ReviewPharmaceutics2024
Advancing Tumor Therapy: Development and Utilization of Protein-Based Nanoparticles.
Review in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Camptothecin Nanoformulations: Recent Advances in Preparation, Bioactivities, and Clinical Perspectives.Annals of biomedical engineering · 2026Review
- Protein-Based Nanomaterials for Cancer Therapy: A Comparative and Translational Perspective.Pharmaceutics · 2026Review
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Advances in Nanoparticle-Based Vitamin Delivery Systems for Precision Nutrition and Improved Bioavailability.AAPS PharmSciTech · 2026Review
- A comprehensive review on plant-derived bioactive saponins as promising antimicrobial agents: from bioavailability challenges, molecular mechanistic insights to therapeutic applications.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- Protein nanoparticles: a promising frontier in reducing lung complications from chemotherapy in pediatric oncology.Biomedical engineering online · 2025Review
- Review
- Protein-based nanoparticles for antimicrobial and cancer therapy: implications for public health.RSC advances · 2025Review
- Review
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
Abstract
Protein-based nanoparticles (PNPs) in tumor therapy hold immense potential, combining targeted delivery, minimal toxicity, and customizable properties, thus paving the way for innovative approaches to cancer treatment. Understanding the various methods available for their production is crucial for researchers and scientists aiming to harness these nanoparticles for diverse applications, including tumor therapy, drug delivery, imaging, and tissue engineering. This review delves into the existing techniques for producing PNPs and PNP/drug complexes, while also exploring alternative novel approaches. The methods outlined in this study were divided into three key categories based on their shared procedural steps: solubility change, solvent substitution, and thin flow methods. This classification simplifies the understanding of the underlying mechanisms by offering a clear framework, providing several advantages over other categorizations. The review discusses the principles underlying each method, highlighting the factors influencing the nanoparticle size, morphology, stability, and functionality. It also addresses the challenges and considerations associated with each method, including the scalability, reproducibility, and biocompatibility. Future perspectives and emerging trends in PNPs' production are discussed, emphasizing the potential for innovative strategies to overcome current limitations, which will propel the field forward for biomedical and therapeutic applications.
Indexed as
Identifiers
What Socratic 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 Socratic graph.