ReviewBiomolecules2025
The Convergence of Biology and Material Science: Biomolecule-Driven Smart Drug Delivery Systems.
Review in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- 4D nanoimaging-guided smart therapeutics: spatiotemporal control of disease microenvironments.RSC advances · 2026Review
- Toward therapnostic integration as a new paradigm for precision management of interstitial cystitis driven by medical-engineering convergence.Discover nano · 2026Review
- Application of Temporally Controlled Release Systems in Periodontal Tissue Regeneration: From Material Design to Therapeutic Strategies.Pharmaceutics · 2026Review
- Plant-derived exosome-like nanovesicles as programmable bio-organic excipients: a next-generation platform for precision and immuno-silent drug delivery.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026Review
- Smart Nanoformulations for Oncology: A Review on Overcoming Biological Barriers with Active Targeting, Stimuli-Responsive, and Controlled Release for Effective Drug Delivery.Pharmaceutics · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Biomolecule-driven smart materials represent a paradigm shift in pharmacology, transitioning drug delivery from a passive process to an active, programmable, and highly specific intervention. These systems, constructed from or functionalized with biological macromolecules such as nucleic acids, peptides, proteins, and polysaccharides, are engineered to sense and respond to specific pathophysiological cues or external triggers. This review provides a comprehensive analysis of this rapidly evolving field. We first delineate the fundamental principles of stimuli-responsive actuation, categorizing systems based on their response to endogenous (pH, redox, enzymes, ROS) and exogenous (temperature, light, magnetic fields) triggers. We then conduct an in-depth survey of the primary biomolecular architectures, examining the unique design space offered by DNA nanotechnology, the functional versatility of peptides and proteins, and the biocompatibility of polysaccharides. Key therapeutic applications in oncology, inflammatory diseases, and gene therapy are discussed, highlighting how these intelligent systems are being designed to overcome critical biological barriers and enhance therapeutic efficacy. Finally, we address the formidable challenges-spanning biocompatibility, manufacturing scalability, and regulatory navigation-that constitute the "bench-to-bedside" chasm. We conclude by exploring future perspectives, including the development of multi-stimuli responsive, logic-gated systems and the transformative potential of artificial intelligence in designing the next generation of personalized nanomedicines.
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.