P11-01

Evaluation of Data-Driven Drug Discovery Approaches: Utilizing Redmine Ticket Management System for Tracking and Analyzing Activities

Kosuke TAKEUCHI *, Takayuki SERIZAWA

Group1, Modality Research Laboratory, DAIICHI SANKYO CO., LTD. 
( * E-mail: kosuke.takeuchi@daiichisankyo.com )

In Daiichi Sankyo Co., Ltd. (DS), a new team, the Data-Driven Drug Discovery (D4) group, was formed, consisting of chemoinformaticians and data scientists. Our main mission was to accelerate the traditional experimental design-make-test-analyze (DMTA) cycle through data science. As a result, we achieved approximately 20% increase in medicinal chemistry project time efficiency[1].
As the next step in our aim, we focused on making concrete and quantitative contributions helping to obtain drug candidates in internal research projects, while maintaining research time efficiency at the same level. To measure D4 activity quantitatively, a new system was developed on Redmine[2], a highly flexible and customizable open-source software (OSS). We have already been using Redmine as a task management system through tickets, so a new feature was appended to record D4 activity on each ticket.
In our presentation, we will show the recording system and our preliminary results. Compared to the previous report[1], we found that we continued committing SAR analysis and patent analysis. Additionally, we also found that there was an increase in proposing compound ideas for research projects. By customizing a task management system, it has become easier to monitor our daily efforts and to analyze which D4 activities are working well retrospectively and quantitatively.
[1] Kunimoto R, Bajorath J & Aoki K. From traditional to data-driven medicinal chemistry – a case study. Drug Discov Today 27, 2065-2070, 2022.
[2] https://www.redmine.org/