INTRODUCTION: The landscape of drug discovery is rapidly evolving, with natural products (NPs) playing a pivotal role in the development of novel therapeutics. Despite their historical significance, challenges persist in fully harnessing their potent...
Model-informed drug development (MIDD) methods play critical role to ensure development of efficacious, and safe individualized therapies. The application of artificial intelligence/machine learning (AI/ML) within the field of drug development has ex...
Angewandte Chemie (International ed. in English)
Jun 1, 2025
Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far, not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeabilit...
The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform the traditionally time-consuming and expensive processes involved in bringing new therapies to mark...
Phytomedicine : international journal of phytotherapy and phytopharmacology
Apr 21, 2025
BACKGROUND: Jiedu Sangen Decoction (JSD) is widely used in the treatment of colorectal cancer (CRC) patients in southern China due to its good clinical efficacy, but the effective active ingredients are still unknown.
Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein and nucleic acid studies. This review summarizes the current status of AI and ML applications in the pharmaceutical sector, fo...
Artificial intelligence (AI) is reshaping preclinical drug research offering innovative alternatives to traditional animal testing. Advanced techniques, including machine learning (ML), deep learning (DL), AI-powered digital twins (DTs), and AI-enhan...
Journal of chemical information and modeling
Apr 15, 2025
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate. Different techniques are available to address the class i...
The future of drug discovery may be artificial intelligence (AI), but its present is not. AI is in its infancy in the field. To help AI mature, developers need nonproprietary, open, large, high-quality datasets to train and validate models, managed b...
CPT: pharmacometrics & systems pharmacology
Apr 7, 2025
With the recent and evolving regulatory frameworks regarding the usage of Artificial Intelligence (AI) in both drug and medical device development, the differentiation between data derived from observed ('true' or 'real') sources and artificial data ...
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