Formulation-Driven Innovation in Antifungal Therapy: From Nanotechnology to AI-Assisted Design

Invasive fungal infections are a major global health threat, contributing substantially to morbidity and mortality, particularly in immunocompromised populations. Despite the availability of four major antifungal drug classes-azoles, polyenes, echinocandins, and flucytosine-current therapies remain constrained by dose-limiting toxicity, suboptimal pharmacokinetics, and the emergence of multidrug resistance. This review critically evaluates formulation-driven strategies to optimize the therapeutic performance of existing antifungal drugs. It discusses the biological, biopharmaceutical, and clinical barriers that limit treatment outcomes and the formulation approaches developed to overcome these challenges. Particular emphasis is placed on nanotechnology-based drug delivery systems, biofilm-targeting strategies, stimuli-responsive platforms, and combination therapies. The review further highlights the emerging role of artificial intelligence (AI)-driven formulation design, predictive modeling, and precision therapeutics in advancing antifungal treatment. The integration of nanotechnology, AI-driven computational modeling, and precision therapeutics offers new opportunities to improve efficacy, reduce toxicity, and enable more personalized antifungal treatment. Together, these advances position formulation science as a key driver of innovation in next generation of antifungal therapy.