Diagnostic antibodies at an inflection point: From discovery platforms to design‐oriented engineering
5 affiliations
- 1Chongqing Essence Biological Engineering Chongqing P. R. China
- 2State Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine China Agricultural University Beijing P. R. China
- 3Department of Outpatient Taihe Hospital Hubei University of Medicine Shiyan P. R. China
- 4The Center for Clinical Molecular Medical Detection The First Affiliated Hospital of Chongqing Medical University Chongqing P. R. China
- 5School of Pharmacy and Bioengineering Taihe Hospital Chongqing University of Technology Chongqing P. R. China
Abstract
Recent advances in antibody discovery technologies have profoundly reshaped in vitro diagnostics (IVD). Over the past century, diagnostic antibody development has evolved from serum‐derived polyclonal and hybridoma‐derived monoclonal antibodies to phage display, single‐B‐cell screening, reverse sequencing, and now AI‐assisted design, firmly establishing antibodies as indispensable components of modern IVD systems. Yet as antibody generation grows increasingly scalable, reproducible, and standardized, conventional metrics like affinity and specificity can no longer fully account for assay‐level diagnostic performance, widening the critical gap between binder acquisition and assay‐ready functionality. This review reveals a clear paradigm shift in diagnostic antibody research: from discovery‐centered strategies to assay‐aware, design‐oriented engineering. We organize current progress around four core themes: inherent tradeoffs among major discovery routes; context‐dependent affinity interpretation; key advances in functional antibody engineering; and AI's emerging role linking sequence optimization with structure, developability, and assay translation. A consistent trend emerges: diagnostic antibodies are evolving from passive molecular recognition reagents into engineered, structurally programmable, system‐integrated analytical units. Future IVD advances will thus depend not only on improved molecular recognition, but also on rational design of antibody behavior within complex diagnostic systems.
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BibTeX
@article{song2026diagnostic,
title = {{Diagnostic antibodies at an inflection point: From discovery platforms to design‐oriented engineering}},
author = {Qitao Song and Lulai Xu and Weilin Wu and Fei Xie and Yantong Pan and Tiantian Yang and Xiaoxia Xu and Yanyin Lin and Lihua Zhang and Jiahui Zhou and Junyou Zhou and Linping Li and Zhanhui Wang and Weijing Yi and Jing Wang},
journal = {View},
year = {2026},
month = oct,
doi = {10.1002/viw.20250218},
url = {https://doi.org/10.1002/viw.20250218},
note = {CC BY},
}
RIS
TY - JOUR
TI - Diagnostic antibodies at an inflection point: From discovery platforms to design‐oriented engineering
AU - Qitao Song
AU - Lulai Xu
AU - Weilin Wu
AU - Fei Xie
AU - Yantong Pan
AU - Tiantian Yang
AU - Xiaoxia Xu
AU - Yanyin Lin
AU - Lihua Zhang
AU - Jiahui Zhou
AU - Junyou Zhou
AU - Linping Li
AU - Zhanhui Wang
AU - Weijing Yi
AU - Jing Wang
PY - 2026
DA - 2026/10/26
JO - View
DO - 10.1002/viw.20250218
UR - https://doi.org/10.1002/viw.20250218
AB - Recent advances in antibody discovery technologies have profoundly reshaped in vitro diagnostics (IVD). Over the past century, diagnostic antibody development has evolved from serum‐derived polyclonal and hybridoma‐derived monoclonal antibodies to phage display, single‐B‐cell screening, reverse sequencing, and now AI‐assisted design, firmly establishing antibodies as indispensable components of modern IVD systems. Yet as antibody generation grows increasingly scalable, reproducible, and standardized, conventional metrics like affinity and specificity can no longer fully account for assay‐level diagnostic performance, widening the critical gap between binder acquisition and assay‐ready functionality. This review reveals a clear paradigm shift in diagnostic antibody research: from discovery‐centered strategies to assay‐aware, design‐oriented engineering. We organize current progress around four core themes: inherent tradeoffs among major discovery routes; context‐dependent affinity interpretation; key advances in functional antibody engineering; and AI's emerging role linking sequence optimization with structure, developability, and assay translation. A consistent trend emerges: diagnostic antibodies are evolving from passive molecular recognition reagents into engineered, structurally programmable, system‐integrated analytical units. Future IVD advances will thus depend not only on improved molecular recognition, but also on rational design of antibody behavior within complex diagnostic systems.
SN - 2688-268X
SN - 2688-3988
ER -