YAKUGAKU ZASSHI
The Pharmaceutical Society of Japan, established in 1880, is one of Japan’s oldest and most distinguished academic societies. The Society currently has around 15,000 members. It publishes three monthly scientific journals. Chemical and Pharmaceutical Bulletin (Chem. Pharm. Bull.) began publication in 1953 as Pharmaceutical Bulletin. It covers chemistry fields in the pharmaceutical and health sciences. Biological and Pharmaceutical Bulletin (Biol. Pharm. Bull.) began publication in 1978 as the Journal of Pharmacobio-Dynamics, which then merged the Journal of Health Science, another former Society’s journal, in 2012. It covers various biological topics in the pharmaceutical and health sciences. Yakugaku Zasshi (Japanese for “Pharmaceutical Science Journal”) has the longest history, with publication beginning in 1881. Yakugaku Zasshi is published mostly in Japanese, except for some articles related to clinical pharmacy and pharmaceutical education, which are published in English. The main aim of the Society’s journals is to advance the pharmaceutical sciences with research reports, scientific communication, and high-quality discussion. The average review time for articles submitted to the journals is around one month for first decision. The complete texts of all of the Society’s journals can be freely accessed through J-STAGE. The Society’s editorial committee hopes that the content of its journals will be useful to your research, and also invites you to submit your own work to the journals.

Chairman of Committee
Hidehiko Nakagawa
Graduate School of Pharmaceutical Sciences, Nagoya City University
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Published by The Pharmaceutical Society of Japan  
18,062 registered articles
(updated on December 14, 2024)
Online ISSN : 1347-5231
Print ISSN : 0031-6903
ISSN-L : 0031-6903
0.3
2022 Journal Impact Factor (JIF)
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Featured article
Volume 144 (2024) Issue 12 Pages 1125-1135
Analysis of Overdose-related Posts on Social Media
Ryuya Sato, Masami Tsuchiya, Rintaro Ichiyama, Soma Hisamura, Satoshi Watabe, Yuki Yanagisawa, Tomohiro Nishiyama, Shuntaro Yada, Eiji Aramaki, Hayato Kizaki, Shungo Imai, Satoko Hori

Intentional overdose (OD) of over-the-counter (OTC) and prescription drugs is becoming a significant social issue all over the world. While previous research has focused on drug misuse, there has been limited analysis using social networking service data. This study aims to analyze posts related to a drug overdose on Twitter® (X®) to understand the characteristics and trends of drug misuse, and to examine the applicability of social media in understanding the current situation of OD through natural language processing techniques. We collected posts in Japanese containing the term “OD” from January 10 to February 8, 2023, and analyzed 30203 posts. Using a pre-trained, fine-tuned bidirectional encoder representations from transformers (BERT) model, we classified the posts into categories, including direct mentions of OD. We examined the content for drug types and emotional context. Among the 5283 posts categorized as “Posts describing ODing,” about one-third included specific drug names or related terms. The most frequently mentioned OTC drugs included active ingredients such as codeine, dextromethorphan, ephedrine, and diphenhydramine. Prescription drugs, particularly benzodiazepines and pregabalin, were also common. Tweets peaked at midnight, suggesting a link between negative emotions and potential OD incidents. Our classifier showed high accuracy in distinguishing OD-related posts. Analyzing Twitter® posts provides valuable insights into the patterns and emotional contexts of drug misuse. Monitoring social networking services for OD-related content could help identify high-risk individuals and inform prevention strategies. Enhanced monitoring and public awareness are crucial to reducing the risks associated with both OTC and prescription drug misuse.
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Editor's pick

Drug misuse, particularly overdose (OD), is a major social issue affecting young people. This study analyzed posts written in Japanese that included the term "OD" from the most popular social media platform, X® (formerly Twitter®), using Natural Language Processing techniques. The posts related to OD comprised both prescription medications and over-the-counter drugs, often using slang terminology. By monitoring social media for OD-related content, it may be possible to identify high-risk individuals and develop effective prevention strategies.

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