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Bioimpacts. 2016;6(2): 71-78. doi: 10.15171/bi.2016.10
PMID: 27525223        PMCID: PMC4981251

Review

Computerized techniques pave the way for drug-drug interaction prediction and interpretation

Reza Safdari 1, Reza Ferdousi 1,2, Kamal Aziziheris 3, Sharareh R. Niakan-Kalhori 1, Yadollah Omidi 2 * ORCID

Cited by CrossRef: 23

1- Wang N, Zhu B, Li X, Liu S, Shi J, Cao D. Comprehensive Review of Drug–Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities. J Chem Inf Model. 2024;64(1):96 [Crossref]
2- Yu L, Xu Z, Cheng M, Lin W, Qiu W, Xiao X. MSEDDI: Multi-Scale Embedding for Predicting Drug—Drug Interaction Events. IJMS. 2023;24(5):4500 [Crossref]
3- Zhang Y, Deng Z, Xu X, Feng Y, Junliang S. Application of Artificial Intelligence in Drug–Drug Interactions Prediction: A Review. J Chem Inf Model. 2024;64(7):2158 [Crossref]
4- Lin Y, Fang X. First, Do No Harm: Predictive Analytics to Reduce In-Hospital Adverse Events. SSRN Journal. 2018; [Crossref]
5- Luo H, Yin W, Wang J, Zhang G, Liang W, Luo J, Yan C. Drug-drug interactions prediction based on deep learning and knowledge graph: A review. iScience. 2024;27(3):109148 [Crossref]
6- Ferdousi R, Jamali A, Safdari R. Identification and ranking of important bio-elements in drug-drug interaction by Market Basket Analysis. Bioimpacts. 2019;10(2):97 [Crossref]
7- Omidi Y, Omidian H. Transformative dynamism in pharmaceutical and biomedical research: Complexity of integration of innovative R & D hubs. Bioimpacts. 2021;11(3):227 [Crossref]
8- Emami N, Pakchin P, Ferdousi R. Computational predictive approaches for interaction and structure of aptamers. Journal of Theoretical Biology. 2020;497:110268 [Crossref]
9- Cottura N, Kinvig H, Grañana‐Castillo S, Wood A, Siccardi M. Drug–Drug Interactions in People Living With HIV at Risk of Hepatic and Renal Impairment: Current Status and Future Perspectives. The Journal of Clinical Pharma. 2022;62(7):835 [Crossref]
10- Lin X, Dai L, Zhou Y, Yu Z, Zhang W, Shi J, Cao D, Zeng L, Chen H, Song B, Yu P, Zeng X. Comprehensive evaluation of deep and graph learning on drug–drug interactions prediction. 2023;24(4) [Crossref]
11- Zheng W, Lin H, Luo L, Zhao Z, Li Z, Zhang Y, Yang Z, Wang J. An attention-based effective neural model for drug-drug interactions extraction. BMC Bioinformatics. 2017;18(1) [Crossref]
12- Zhang R, Wang X, Wang P, Meng Z, Cui W, Zhou Y. HTCL-DDI: a hierarchical triple-view contrastive learning framework for drug–drug interaction prediction. 2023;24(6) [Crossref]
13- Westarb G, Stefenon S, Hoppe A, Sartori A, Klaar A, Leithardt V. Complex graph neural networks for medication interaction verification. IFS. 2023;44(6):10383 [Crossref]
14- Yan C, Duan G, Zhang Y, Wu F, Pan Y, Wang J. Predicting Drug-Drug Interactions Based on Integrated Similarity and Semi-Supervised Learning. IEEE/ACM Trans Comput Biol and Bioinf. 2022;19(1):168 [Crossref]
15- Kabir M, Rahman A, Hasan M, Mridha M. Computer vision algorithms in healthcare: Recent advancements and future challenges. Computers in Biology and Medicine. 2025;185:109531 [Crossref]
16- Qiu Y, Zhang Y, Deng Y, Liu S, Zhang W. A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection. IEEE/ACM Trans Comput Biol and Bioinf. 2022;19(4):1968 [Crossref]
17- Vandghanooni S, Eskandani M, Barar J, Omidi Y. Bispecific therapeutic aptamers for targeted therapy of cancer: a review on cellular perspective. J Mol Med. 2018;96(9):885 [Crossref]
18- Thomas L, Birangal S, Ray R, Sekhar Miraj S, Munisamy M, Varma M, S.V. C, Banerjee M, Shenoy G, Rao M. Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data. Therapeutic Advances in Drug Safety. 2021;12 [Crossref]
19- Han K, Cao P, Wang Y, Xie F, Ma J, Yu M, Wang J, Xu Y, Zhang Y, Wan J. A Review of Approaches for Predicting Drug–Drug Interactions Based on Machine Learning. Front Pharmacol. 2022;12 [Crossref]
20- Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, Masoudi-Nejad A. DrugR+: A comprehensive relational database for drug repurposing, combination therapy, and replacement therapy. Computers in Biology and Medicine. 2019;109:254 [Crossref]
21- Ferdousi R, Safdari R, Omidi Y. Computational prediction of drug-drug interactions based on drugs functional similarities. Journal of Biomedical Informatics. 2017;70:54 [Crossref]
22- He J, Sun Y, Ling J. A Molecular Fragment Representation Learning Framework for Drug–Drug Interaction Prediction. Interdiscip Sci Comput Life Sci. 2024; [Crossref]

As a peer-reviewed international open-access journal, BioImpacts publishes articles on basic and translational aspects of pharmaceutical and biomedical sciences. 
Acceptance rate: 24% 
Publication fee: Free of charge