Good manufacturing practice and data science approach for development, manufacture, and supply of the safe and effective pharmaceutical products

Our laboratory is the first group in Japan to offer specialized education and research in regulatory science in Good Manufacturing Practice (GMP) / Good Gene, Cellular, and Tissue-based Products Manufacturing Practice (GCTP), and data science (DS) in pharmacology.
To contribute to the development of pharmaceuticals and regenerative medicinal products, as well as manufacturing and quality control, we aim to be a center of specialized research by collaborating with companies, universities, medical institutions, and government agencies from various perspectives.

Regulatory Science (RS) is defined as "the science to adjust the results of various science and technology to the most desirable form in harmony with people and society by making accurate predictions, evaluations, and judgments based on evidence for the purpose of making the results of science and technology useful to people and society. This laboratory aims to contribute to a safe and secure society where quality-assured pharmaceuticals are distributed by researching rational methods and regulatory systems that manufacturers of pharmaceuticals to properly operate GMP/GCTP, targeting the fields of manufacturing and quality control of pharmaceutical/regenerative medicinal products. Furthermore, we will research the proper application of evolving science and technology to GMP/GCTP guidelines. We will also collaborate with regulatory authorities, industry associations, and local communities to create an educational foundation for the development of human resources with expertise in manufacturing and quality control of pharmaceutical/regenerative medicinal products. In order to spread the same level of GMP education and human resource development in Japan, we are conducting joint research with the Faculty of Pharmaceutical Sciences of Tokyo University of Science and Kumamoto Health Science University, which have GMP courses.

A variety of processes in the human body are involved after a drug is administered until it travels through the body, reaches the target tissue, and exerts its medicinal effects. If we can understand the biological principles behind such drug effects, it will be possible to develop safer and more effective therapeutic methods and evaluate them. In our group, we combine data science (DS) and mathematical modeling to elucidate the mechanisms of pharmaceutical effects and disease development, and to quantitatively predict the efficacy and safety of treatments. By introducing the DS approach, we aim to discover the factors that contribute to the efficacy and safety of medicines. On the other hand, we will create a framework for quantitatively evaluating and predicting the course and outcome of pharmaceutical treatment by constructing theoretical concepts of unknown biological processes, describing them in the form of mathematical models, and performing simulations on a computer. The goal is to gain a comprehensive multi-level insight of the efficacy and safety of medicines from perspectives that cross medical, pharmaceutical, and biological sciences.