Precision medicine has encouraged a shift from standardized treatment strategies toward decision-making based on individual patient characteristics. This concept is increasingly relevant to prosthodontics, where treatment outcomes are influenced by biological, anatomical, functional, behavioral, esthetic, and psychosocial factors. Contemporary digital technologies and biomaterials provide new opportunities to incorporate these variables into prosthodontic treatment planning, but their clinical value varies according to indication and level of evidence. This narrative review examines the emerging concept of precision prosthodontics with emphasis on patient-specific risk assessment, digital diagnostics, biomaterial selection, implant rehabilitation, functional and occlusal assessment, patient-reported outcomes, and individualized maintenance. Particular attention is given to the distinction between established clinical applications and emerging technologies that remain insufficiently validated for routine use. The review also proposes a Precision Functional Assessment Pyramid comprising biological assessment, functional evaluation, digital assessment, personalized prosthetic design, and patient-centered outcomes. Current evidence supports the selective use of digital workflows, prosthetically driven implant planning, contemporary biomaterials, functional assessment, and patient-reported outcome measures in appropriately selected clinical situations. However, evidence remains heterogeneous for several emerging technologies, particularly artificial intelligence, predictive analytics, digital twins, and biomarker-based approaches. High technical accuracy does not necessarily translate into improved patient outcomes, and long-term prospective evidence remains limited. Precision prosthodontics should therefore be regarded as an evolving decision-making framework rather than a technology-driven replacement for conventional prosthodontic principles. Future research should establish which components provide measurable clinical benefit, identify appropriate patient populations, and evaluate long-term clinical, patient-reported, and economic outcomes.
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Sikri et al. (2026) studied this question.
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