A major limitation in the development of new diabetes therapies is the poor predictive capacity of current in vivo and in vitro models. Animal models show significant differences from humans in islet development, cytoarchitecture, and morphology, which reduces their translational relevance. Conversely, existing in vitro models are overly simplistic and lack key components of the pancreatic microenvironment, including stromal cells, extracellular matrix cues, and the native endocrine niche composed of pancreatic islets and a fenestrated vascular network. To overcome these limitations, bioprinting technologies enables precise spatial placement of cells and biomaterials, supporting the creation of complex multicellular systems with defined architecture and biochemical properties. Although bioprinting approaches such as inkjet, extrusion, and DLP printing have been used to fabricate insulin-producing constructs, they still struggle to reproduce the structural and cellular complexity of native pancreas in a fast, scalable, and safe manner. This thesis addresses several key aspects required to design an endocrine pancreatic bioprinted construct for use either as an in vitro model or as a potential therapeutic implant for T1D. Part I focuses on expanding the design freedom and scalability of bioprinting by converging well-established biofabrication techniques with recently developed methodologies. A major limitation of volumetric bioprinting (VBP) is the difficulty in generating constructs containing multiple independent structural elements. Chapter 2 introduces Embedded Extrusion-Volumetric Printing, which merges VBP and embedded extrusion bioprinting. This approach enables rapid fabrication of centimeter-scale, multi-material constructs with high-density patterning of multiple cell types. GelMA-based granular bioresins were engineered to function as both light-responsive resins and support baths. EmVP was applied to create synthetic biology-inspired intercellular interaction models, such as adipocyte differentiation regulated by optogenetically engineered pancreatic cells. Chapter 3 presents an alternative EmVP support bath based on optically transparent GelMA formulations with tunable molecular weight. By adjusting molecular weight and methacrylation, the mechanical properties of native pancreas were mimicked, improving cell self-organization into pseudo-islets. Chapter 4 introduces GRACE (Generative, Adaptive, Context-Aware 3D Printing), a workflow integrating 3D imaging, computer vision, and parametric modelling. GRACE enables the creation of adaptive vascular-like geometries, precise alignment of sequential prints, and overprinting on opaque surfaces through shadow-correction algorithms. Part II applies these technologies to generate functional endocrine pancreatic models. Chapter 5 reviews the essential building blocks for model design, including fabrication methods, cell sources, biomaterials, and synthetic biology. Chapter 6 details PSC-derived islets containing multiple mono-hormonal endocrine subtypes and their integration into 50–100 mm³ volumetrically bioprinted constructs produced in under 30 seconds. These tissues supported dynamic culture and real-time monitoring of insulin secretion under glucose stimulation and drug exposure. Chapter 7 introduces microgel- and microcapsule-based building blocks, annealed via volumetric bioprinting into microporous, flow-permissive geometries that support endothelial cell inclusion and co-culture. Chapter 8 demonstrates combining bioprinting with synthetic biology through light-triggered activation of optogenetic circuits relevant to β-cell function. Part III (Chapter 9) addresses translational and regulatory considerations for bioengineered pancreatic implants. Together, these studies illustrate how multi-technology bioprinting, stem cell–derived models, specialized biomaterials, and synthetic biology can generate advanced pancreatic platforms with native-like function.