Harnessing Artificial Intelligence for Next-Generation Biomaterials

The field of biomaterials is undergoing a transformative shift, driven by the integration of artificial intelligence (AI) into every aspect of material discovery and application. Traditionally reliant on iterative, trial-and-error methodologies, biomaterials research is now propelled by advanced computational modeling, predictive analytics, and high-throughput data-driven strategies that offer unprecedented precision. Recent studies highlight how deep learning and neural networks can forecast the impact of alterations in polymer chemistry, nanostructure, or crosslinking on material properties. Coupled with AI-powered simulation tools, these technologies advance the prediction of biological responses, such as protein adsorption, cell adhesion, and immune compatibility, within physiological environments, thereby paving the way for tailor-made solutions in personalized medicine. However, the rapid advancement in AI-enabled biomaterials also raises pressing questions regarding ethical considerations and the regulatory frameworks required to ensure safe and responsible deployment.This Research Topic aims to consolidate current advancements at the interface of AI and biomaterials science, capturing how machine learning, deep learning, and advanced neural networks are revolutionizing scientific discovery, optimization, and translational relevance. The objective is to elucidate the power of AI in optimizing materials composition and performance, as well as its potential to replicate pathophysiological phenomena both in silico and in laboratory models, thereby improving clinical outcomes. Critical attention will also be given to the evolving regulatory landscape and the establishment of liability frameworks for autonomous AI tools in biomedical contexts. Through this focus, the Research Topic intends to foster a holistic understanding of the opportunities and challenges that shape the future of personalized and sustainable healthcare solutions developed from next-generation biomaterials.To gather further insights in the rapidly growing and evolving intersection of AI and biomaterials, this Research Topic will focus on novel studies and reviews that address computational, translational, and ethical aspects, while limiting the scope to biomaterials and their healthcare applications. We welcome contributions covering, but not limited to, the following themes:• AI-driven transformation in materials science• The role of machine learning and deep learning in biomaterials research• AI-enabled model development and optimization for enhanced clinical relevance• Predictive biomaterials and their impact on therapeutic outcomes• Ethical and regulatory frameworks surrounding AI in biomaterials and implants Topic editors: Banani Kundu, Kapil D. Patel, Byung-Gyu Kim Source: https://www.frontiersin.org/research-topics/79338/harnessing-artificial-intelligence-for-next-generation-biomaterials