Nanobiotechnology and AI Convergence for Antimicrobial Resistance and Predictive Precision Therapeutics

This chapter presents the Reyed Precision Convergence Framework for Antimicrobial Resistance (RPCF-AMR) as a systemic redefinition of AMR, beyond microbial-centric views. Integrating nanobiotechnology, AI-driven modeling (NexDi), and multi-scale architectures (SCF–DNPS), it addresses dynamics across host, microbial, environmental, and policy domains. Molecular dynamics, machine learning, and nanocarrier design converge to anticipate intracellular drug availability, bypass classical resistance, and optimize precision. Translational pathways, including programmable nanomaterials and stimuli-responsive carriers, operationalize One Health stewardship while reducing selective pressures in human, animal, and ecological reservoirs. RPCF-AMR reconciles historical surveillance gaps with multi-modal interventions, establishing a deployable reference standard. Through modeling and continuous feedback, it ensures predictive reliability, clinical relevance, and global scalability, defining a trajectory toward effective AMR control by 2040.