In Silico Predictions of Various ADME/Tox Parameters The objective of this program is to apply a number of novel machine learning-based molecular modeling schemes, namely pharmacophore ensemble/support vector machine (PhE/SVM), hierarchical support vector regression (HSVR), and SVM-Pose/SVM-Score combinatorial ensemble docking, to predict various drug absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) properties play a significant role in contributing the high attrition rate of drug candidates in the drug discovery and development process. Chemistry, chemical engineering, life science, pharmaceutical science, toxicology, and/or computer science major undergraduate and/or master program students from Malaysia, Singapore, Vietnam, India, Indonesia and Thailand are more than welcome to apply for this program to learn the state-of-art technologies in the modern era of drug discovery and development.