Artificial intelligence, drug repurposing and peer review

COVID-19: consider cytokine storm syndromes and immunosuppression

Mehta, P., McAuley, D. F., Brown, M., Sanchez, E., Tattersall, R. S., & Manson, J. J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30628-0 · Cited by 9,664 · see citing works

Remdesivir for the Treatment of Covid-19 — Final Report

Beigel, J. H., Tomashek, K. M., Dodd, L. E., Mehta, A. K., Zingman, B. S., Kalil, A. C., Hohmann, E., Chu, H. Y., Luetkemeyer, A., Kline, S., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2007764 · Cited by 7,267 · see citing works

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C. H., & Kang, J. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz682 · Cited by 7,218 · see citing works

Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro

Wang, M., Cao, R., Zhang, L., Yang, X., Liu, J., Xu, M., Shi, Z., Hú, Z., Zhong, W., & Xiao, G. (2020) · Cell Research · doi:10.1038/s41422-020-0282-0 · Cited by 6,967 · see citing works

In Vitro Antiviral Activity and Projection of Optimized Dosing Design of Hydroxychloroquine for the Treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

Yao, X., Ye, F., Zhang, M., Cui, C., Huang, B., Niu, P., Liu, X., Zhao, L. Y., Dong, E., Song, C., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa237 · Cited by 2,665 · see citing works

Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies

Gao, J., Tian, Z., & Yang, X. (2020) · BioScience Trends · doi:10.5582/bst.2020.01047 · Cited by 2,592 · see citing works

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies

Nagendran, M., Chen, Y., Lovejoy, C. A., Gordon, A. C., Komorowski, M., Harvey, H., Topol, E. J., Ioannidis, J. P. A., Collins, G. S., & Maruthappu, M. (2020) · BMJ · doi:10.1136/bmj.m689 · Cited by 1,152 · see citing works

Hydroxychloroquine in patients with mainly mild to moderate coronavirus disease 2019: open label, randomised controlled trial

Tang, W., Cao, Z., Han, M., Wang, Z., Chen, J., Sun, W., Wu, Y., Xiao, W. L., Liu, S., Chen, E., et al. (2020) · BMJ · doi:10.1136/bmj.m1849 · Cited by 1,129 · see citing works

Hydroxychloroquine with or without Azithromycin in Mild-to-Moderate Covid-19

Cavalcanti, A. B., Zampieri, F. G., Rosa, R. G., Azevedo, L. C. P., Veiga, V. C., Avezum, Á., Damiani, L. P., Marcadenti, A., Kawano-Dourado, L. B., Lisboa, T. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2019014 · Cited by 1,082 · see citing works

Effect of High vs Low Doses of Chloroquine Diphosphate as Adjunctive Therapy for Patients Hospitalized With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Randomized Clinical Trial

Borba, M. G. S., Val, F. F. A., Sampaio, V. S., Alexandre, M. A. A., Melo, G. C., Brito, M., Mourão, M. P. G., Brito-Sousa, J. D., Baía-da-Silva, D., Guerra, M. V. F., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.8857 · Cited by 1,038 · see citing works

Tocilizumab in patients with severe COVID-19: a retrospective cohort study

Guaraldi, G., Meschiari, M., Cozzi-Lepri, A., Milic, J., Tonelli, R., Menozzi, M., Franceschini, E., Cuomo, G., Orlando, G., Borghi, V., et al. (2020) · The Lancet Rheumatology · doi:10.1016/s2665-9913(20)30173-9 · Cited by 939 · see citing works

Efficacy of hydroxychloroquine in patients with COVID-19: results of a randomized clinical trialPreprint

Chen, Z., Hu, J., Zhang, Z., Jiang, S., Han, S., Yan, D., Zhuang, R., Hu, B., & Zhang, Z. (2020) · medRxiv · doi:10.1101/2020.03.22.20040758 · Cited by 844 · see citing works

No evidence of rapid antiviral clearance or clinical benefit with the combination of hydroxychloroquine and azithromycin in patients with severe COVID-19 infection

Molina, J., Delaugerre, C., LeGoff, J., Melo‐Lima, B. L., Ponscarme, D., Goldwirt, L., & Castro, N. D. (2020) · Médecine et Maladies Infectieuses · doi:10.1016/j.medmal.2020.03.006 · Cited by 747 · see citing works

[A pilot study of hydroxychloroquine in treatment of patients with moderate COVID-19].

