A Review of Artificial Intelligence in 3D Printing. Part A: From Scaffold Design to Pre-Print Optimization

Three-dimensional (3D) printing offers significant potential in craniofacial surgery by enabling the production of patient-specific scaffolds and implants that precisely restore both function and aesthetics to compromised tissue structures. While this technology presents distinct advantages, ongoing challenges persist in optimizing design parameters, geometry, and material selection, as these processes traditionally rely on comprehensive mechanical testing and iterative characterization. The emergence of artificial intelligence (AI) has notably influenced clinical practice, extending into biomedical 3D printing workflows. AI-driven advancements have improved imaging and anatomical reconstruction through automated segmentation, as well as more efficient computer-aided design of patient-specific implants, scaffolds, and surgical tools. These advancements have streamlined the design-to-print process and reduced operator variability. This review provides an overview of the role of AI in enhancing the design and optimization stages of the additive manufacturing workflow. Key challenges and barriers are discussed, relevant applications and technological advancements are outlined, and prospective avenues for future research are identified.