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A Comprehensive Procedure to Evaluate the In Vivo Performance of Cancer Nanomedicines
Published on: March 4, 2017
Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape
Ainara Salgado1, Sara Zalba1, Juan José Lasarte2
1Department of Pharmaceutical Sciences, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdisNA), Pamplona, Spain.
Abstract:
Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal subtypes due to late diagnosis, the absence of early biomarkers, and the presence of a complex tumor microenvironment (TME). This TME is characterized by a dense desmoplastic stroma, hypovascularization, immunosuppression, and an acidic extracellular pH. All of these factors hinder the delivery and efficacy of conventional therapies, especially in advanced stages. Nanoparticles (NPs), including liposomes, polymeric micelles, albumin-bound particles and lipid nanoparticles, have emerged as a promising tool for overcoming TME barriers, and enhance drug delivery in tumor while minimizing systemic toxicity. NPs can exploit mechanisms such as the Enhanced Permeability and Retention (EPR) effect and active targeting. Clinically approved NPs such as Nab-Paclitaxel and liposomal Irinotecan have demonstrated improved pharmacokinetics and therapeutic benefits in PDAC. Furthermore, ongoing clinical trials are exploring novel NP-based strategies such as gene delivery, radiosensitization, immunomodulation and ferroptosis induction. Despite these promising advances, significant challenges remain, including poor tumor penetration, heterogeneity in EPR, and immune recognition of NPs leading to their clearance from bloodstream before reaching the tumor. Innovative solutions such as biomimetic coatings, stimuli-responsive systems and personalized formulations, are being evaluated to enhance NP performance. Standardization of NP characterization and data reporting are essential to accelerating clinical translation. The integration of artificial intelligence and machine learning could further optimize NP design and patient stratification. Overall, nanotechnology represents a crucial frontier of research for developing more effective and personalized pancreatic cancer treatments.
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