Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry DOI Creative Commons
Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt

et al.

Chemical Society Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

We offer ten diverse perspectives exploring the transformative potential of artificial intelligence (AI) in chemistry, highlighting many challenges we face, and offering strategies to address them.

Language: Английский

Artificial intelligence in drug development for delirium and Alzheimer’s disease DOI Creative Commons
Ruixue Ai, Xianglu Xiao,

Shuling Deng

et al.

Acta Pharmaceutica Sinica B, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Neuromuscular Electrodiagnostic Medicine: Future Perspectives DOI Open Access
Faye Y. Chiou‐Tan

Journal of Electrodiagnosis and Neuromuscular Diseases, Journal Year: 2025, Volume and Issue: 27(1), P. 6 - 11

Published: April 29, 2025

Advances in neuromuscular medicine have ushered a new era of discovery and research. Innovations emerged fascicular electrodiagnosis, high-frequency musculoskeletal ultrasound, treatments for diseases. This article discusses the latest discoveries impacting medicine. These include development nerve clinics, integration artificial intelligence, explorations space In education, fellowships are being established to meet these evolving needs. Just as historic journey moon spawned race, has entered period renaissance.

Language: Английский

Citations

0
Machine learning: Python tools for studying biomolecules and drug design DOI
Fedor V. Ryzhkov, Yuliya E. Ryzhkova, Michaïl N. Elinson

et al.

Molecular Diversity, Journal Year: 2025, Volume and Issue: unknown

Published: April 29, 2025

Language: Английский

Citations

0
AI-Driven Drug Discovery for Rare Diseases DOI

Amit Gangwal,

Antonio Lavecchia

Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 17, 2024

Rare diseases (RDs), affecting 300 million people globally, present a daunting public health challenge characterized by complexity, limited treatment options, and diagnostic hurdles. Despite legislative efforts, such as the 1983 US Orphan Drug Act, more than 90% of RDs lack effective therapies. Traditional drug discovery models, marked lengthy development cycles high failure rates, struggle to meet unique demands RDs, often yielding poor returns on investment. However, advent artificial intelligence (AI), encompassing machine learning (ML) deep (DL), offers groundbreaking solutions. This review explores AI's potential revolutionize for overcoming these challenges. It discusses AI-driven advancements, repurposing, biomarker discovery, personalized medicine, genetics, clinical trial optimization, corporate innovations, novel target identification. By synthesizing current knowledge recent breakthroughs, this provides crucial insights into how AI can accelerate therapeutic ultimately improving patient outcomes. comprehensive analysis fills critical gap in literature, enhancing understanding pivotal role transforming RD research guiding future efforts vital area medicine.

Language: Английский

Citations

3
Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry DOI Creative Commons
Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt

et al.

Chemical Society Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

We offer ten diverse perspectives exploring the transformative potential of artificial intelligence (AI) in chemistry, highlighting many challenges we face, and offering strategies to address them.

Language: Английский

Citations

0