Abstract

ARTIFICIAL INTELLIGENCE AND NANOPOLYMERS: BRIDGING PREDICTIVE MODELING WITH EXPERIMENTAL DISCOVERY

Bindu Rathore, Mahendra Sharma*, Satendra Tiwari, Megha Nigam, Sachin Dangi, Sumit Kumar

.

Abstract

Artificial Intelligence (AI) and nanopolymers are moving towards a revolutionary paradigm that interconnects predictive modeling with experimental discovery. Tunable properties, biodegradability, and stimuli responsiveness Filtered to include only important concepts, nanopolymers, which have emerged as next-generation drug delivery and biomedical vehicles, can be used because of their variable characteristics, biodegradability, and stimuli responsiveness. The complexity of polymer drug interactions, nonhomogeneous patient response, and inabilities of preclinical translation, however, require sophisticated computational packages. To discover innovative functional molecules and compounds, AI has become a potent force in polymer science with the potential to forecast or predict polymer properties, or optimize the design of nanocarriers as well as shortening the discovery cycle. Quantum computing, machine learning (ML), and swarm intelligencebased methods enable the analysis of polymers to be rapidly screened, toxicity to be predicted, and nanocarriers can be rationally designed. Predictive modeling using AI with experimental studies like that of molecular dynamics simulations, and high-throughput screening lowers the cost and wasted time in the nanomedicine development process. In this review, the developements at the interface of AI and nanopolymers in predictive design of nanopolymers nanocarriers, analysis of compatibility between drugs and nanopolymers, regulatory issues and ethical considerations are discussed. Moreover, it emphasizes the concept that with experimental confirmation, and AI-based modeling a synergistic feedback loop can be established to catalyze innovation in drug delivery, personalized medicine, and smart therapeutic platforms. Finally, we summarize by listing the directions in the future that the hybrid AI-experimental framework with transparency made possible by blockchains and quantum-aided simulated may transform the polymer research and translational nanomedicine fields.

Keywords: Artificial intelligence, nanopolymers, predictive modeling, drug delivery, molecular dynamics, smart materials, biomedical applications, experimental discovery.