Chen, J., Liu, D., Liu, L., Liu, P., Xu, Q., Xia, L., Ling, Y., Huang, D. F., Song, S., Zhang, D., et al. (2020) · PubMed Central · doi:10.3785/j.issn.1008-9292.2020.03.03 · Cited by 662 · see citing works

Anakinra for severe forms of COVID-19: a cohort study

Huet, T., Beaussier, H., Voisin, O., Jouveshomme, S., Dauriat, G., Lazareth, I., Sacco, E., Naccache, J., Bézie, Y., Laplanche, S., et al. (2020) · The Lancet Rheumatology · doi:10.1016/s2665-9913(20)30164-8 · Cited by 643 · see citing works

Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data

Aliper, A., Plis, S., Artemov, A., Ulloa, A., Mamoshina, P., & Zhavoronkov, A. (2016) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.6b00248 · Cited by 610 · see citing works

Of chloroquine and COVID-19

Touret, F., & de Lamballerie, X. N. (2020) · Antiviral Research · doi:10.1016/j.antiviral.2020.104762 · Cited by 544 · see citing works

COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread

McCall, B. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30054-6 · Cited by 396 · see citing works

In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication

Touret, F., Gilles, M., Barral, K., Nougaırède, A., van Helden, J., Decroly, É., de Lamballerie, X. N., & Coutard, B. (2020) · Scientific Reports · doi:10.1038/s41598-020-70143-6 · Cited by 389 · see citing works

Target identification among known drugs by deep learning from heterogeneous networks

Zeng, X., Zhu, S., Lu, W., Liu, Z., Huang, J., Zhou, Y., Fang, J., Huang, Y., Guo, H., Li, L., et al. (2020) · Chemical Science · doi:10.1039/c9sc04336e · Cited by 357 · see citing works

Pandemic publishing poses a new COVID-19 challenge

Palayew, A., Norgaard, O., Safreed-Harmon, K., Andersen, T. H., Rasmussen, L. N., & Lazarus, J. V. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0911-0 · Cited by 258 · see citing works

Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning

Zeng, X., Song, X. H., Ma, T., Pan, X., Zhou, Y., Hou, Y., Zhang, Z., Li, K., Karypis, G., & Cheng, F. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00316 · Cited by 258 · see citing works

Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study

Lane, J. C. E., Weaver, J., Kostka, K., Duarte-Salles, T., Abrahao, M. T. F., Alghoul, H., Alser, O., Alshammari, T. M., Biedermann, P., Banda, J. M., et al. (2020) · The Lancet Rheumatology · doi:10.1016/s2665-9913(20)30276-9 · Cited by 258 · see citing works

Lancet retracts 12-year-old article linking autism to MMR vaccines

Eggertson, L. (2010) · Canadian Medical Association Journal · doi:10.1503/cmaj.109-3179 · Cited by 249 · see citing works

DeepFam: deep learning based alignment-free method for protein family modeling and prediction

Seo, S., Oh, M., Park, Y., & Kim, S. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty275 · Cited by 134 · see citing works

Use of Baricitinib in Patients With Moderate to Severe Coronavirus Disease 2019

Titanji, B. K., Farley, M. M., Mehta, A., Connor‐Schuler, R., Moanna, A., Cribbs, S. K., O’Shea, J., DeSilva, K. E., Chan, B., Edwards, A., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa879 · Cited by 132 · see citing works

Computational and Practical Aspects of Drug Repositioning

Oprea, T. I., & Overington, J. P. (2015) · Assay and Drug Development Technologies · doi:10.1089/adt.2015.29011.tiodrrr · Cited by 114 · see citing works

