In the United States, 1.5 million individuals suffer a fracture due to bone disease each year. In addition, there are many unknown mechanisms behind how muscular disorders and mechanical load adversely affect bone development, such as in the disease distal arthrogryposis. Disease research in human cell models has greater translational potential compared to animal models but have faced challenges when constructing highly-specialized tissues such as bone. We propose a novel, three-dimensional bone tissue model as a platform for musculoskeletal disease modeling that allows for compressive loading. By seeding induced pluripotent stem cell (iPSC) derived osteoblasts and osteoclasts in a 3D, porous, hydroxyapatite-coated poly-L-lactide scaffold, we propose to generate a bone tissue model that replicates human tissue in a laboratory. By applying compression to the novel 3D bone tissue model, we expect to observe phenotypes of bone disorders and bone development under mechanical loading. We propose to induce osteoblast and osteoclasts lineage from mesenchymal progenitor cells and hematopoietic progenitor cells, respectively, and co-culture to identify optimal conditions for cell growth. Preliminary experiments have found success in culturing active osteoblasts from iPSC-derived mesenchymal progenitor cells. By screening for markers of cell proliferation, calcium deposition, bone resorption and secretion, the cultures can be assessed for their robustness. In parallel, a porous scaffold will be fabricated by dissolving poly-L-lactide in chloroform and molding over sodium chloride particles. Coating said scaffold in fibronectin and hydroxyapatite will improve cell adhesion and uptake bone secretion. Seeding osteoclast and osteoblasts cells in a porous scaffold will allow for improved cell diffusion and 3D growth, mimicking the human microenvironment. We expect that combining robust, osteogenic tissue culture on a bioactive scaffold that allows 3D bone growth with mechanical loading will reveal phenotypes of distal arthrogryposis. Thus, this method has significant applications in accelerating laboratory findings to clinical research.