Research Progress on Antibody Drug Development under the Guidance of Artificial Intelligence

Nuo Xu

doi:10.54254/2753-8818/2025.AU24869

Theoretical and Natural ScienceOpen access

Research Progress on Antibody Drug Development under the Guidance of Artificial Intelligence

Research Article

Open Access

Research Progress on Antibody Drug Development under the Guidance of Artificial Intelligence

Nuo Xu ^1*

¹ School of Life Sciences, Lanzhou University,Lanzhou, China

^*Corresponding author: xun2021@lzu.edu.cn

Published on 20 July 2025

TNS Vol.126

ISSN (Print): 2753-8826

ISSN (Online): 2753-8818

ISBN (Print): 978-1-80590-265-2

ISBN (Online): 978-1-80590-266-9

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Abstract

Due to their high specificity and low toxicity, antibody drugs have emerged as a key therapeutic approach for the treatment of cancer and autoimmune diseases. In recent years, artificial intelligence (AI), as the driving force of the Fourth Industrial Revolution, has been reshaping the paradigm of antibody drug development. This paper systematically reviews the application of AI throughout the entire development pipeline of antibody drugs, including target discovery and validation, antibody design and optimization, experimental design and functional verification, as well as preclinical and clinical research. Although AI holds great promise in the field of antibody development, it still faces a number of challenges, such as inconsistent data quality, poor model interpretability, and unresolved issues in technology ethics. The integration and advancement of generative AI and cutting-edge computational technologies are expected to accelerate the transformation of antibody drug development toward a more intelligent and precise direction.

Keywords:

Antibody drugs, Artificial intelligence, Drug development

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Cite this article

Xu,N. (2025). Research Progress on Antibody Drug Development under the Guidance of Artificial Intelligence. Theoretical and Natural Science,126,10-15.

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: 978-1-80590-265-2(Print) / 978-1-80590-266-9(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.126

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

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