Harnessing Artificial Intelligence for Microneedle-Mediated Transdermal Delivery of Stimulus-Responsive Nanocarriers: A New Frontier in Personalized Cancer Immunotherapy

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Immunotherapy has transformed oncology, but immune-related adverse effects and suboptimal tumor accumulation often hamper conventional systemic delivery. Local delivery systems that integrate microneedles (MNs) with nanocarriers responsive to tumor microenvironments (TMEs) triggered by acidic, hypoxic, or enzyme-specific pH offer a precision strategy to overcome these barriers. Although in vivo studies have validated this hardware synergy, we argue that the field faces a critical bottleneck: the complexity of the multi-parameter design and non-linear discharge kinetics of these intelligent systems has exceeded the capacity of traditional experimental optimization methods. This review proposes the thesis that integrating artificial intelligence (AI) and machine learning (ML) into control software is no longer an optional complement but an imperative component for advancing this field. We comprehensively outline how AI/ML facilitates the shift from empirical to rational design: from predicting complex release kinetics and optimizing formulations, to personalizing hardware designs based on the patient's 'omics' profile. Further, we synthesize the potential of theranostic platforms, envisioning autonomous, closed-loop systems in which AI dynamically analyzes real-time biosensor data (seeing), calculates optimal responses (thinking), and triggers the release of precision drugs (acting).