The data that is difficult to handle is the most rewarding challenge.
Pharmaceutical companies were not initially on Tanabe’s radar as somewhere that he could make use of theoretical statistics, but his interest was piqued when he heard that a graduate from his graduate school laboratory was working for a pharmaceutical company. ‘At Chugai Pharmaceutical’s company information session, they explained that the company needs knowledge of data science, and the work of handling post-marketing data in the safety area held particular appeal for me. I heard that safety data, such as information about adverse drug reactions, is obtained under various conditions. Statistically analyzing such information is obviously very difficult, but this actually made me feel that it would be all the more rewarding. I was also fascinated by the idea that I could build a career as a data science expert at Chugai Pharmaceutical, so I applied to join the company.’
Discover themes and come up with solutions by oneself within the company.
Tanabe’s methodology for designing sample size for post-marketing surveillance was well received within the company and has already been put into practice in the field. He is keen to gain more and more such experiences with these kinds of initiatives. ‘I actively communicate with various people in the division and ask them if they have any problems in the course of their operations. When an issue comes to light through that process, I consider how it can be solved with data science, and work on collecting any missing data. Such data is difficult to handle, so there have been many tricky cases. In addition, depending on the theme, we need to learn specialized knowledge of drugs and diseases. Even so, I feel a great sense of accomplishment when I am able to propose solutions based on my approach and establish a new operation model.’
Building a system to predict adverse drug reactions for the sake of patients.
Tanabe aspires to delve more deeply into techniques in an environment where he can grow significantly as a data scientist. He also wants to obtain even more knowledge about machine learning. His current target is to leverage data science to create an innovative system for drug safety. ‘The kind of safety data I am most interested in is, of course, information on adverse drug reactions. What adverse drug reactions are likely to occur when a marketed drug is used? If I can create a system that enables us to predict this, I will be able to make a major contribution to patients’ health. This is my major goal at the moment. In the future, I want to become a specialist who has a detailed knowledge of all data possessed by Chugai Pharmaceutical and the ability to create new value in areas such as drug discovery.’
*The contents of this article, and the divisions that the people featured in this article belonged to and the names of those divisions are current as of the time of the interview.