AIMC Topic: 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 ...
Drug Discovery Molecular Imaging Forecasting Artificial Intelligence
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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...
Metabolic Clearance Rate Pharmacokinetics Pharmaceutical Preparations Animals Machine Learning Biological Availability Models, Biological Rats Drug Discovery
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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 Entropy Proteins 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 ...
Neural Networks, Computer Humans Drug Discovery Drug Delivery Systems Deep Learning Proteins
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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 Proteins Drug Discovery
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Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery.

Journal of computer-aided molecular design Mar 19, 2022
The support vector machine (SVM) algorithm is one of the most widely used machine learning (ML) methods for predicting active compounds and molecular properties. In chemoinformatics and drug discovery, SVM has been a state-of-the-art ML approach for ...
Drug Discovery Algorithms Cheminformatics Support Vector Machine
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Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.

International journal of molecular sciences Mar 17, 2022
The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponent...
COVID-19 Drug Treatment Small Molecule Libraries Humans High-Throughput Nucleotide Sequencing COVID-19 Artificial Intelligence Structure-Activity Relationship Antiviral Agents Drug Design SARS-CoV-2 Ligands Drug Discovery Drug Evaluation, Preclinical
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Oncological drug discovery: AI meets structure-based computational research.

Drug discovery today Mar 14, 2022
The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the di...
Machine Learning Drug Discovery Artificial Intelligence
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Generative machine learning for de novo drug discovery: A systematic review.

Computers in biology and medicine Mar 13, 2022
Recent research on artificial intelligence indicates that machine learning algorithms can auto-generate novel drug-like molecules. Generative models have revolutionized de novo drug discovery, rendering the explorative process more efficient. Several...
Drug Discovery Machine Learning Drug Design Artificial Intelligence Neural Networks, Computer
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