ReviewJournal of materials science. Materials in medicine2025
Biomaterials for CNS disorders: a review of development from traditional methods to AI-assisted optimization.
Review in Journal of materials science. Materials in medicine, 2025. 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.
- Therapeutic potential of edaravone and flurbiprofen in valproic acid-induced autism: Targeting oxidative stress and neuroinflammation.IBRO neuroscience reports · 2026Article
- Web-based AI application for enhanced dental disease diagnosis using advanced object detection integrated with transformer-based attention mechanism.Oral radiology · 2026Article
- Research Progress on Novel Lead Compounds for Central Nervous System Diseases.Pharmaceuticals (Basel, Switzerland) · 2026Review
- The Potential and Prospects of Hydrogel Applications in Traumatic Brain Injury Treatment.Current issues in molecular biology · 2026Review
- Innovative Biomaterials for Modulating Neuroinflammation and Promoting Repair After Traumatic Brain Injury.Pharmaceutics · 2026Review
- Engineering neuroimmune regulation: biomaterial and nanotechnology platforms for neuropathology diagnosis and targeted immunomodulation.Frontiers in immunology · 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
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Treating neurodegenerative and traumatic brain disorders is profoundly challenging due to factors like permanent tissue loss and the restrictive nature of the Blood-Brain Barrier (BBB), which limits drug delivery to the brain. Biomaterials offer a promising therapeutic strategy, serving as scaffolds for tissue regeneration or as platforms for the controlled and sustained release of therapeutic agents. These materials can localize treatment to the site of injury and prevent the rapid clearance of drugs from circulation. However, the development of biomaterials with the precise properties required for these complex applications is often slow and resource-intensive when using traditional trial-and-error methods. Artificial intelligence (AI) is emerging as a paradigm shift to overcome this limitation, poised to revolutionize the field by enabling the intelligent design, virtual screening, and rapid selection of optimal biomaterials. By analyzing vast datasets of material and biological properties, AI can accelerate the development of more effective and personalized treatments. This review examines innovative biomaterials and their applications in conditions such as ischemic stroke, spinal cord injury, and neurodegenerative diseases. A central focus is placed on how the integration of AI is accelerating the discovery of novel treatments, paving the way for the future of therapy for neurological disorders.
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.