Hydroxychloroquine for the Prevention of Covid-19 — Searching for Evidence

Cohen, M. S. (2020) · New England Journal of Medicine · doi:10.1056/nejme2020388 · Cited by 112 · see citing works

Efficacy and safety of umifenovir for coronavirus disease 2019 (COVID‐19): A systematic review and meta‐analysis

Huang, D., Yu, H., Wang, T., Yang, H., Yao, R., & Liang, Z.-A. (2020) · Journal of Medical Virology · doi:10.1002/jmv.26256 · Cited by 100 · see citing works

The COVID-19 Drug and Gene Set Library

Kuleshov, M. V., Stein, D. J., Clarke, D. J. B., Kropiwnicki, E., Jagodnik, K. M., Bartal, A., Evangelista, J. E., Hom, J., Cheng, M., Bailey, A., et al. (2020) · Patterns · doi:10.1016/j.patter.2020.100090 · Cited by 85 · see citing works

A Guide to Dictionary-Based Text Mining

Cook, H., & Jensen, L. J. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9089-4_5 · Cited by 26 · see citing works

Hydroxychloroquine prophylaxis for high-risk COVID-19 contacts in India: a prudent approach

Tilangi, P., Desai, D., Khan, A. R., & Soneja, M. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30430-8 · Cited by 24 · see citing works

Autism, inflammatory bowel disease, and MMR vaccine

Bhatt, R. (1998) · The Lancet · doi:10.1016/s0140-6736(05)79085-1 · Cited by 1 · see citing works

Artificial Intelligence for Drug Discovery: Are We There Yet?

Hasselgren, C., & Oprea, T. I. (2024) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-040323-040828 · Cited by 236 · see citing works

A critical overview of computational approaches employed for COVID-19 drug discovery

Muratov, E. N., Amaro, R., Andrade, C. H., Brown, N., Ekins, S., Fourches, D., Isayev, O., Kozakov, D., Medina-Franco, J. L., Merz, K. M., et al. (2021) · Chemical Society Reviews · doi:10.1039/d0cs01065k · Cited by 206 · see citing works

DrugCentral 2021 supports drug discovery and repositioning

Avram, S., Bologa, C. G., Holmes, J., Bocci, G., Wilson, T. B., Nguyen, D.-T., Curpan, R., Halip, L., Bora, A., Yang, J. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa997 · Cited by 189 · see citing works

TCRD and pharos 2021: mining the human proteome for disease biology

Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa993 · Cited by 160 · see citing works

The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

Piccialli, F., Cola, V. S. D., Giampaolo, F., & Cuomo, S. (2021) · Information Systems Frontiers · doi:10.1007/s10796-021-10131-x · Cited by 153 · see citing works

Antimicrobial Peptides towards Clinical Application—A Long History to Be Concluded

Cresti, L., Cappello, G., & Pini, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25094870 · Cited by 120 · see citing works

Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: an integrated computational approach

Mishra, C. B., Pandey, P., Sharma, R. D., Malik, M. Z., Mongre, R. K., Lynn, A. M., Prasad, R., Jeon, R., & Prakash, A. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa378 · Cited by 101 · see citing works

DrugCentral 2023 extends human clinical data and integrates veterinary drugs

Avram, S., Wilson, T. B., Curpan, R., Halip, L., Borota, A., Bora, A., Bologa, C. G., Holmes, J., Knockel, J., Yang, J. J., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1085 · Cited by 101 · see citing works

Potential Therapeutic Targets and Vaccine Development for SARS-CoV-2/COVID-19 Pandemic Management: A Review on the Recent Update

Anand, U., Jakhmola, S., Indari, O., Jha, H. C., Chen, Z., Tripathi, V. S., & de la Lastra, J. M. P. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.658519 · Cited by 83 · see citing works

Artificial intelligence-assisted tools for redefining the communication landscape of the scholarly world

