Background: Patients who suffer from acetabular bone defects are often subjected to a decreased mobility and a loss of independence. To treat these bone defects, standard hemispherical acetabular implants offer in most cases the solution. However, when these defects are large, a custom triflange acetabular implant is needed. Although this type of implant performs well in general, it also has some drawbacks. These include higher costs and a longer design- and development cycle, since every implant is custom-made to the patient. In addition, it is expected that the triflange implant causes more stress-shielding (loss in bone-mineral-density (BMD) due to insufficient loads) than the standard implant. However, the evidence for this last statement is quite weak, since studies on both cups use different parameters,materials and environments. Objective: The objective of this study is to determine if the custom triflange cup causes indeed more stress-shielding than the standard hemispherical cup. Furthermore, the goal is to find a solution for this and the other above-mentioned drawbacks of the custom triflange cup. Therefore, the goal is to study the potential of a deformable acetabular cup, which in theory should solve these issues of the triflange cup. Methods: First a statistical shape model (SSM) of the human pelvis was developed to find patterns in defects of the pelvis, which could eliminate the need for customization. Next, a Finite Element (FE) Model with a bone-remodelling algorithm was developed to determine the difference in stress-shielding between the standard and the triflange cup. Furthermore, a FE model of a deformable implant is developed which is pressed into multiple defected pelvises. Finally, a machine-algoirthm is trained to predict the optimal deformable cup parameters, based on the type of defects. Results: Several modes of deformation were found with the SSM, which were utilised in creating damaged pelvises for the Finite Element Model. Furthermore, it was found that the custom triflange cup decreases the BMD of the pelvis by 28.6% compared to pelvis without cup. With a deformable implant, this decrease can be reduced to 7.1%, which is in the similair range as the standard hemispherical cup. Finally, it was found that the machine-learning algorithm can successfully predict the optimal cup parameters, based on the type and size of defects.