Quantitative Analysis and Predictive Modeling of Nonspecific Adsorption of Recombinant Adeno-Associated Virus onto Solid Surfaces

Recombinant adeno-associated virus (rAAV) has been increasingly employed for <i>in vivo</i> gene therapy. To ensure the particle concentration meets specifications, strategies are necessary to minimize nonspecific adsorption of rAAVs onto solid surfaces during manufacturing and drug-product dispensing into vials. In this study, we first elucidated the physicochemical factors contributing to nonspecific adsorption of rAAVs by evaluating their adsorption on model surfaces with systematically controlled hydrophilicity and surface charge. Subsequently, we constructed a predictive model through multiple regression analysis of rAAV adsorption under various formulation conditions and the physicochemical parameters of both rAAV serotypes and investigated surfaces. The results revealed that both electrostatic and hydrophobic interactions were responsible for rAAV adsorption. Consequently, we designed a hydrophilic and near-neutral surface coating, which greatly suppressed the adsorption of multiple rAAV serotypes, even under the formulation conditions of marketed products, demonstrating the high versatility and predictive accuracy of the model. These findings validated the effectiveness of the surface modification strategy developed to ensure the stable manufacturing and quality control of rAAV products, offering a foundation for further material development toward clinical applications.