Modeling and administration scheduling of fractional-order pharmacokinetic systems [PDF]
arXiv, 2017 Fractional-order dynamical systems were recently introduced in the field of pharmacokinetics where they proved powerful tools for modeling the absorption, disposition, distribution and excretion of drugs which are liable to anomalous diffusion, deep tissue trapping and other nonlinear phenomena.
arxiv
Impact of gastrointestinal physiology on drug absorption in special populations - An UNGAP review.
European Journal of Pharmaceutical Sciences, 2020 Cordula Stillhart +19 more
semanticscholar +1 more source
Drug classification based on X-ray spectroscopy combined with machine learning [PDF]
arXivThe proliferation of new types of drugs necessitates the urgent development of faster and more accurate detection methods. Traditional detection methods have high requirements for instruments and environments, making the operation complex. X-ray absorption spectroscopy, a non-destructive detection technique, offers advantages such as ease of operation,
arxiv
Chemi-net: a graph convolutional network for accurate drug property prediction [PDF]
arXiv, 2018 Absorption, distribution, metabolism, and excretion (ADME) studies are critical for drug discovery. Conventionally, these tasks, together with other chemical property predictions, rely on domain-specific feature descriptors, or fingerprints. Following the recent success of neural networks, we developed Chemi-Net, a completely data-driven, domain ...
arxiv
Towards Evolutionary-based Automated Machine Learning for Small Molecule Pharmacokinetic Prediction [PDF]
arXivMachine learning (ML) is revolutionising drug discovery by expediting the prediction of small molecule properties essential for developing new drugs. These properties -- including absorption, distribution, metabolism and excretion (ADME)-- are crucial in the early stages of drug development since they provide an understanding of the course of the drug ...
arxiv
Optimal switching strategies in multi-drug therapies for chronic diseases [PDF]
arXivAntimicrobial resistance is a threat to public health with millions of deaths linked to drug resistant infections every year. To mitigate resistance, common strategies that are used are combination therapies and therapy switching. However, the stochastic nature of pathogenic mutation makes the optimization of these strategies challenging.
arxiv
MoleculesBiological variability poses significant challenges in the development of effective therapeutics, particularly when it comes to drug solubility and bioavailability. Poor solubility across varying physiological conditions often leads to reduced absorption
Yue Zhuo, Yong-Gang Zhao, Yun Zhang
doaj +1 more source
SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction [PDF]
arXivIn drug discovery, predicting the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of small-molecule drugs is critical for ensuring safety and efficacy. However, the process of accurately predicting these properties is often resource-intensive and requires extensive experimental data.
arxiv
Integration of Genetic Algorithms and Deep Learning for the Generation and Bioactivity Prediction of Novel Tyrosine Kinase Inhibitors [PDF]
arXivThe intersection of artificial intelligence and bioinformatics has enabled significant advancements in drug discovery, particularly through the application of machine learning models. In this study, we present a combined approach using genetic algorithms and deep learning models to address two critical aspects of drug discovery: the generation of novel
arxiv
Effective combination of cold physical plasma and chemotherapy against Ewing sarcoma cells in vitro
Scientific ReportsEwing's sarcoma (ES) is the second most common bone tumor in children and adolescents and is highly malignant. Although the new chemotherapy has significantly improved the survival rate for ES from about 10 to 75%, the survival rate for metastatic tumors
Andreas Nitsch +9 more
doaj +1 more source