AI-ENHANCED POLYMER-BASED NANOPLATFORMS FOR DRUG/GENE DELIVERY

Recent progress in gene therapy has ushered in a new era of medicinal treatments and established a foundation for next-generation technologies. The success of gene therapy is significantly dependent on an effective gene delivery system. In this regard, both natural and synthetic macromolecules play a crucial role in soft nanotechnology, enabling the creation of delivery vectors with customized compositions and functionalities. We present an innovative computational approach aimed at optimizing polymer and/or nanocomposite structures as efficient components for polymer-based nanoplatforms (PBNs). These PBNs are envisioned as vital frameworks for evolving from traditional drug and gene delivery techniques to personalized medicine. By merging state-of-the-art artificial intelligence with advanced modeling methods, we enhance the adaptive design of these polymer-based nanoplatforms in a synergistic way.