AIMC Topic: Drug Discovery

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In silico prediction of potential drug-induced nephrotoxicity with machine learning methods.

Journal of applied toxicology : JAT Apr 29, 2022
In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxicity for drug candidates is critical to the success of clinical trials. Therefore, it is very importa...
Drug-Related Side Effects and Adverse Reactions Computer Simulation Algorithms Support Vector Machine Drug Discovery Humans Machine Learning
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Modern machine learning for tackling inverse problems in chemistry: molecular design to realization.

Chemical communications (Cambridge, England) Apr 28, 2022
The discovery of new molecules and materials helps expand the horizons of novel and innovative real-life applications. In pursuit of finding molecules with desired properties, chemists have traditionally relied on experimentation and recently on comb...
Machine Learning Drug Design Bayes Theorem Deep Learning Drug Discovery
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Machine learning approaches and their applications in drug discovery and design.

Chemical biology & drug design Apr 23, 2022
This review is focused on several machine learning approaches used in chemoinformatics. Machine learning approaches provide tools and algorithms to improve drug discovery. Many physicochemical properties of drugs like toxicity, absorption, drug-drug ...
Ligands Molecular Docking Simulation Drug Discovery Drug Design Artificial Intelligence Machine Learning
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From traditional to data-driven medicinal chemistry: A case study.

Drug discovery today Apr 20, 2022
Artificial intelligence (AI) and data science are beginning to impact drug discovery. It usually takes considerable time and efforts until new scientific concepts or technologies make a transition from conceptual stages to practical applicability and...
Pilot Projects Artificial Intelligence Chemistry, Pharmaceutical Drug Discovery
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Multimodal molecular imaging in drug discovery and development.

Drug discovery today Apr 13, 2022
In addition to individual imaging techniques, the combination and integration of several imaging techniques, so-called multimodal imaging, can provide large amounts of anatomical, functional, and molecular information accelerating drug discovery and ...
Artificial Intelligence Drug Discovery Forecasting Molecular Imaging
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Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure.

Molecular pharmaceutics Apr 12, 2022
Animal pharmacokinetic (PK) data as well as human and animal in vitro systems are utilized in drug discovery to define the rate and route of drug elimination. Accurate prediction and mechanistic understanding of drug clearance and disposition in anim...
Machine Learning Pharmaceutical Preparations Metabolic Clearance Rate Biological Availability Models, Biological Pharmacokinetics Drug Discovery Rats Animals
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Improving Predictions with a Multitask Convolutional Siamese Network.

Journal of chemical information and modeling Apr 5, 2022
The lead optimization phase of drug discovery refines an initial hit molecule for desired properties, especially potency. Synthesis and experimental testing of the small perturbations during this refinement can be quite costly and time-consuming. Rel...
Neural Networks, Computer Ligands Proteins Entropy Drug Discovery
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Machine Learning guided early drug discovery of small molecules.

Drug discovery today Mar 29, 2022
Machine learning (ML) approaches have been widely adopted within the early stages of the drug discovery process, particularly within the context of small-molecule drug candidates. Despite this, the use of ML is still limited in the pharmacokinetic/ph...
Drug Discovery Machine Learning
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SSGraphCPI: A Novel Model for Predicting Compound-Protein Interactions Based on Deep Learning.

International journal of molecular sciences Mar 29, 2022
Identifying compound-protein (drug-target, DTI) interactions (CPI) accurately is a key step in drug discovery. Including virtual screening and drug reuse, it can significantly reduce the time it takes to identify drug candidates and provide patients ...
Drug Discovery Proteins Deep Learning Humans Drug Delivery Systems Neural Networks, Computer
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Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging Mar 29, 2022
Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to cla...
Artificial Intelligence Drug Repositioning Drug Discovery Proteins
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