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...
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...
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.
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...
Journal of chemical information and modeling
38639496
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...
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...
Journal of controlled release : official journal of the Controlled Release Society
39146980
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...
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. ...
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...
Food research international (Ottawa, Ont.)
40356129
Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses significant environmental and health risks. This study quantified 15 PFAS compounds across various tissues (liver, kidney, gill, muscle, skin, lung, b...