Razack, H. I. A., Mathew, S. T., Saad, F. F. A., & Alqahtani, S. A. (2021) · Science Editing · doi:10.6087/kcse.244 · Cited by 82 · see citing works

Alkaloids in Contemporary Drug Discovery to Meet Global Disease Needs

Daley, S.-K., & Cordell, G. A. (2021) · Molecules · doi:10.3390/molecules26133800 · Cited by 76 · see citing works

Virtual and In Vitro Antiviral Screening Revive Therapeutic Drugs for COVID-19

Bocci, G., Bradfute, S. B., Ye, C., Garcia, M. J., Parvathareddy, J., Reichard, W., Surendranathan, S., Bansal, S., Bologa, C., Perkins, D. J., et al. (2020) · ACS Pharmacology & Translational Science · doi:10.1021/acsptsci.0c00131 · Cited by 59 · see citing works

Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains

Lin, T.-T., Yang, L., Lin, C., Wang, C.-T., Lai, C.-W., Ko, C.-F., Shih, Y., & Chen, S. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076788 · Cited by 57 · see citing works

Longevity medicine: upskilling the physicians of tomorrow

Bischof, E. Y., Scheibye‐Knudsen, M., Siow, R. C. M., & Moskalev, A. (2021) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(21)00024-6 · Cited by 51 · see citing works

Overview of current state of research on the application of artificial intelligence techniques for COVID-19

Kumar, V., Singh, D., Kaur, M., & Damaševičius, R. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.564 · Cited by 50 · see citing works

Drug Repurposing by Siderophore Conjugation: Synthesis and Biological Evaluation of Siderophore‐Methotrexate Conjugates as Antibiotics

Zhao, S. Y., Wang, Z., Lin, Z., Wei, G., Wen, X., Li, S., Yang, X., Zhang, Q., Jing, C., Dai, Y., et al. (2022) · Angewandte Chemie International Edition · doi:10.1002/anie.202204139 · Cited by 41 · see citing works

Open science approaches to COVID-19

Tse, E. G., Klug, D. M., & Todd, M. H. (2020) · F1000Research · doi:10.12688/f1000research.26084.1 · Cited by 39 · see citing works

AI drug discovery screening for COVID-19 reveals zafirlukast as a repurposing candidate

Delijewski, M., & Haneczok, J. (2020) · Medicine in Drug Discovery · doi:10.1016/j.medidd.2020.100077 · Cited by 41 · see citing works

Computational drug repurposing by exploiting large-scale gene expression data: Strategy, methods and applications

He, H., Duo, H., Hao, Y., Zhang, X., Zhou, X., Zeng, Y., Li, Y., & Li, B. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106671 · Cited by 35 · see citing works

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Buzdin, A. A., Tkachev, V., Zolotovskaia, M., Garazha, A., Moshkovskii, S. A., Borisov, N. M., Гайфуллин, Н., Sorokin, M., & Suntsova, M. (2021) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2021.02.005 · Cited by 34 · see citing works

Current status and recent trends in innovative tactics and the One Health approach to address the challenge of methicillin-resistant Staphylococcus aureus infections: a comprehensive review

Hajhamed, N. M., Mohamed, N. S., Abdalla, A. E., Ebrahim, R. M. A., Mohammed, S. I., Bakheit, A. M., Azhary, A., Ahmed, A. E., Abdelbagi, A., Ali, M. S. E., et al. (2025) · Discover Medicine · doi:10.1007/s44337-025-00300-1 · Cited by 30 · see citing works

Graph Neural Networks for COVID-19 Drug Discovery

Cheung, M., & Moura, J. M. F. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9378164 · Cited by 27 · see citing works

Machine learning enabled identification of potential SARS-CoV-2 3CLpro inhibitors based on fixed molecular fingerprints and Graph-CNN neural representations

Haneczok, J., & Delijewski, M. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103821 · Cited by 26 · see citing works

Trends in orphan medicinal products approvals in the European Union between 2010–2022

Bouwman, L., Sepodes, B. M. N., Leufkens, H. G. M., & Torre, C. (2024) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-024-03095-z · Cited by 25 · see citing works

