Therapeutic Targets, Pharmacological Mechanisms, and Delivery Strategies for Diabetic Peripheral Neuropathy
Abstract
With the global diabetes population projected to reach 783 million by 2045, diabetic peripheral neuropathy (DPN) remains a common and debilitating complication characterized by metabolic stress, inflammation, and microvascular dysfunction. This review summarizes current interventions for DPN from the perspective of therapeutic targets, pharmacological mechanisms, and emerging delivery strategies. Conventional pharmacotherapy mainly provides symptomatic relief; first-line analgesics such as duloxetine and pregabalin offer only moderate benefit, with a number needed to treat of approximately 4-5. Natural products, including resveratrol, ginkgo biloba, and tanshinone IIA, show antioxidant and anti-inflammatory potential, although supporting evidence remains largely preclinical. Emerging targeted therapies and nanocarrier-based delivery systems may improve disease modification and drug bioavailability. Overall, DPN treatment remains limited by the lack of disease-modifying therapies, insufficient high-quality clinical evidence, and major translational barriers. Future priorities include mechanism-based stratification, combination strategies, and rigorous trials incorporating objective and patient-reported outcomes.
Read the paper
Related studies
- Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
- De Novo Transcriptome Analysis and Detection of Antimicrobial Peptides of the American Cockroach Periplaneta americana (Linnaeus)
- Molecular Characterization and Expression Profiling of Tomato GRF Transcription Factor Family Genes in Response to Abiotic Stresses and Phytohormones
- Assembly of Tight Junction Strands: Claudin-10b and Claudin-3 Form Homo Tetrameric Building Blocks that Polymerise in a Channel-Independent Manner
- Update of the Pompe variant database for the prediction of clinical phenotypes: Novel disease‐associated variants, common sequence variants, and results from newborn screening
- Machine Learning-Based SERS Chemical Space for Two-Way Prediction of Structures and Spectra of Untrained Molecules
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.