AIMC Topic: Drug Development

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An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives.

Journal of drug targeting May 6, 2024
There are over 100 types of human cancer, accounting for millions of deaths every year. Lung cancer alone claims over 1.8 million lives per year and is expected to surpass 3.2 million by 2050, which underscores the urgent need for rapid drug developm...
Humans Antineoplastic Agents Lung Neoplasms Drug Development Machine Learning Drug Design
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The role and future prospects of artificial intelligence algorithms in peptide drug development.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie May 6, 2024
Peptide medications have been more well-known in recent years due to their many benefits, including low side effects, high biological activity, specificity, effectiveness, and so on. Over 100 peptide medications have been introduced to the market to ...
Humans Artificial Intelligence Animals Peptides Drug Discovery Machine Learning Algorithms Drug Development
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A comprehensive assessment of machine learning algorithms for enhanced characterization and prediction in orodispersible film development.

International journal of pharmaceutics May 3, 2024
Orodispersible films (ODFs) have emerged as innovative pharmaceutical dosage forms, offering patient-specific treatment through adjustable dosing and the combination of diverse active ingredients. This expanding field generates vast datasets, requiri...
Dosage Forms Administration, Oral Chemistry, Pharmaceutical Algorithms Machine Learning Drug Delivery Systems Pilot Projects Support Vector Machine Drug Development Pharmaceutical Preparations
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Use of Artificial Intelligence in Drug Development.

JAMA network open May 1, 2024
Artificial Intelligence Drug Development Humans
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Recent advances in the development of DprE1 inhibitors using AI/CADD approaches.

Drug discovery today Apr 25, 2024
Tuberculosis (TB) is a global lethal disease caused by Mycobacterium tuberculosis (Mtb). The flavoenzyme decaprenylphosphoryl-β-d-ribose 2'-oxidase (DprE1) plays a crucial part in the biosynthesis of lipoarabinomannan and arabinogalactan for the cell...
Drug Development Humans Mycobacterium tuberculosis Bacterial Proteins Artificial Intelligence Animals Drug Design Antitubercular Agents Enzyme Inhibitors Computer-Aided Design Drug Discovery Tuberculosis Alcohol Oxidoreductases
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Unleashing the power of generative AI in drug discovery.

Drug discovery today Apr 23, 2024
Artificial intelligence (AI) is revolutionizing drug discovery by enhancing precision, reducing timelines and costs, and enabling AI-driven computer-aided drug design. This review focuses on recent advancements in deep generative models (DGMs) for de...
Drug Design Drug Discovery Drug Development Algorithms Computer-Aided Design Humans Artificial Intelligence
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[The revolution of AI in drug development].

Medecine sciences : M/S Apr 23, 2024
Artificial intelligence and machine learning enable the construction of predictive models, which are currently used to assist in decision-making throughout the process of drug discovery and development. These computational models can be used to repre...
Humans Drug Discovery Drug Development Computer Simulation Precision Medicine Artificial Intelligence Machine Learning
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Leveraging Modeling and Simulation to Enhance the Efficiency of Bioequivalence Approaches for Generic Drugs: Highlights from the 2023 Generic Drug Science and Research Initiatives Public Workshop.

The AAPS journal Apr 8, 2024
The 2023 Generic Drug Science and Research Initiative Public Workshop organized by the U.S. Food and Drug Administration (FDA) discussed the research needs to improve and enhance bioequivalence (BE) approaches for generic drug development. FDA takes ...
Drugs, Generic United States Food and Drug Administration Therapeutic Equivalency United States Drug Development Artificial Intelligence
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Editorial: Artificial intelligence in drug discovery and development.

Methods (San Diego, Calif.) Apr 4, 2024
Artificial Intelligence Drug Discovery Drug Development Humans
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Towards explainable interaction prediction: Embedding biological hierarchies into hyperbolic interaction space.

PloS one Mar 21, 2024
Given the prolonged timelines and high costs associated with traditional approaches, accelerating drug development is crucial. Computational methods, particularly drug-target interaction prediction, have emerged as efficient tools, yet the explainabi...
Drug Development Machine Learning Proteins Drug Discovery
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