Creating Predictable Esthetic Implant Supported Restorations: Moving from Analog to Digital solutions Using Evidence Based Concepts

Delivering predictable, esthetic implant restorations is challenging due to patient variability and the limitations of traditional workflows. This presentation outlines a simplified, technology-driven approach that enables clinicians and teams to efficiently capture and analyze data, create evidence-based treatment plans, and execute them with precision. Using digital tools and AI from planning through provisionalization and final restoration the workflow improves consistency and scalability across cases from single tooth to full arch.

Implant supported restorations carry a high level of responsibility for producing predictable outcomes. Patients present with individualized anatomic features and requests for specific desired results. How do we predictably deliver esthetic implant supported restorations efficiently on a daily basis. Analog workflows are time consuming, expensive and limited. Digital workflows sound complex and unreliable.

This presentation will discuss simplified step by step clinical workflows using technology that empowers both the dr and their staffs to rapidly collect data, comprehensively analyze patients by integrating the collected data and creating predictable evidence based treatment plans. Custom treatment tools are produced to efficiently and effectively carry out the treatment plan.  Provisionalization is enabled, abutment types and designs as well as restorative materials are selected, while AI algorithms confirm implant positions. These concepts will be discussed from the single tooth through full arch FP-1 implant treatment.