The Polymer Society of Korea

Abstract

Wet-spun collagen fibers have traditionally been derived from mammalian collagen; however, concerns over zoonotic disease risk and ethical constraints remain. Fish skin, which exhibits low immunogenicity and is abundantly available as a byproduct of the marine industry, is a promising sustainable source for high–value-added materials. But fish-derived collagen has a lower hydroxyproline content (key to fiber strength) than mammalian collagen and is often collected as mixed species waste without source separation. In this study, we integrated AI-based prediction with experimental validation to establish a wet-spinning protocol for collagen extracted from mixed fish-skin waste. We confirmed the predicted solvent system experimentally, demonstrating data-driven solvent design for collagen spinning from unclassified raw materials. This hybrid strategy advances sustainable collagen fiber spinning and highlights the broader potential of AI-assisted approaches in materials science.