From Virtual Modelling to Smarter Endodontic Innovation: In Silico Research for Translational Decision Making

AIM: To discuss how in silico research may function as an early translational decision layer in endodontics by supporting the prioritisation of hypotheses, technologies and experimental conditions before biological and clinical validation. SUMMARY: Endodontic outcomes emerge from interacting anatomical, mechanical, chemical, microbial and host-related variables. Conventional studies using extracted teeth, artificial canals, selected microbial models and standardised tests remain essential, yet cannot represent the full variability encountered in clinical settings. In silico approaches, including finite element analysis, computational fluid dynamics, probabilistic simulations, molecular modelling and predictive toxicology, may extend preclinical investigation by mapping plausible scenarios across pathological pathways, instrument performance, biomaterials and irrigation. Their contribution depends on a clearly defined context of use, justified input data, transparent assumptions, verification, validation, sensitivity analysis and uncertainty assessment. Computational outputs should be interpreted according to the question the model was designed to address and should guide subsequent experimental selection rather than be treated as independent evidence of clinical effectiveness.