データ駆動的抗タンパク質吸着・抗細胞接着表面設計：情報科学を用いたバイオマテリアルデザインへの挑戦

抄録

In this review, we present the current situation of designs of biomaterials using techniques of informatics. In particular, we discuss the prediction the responses of proteins and cells toward materials and data-driven design of new biomaterials. We introduce our recent work, in which we analyzed the correlation among chemical structures of molecules constituting self-assembled monolayers (SAMs), amounts of adsorbed protein, a density of adhered platelets by machine learning using an artificial neural network model. The main conclusion is that the quality of the database is a critical factor in determining the accuracy of the prediction and material design. We also discuss technical issues to develop databases efficiently and systematically to expand the possibility of data-driven strategies to design biomaterials.