Medical Applications of Generative Design and 3D Printing
3D printing is becoming a major tool in manufacturing, industrial, medical, and sociocultural applications. This technology allows the construction of a three-dimensional object from 3D models through processes that require the deposition of materials, such as liquid molecules or grain powders, that are joined or solidified together to generate functional objects.
In manufacturing and industry, 3D printing or additive manufacturing plays a major role in the rapid prototyping of new parts and devices that can be used as starting points for large-scale manufacturing of products [1].
What is Generative Design?
Generative design is a computer-based methodology that automates the generation of virtual and optimal design solutions based on parameters, such as spatial requirements, materials, manufacturing methods, and cost constraints. The results are shapes that look organic and perform better than parts designed by traditional approaches [2].
Generative Design Benefits
Generative Design is a form of artificial intelligence that leverages the power of the cloud to create better products. It also explores multiple design options in less time than it takes to develop a single concept using traditional methods. This results in rapid prototyping and cost-effective manufacturing of a product.
For instance, generative design software can optimize a part weight, identify, and eliminate weak design areas, and reduce overall manufacturing and maintenance costs by integrating several parts into a single part. These steps are extremely important when designing products that are used for medical applications and that require a high degree of complexity and a lower cost of production.
Generative Design Applications in Medicine
Applications of generative design are numerous and are found in several industries, including manufacturing, aerospace, architecture, construction, and medicine. Generative design in 3D printing or additive manufacturing is becoming an essential tool in creating 3D models for the manufacturing of daily products, such as furniture, footwear, clothing, and art objects.
In the clinical field, generative design has a high potential to be used for personalized and customized medical applications, such as the generation of tissues and organs, disease models, drug delivery systems, implants, medical instruments, prosthetics, orthotics, and additive manufacturing objects for medical visualization and communication usages [3] [4].
For instance, biofabrication that relies on 3D printing focuses on the automated generation of tissue constructs through bioprinting, bioassembly, and subsequent generation of structures that closely match the composition and structure of native tissues, such as cartilage, bone, skin, periodontal tissues, different types of vascularized tissues, and cardiovascular tissues [4] [5] [6] [7] [8] [9].
Another advantage of this approach is its potential use in vitro as tissue analogies in toxicologic studies and disease models or for drug screening, which would also decrease the need for animal experiments.
Limitations of Bioprinting
Bioprinting is a technology that has the potential to revolutionize the medical field by printing organs and tissues for transplant. However, there are some limitations to this technology that need to be addressed before it can be widely used.
One of the biggest limitations is the lack of a standardized protocol for printing tissues and organs. Each lab may use a different method, which can lead to inconsistencies in the final product.
Another limitation is the difficulty of printing large tissues and organs. This is due to the fact that bioprinters are limited in terms of size and resolution. Finally, bioprinting is still in its early stages and there are many unknowns about how it will be used in the future.
For example, it is not clear how well-printed tissues will function in vivo or whether they will be rejected by the body.
Conclusion
Generative design is a combination of the amazing power of artificial intelligence (AI), machine learning (ML), and designer talent, that lead to the generation of innovative CAD models according to specified requirements and constraints.
In the medical field, biofabrication using 3D printing has found numerous applications in many areas of biomedical research and clinical practice. The opportunities for further application areas are only increasing in number, complexity, and added value.
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