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OpenIO: An open framework for AI-native immunotherapy
Yingcheng Wu1, Hao Xiao1, Nan Jiang1
1Department of Hepatobiliary Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; State Key Laboratory of Genetics and Development of Complex Phenotypes; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education; Institutes of Biomedical Sciences; National Engineering Center for Immunotherapy; Human Phenome Institute, Fudan University; Shanghai Academy of Natural Sciences, Shanghai, China.
Open Immune Oncology (OpenIO) uses AI and omics data to advance precision oncology. This framework enables AI-driven engineering of immunotherapies, moving beyond empirical methods for better cancer treatment.
Area of Science:
- Computational Biology
- Immunology
- Oncology
Background:
- Precision oncology aims to tailor cancer treatments to individual patients.
- Current immunotherapy approaches often rely on empirical screening.
- Integrating diverse biological data is crucial for advancing treatment strategies.
Purpose of the Study:
- To introduce Open Immune Oncology (OpenIO), a novel framework.
- To integrate generative artificial intelligence (AI) and omics data for precision oncology.
- To facilitate the transition towards AI-native engineering of immunotherapies.
Main Methods:
- Leveraging biological scaling laws.
- Utilizing foundation models in AI.
- Integrating generative AI with omics data.
Main Results:
- The proposed framework, OpenIO, enables a more rational approach to immunotherapy development.
- It facilitates the transition from empirical screening to AI-driven therapeutic engineering.
- Potential for enhanced precision in oncology treatments.
Conclusions:
- Open Immune Oncology (OpenIO) offers a new paradigm for precision oncology.
- The framework supports AI-native engineering of immunotherapies.
- This approach promises to optimize cancer treatment strategies through advanced AI and omics integration.
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