Managing Pandemics with Health Informatics: Successes and Challenges

Basit, M. A., Lehmann, C. U., & Medford, R. J. (2021) · Yearbook of Medical Informatics · doi:10.1055/s-0041-1726478 · Cited by 25 · see citing works

Early Returns on Small Molecule Therapeutics for SARS-CoV-2

Namchuk, M. (2021) · ACS Infectious Diseases · doi:10.1021/acsinfecdis.0c00874 · Cited by 21 · see citing works

AI-powered drug repurposing for developing COVID-19 treatments

Liu, Z., Chen, X., Carter, W., Moruf, A., Komatsu, T. E., Pahwa, S., Chan‐Tack, K. M., Snyder, K., Petrick, N., Cha, K., et al. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824010-6.00005-8 · Cited by 21 · see citing works

Artificial intelligence as an enabler of quick and effective production repurposing: an exploratory review and future research propositions

Naz, F., Kumar, A., Agrawal, R., Garza-Reyes, J., Majumdar, A., & Chokshi, H. (2023) · Production Planning & Control · doi:10.1080/09537287.2023.2248947 · Cited by 20 · see citing works

Discovering Novel Antimicrobial Peptides in Generative Adversarial NetworkPreprint

Lin, T.-T., Yang, L., Wang, C.-T., Lai, G.-W., Ko, C.-F., Shih, Y., Chen, S., & Lin, C. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.22.469634 · Cited by 21 · see citing works

Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature

Khamisy‐Farah, R., Gilbey, P., Furstenau, L. B., Sott, M. K., Farah, R. E., Viviani, M., Bisogni, M., Kong, J. D., Ciliberti, R., & Bragazzi, N. L. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18178989 · Cited by 20 · see citing works

Holistic Approach for Artificial Intelligence Implementation in Pharmaceutical Products Lifecycle: A Meta-Analysis

Koshechkin, K. A., Lebedev, G. S., Fartushniy, E., & Orlov, Y. L. (2022) · Applied Sciences · doi:10.3390/app12168373 · Cited by 21 · see citing works

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug RepurposingPreprint

Quazi, S. (2021) · Preprints.org · doi:10.20944/preprints202105.0346.v1 · Cited by 19 · see citing works

Tizoxanide Promotes Apoptosis in Glioblastoma by Inhibiting CDK1 Activity

Huang, S. Q., Xiao, J., Wu, J., Liu, J., Feng, X., Yang, C., Xiang, D., & Luo, S. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.895573 · Cited by 18 · see citing works

Fighting COVID-19 with Artificial Intelligence

Monteleone, S., Kellici, T. F., Southey, M., Bodkin, M. J., & Heifetz, A. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-1787-8_3 · Cited by 17 · see citing works

The Future of ChatGPT in Medicinal Chemistry: Harnessing AI for Accelerated Drug Discovery

Pradhan, T., Gupta, O., & Chawla, G. (2024) · ChemistrySelect · doi:10.1002/slct.202304359 · Cited by 17 · see citing works

Drug repositioning by merging active subnetworks validated in cancer and COVID-19

Lucchetta, M., & Pellegrini, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-99399-2 · Cited by 16 · see citing works

Artificial Neural Network-Based Study Predicts GS-441524 as a Potential Inhibitor of SARS-CoV-2 Activator Protein Furin: a Polypharmacology Approach

Dhanalakshmi, M., Das, K., Pandya, M. D., Shah, S., Gadnayak, A., Dave, S., & Das, J. (2022) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-022-03928-2 · Cited by 16 · see citing works

Benefits and Challenges of Using AI for Peer Review: A Study on Researchers’ Perceptions

Giray, L. (2024) · The Serials librarian · doi:10.1080/0361526x.2024.2428377 · Cited by 13 · see citing works

An overview of artificial intelligence and big data analytics for smart healthcare: requirements, applications, and challenges

