ReviewPharmaceutics2024
Recent Progress in Multifunctional Stimuli-Responsive Combinational Drug Delivery Systems for the Treatment of Biofilm-Forming Bacterial Infections.
Review in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Nanoparticle-based therapeutic platforms for inflammatory disorders of the urinary system: Engineering local delivery, biointerface regulation, and smart responsive therapy.Materials today. Bio · 2026Review
- Smart Nano-Antibiotics: AI-Guided Stimuli-Responsive Nanoplatforms for Precision Antimicrobial Therapy.Antibiotics (Basel, Switzerland) · 2026Review
- Smart Antibiofilm Platforms Based on Synthetic Antimicrobial Peptides-Engineered Hydrogels.Polymers · 2026Review
- Review
- Nanomedicine in the Fight Against Multidrug-Resistant Infections: A Review on Emerging Strategies and Translational Prospects.International journal of nanomedicine · 2025Review
- Engineering pH and Temperature-Triggered Drug Release with Metal-Organic Frameworks and Fatty Acids.Molecules (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Drug-resistant infectious diseases pose a substantial challenge and threat to medical regimens. While adaptive laboratory evolution provides foresight for encountering such situations, it has inherent limitations. Novel drug delivery systems (DDSs) have garnered attention for overcoming these hurdles. Multi-stimuli responsive DDSs are particularly effective due to their reduced background leakage and targeted drug delivery to specific host sites for pathogen elimination. Bacterial infections create an acidic state in the microenvironment (pH: 5.0-5.5), which differs from normal physiological conditions (pH: 7.4). Infected areas are characterized by the overexpression of hyaluronidase, gelatinase, phospholipase, and other virulence factors. Consequently, several effective stimuli-responsive DDSs have been developed to target bacterial pathogens. Additionally, biofilms, structured communities of bacteria encased in a self-produced polymeric matrix, pose a significant challenge by conferring resistance to conventional antimicrobial treatments. Recent advancements in nano-drug delivery systems (nDDSs) show promise in enhancing antimicrobial efficacy by improving drug absorption and targeting within the biofilm matrix. nDDSs can deliver antimicrobials directly to the biofilm, facilitating more effective eradication of these resilient bacterial communities. Herein, this review examines challenges in DDS development, focusing on enhancing antibacterial activity and eradicating biofilms without adverse effects. Furthermore, advances in immune system modulation and photothermal therapy are discussed as future directions for the treatment of bacterial diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.