Advanced experimental models and computational tools provide dynamic frameworks for understanding oral disease progression

Photo by Rick Rothenberg / Unsplash

Frontiers in Medicine Published June 9, 2026 Medically reviewed June 9, 2026 Study authors: Jia Huang, Justin Le-Tran, Nika S. Kobayashi, Yoshifumi Kobayashi, Emi Shimizu DOI ↗ By Dr. Ji-eun Park, MD · Brain, Mind & Pain

Key Takeaway

Note that advanced models and AI tools offer more dynamic research frameworks for studying oral disease progression.

This mini-review explores the evolution of experimental models and computational tools used to study various oral conditions, including dental caries, periodontitis, and oral cancers. The scope covers the transition toward more dynamic systems, such as saliva-derived biofilm systems, organ-on-chip platforms, patient-derived organoids, and xenografts.

The authors synthesize how these models, combined with analytical techniques like spatial transcriptomics, radiomics, and AI-assisted image analysis, are increasingly used to link molecular signatures with functional disease outcomes. These advancements aim to provide a more nuanced understanding of oral diseases compared to traditional methods.

Several limitations are noted regarding current technologies, specifically the challenges in modeling chronic disease progression, incorporating viral and autoimmune components, and achieving reproducibility through standardization across different platforms. While these tools offer significant research potential, they currently serve as foundational models rather than direct clinical diagnostic tools.

Practice relevance is centered on the development of patient-relevant frameworks for understanding oral diseases. The review notes that while these innovations provide better insights into disease mechanisms, specific clinical outcomes or evidence of efficacy in human patients have not been established.

Study Details

Study typeSystematic review

EvidenceLevel 1

PublishedJun 2026

View Original Abstract ↓

Oral diseases represent one of the most widespread global health burdens, affecting billions of people worldwide, causing pain, disability, and substantial treatment costs. Despite their prevalence, progress in prevention and therapy has been limited, in part, by experimental models that do not fully capture the complexity of the oral biological and environmental landscape. Over the past decade, however, major advances in model development have expanded the possibilities for studying oral disease. This mini-review summarizes advances from 2015 to 2025, focusing on caries and endodontic infections, gingivitis and periodontitis, peri-implantitis, mucosal disorders, oral and oropharyngeal cancers, and salivary gland diseases. Recent innovations include saliva-derived biofilm systems that reproduce ecological transitions, organ-on-chip systems that replicate fluid dynamics, and patient-derived organoids and xenografts that preserve clinical characteristics. In parallel, immune-integrated models now allow direct interrogation of host responses to pathogens. Separate from these experimental platforms, advanced analytical and computational approaches, including single-cell profiling, spatial transcriptomics, radiomics, and artificial intelligence (AI)-assisted image analysis, are increasingly linking molecular signatures with structural and functional disease outcomes. Together, these experimental models and complementary analytical tools mark a shift from reductionist approaches toward dynamic, patient-relevant frameworks that better capture the complexity of oral diseases. Remaining challenges include modeling chronic disease progression, incorporating viral and autoimmune components, and improving reproducibility through standardization across platforms. Addressing these limitations will be important for translating next-generation experimental models into clinically meaningful advances in oral health care.