Chui, K. T., Lytras, M. D., Visvizi, A., & Sarirete, A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822060-3.00015-2 · Cited by 17 · see citing works

Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites

Popov, P. A., Kalinin, R. E., Buslaev, P., Kozlovskii, I., Zaretckii, M., Karlov, D. S., Gabibov, A. G., & Stepanov, A. V. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad459 · Cited by 14 · see citing works

Artificial Intelligence in the Paradigm Shift of Pharmaceutical Sciences: A Review

Tade, R. S., Jain, S. N., Satyavijay, J. T., Shah, P. N., Bari, T. D., Patil, T. M., & Shah, R. P. (2023) · Nano Biomedicine and Engineering · doi:10.26599/nbe.2023.9290043 · Cited by 19 · see citing works

Discovery of new drug indications for COVID-19: A drug repurposing approach

Kumari, P., Pradhan, B., Koromina, M., Patrinos, G. P., & Steen, K. V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0267095 · Cited by 13 · see citing works

Modern computational intelligence based drug repurposing for diabetes epidemic

Mohanty, S., Rashid, M. H. A., Mohanty, C., & Swayamsiddha, S. (2021) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2021.06.017 · Cited by 13 · see citing works

Drug repurposing for reducing the risk of cataract extraction in patients with diabetes mellitus: integration of artificial intelligence-based drug prediction and clinical corroboration

Gao, Z., Gorenflo, M. P., Kaelber, D. C., Monnier, V. M., & Xu, R. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1181711 · Cited by 12 · see citing works

A review of SARS-CoV-2 drug repurposing: databases and machine learning models

Elkashlan, M., Ahmad, R. M., Hajar, M., Jasmi, F. A., Corchado, J. M., Nasarudin, N. A., & Mohamad, M. S. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1182465 · Cited by 14 · see citing works

COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments

Hamed, A. A., Fandy, T. E., Tkaczuk, K. L., Verspoor, K. M., & Lee, B. S. (2022) · Pharmaceutics · doi:10.3390/pharmaceutics14030567 · Cited by 11 · see citing works

A comprehensive review on the application of artificial intelligence in drug discovery.

Sahoo, A., & Dar, G. M. (2021) · The Applied Biology & Chemistry Journal · doi:10.52679/tabcj.2021.0007 · Cited by 9 · see citing works

An overview of artificial intelligence in drug development

Philip, A. K., & Faiyazuddin, M. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-89925-3.00001-0 · Cited by 7 · see citing works

Drug Repurposing by Siderophore Conjugation: Synthesis and Biological Evaluation of Siderophore‐Methotrexate Conjugates as Antibiotics

Zhao, S. Y., Wang, Z., Lin, Z., Wei, G., Wen, X., Li, S., Yang, X., Zhang, Q., Jing, C., Dai, Y., et al. (2022) · Angewandte Chemie · doi:10.1002/ange.202204139 · Cited by 7 · see citing works

Web resources facilitate drug discovery in treatment of COVID-19

Mei, L., Jin, Y., Wang, Z., Hao, G., & Yang, G. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.04.018 · Cited by 6 · see citing works

Emerging Treatment Approaches for COVID-19 Infection: A Critical Review

Bharadwaj, A., Kaur, R., & Gupta, S. K. (2023) · Current Molecular Medicine · doi:10.2174/1566524023666230417112543 · Cited by 5 · see citing works

Amphetamine use and Parkinson’s disease: integration of artificial intelligence prediction, clinical corroboration, and mechanism of action analyses

Gorenflo, M. P., Gao, Z., Davis, P. B., Kaelber, D. C., & Xu, R. (2025) · PLoS ONE · doi:10.1371/journal.pone.0323761 · Cited by 4 · see citing works

Artificial Neural Network Based Study Predicting GS-441524 As Potential Inhibitor of SARS COV-2 Activator Protein Furin: A Polypharmacology ApproachPreprint

Dhanalakshmi, M., Das, K., Pandya, M. D., Shah, S. B., Gadnayak, A., Dave, S., & Das, J. (2021) · Research Square · doi:10.21203/rs.3.rs-513443/v1 · Cited by 4 · see citing works

