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Review
. 2023 Oct 22;15(10):e47486.
doi: 10.7759/cureus.47486. eCollection 2023 Oct.

Artificial Intelligence's Impact on Drug Discovery and Development From Bench to Bedside

Affiliations
Review

Artificial Intelligence's Impact on Drug Discovery and Development From Bench to Bedside

K S Vidhya et al. Cureus. .

Abstract

Artificial intelligence (AI) techniques have the potential to revolutionize drug release modeling, optimize therapy for personalized medicine, and minimize side effects. By applying AI algorithms, researchers can predict drug release profiles, incorporate patient-specific factors, and optimize dosage regimens to achieve tailored and effective therapies. This AI-based approach has the potential to improve treatment outcomes, enhance patient satisfaction, and advance the field of pharmaceutical sciences. International collaborations and professional organizations play vital roles in establishing guidelines and best practices for data collection and sharing. Open data initiatives can enhance transparency and scientific progress, facilitating algorithm validation.

Keywords: artificial intelligence in healthcare; drug design; drug discovery research; future of healthcare; nano technology.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Flowchart showing pharmaceutical drug manufacturing process
Figure 2
Figure 2. Flowchart showing areas of artificial intelligence application in drug design
Figure 3
Figure 3. Flowchart of overview of Virtual Screening
Figure 4
Figure 4. Schematic representation of Feedback System Control (FSC) in optimizing nanocarrier combination therapy
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
Figure 5
Figure 5. Stimulus responsive nanoplatforms in smart drug delivery system
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
Figure 6
Figure 6. Integrating wearable technologies with drug delivery systems
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

References

    1. Artificial intelligence in healthcare: transforming the practice of medicine. Bajwa J, Munir U, Nori A, Williams B. Future Healthc J. 2021;8:188–194. - PMC - PubMed
    1. Imagenet: a large-scale hierarchical image database. Deng J, Dong W, Socher R, et al. 2009 IEEE Conf Comput Vis Pattern Recognit. 2009:248–255.
    1. Data-driven modeling methods and techniques for pharmaceutical processes. Dong Y, Yang T, Xing Y, et al. Processes. 2023;11:2096.
    1. Artificial intelligence in pharmaceutical and healthcare research. Bhattamisra SK, Banerjee P, Gupta P, et al. Big Data Cogn Comput. 2023;7:10.
    1. Machine learning directed drug formulation development. Bannigan P, Aldeghi M, Bao Z, Häse F, Aspuru-Guzik A, Allen C. Adv Drug Deliv Rev. 2021;175:113806. - PubMed

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