The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice
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Submitted
21 December 2021
Published
31 May 2022
Keywords:
-
Microbial infections, Molecular docking, Molecular superimposition, 3D-pharmacophore, Drugs, Vaccines
Abstract
In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.
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References
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6. Takebe T, Imai R, Ono S. The Current Status of Drug Discovery and Development as Originated in United States Academia: The Influence of Industrial and Academic Collaboration on Drug Discovery and Development. Clin Transl Sci. 2018;11(6):597-606. doi:10.1111/cts.12577
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12. Zhao L, Ciallella HL, Aleksunes LM, Zhu H. Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling. Drug Discov Today. 2020;25(9):1624-38. doi:10.1016/j.drudis.2020.07.005
13. Pinzi L, Rastelli G. Molecular Docking: Shifting Paradigms in Drug Discovery. Int J Mol Sci. 2019;20(18):4331. doi:10.3390/ijms20184331
14. Thomford NE, Senthebane DA, Rowe A, Munro D, Seele P, Maroyi A, et al. Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery. Int J Mol Sci. 2018;19(6):1578. doi:10.3390/ijms19061578
15. Marchenko O, Fedorov V, Lee JJ, Nolan C, Pinheiro J. Adaptive Clinical Trials: Overview of Early-Phase Designs and Challenges. Ther Innov Regul Sci. 2014;48(1):20-30. doi:10.1177/2168479013513889
16. Vatansever S, Schlessinger A, Wacker D, Kaniskan HU, Jin J, Zhou MM, et al. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev. 2021;41(3):1427-73. doi:10.1002/med.21764
17. Mouchlis VD, Afantitis A, Serra A, Fratello M, Papadiamantis AG, Aidinis V, et al. Advances in de Novo Drug Design: From Conventional to Machine Learning Methods. Int J Mol Sci. 2021;22(4):1676. doi:10.3390/ijms22041676
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19. Zhou SF, Zhong WZ. Drug Design and Discovery: Principles and Applications. Molecules. 2017;22(2):279. doi:10.3390/molecules22020279
20. Hughes JP, Rees S, Kalindjian SB, Philpott KL. Principles of early drug discovery. Br J Pharmacol. 2011;162(6):1239-49. doi:10.1111/j.1476-5381.2010.01127.x
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1.
Kandi V, Vundecode A, Godalwar TR, Dasari S, Vadakedath S, Godishala V. The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice. Borneo J Pharm [Internet]. 2022May31 [cited 2024Apr.19];5(2):161-78. Available from: https://journal.umpr.ac.id/index.php/bjop/article/view/3013
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