ReviewBioengineering (Basel, Switzerland)2025
Leveraging Artificial Intelligence and Machine Learning for Characterizing Protein Corona, Nanobiological Interactions, and Advancing Drug Discovery.
Review in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Polysaccharide-Modified Gold Nanorod and Polydopamine Nanocarriers for Near-Infrared Light-Responsive Biomedical Applications: A Comparative Review.Molecules (Basel, Switzerland) · 2026Review
- Combinatorial cancer therapy mediated by hydroxyapatite nanoparticles: a comprehensive review.Medical oncology (Northwood, London, England) · 2026Review
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Advancing nanomedicine with machine learning: predicting protein corona and nano-bio interactions.Nanomedicine (London, England) · 2026Review
- Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.CPT: pharmacometrics & systems pharmacology · 2026Review
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Sorafenib nanomedicine in HCC: nano-bio interactions and combination therapies.Journal of nanobiotechnology · 2026Review
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Artificial Intelligence in the Design and Development of Nanoparticle Drug Delivery Systems: A Systematic Review.Advances in pharmacological and pharmaceutical sciences · 2026Review
- Cancer-Associated Fibroblast-Targeted Nanomedicine in Solid Tumor Therapy: From Mechanisms of Therapeutic Resistance to Precision Stromal Modulation.International journal of nanomedicine · 2026Review
- BioMutation: a portable graphical user interface for mutagenesis and feature analysis in proteins, nucleic acids, and their complexes.Frontiers in genetics · 2026Article
- Decoy Nanoparticles and Protein Corona Modulation: A Novel Frontier in Sepsis Treatment.International journal of nanomedicine · 2026Review
- Smart hybrid nanomaterials for chronic infections: microbiome-responsive and sustainable therapeutic platforms.Journal of nanobiotechnology · 2025Review
- Emerging Approaches for the Discovery of Lipid-Based RNA Delivery Systems.Pharmaceutics · 2025Review
- In Silico Forensic Toxicology: Is It Feasible?Toxics · 2025Review
- Peptide-Based Inorganic Nanoparticles as Efficient Intracellular Delivery Systems.Pharmaceutics · 2025Review
- Nano-Phytomedicine: Harnessing Plant-Derived Phytochemicals in Nanocarriers for Targeted Human Health Applications.Molecules (Basel, Switzerland) · 2025Review
- Overcoming translational barriers in RNA-protein docking: enhancing computational accuracy for targeted drug discovery.Future medicinal chemistry · 2025Review
- Deciphering molecular pathways driving cancer invasion and metastasis: advances and therapeutic prospects.Frontiers in oncology · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), including the protein corona's formation, significantly affect NP behavior, biodistribution, cellular uptake, and toxicity. Comprehending these interactions is pivotal for advancing the design of NPs to augment their efficacy and safety in biomedical applications. While traditional nanomedicine design relies heavily on experimental work, the use of data science and machine learning (ML) is on the rise to predict the synthesis and behavior of nanomaterials (NMs). Nanoinformatics combines computational simulations with laboratory studies, assessing risks and revealing complex nanobio interactions. Recent advancements in artificial intelligence (AI) and ML are enhancing the characterization of the protein corona and improving drug discovery. This review discusses the advantages and limitations of these approaches and stresses the importance of comprehensive datasets for better model accuracy. Future developments may include advanced deep-learning models and multimodal data integration to enhance protein function prediction. Overall, systematic research and advanced computational tools are vital for improving therapeutic outcomes and ensuring the safe use of NMs in medicine.
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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.