In oncologic patients achieving long-term survival after mandibular reconstruction with load-bearing alloplastic implants, implant stability remains a recurring clinical problem. Despite the improvements achieved with patient-specific implants, progressive screw and implant loosening under sustained masticatory loading remain persistent long-term complications (Yang, 2024). Underlying this loss of stability, bone remodeling plays a central role: stress shielding and local overload around fixation screws induce adverse changes in peri-implant bone quality and structure. These remodeling processes are difficult to predict and control in the compromised biological environment. For patients achieving long-term survival, implant performance is also governed by cyclic mastication, rendering fatigue behavior clinically relevant (Yang, 2024; Shi, 2021). Consequently, implant stiffness, long-term structural integrity and load distribution at the bone-implant and screw-bone interfaces must be considered together to mitigate stress shielding, preserve fixation stability, and reduce the risk of fatigue-driven failure over extended time. To simultaneously achieve these performance requirements, structural topology optimization can be applied. A topology optimization algorithm determines how material can be optimally redistributed within a given design domain to achieve a desired mechanical performance subject to imposed constraints. In implant design, objective functions and constraints are selected to reflect clinically driving performance metrics. For example, bone resorption can be mitigated by closely matching the structural stiffness of the implant to that of bone, thereby optimizing long-term implant stability. In the literature on hip implants, promising results have already been achieved (Garner, 2022), where local bone resorption has been concurrently optimized against interface failure. To apply this technique to other implants, new objective functions must be identified that accurately reflect implant-specific performance metrics. In this work, such a multi-objective, density-based topology optimization problem is formulated for alloplastic mandibular implants. An initial simplified case study is proposed to investigate this algorithm.