Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze...
Machine Learning (ML) and Artificial Intelligence (AI) have become an integral part of the drug discovery and development value chain. Many teams in the pharmaceutical industry nevertheless report the challenges associated with the timely, cost effec...
In the past 40 years, therapeutic antibody discovery and development have advanced considerably, with machine learning (ML) offering a promising way to speed up the process by reducing costs and the number of experiments required. Recent progress in ...
3D structure-based drug design (SBDD) is considered a challenging and rational way for innovative drug discovery. Geometric deep learning is a promising approach that solves the accurate model training of 3D SBDD through building neural network model...
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to a readily accessible tool for cancer researchers. AI-based tools can boost research productivity in daily workflows, but can also extract hidden informati...
Journal of chemical information and modeling
May 15, 2024
Drug discovery pipelines nowadays rely on machine learning models to explore and evaluate large chemical spaces. While including 3D structural information is considered beneficial, structural models are hindered by the availability of protein-ligand ...
Journal of chemical information and modeling
May 13, 2024
Personalized cancer treatment requires a thorough understanding of complex interactions between drugs and cancer cell lines in varying genetic and molecular contexts. To address this, high-throughput screening has been used to generate large-scale dr...
Journal of chemical information and modeling
May 13, 2024
Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, validation, and application. Several modern strategies aim to mitigate the challenges associated w...
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