Multifunctional Nanomaterials for Precision Diagnostics and Drug Delivery: AI-Assisted Biosensing, Barrier-Directed Transport, Stimuli-Responsive Release, and Theranostic Integration

Nanomaterials are increasingly expected to do more than transport a payload, yet added complexity is useful only when it resolves a rate-limiting diagnostic, transport, release, or monitoring problem. This review develops a function-first framework for precision diagnostics and drug delivery in which formation and processing are linked to nanoscale structure, material properties, demonstrated function, route-specific evidence, and translational value. The scope includes AI-assisted plasmonic and terahertz biosensing; biopolymer nanoparticles and hydrogel depots; barrier-directed nose-to-brain and systemic delivery; graphene and carbon nanotube interfaces; lipid nanoparticles for nucleic acid packaging and endosomal escape; nanoporous, magnetic, and plasmonic carriers; and closed-loop theranostic systems. A platform is treated as genuinely multifunctional only when at least two deliberately engineered functions are experimentally supported and either act on distinct rate-limiting steps or close a sensing–intervention–monitoring loop. This review therefore distinguishes total loading from bioavailable payload, cellular uptake from productive delivery, imaging labels from intact carrier fate, and nominal stimulus responsiveness from controlled release in response to a physiologically realistic trigger. Recent independent studies are used to broaden comparisons across material classes and to separate proof-of-concept performance from translational evidence. Artificial intelligence is considered in three distinct roles—sensor interpretation, formulation/material optimization, and prediction of in vivo behavior—with external validation and, where a model is intended to guide decisions, prospective testing treated as essential. The resulting framework emphasizes biological identity, route-specific safety, carrier-versus-payload tracking, critical quality attributes, manufacturing reproducibility, and a minimum-evidence roadmap from concept to product.