AIMC Topic: Blood-Brain Barrier

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Transparent Machine Learning Model to Understand Drug Permeability through the Blood-Brain Barrier.

Journal of chemical information and modeling
The blood-brain barrier (BBB) selectively regulates the passage of chemical compounds into and out of the central nervous system (CNS). As such, understanding the permeability of drug molecules through the BBB is key to treating neurological diseases...

HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data.

Nature communications
In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cells, labeling all case cells as affected, when in reality only a small fraction of them may actually be perturbed. Here, using simulations, we demonstr...

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Journal of molecular modeling
CONTEXT: This study investigates the potential of leveraging molecular properties, as determined by MD-LOVIs software and machine learning techniques, to predict the ability of compounds to cross the blood-brain barrier (BBB). Accurate prediction of ...

A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.

Molecular pharmaceutics
Given the aging populations in advanced countries globally, many pharmaceutical companies have focused on developing central nervous system (CNS) drugs. However, due to the blood-brain barrier, drugs do not easily reach the target area in the brain. ...

DeepBP: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN.

Journal of advanced research
INTRODUCTION: The blood-brain barrier (BBB) serves as a critical structural barrier and impedes the entry of most neurotherapeutic drugs into the brain. This poses substantial challenges for central nervous system (CNS) drug development, as there is ...

Neurological insights into brain-targeted cancer therapy and bioinspired microrobots.

Drug discovery today
Cancer, a multifaceted and pernicious disease, continuously challenges medicine, requiring innovative treatments. Brain cancers pose unique and daunting challenges due to the intricacies of the central nervous system and the blood-brain barrier. In t...

Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.

Scientific reports
Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improv...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychiatry research
Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a prot...

Prediction of blood-brain barrier permeability using machine learning approaches based on various molecular representation.

Molecular informatics
The assessment of compound blood-brain barrier (BBB) permeability poses a significant challenge in the discovery of drugs targeting the central nervous system. Conventional experimental approaches to measure BBB permeability are labor-intensive, cost...

Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.

British journal of clinical pharmacology
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...