ReviewMolecular informatics2025
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.
Review in Molecular informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- A‑iMPO: A Design-Time Prediction Toolbox for Blood Brain Barrier Permeation Using an Integrated and Interpretable Multiparameter Optimization Framework.ACS medicinal chemistry letters · 2026Article
- Evaluating the Incremental Value of Three-Dimensional Conformer Descriptors for Blood-Brain Barrier Permeability Prediction Using the B3DB Benchmark Dataset.Pharmaceutics · 2026Article
- Mechanisms and integrative machine learning approaches to blood-brain barrier biomarker profiling for personalized ischemic stroke management.Physiological reports · 2026Review
- Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision.Pharmacopsychiatry · 2026Review
- Artificial intelligence revolutionizing CNS drug discovery and development.Drug discovery today · 2026Review
- From Polyphenols to Prodrugs: Bridging the Blood-Brain Barrier with Nanomedicine and Neurotherapeutics.International journal of molecular sciences · 2026Review
- Engineering Nanocarriers for Dopamine Stabilization and Targeted Brain Delivery: Mechanisms, Approaches and Translational Challenges.International journal of nanomedicine · 2026Review
- In Silico Modeling of Nanoparticle Transport across the Blood-Brain Barrier: A Systematic Review.Computational and structural biotechnology journal · 2026Review
- Predicting blood-brain barrier permeability of chemicals by machine learning modeling.NAM journal · 2026Article
- Integrative Profiling for BBB Permeability Using Capillary Electrochromatography, Experimental Physicochemical Parameters, and Ensemble Machine Learning.International journal of molecular sciences · 2025Article
- Antioxidant Natural Compounds Integrated with Targeted Protein Degradation: A Multi-Modal Strategy for Alzheimer's Disease Therapy.Antioxidants (Basel, Switzerland) · 2025Review
- Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.Molecular informatics · 2025Review
- Predicting 12-month functional outcome in Guillain-Barré syndrome by combining acute-phase clinical data and traditional Chinese medicine syndrome features: a retrospective machine learning study.Frontiers in neurologyArticle
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
The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of certain molecules between the general somatic circulatory system to the central nervous system (CNS). While the BBB maintains homeostasis by regulating the molecular environment induced by cerebrovascular perfusion, it also presents significant challenges in developing therapeutics intended to act on CNS targets. Many drug development practices rely partly on extensive cell and animal models to predict, to an extent, whether prospective therapeutic molecules can cross the BBB. In interest to reduce costs and improve prediction accuracy, many propose using advanced computational modeling of BBB permeability profiles leveraging empirical data. Given the scale of growth in machine learning and deep learning, we review the most recent machine learning approaches in predicting BBB permeability.
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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.