ReviewPharmaceutics2026
Stimuli-Responsive Nanocarriers as Next-Generation on-Demand Drug Delivery Systems for Cancer Therapy: Mechanistic Insights, Trigger Modalities, and Translational Challenges.
Review in Pharmaceutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemotherapy has been used in cancer treatment for decades; however, standard chemotherapy treatments still have significant weaknesses, including collateral damage to healthy tissue, rapid development of drug resistance, and dose-limiting toxicity that limits therapeutic value. There is now an alternative approach using polymer materials that are responsive to biological stimuli that will allow for improved treatment of cancer while avoiding the limitations. Responsive polymer materials are designed to be inert during circulation until they reach their site of action; then, they will respond to specific triggers. These smart carriers respond to stimuli present in the tumor microenvironment (e.g., low pH, high glutathione levels, and increased proteolytic activity) or external stimuli applied at the bedside (e.g., localized heat, light, ultrasound, and applied magnetic fields). In both cases, there is a consistent pattern where the drug is released exactly where/when it is needed, with minimal drug release occurring outside that location and timeframe. Therefore, it is theorized that the use of polymeric-based delivery systems with stimuli-regulated drug release will significantly increase the concentration of drug delivered intratumorally, decrease the drug toxicity, and provide a potential mechanism to overcome the development of multidrug resistance from a variety of cancer treatments. To date, various types of responsive polymers have been developed and could be combined to give rise to a wide variety of different vehicle systems (e.g., micelles, nanogels, hydrogels, and hybrid delivery systems), with many of these carriers designed to respond to multiple stimuli simultaneously. Nonetheless, significant challenges remain in the clinical application of these materials due to tumor heterogeneity, immune system interactions, reproducibility issues, polymer chemistry advances, surface chemistry, and other interaction mechanisms. As a result of all of these evolving regulatory systems, as well as some of the emerging areas of polymer chemistry and surface engineering, theranostic integration will allow for new routes to provide therapy for patients with cancer. Additionally, because of these scientific advances, there will also be more opportunities to provide targeted, controllable, and on-demand treatments to patients using stimuli-responsive polymers.
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.