AIxBio: Opportunities to Strengthen Health Security

Attal-Juncqua, A., Cicero, A. J., Zhu, A. W., & Inglesby, T. (2026) · Health Security · doi:10.1177/23265094261418815 · Cited by 4 · see citing works

AI in Longevity Medicine

Radenković, D., Zhavoronkov, A. A., & Bischof, E. Y. (2021) · Springer eBooks · doi:10.1007/978-3-030-58080-3_248-1 · Cited by 3 · see citing works

Study on the Spatial Structure and City Form Construction of River Valley‐Type Cities in the Context of Artificial Intelligence—A Case Study of Northwest China

Liu, X., Luo, Y., & Huang, M. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/4202745 · Cited by 3 · see citing works

Polypharmacology in Drug Design and Discovery—Basis for Rational Design of Multitarget Drugs

Wang, Z., & Yang, B. (2022) · Springer eBooks · doi:10.1007/978-3-031-04998-9_12 · Cited by 3 · see citing works

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

Maria, N. I., Rapicavoli, R. V., Alaimo, S., Bischof, E. Y., Stasuzzo, A., Broek, J. A. C., Pulvirenti, A., Mishra, B., Duits, A. J., & Ferro, A. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14115 · Cited by 3 · see citing works

Drug Repurposing for COVID-19 using Computational Methods

Prakash, O., & Khan, F. (2023) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9789815123197123010010 · Cited by 2 · see citing works

Transformative technologies for the future of camel welfare: Artificial intelligence for improved diagnostics, therapeutics and health outcomes

Ahmed, A., Saad, S., Mohamed, M., Afzal, S., Ahmed, A., Albokhadaim, I. F., & Kandeel, M. K. (2024) · Journal of Camel Practice and Research · doi:10.5958/2277-8934.2024.00001.8 · Cited by 2 · see citing works

Rapid Identification of Druggable Targets and the Power of the PHENotype SIMulator for Effective Drug Repurposing in COVID-19Preprint

Maria, N. I., Rapicavoli, R. V., Alaimo, S., Bischof, E. Y., Stasuzzo, A., Broek, J. A. C., Pulvirenti, A., Mishra, B., Duits, A. J., & Ferro, A. (2021) · Research Square · doi:10.21203/rs.3.rs-287183/v1 · Cited by 2 · see citing works

Advances in Network-Based Drug Repositioning

Pellegrini, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-55248-9_5 · Cited by 1 · see citing works

The Emergence and Impact of Artificial Intelligence in Biotechnology

Ali, J. (2024) · BIOEDUSCIENCE · doi:10.22236/jbes/12578 · Cited by 1 · see citing works

Deep Probabilistic Matrix Factorization on Graphs: Application to Drug Repositioning in Antimicrobial Resistance

Chatterjee, S., Jain, S., Kumar, K., Chouzenoux, É., & Majumdar, A. (2025) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbbio.2025.3570865 · Cited by 1 · see citing works

The evolution of healthcare and artificial intelligence integration

Bonthu, M. G., Gayatri, A. P., Srinivas, N., & Borse, L. B. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-43823-3.00007-8 · Cited by 1 · see citing works

Artificial intelligence: Blessing or curse?

Briganti, G. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23655-6.00005-8 · Cited by 1 · see citing works

Reductionism Ad Absurdum: The Misadventures of Structural Biology in the Time of Coronavirus

Svetlov, D., & Artsimovitch, I. (2021) · ACS Infectious Diseases · doi:10.1021/acsinfecdis.1c00492 · Cited by 1 · see citing works

Rationalizing Viral Drug Target Identification Using Computational Approaches : The SARS-CoV-2 Spike Glycoprotein S Case StudyPreprint

Popov, P. A., Buslaev, P., Kozlovskii, I., Zaretskii, M., Karlov, D. S., & Morozov, A. (2020) · ChemRxiv · doi:10.26434/chemrxiv.13251560.v1 · Cited by 1 · see citing works

