ReviewBioactive materials2026
Responsive nanomedicine strategies achieve pancreatic cancer precise theranostics.
Review in Bioactive materials, 2026. 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.
- Electric Field-Empowered Nanozymes: From Passive Adaptation to Active Precision Therapy.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Precision nanomedicine for lung metastatic osteosarcoma: challenges, therapeutic strategies, and perspectives.Materials today. Bio · 2026Review
- Emerging nano-immunotherapeutic strategies achieve metastatic colorectal cancer precision therapy.Journal of nanobiotechnology · 2026Review
- Nanotechnology-Driven Cancer Therapies for Precision Oncology: Advances and Clinical Outlook.International journal of nanomedicine · 2026Review
- Biomaterials in pancreatic surgery: progress and challenges in preoperative, intraoperative and postoperative care.Theranostics · 2026Review
- Biomolecule-Photosensitizer Conjugates: A Strategy to Enhance Selectivity and Therapeutic Efficacy in Photodynamic Therapy.Pharmaceuticals (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC), the predominant subtype of pancreatic cancer, ranks among the deadliest malignancies worldwide, with a 5-year survival rate remaining below 13 %. Its poor prognosis stems from complex anatomical barriers, a dense and heterogeneous tumor microenvironment (TME), and intricate molecular regulatory networks that collectively hinder early detection and limit therapeutic efficacy. Nanomedicine offers promising solutions by enhancing drug loading, improving delivery, counteracting drug resistance, and enabling stimuli-responsive control. Notably, stimuli-responsive nanotherapeutics have emerged as a transformative strategy, achieving precise drug release through activation by endogenous TME cues (e.g., acidic pH, redox gradients, hypoxia, enzyme overexpression) or exogenous triggers (e.g., ultrasound, light, magnetic fields). Endogenous-responsive systems autonomously activate at tumor sites, enhancing intratumoral drug accumulation and reducing off-target effects, while exogenous-responsive platforms enable spatiotemporal control through external modulation. Multi-responsive systems integrate both mechanisms to achieve dynamic and synergistic therapeutic effects, holding significant promise for PDAC theranostics. This review summarizes recent advances in stimuli-responsive nanotherapeutics for PDAC, detailing their activation mechanisms, biomedical applications, and theranostic potential across endogenous, exogenous, and multi-responsive modalities. It further discusses current challenges and future directions for translating these technologies into clinical practice.
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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.