AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Drug Industry

Showing 21 to 30 of 75 articles

Clear Filters

What place for intelligent automation and artificial intelligence to preserve and strengthen vigilance expertise in the face of increasing declarations?

Therapie
In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI) and led its experts to confirm the potential contribution and theoretical benefit of AI in clinical research, pharmacovigilance, and in improving th...

Revolutionizing Pharmaceutical Industry: The Radical Impact of Artificial Intelligence and Machine Learning.

Current pharmaceutical design
This article explores the significant impact of artificial intelligence (AI) and machine learning (ML) on the pharmaceutical industry, which has transformed the drug development process. AI and ML technologies provide powerful tools for analysis, dec...

Adapting artificial intelligence into the evolution of pharmaceutical sciences and publishing: Technological darwinism.

Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques

SAr Regioselectivity Predictions: Machine Learning Triggering DFT Reaction Modeling through Statistical Threshold.

Journal of chemical information and modeling
Fast and accurate prospective predictions of regioselectivity can significantly reduce the time and resources spent on unproductive transformations in the pharmaceutical industry. Density functional theory (DFT) reaction modeling through transition s...

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

Chemical research in toxicology
The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-ran...

PatentNetML: A Novel Framework for Predicting Key Compounds in Patents Using Network Science and Machine Learning.

Journal of medicinal chemistry
Patents play a crucial role in drug research and development, providing early access to unpublished data and offering unique insights. Identifying key compounds in patents is essential to finding novel lead compounds. This study collected a comprehen...

AI-Driven Enhancements in Drug Screening and Optimization.

Methods in molecular biology (Clifton, N.J.)
The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, qua...

What they forgot to tell you about machine learning with an application to pharmaceutical manufacturing.

Pharmaceutical statistics
Predictive models (a.k.a. machine learning models) are ubiquitous in all stages of drug research, safety, development, manufacturing, and marketing. The results of these models are used inside and outside of pharmaceutical companies for the purpose o...