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Artificial intelligence-enabled safety monitoring in Alzheimer's disease clinical trials.
J Prev Alzheimers Dis
January 2025
Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, United States.
Background: Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by expert clinicians.
Objectives: Our study explores the use of natural language processing (NLP) and artificial intelligence (AI) methods to streamline and standardize clinician coding of adverse event data in Alzheimer's disease (AD) clinical trials.
White Depressed Areas and Tumor Infiltrating Lymphocytes: The Cancer Cure That Lies Within?
J Cutan Pathol
January 2025
Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital/Mass General Brigham, Boston, Massachusetts, USA.
This brief overview is inspired by seminal contributions by the late Dr. Martin C. Mihm, Jr.
View Article and Find Full Text PDFStructure-based drug design with equivariant diffusion models.
Nat Comput Sci
December 2024
École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Article Synopsis
- - Structure-based drug design (SBDD) focuses on creating small molecules that accurately target specific proteins, using structural data to help propose new drug candidates.
- - Current methods typically require extensive dataset preparation and retraining for different tasks, while our approach introduces a single pretrained model that can handle multiple design challenges.
- - We introduce DiffSBDD, a diffusion model that generates new ligands based on protein structures, and demonstrate how it can be enhanced with constraints for better drug candidate quality.
RNA-Puzzles Round V: blind predictions of 23 RNA structures.
Nat Methods
December 2024
GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China.
Article Synopsis
- - RNA-Puzzles is a collaborative project focused on improving the prediction of RNA three-dimensional structures, with predictions made by modeling groups before experimental structures are published.
- - A significant set of predictions was made by 18 groups for 23 different RNA structures, including various elements like ribozymes and aptamers.
- - The study highlights key challenges in RNA modeling, such as identifying helix pairs and ensuring proper stacking, and notes that some top-performing groups also excelled in a separate competition (CASP15).
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