1. Chopra H, Baig AA, Gautam RK, Kamal MA. Application of Artificial Intelligence in Drug Discovery. Curr Pharm Des 2022;28:2690-2703 [ DOI:10.2174/1381612828666220608141049] 2. Sandeep Ganesh G, Kolusu AS, Prasad K, Samudrala PK, Nemmani KVS. Advancing health care via artificial intelligence: From concept to clinic. Eur J Pharmacol 2022;934:175320. [ DOI:10.1016/j.ejphar.2022.175320] 3. Li S, Chen J, Hu Y, Ye M. Editorial: Network pharmacology and AI. J Ethnopharmacol 2023;307:116260. [ DOI:10.1016/j.jep.2023.116260] 4. Badillo S, Banfai B, Birzele F, Davydov II, Hutchinson L, Kam-Thong T, et al. An Introduction to Machine Learning. Clin Pharmacol Ther 2020 Apr;107:871-885. [ DOI:10.1002/cpt.1796] 5. Smith GF. Artificial Intelligence in Drug Safety and Metabolism. Methods Mol Biol 2022;2390:483-501. [ DOI:10.1007/978-1-0716-1787-8_22] 6. Murali K, Kaur S, Prakash A, Medhi B. Artificial intelligence in pharmacovigilance: Practical utility. Indian J Pharmacol 2019;51:373-376. [ DOI:10.4103/ijp.IJP_814_19] 7. Johnson M, Patel M, Phipps A, van der Schaar M, Boulton D, Gibbs M. The potential and pitfalls of artificial intelligence in clinical pharmacology. CPT Pharmacometrics Syst Pharmacol 2023;12:279-284. [ DOI:10.1002/psp4.12902] 8. Romm EL, Tsigelny IF. Artificial Intelligence in Drug Treatment. Annu Rev Pharmacol Toxicol 2020;60:353-369. [ DOI:10.1146/annurev-pharmtox-010919-023746] 9. van der Lee M, Swen JJ. Artificial intelligence in pharmacology research and practice. Clin Transl Sci 2023;16:31-36. [ DOI:10.1111/cts.13431] 10. Basile AO, Yahi A, Tatonetti NP. Artificial Intelligence for Drug Toxicity and Safety. Trends Pharmacol Sci 2019;40:624-635. [ DOI:10.1016/j.tips.2019.07.005] 11. Kumar M, Nguyen TPN, Kaur J, Singh TG, Soni D, Singh R, et al. Opportunities and challenges in application of artificial intelligence in pharmacology. Pharmacol Rep 2023;75:3-18. [ DOI:10.1007/s43440-022-00445-1] 12. Lin E, Lin CH, Lane HY. Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches. Int J Mol Sci 2020;21:969. [ DOI:10.3390/ijms21030969] 13. Cascella M, Schiavo D, Cuomo A, Ottaiano A, Perri F, Patrone R, et al. Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives. Pain Res Manag 2023;2023:6018736. [ DOI:10.1155/2023/6018736] 14. Bender A, Cortes-Ciriano I. Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data. Drug Discov Today 2021;26:1040-1052. [ DOI:10.1016/j.drudis.2020.11.037] 15. Ballester PJ, Stevens R, Haibe-Kains B, Huang RS, Aittokallio T. Artificial intelligence for drug response prediction in disease models. Brief Bioinform 2022;23:bbab450. 16. Poalelungi DG, Musat CL, Fulga A, Neagu M, Neagu AI, Piraianu AI, et al. Advancing Patient Care: How Artificial Intelligence Is Transforming Healthcare. J Pers Med 2023;13:1214. [ DOI:10.3390/jpm13081214] 17. Rashid MBMA, Chow EK. Artificial Intelligence-Driven Designer Drug Combinations: From Drug Development to Personalized Medicine. SLAS Technol 2019;24:124-125. [ DOI:10.1177/2472630318800774] 18. Mukherjee K. 40 Years of Trends in Pharmacological Sciences: Blending Man and Machine. Trends Pharmacol Sci 2019;40:541-542. [ DOI:10.1016/j.tips.2019.06.006] 19. Wang W, Ye Z, Gao H, Ouyang D. Computational pharmaceutics - A new paradigm of drug delivery. J Control Release 2021;338:119-136. [ DOI:10.1016/j.jconrel.2021.08.030] 20. Damiati SA. Digital Pharmaceutical Sciences. AAPS PharmSciTech 2020;21:206. [ DOI:10.1208/s12249-020-01747-4] 21. Persidis A, Persidis A. Artificial intelligence for drug design. Nat Biotechnol 1997;15:1035-6. [ DOI:10.1038/nbt1097-1035] 22. Chan HCS, Shan H, Dahoun T, Vogel H, Yuan S. Advancing Drug Discovery via Artificial Intelligence. Trends Pharmacol Sci 2019;40:592-604. [ DOI:10.1016/j.tips.2019.06.004] 23. Zhavoronkov A, Vanhaelen Q, Oprea TI. Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology? Clin Pharmacol Ther 2020;107:780-785. [ DOI:10.1002/cpt.1795] 24. Asl BA, Mogharizadeh L, Khomjani N, Rasti B, Pishva SP, Akhtari K, et al. Probing the interaction of zero valent iron nanoparticles with blood system by biophysical, docking, cellular, and molecular studies. Int J Biol Macromol 2018 1;109:639-650. [ DOI:10.1016/j.ijbiomac.2017.12.085] 25. Yang X, Wang Y, Byrne R, Schneider G, Yang S. Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery. Chem Rev 2019;119:10520-10594. [ DOI:10.1021/acs.chemrev.8b00728] 26. Munteanu CR, Dorado J, Pazos A. Artificial intelligence techniques in medicinal chemistry. Curr Top Med Chem 2013;13:525. [ DOI:10.2174/1568026611313050001] 27. Duch W, Swaminathan K, Meller J. Artificial intelligence approaches for rational drug design and discovery. Curr Pharm Des 2007;13:1497-508. [ DOI:10.2174/138161207780765954] 28. Farghali H, Kutinová Canová N, Arora M. The potential applications of artificial intelligence in drug discovery and development. Physiol Res 2021;70:S715-722. [ DOI:10.33549/physiolres.934765] 29. Noor F, Asif M, Ashfaq UA, Qasim M, Tahir Ul Qamar M. Machine learning for synergistic network pharmacology: a comprehensive overview. Brief Bioinform 2023;24:bbad120. [ DOI:10.1093/bib/bbad120] 30. Liu Q, Huang R, Hsieh J, Zhu H, Tiwari M, Liu G, et al. Landscape Analysis of the Application of Artificial Intelligence and Machine Learning in Regulatory Submissions for Drug Development From 2016 to 2021. Clin Pharmacol Ther 2023;113:771-774. [ DOI:10.1002/cpt.2668] 31. Trajanov D, Trajkovski V, Dimitrieva M, Dobreva J, Jovanovik M, Klemen M, et al. Review of Natural Language Processing in Pharmacology. Pharmacol Rev 2023;75:714-738. [ DOI:10.1124/pharmrev.122.000715] 32. Muratov EN, Bajorath J, Sheridan RP, Tetko IV, Filimonov D, Poroikov V, et al. QSAR without borders. Chem Soc Rev 2020;49:3525-3564. [ DOI:10.1039/D0CS00098A] 33. Iman M, Shafaroodi H, Davood A, Abedini M, Pishva P, Taherkhani M, et al. Design and Synthesis of 2-(Arylmethylideneamino) Isoindolines as New Potential Analgesic and Anti-Inflammatory Agents: A Molecular Hybridization Approach. Curr Pharm Des 2016;22:5760-5766. [ DOI:10.2174/1381612822666160701072127] 34. Asl BA, Mogharizadeh L, Khomjani N, Rasti B, Pishva SP, Akhtari K, et al. Probing the interaction of zero valent iron nanoparticles with blood system by biophysical, docking, cellular, and molecular studies. Int J Biol Macromol 2018;109:639-650. [ DOI:10.1016/j.ijbiomac.2017.12.085] 35. Sarkar C, Das B, Rawat VS, Wahlang JB, Nongpiur A, Tiewsoh I, et al. Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development. Int J Mol Sci 2023;24:2026. [ DOI:10.3390/ijms24032026] 36. Huang Y, Li C, Shi D, Wang H, Shang X, Wang W, et al. Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms. EPMA J 2023;14:73-86. [ DOI:10.1007/s13167-023-00315-7] 37. Schneider G, Clark DE. Automated De Novo Drug Design: Are We Nearly There Yet? Angew Chem Int Ed Engl 2019;58:10792-10803. [ DOI:10.1002/anie.201814681] 38. Zagotto G, Bortoli M. Drug Design: Where We Are and Future Prospects. Molecules 2021;26:7061. [ DOI:10.3390/molecules26227061] 39. Rudmann D, Albretsen J, Doolan C, Gregson M, Dray B, Sargeant A, et al. Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies. Toxicol Pathol 2021;49:938-949. [ DOI:10.1177/0192623320973986] 40. Putin E, Mamoshina P, Aliper A, Korzinkin M, Moskalev A, Kolosov A, et al. Deep biomarkers of human aging: Application of deep neural networks to biomarker development. Aging (Albany NY) 2016;8:1021-33. [ DOI:10.18632/aging.100968]
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