outcomes: A Systematic Literature Review on Features and Effects, Medical Journal of the Islamic Republic of Iran (2021)

Experts (# of related papers)

Reza Safdari (2)

Leila Shahmoradi (1)

Style	Citing Format
MLA	Safdari R, et al.. "Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation." BioImpacts, vol. 6, no. 2, 2016, pp. 71-78.
APA	Safdari R, Ferdousi R, Aziziheris K, Niakankalhori SR, Omidi Y (2016). Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation. BioImpacts, 6(2), 71-78.
Chicago	Safdari R, Ferdousi R, Aziziheris K, Niakankalhori SR, Omidi Y. "Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation." BioImpacts 6, no. 2 (2016): 71-78.
Harvard	Safdari R et al. (2016) 'Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation', BioImpacts, 6(2), pp. 71-78.
Vancouver	Safdari R, Ferdousi R, Aziziheris K, Niakankalhori SR, Omidi Y. Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation. BioImpacts. 2016;6(2):71-78.
BibTex	@article{ author = {Safdari R and Ferdousi R and Aziziheris K and Niakankalhori SR and Omidi Y}, title = {Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation}, journal = {BioImpacts}, volume = {6}, number = {2}, pages = {71-78}, year = {2016} }
RIS	TY - JOUR AU - Safdari R AU - Ferdousi R AU - Aziziheris K AU - Niakankalhori SR AU - Omidi Y TI - Computerized Techniques Pave the Way for Drug-Drug Interaction Prediction and Interpretation JO - BioImpacts VL - 6 IS - 2 SP - 71 EP - 78 PY - 2016 ER -

Science Communicator Platform

Authors

Authors Affiliations

Abstract