ArticleFrontiers in pharmacology2023
Development and validation of PAMPA-BBB QSAR model to predict brain penetration potential of novel drug candidates.
Article in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- DeepBBB: A Data-Composition-Aware Graph Screening Workflow for BBB-Focused CNS Library Construction and Prospective PAMPA-BBB Evaluation.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Dual-drug delivery system based on cubosomes for glioblastoma therapy: electrochemical, structural and biological characterization.Nanoscale advances · 2026Article
- Leveraging quantum chemical properties in transfer learning for predicting blood-brain barrier permeability of drugs.Drug delivery and translational research · 2026Article
- Nitrogen-Doped Graphene Quantum Dots Conjugated to Leucettinib-21 Rescue Differentiating Zebrafish Purkinje Cells by Inhibiting Dyrk1A Kinase.ACS applied nano materials · 2026Article
- Network-Medicine-Guided Drug Repurposing for Alzheimer's Disease: A Multi-Dimensional Systems Pharmacology Approach.International journal of molecular sciences · 2025Article
- Review
- Synthesis and Biological Evaluation of Novel Ramalin Derivatives as Multi-Target Agents for Alzheimer's Disease.Molecules (Basel, Switzerland) · 2025Article
- Investigating blood-brain barrier penetration and neurotoxicity of natural products for central nervous system drug development.Scientific reports · 2025Article
- Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.Molecular informatics · 2025Review
- Development and Blood-Brain Barrier Penetration of Nanovesicles Loaded with Cannabidiol.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Developing a predictive model for blood-brain-barrier permeability to explore relevance ofFrontiers in toxicology · 2025Article
- Design of an innovative nanovehicle to enhance brain permeability of a novel 5-HT6 receptor antagonist.International journal of pharmaceutics: X · 2024Article
- Serine/Threonine Protein Kinases as Attractive Targets for Anti-Cancer Drugs-An Innovative Approach to Ligand Tuning Using Combined Quantum Chemical Calculations, Molecular Docking, Molecular Dynamic Simulations, and Network-like Similarity Graphs.Molecules (Basel, Switzerland) · 2024Article
- Experimental and Computational Methods to Assess Central Nervous System Penetration of Small Molecules.Molecules (Basel, Switzerland) · 2024Review
- Article
- Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.Future medicinal chemistry · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Efficiently circumventing the blood-brain barrier (BBB) poses a major hurdle in the development of drugs that target the central nervous system. Although there are several methods to determine BBB permeability of small molecules, the Parallel Artificial Membrane Permeability Assay (PAMPA) is one of the most common assays in drug discovery due to its robust and high-throughput nature. Drug discovery is a long and costly venture, thus, any advances to streamline this process are beneficial. In this study, ∼2,000 compounds from over 60 NCATS projects were screened in the PAMPA-BBB assay to develop a quantitative structure-activity relationship model to predict BBB permeability of small molecules. After analyzing both state-of-the-art and latest machine learning methods, we found that random forest based on RDKit descriptors as additional features provided the best training balanced accuracy (0.70 ± 0.015) and a message-passing variant of graph convolutional neural network that uses RDKit descriptors provided the highest balanced accuracy (0.72) on a prospective validation set. Finally, we correlated
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.