AIMC Topic: Drug Discovery

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Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development.

International journal of molecular sciences Jan 19, 2023
The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation...
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Technology Drug Design Drug Discovery
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Transformer-based deep learning method for optimizing ADMET properties of lead compounds.

Physical chemistry chemical physics : PCCP Jan 18, 2023
A successful drug needs to exhibit both effective pharmacodynamics (PD) and safe pharmacokinetics (PK). However, the coordinated optimization of PD and PK properties in molecule generation tasks remains a great challenge for most existing methods, es...
Molecular Docking Simulation Drug Discovery Deep Learning
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Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction.

International journal of molecular sciences Jan 17, 2023
Drug distribution is an important process in pharmacokinetics because it has the potential to influence both the amount of medicine reaching the active sites and the effectiveness as well as safety of the drug. The main causes of 90% of drug failures...
Artificial Intelligence Drug Design Drug Discovery
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Artificial intelligence as a smart approach to develop antimicrobial drug molecules: A paradigm to combat drug-resistant infections.

Drug discovery today Jan 13, 2023
Antimicrobial resistance (AMR) is a silent pandemic with the third highest global mortality. The antibiotic development pipeline is scarce even though AMR has escalated uncontrollably. Artificial intelligence (AI) is a revolutionary approach, acceler...
Artificial Intelligence Anti-Bacterial Agents Anti-Infective Agents Drug Discovery
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Explaining Accurate Predictions of Multitarget Compounds with Machine Learning Models Derived for Individual Targets.

Molecules (Basel, Switzerland) Jan 13, 2023
In drug discovery, compounds with well-defined activity against multiple targets (multitarget compounds, MT-CPDs) provide the basis for polypharmacology and are thus of high interest. Typically, MT-CPDs for polypharmacology have been discovered seren...
Machine Learning Drug Discovery Polypharmacology
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Opportunities and challenges in application of artificial intelligence in pharmacology.

Pharmacological reports : PR Jan 9, 2023
Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a hug...
Humans Artificial Intelligence Machine Learning Algorithms Drug Discovery
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Deep learning in image-based phenotypic drug discovery.

Trends in cell biology Jan 7, 2023
Modern drug discovery approaches often use high-content imaging to systematically study the effect on cells of large libraries of chemical compounds. By automatically screening thousands or millions of images to identify specific drug-induced cellula...
Artificial Intelligence Machine Learning Phenotype Drug Discovery Deep Learning
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AlphaFold2 protein structure prediction: Implications for drug discovery.

Current opinion in structural biology Jan 6, 2023
The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificia...
Artificial Intelligence Drug Design Drug Discovery Proteins
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On the ability of machine learning methods to discover novel scaffolds.

Journal of molecular modeling Dec 27, 2022
The recent advances in the application of machine learning to drug discovery have made it a 'hot topic' for research, with hundreds of academic groups and companies integrating machine learning into their drug discovery projects. Nevertheless, there ...
Machine Learning Anti-Bacterial Agents Drug Discovery Thiadiazoles
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Traditional Machine and Deep Learning for Predicting Toxicity Endpoints.

Molecules (Basel, Switzerland) Dec 26, 2022
Molecular structure property modeling is an increasingly important tool for predicting compounds with desired properties due to the expensive and resource-intensive nature and the problem of toxicity-related attrition in late phases during drug disco...
Machine Learning Drug Discovery Deep Learning Molecular Structure
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