Human fungal pathogen Candida albicans causes oral infectious diseases such as oral thrush in immunocompromised patients with hyposalivation, diabetes mellitus, prolonged use of anti-biotics or immunosuppressive medicines and poor oral hygiene. An anti-fungal medication classified as a BCS class II drug, Clotrimazole has high permeability and low solubility in water. It is commercially available as lozenges, which do not uniformly distribute the drug within saliva for local therapy. This results in higher dose frequency and lower patient compliance. Therefore, in this study we proposed a niosomal based subgingival film formulation of clotrimazole for enhancing drug efficacy by improving drug solubilization capacity and improving patient compliance by prolonging the release of drug at the targeted site and reducing the dose frequency to show effective anti-fungal activity. The prepared niosomal film showed good entrapment efficiency and anti-fungal activity. Niosomal film showed better release pattern than drug loaded film.

This paper explores the transformative impact of computational pharmaceutics, integrating AI, multi-scale modeling, quantum computing, AI-driven drug discovery, and blockchain frameworks. Molecular dynamics simulations provide insights into atomic behaviors crucial for drug design. Quantum computing reduces computational costs for simulating protein-drug interactions. AI and Graph Neural Networks accelerate drug discovery and personalized medicine. Blockchain frameworks facilitate secure pharmacogenetic data sharing. These advancements revolutionize drug development, offering unprecedented efficiency, innovation, and personalized treatments.