The future of bone regeneration: Artificial intelligence in biomaterials discovery

Bone defect is a highly prevalent disorder. Given that many people, especially the elderly are suffering from it, there's an urgent need for the development of bone tissue regeneration engineering. Multifarious artificial bone substitute biomaterials such as metals, bioceramics and polymers have been favored over autologous and allogeneic bone grafts because of their ease of sampling and good biocompatibility. However, not all the existing materials can fulfill the excellent properties of promoting bone regeneration, while new materials are difficult to tap. The advent of the age of big data has enabled artificial intelligence to provide fresh insights for materials discovery. Machine learning is a branch of AI, which can complete complex calculations and data analysis accurately and efficiently, so as to realize the discovery and reuse of materials. This article describes various machine learning models and reviews their examples in predicting the properties of bone regeneration materials, including biocompatibility, mechanical properties, toxicity, antibacterial properties, degradability, angiogenic and osteogenic properties. It allows people to more systematically capture a whole picture of bone regeneration, and hopefully provides a useful glimpse into the discovery of materials for bone regeneration.