SynBioBeta 2026: AI-Enabled Multiscale Systems Biology for Precision Medicine and Regenerative Health

This collection is part of a series of SynBioBeta 2026 Research Topics. Please see other Research Topics in the collection here:
SynBioBeta 2026: Programmable Molecular Biology
SynBioBeta 2026: Synthetic Biology for Space Health, Closed-Loop Life Support, and Off-World Biotechnology

The field of precision medicine is undergoing a profound transformation as artificial intelligence (AI), systems biology, and molecular biosciences converge to create integrative frameworks that capture and model biological complexity across multiple scales. Traditional biomedical research has often been constrained by the compartmentalization of biological data, where discoveries at the molecular level rarely translate seamlessly into clinical outcomes. Recent advances in machine learning, multiscale modeling, and high-resolution omics technologies are now breaking these barriers. Landmark studies are demonstrating how integrating genomics, transcriptomics, proteomics, and metabolomics within AI-enabled systems can reveal emergent properties of cells, tissues, and organs.

However, despite this progress, major knowledge gaps persist. These include challenges in unifying heterogeneous datasets, interpreting foundation models in the context of biology, and translating molecular insights into tangible patient benefits. What remains missing is a systematic approach to integrate mechanistic and predictive models that can guide regenerative and individualized therapeutic strategies.

This Research Topic aims to advance the development of AI-driven frameworks that connect molecular biology with systems-level physiology to enable precision and regenerative medicine. The goal is to highlight computational and experimental approaches that bridge molecular mechanisms, disease modeling, and therapeutic design. Key questions include how multimodal data and large-scale foundation models can inform biological understanding, how cell and tissue regeneration can be computationally optimized, and how mechanistic knowledge can be embedded in predictive models to enhance diagnosis, treatment response, and long-term health outcomes. By bringing together systems biology, synthetic biology, and artificial intelligence, this topic seeks to enable a new generation of biology-driven medicine in which predictive models not only describe disease progression but also actively guide precise, durable interventions.

To gather further insights in the intersection of artificial intelligence, systems biology, and translational medicine, we welcome articles addressing, but not limited to, the following themes:

o Multimodal, multiscale, and foundation models for biological systems
o Single-cell and spatial omics integration for personalized and regenerative health
o Discovery of biomarkers and therapeutic targets using AI-augmented workflows
o Data-driven design of engineered cell and gene therapies
o Computational-experimental frameworks for regenerative and precision medicine
o AI-assisted interpretation of molecular mechanisms underlying therapy response and aging

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Artificial intelligence, systems biology, precision medicine, regenerative medicine, multiscale modeling, multi-omics integration, foundation models, single-cell omics, biomarker discovery, computational drug design

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.