Background: The neuroprotective efficacy of glibenclamide (GLIB) has been demonstrated in multiple rodent models of ischemia, hemorrhagic stroke, traumatic brain damage, spinal cord injury, and metastatic brain tumors. Due to its poor solubility, GLIB has low oral bioavailability, limiting its transportation to the brain via the oral route. Objectives: Here, we attempted to develop and optimize an intranasal mucoadhesive in situ gel of GLIB-loaded bilosomes using a 3² Box–Behnken design for brain drug delivery. Methods: To facilitate a longer residence time of the administered dose within the nasal cavity, the prepared bilosomes were loaded into a mucoadhesive in situ gel providing resistance to rapid mucociliary clearance. The amounts of sodium deoxycholate, the cholesterol/Span 40 mixture, and the molar ratio between the mixture’s components were chosen as independent variables, while the entrapment efficiency and in vitro drug release were selected as dependent variables. Results and conclusions: The optimal formulation was analyzed for particle size and entrapment efficiency, which were found to be 270.6 nm and 68.39%, respectively. In vitro drug release from optimal formulation after 12 h was 87.29 ± 1.98% as compared to 52.01 ± 2.04% of plain in situ gel of drug. An in vivo brain drug delivery study performed on Swiss albino mice showed that the brain concentration of drug through intranasal administration from mucoadhesive in situ gel of GLIB-bilosomes after 12 h was 2.12 ± 0.16 µg/mL as compared to 0.68 ± 0.04 µg/mL from plain in situ gel of drug. Conclusively, the developed bilosomal formulation offers a favorable intranasal substitute with enhanced therapeutic drug delivery to the brain.

Cancer remains a leading global health challenge, necessitating continuous advancements in diagnostics and therapeutics to enhance patient outcomes. According to the recent data of the American Cancer Society, an estimated 20 million new cancer cases and 9.7 million cancer deaths occurred globally in 2022, with cases projected to reach 35 million by 2050. Early and accurate diagnosis is critical for effective treatment, and the traditional methods often lack sensitivity and specificity. Advanced analytical techniques, comprising molecular and genomic diagnostics, next-generation sequencing (NGS), and artificial intelligence (AI)-driven imaging, have significantly enhanced early detection and real-time tumor monitoring. In therapeutics, precision oncology has emerged as a transformative approach, integrating immunotherapy, gene editing (CRISPR), matrix-assisted laser desorption/ionization (MALDI), CAR-T cell therapy, and nanotechnology-based delivery for targeted treatment. Dual-purpose tools like NGS, predictive modeling, and molecular profiling bridge both domains, enhancing predictive accuracy via multimodal data fusion as a paradigm-shifting analytical platform revolutionizing traditional approaches. Despite advancements, resistance and accessibility challenges entail continued innovation. These advancements, driven by the convergence of biotechnology, data science, and molecular medicine, substantiate diagnostic accuracy and therapeutic precision. This review critically examines current analytical innovations, including molecular, imaging modalities, biosensors, and therapy-guiding analytics, highlighting their integration within precision oncology frameworks.