Peer Review #1 of "Overview of current state of research on the application of artificial intelligence techniques for COVID-19 (v0.2)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.564v0.2/reviews/1

Chapter 12 AI in COVID-19 era, infodemic, and post-COVID-19 era

Oshida, Y. (2021) · De Gruyter eBooks · doi:10.1515/9783110717853-013

AI in Longevity Medicine

Radenković, D., Zhavoronkov, A. A., & Bischof, E. Y. (2022) · Springer eBooks · doi:10.1007/978-3-030-64573-1_248

Rationalizing Viral Drug Target Identification Using Computational Approaches : The SARS-CoV-2 Spike Glycoprotein S Case StudyPreprint

Popov, P. A., Buslaev, P., Kozlovskii, I., Zaretskii, M., Karlov, D. S., & Morozov, A. (2020) · ChemRxiv · doi:10.26434/chemrxiv.13251560

Repurposing of Therapeutic Approaches for the Treatment of Vitiligo

Tushir, S., Yadav, M., Kumar, A., & Joshi, K. (2023) · Springer eBooks · doi:10.1007/978-981-19-5399-6_25

Role of Artificial Intelligence (AI) and Machine Learning (ML) in Drug Purposing

Chowdhury, N., & Nanjappan, S. K. (2024) · Springer eBooks · doi:10.1007/978-981-97-5016-0_4

AI-driven drug repurposing in precision medicine: Transforming existing therapies into targeted solutions

Iqbal, S., Zheng, X., Hu, S., Pal, D., & Shen, B. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-44430-2.00009-8

Augmented optimization of medical side effects—avoiding the crisis of complications with artificial intelligence

Sapa, H., Ayana, K., Prajitha, P. G., Shona, S. S., Althaf Umar, K. P., Kaladhar, K., Praveen, V. P., Vivek, N., K, P., Venugopal, B. S., et al. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-40441-2.00001-9

Beyond Docking: Intelligent Modeling and the New Landscape of Drug-Protein Interactions

Taha, M. M., Tayel, A., & Shoeib, H. O. T. A. T. (2025) · Biomedical engineering · doi:10.5772/intechopen.1013595

Artificial Intelligence in Peer Review: A Bibliometric-Guided Thematic Review and a Task-Contingent Legitimacy Framework

Kim, E., & Singh, V. (2026) · Publications · doi:10.3390/publications14040063

Artificial intelligence across the gastric cancer care continuum: Clinical evidence, multimodal integration, and translation

Yang, J., Tang, J., & He, J. (2026) · iScience · doi:10.1016/j.isci.2026.117725

Blueprint for Drug Repurposing Success: Foundational Concepts and Practical Framework

Ray, A., Dey, S., & Sur, D. (2026) · Drug Development Research · doi:10.1002/ddr.70270 · Cited by 1 · see citing works

Computational Drug Repurposing Utilizing AI: A Comprehensive Review of Techniques and Applications

Das, S. M., & Mondal, A. C. (2026) · CRC Press eBooks · doi:10.1201/9781003743767-172

DRUG REPURPOSING IN THE ERA OF ARTIFICIAL INTELLIGENCE: FROM MOLECULAR INSIGHTS TO CLINICAL TRANSLATION

Satti Naga Santhosh Reddy1, T. S. S. M. (2026) · European Journal Pharmaceutical and Medical Research · doi:10.5281/zenodo.22686872

Machine Learning and Artificial Intelligence in drug repurposing – challenges and perspectivesPreprint

Anokian, E., Bernett, J., Freeman, A., List, M., Santamaría, L. P., Tanoli, Z., & Bonnin, S. (2024) · doi:10.58647/drugarxiv.pr000007.v1 · Cited by 4 · see citing works

AI–Driven Drug Repurposing: A Case-Based Review With Insights From Traditional Approaches.

Mohanambigai R. N., M. P. T. S., & Dr Sathyaprabha, G. (2025) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.15711335