About

The Journal of Machine Learning in Pharmaceutical Research (JMLPR) is a peer-reviewed publication dedicated to advancing the theory, algorithms, and applications of machine learning (ML) techniques in pharmaceutical research and development. With the increasing volume and complexity of biomedical data, JMLPR provides a platform for researchers, pharmaceutical scientists, and industry professionals to explore innovative ML solutions that enhance drug discovery, improve target identification, and optimize therapeutic development. The journal covers a wide range of topics, including predictive modeling, structure-activity relationship analysis, drug design, pharmacokinetics, and pharmacodynamics. JMLPR welcomes original research articles, review papers, and methodological developments that demonstrate the utility and effectiveness of ML technologies in pharmaceutical research. By fostering collaboration between ML researchers and pharmaceutical practitioners, JMLPR aims to accelerate the discovery and development of safe and effective therapeutics that address unmet medical needs and improve patient outcomes.