AIMC Topic: Tissue Distribution
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Tracheal Targeted Nanogrid Delivery Systems of Dexamethasone Visualized by Single-Particle Tracing and Multiscale Pathological Mapping.
ACS nano
Jun 4, 2025
Current clinical treatment of pulmonary diseases requires an advanced three-dimensional (3D) pathological atlas of the microenvironment, particularly the trachea, which is predominantly affected by lung disorders. In this study, the gridded cyclodext...
Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models.
Scientific reports
Jan 6, 2025
This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset derived from research on nanoparticle behavior for cancer treatment. The dataset includes both categorica...
A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.
Molecular pharmaceutics
Sep 26, 2024
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. ...
Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.
Journal of controlled release : official journal of the Controlled Release Society
Aug 16, 2024
Nanoparticles (NPs) can be designed for targeted delivery in cancer nanomedicine, but the challenge is a low delivery efficiency (DE) to the tumor site. Understanding the impact of NPs' physicochemical properties on target tissue distribution and tum...
Exposure Pathways of Ambient Magnetite Nanoparticles Revealed by Machine Learning-Aided Single-Particle Mass Spectrometry.
Nano letters
Jul 2, 2024
Nanosized ultrafine particles (UFPs) from natural and anthropogenic sources are widespread and pose serious health risks when inhaled by humans. However, tracing the inhaled UFPs is extremely difficult, and the distribution, translocation, and metab...
Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each Tissue.
Journal of chemical information and modeling
Apr 19, 2024
Artificial intelligence is expected to help identify excellent candidates in drug discovery. However, we face a lack of data, as it is time-consuming and expensive to acquire raw data perfectly for many compounds. Hence, we tried to develop a novel q...
A framework for prediction of personalized pediatric nuclear medical dosimetry based on machine learning and Monte Carlo techniques.
Physics in medicine and biology
Apr 7, 2023
A methodology is introduced for the development of an internal dosimetry prediction toolkit for nuclear medical pediatric applications. The proposed study exploits Artificial Intelligence techniques using Monte Carlo simulations as ground truth for a...
A deep-learning-based prediction model for the biodistribution of Y microspheres in liver radioembolization.
Medical physics
Oct 21, 2021
BACKGROUND: Radioembolization with Y microspheres is a treatment approach for liver cancer. Currently, employed dosimetric calculations exhibit low accuracy, lacking consideration of individual patient, and tissue characteristics.
Prioritizing and characterizing functionally relevant genes across human tissues.
PLoS computational biology
Jul 16, 2021
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...
Genome, Human
Tissue Distribution
Gene Expression Regulation, Developmental
Male
Neoplasms
Transcriptome
Humans
Genome-Wide Association Study
Machine Learning
Software
Female
Protein Interaction Maps
Computational Biology
Transcription Factors
Gene Regulatory Networks
Models, Genetic
Genetic Association Studies
Multigene Family
Machine learning models for classification tasks related to drug safety.
Molecular diversity
Jun 10, 2021
In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015-2021). The study fo...
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