Application of Artificial Intelligence in Drug Discovery and Development: Targeted Design and Toxicological Property Prediction

Xinran Wang

doi:10.54254/2753-8818/2025.AU27100

Theoretical and Natural ScienceOpen access

Application of Artificial Intelligence in Drug Discovery and Development: Targeted Design and Toxicological Property Prediction

Research Article

Open Access

Application of Artificial Intelligence in Drug Discovery and Development: Targeted Design and Toxicological Property Prediction

Xinran Wang ^1*

¹ University of Toronto

^*Corresponding author: xinranz.wang@mail.utoronto.ca

Published on 24 September 2025

TNS Vol.137

ISSN (Print): 2753-8826

ISSN (Online): 2753-8818

ISBN (Print): 978-1-80590-371-0

ISBN (Online): 978-1-80590-372-7

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Abstract

Traditional technologies for new drug research and development face numerous challenges, such as the lack of high-success-rate tools for virtual design of drug molecules based on protein three-dimensional structures (a limitation to research and development efficiency), the absence of reliable methods for generating new scaffold drug molecules, and a shortage of fast, reliable, low-cost models for drug toxicology prediction. AI can accurately predict protein structures to accelerate target design, efficiently generate new scaffold molecules adapted to targets, and greatly enhance the generalization ability of protein-ligand binding predictions. Some AI models have shown excellent performance in pharmacotoxicology prediction and treatment evaluation. These new technologies significantly shorten research and development cycles, reduce costs, improve prediction accuracy and efficiency, and drive the transformation of new drug research and development from experience-driven to data-driven approaches. This article reviews the application status and progress of AI tools in drug research and development, which focuses on two areas: AI-driven cancer drug target identification and optimization, and toxicology prediction and evaluation tools.

Keywords:

Artificial Intelligence, Targeted Drug Design, Toxicology Prediction, Tamgen

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References

[1]. Bajwa, J., Munir, U., Nori, A. and Williams, B. (2021) Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthcare Journal, 8(2), e188-e194.

[3]. Wu, H.C., Chang, D.K. and Huang, C.T. (2006) Targeted therapy for cancer. Journal of Cancer Molecules, 2(2), 57-66.

Cite this article

Wang,X. (2025). Application of Artificial Intelligence in Drug Discovery and Development: Targeted Design and Toxicological Property Prediction. Theoretical and Natural Science,137,8-12.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICBioMed 2025 Symposium: AI for Healthcare: Advanced Medical Data Analytics and Smart Rehabilitation

ISBN: 978-1-80590-371-0(Print) / 978-1-80590-372-7(Online)

Editor: Alan Wang

Conference website: https://2025.icbiomed.org/auckland.html

Conference date: 17 October 2025

Series: Theoretical and Natural Science

Volume number: Vol.137

ISSN: 2753-8818(Print) / 2753-8826(Online)

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