The DOI matches its Crossref record; 256 of the 256 references it cites were found in a registry or an index.
The significance of artificial intelligence in drug delivery system design
Abstract
Over the last decade, increasing interest has been attracted towards the application of artificial intelligence (AI) technology for analyzing and interpreting the biological or genetic information, accelerated drug discovery, and identification of the selective small-molecule modulators or rare molecules and prediction of their behavior. Application of the automated workflows and databases for rapid analysis of the huge amounts of data and artificial neural networks (ANNs) for development of the novel hypotheses and treatment strategies, prediction of disease progression, and evaluation of the pharmacological profiles of drug candidates may significantly improve treatment outcomes. Target fishing (TF) by rapid prediction or identification of the biological targets might be of great help for linking targets to the novel compounds. AI and TF methods in association with human expertise may indeed revolutionize the current theranostic strategies, meanwhile, validation approaches are necessary to overcome the potential challenges and ensure higher accuracy. In this review, the significance of AI and TF in the development of drugs and delivery systems and the potential challenging issues have been highlighted.
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Cites
2 retracted
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Cited by
Artificial intelligence in drug discovery and development
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery
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“However, these techniques also impose challenges such as inaccuracy and inefficiency [3].”
BackgroundArtificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development
Sarkar, C., Das, B., Rawat, V. S., Wahlang, J. B., Nongpiur, A., Tiewsoh, I., Lyngdoh, N. M., Das, D., Bidarolli, M., & Sony, H. T. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24032026 · Cited by 347
The strategies and techniques of drug discovery from natural products
Zhang, L., Song, J., Kong, L., Yuan, T., Li, W., Zhang, W., Hou, B., Lu, Y., & Du, G. (2020) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2020.107686 · Cited by 313
Frontiers in the treatment of glioblastoma: Past, present and emerging
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Metadata
- Authors
- Hassanzadeh, P., Atyabi, F., & Dinarvand, R.
- Venue
- Advanced Drug Delivery Reviews
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 151-152
- Pages
- 169-190
- ISSN
- 0169-409X (ISSN-L)
- OpenAlex
- W2944812497
- Cited by
- 305
- References
- 256
- FWCI
- 1.11
- Type
- journal article
- Language
- en
- Open access
- closed
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