Satellite glial cells (SGCs) in sensory ganglia are increasingly recognized as active regulators of neuronal excitability and inflammatory signaling involved in pain conditions. In craniofacial and orofacial pain, trigeminal SGCs exhibit stimulus-dependent responses that develop over time and contribute to disease-related plasticity. Additionally, advances in experimental modeling, computational analysis, and data integration have fueled interest in “digital twins” as tools for hypothesis generation and decision support in biomedicine. However, most current biomedical applications are loosely defined and rarely explicitly address glial biology. Here, we propose a digital twin-inspired framework focused on trigeminal satellite glial cells to combine stimulus-response experiments with computational state modeling. Instead of claiming a fully developed digital twin, we describe a hybrid experimental–computational approach where glial activation states are inferred from measurable outputs, iteratively refined, and used to explore what-if scenarios related to pain mechanisms and treatments. These scenarios are intended to guide experimental design and hypothesis prioritization rather than to generate clinical predictions. We detail how this framework could enhance understanding of underlying mechanisms, prioritize potential interventions, and align with New Approach Methodologies (NAMs) and the 3Rs by reducing exploratory animal use. We also discuss key limitations, including biological simplification, uncertainty, and translational challenges. By viewing glial systems as dynamic, updateable entities rather than static readouts, this approach offers a practical and ethically grounded pathway toward more integrated research on craniofacial pain.
Parisa Gazerani (Fri,) studied this question.