Cutting edge approach using Modeling and Simulation, AI in drug development -How to boost the clinical drug development-

How quickly reach the goal / establish the platform of artificial intelligence (AI) for drug development is one of the biggest issue for most of pharmaceutical company. Model informed drug development (MIDD) is applied across the drug development phase, and biology / physiology based sciences. One of the key expected outcomes by MIDD is to estimate 3 view points of RIGHT which are "RIGHT dose", "RIGHT patients", and "RIGHT timing". To obtain three RIGHT, it is required to demonstrate drug exposure, drug penetration, pharmacodynamic biomarker response, and clinical outcomes. Quantitative system pharmacology (QSP) model is one the tool find these "RIGHT" and is give us the hypothetical resolution against the research/clinical questions. Integrated into wet experimental data, genetic analysis, drug binding, metabolism, polymorphisms, biological pathways. Accurate computational power is required to establish the appropriate quality of QSP model, therefore abilities of AI is required. To implementation of AI to resolve the dedicated model, it is expected to accelerated the speed of drug development and QSP model primed to change the landscape of drug development. Company-Organized Symposium