著者

Hayato Akimoto Takuya Nagashima Kimino Minagawa Takashi Hayakawa Yasuo Takahashi Satoshi Asai

出版者

The Pharmaceutical Society of Japan

雑誌

Biological and Pharmaceutical Bulletin (ISSN:09186158)

巻号頁・発行日

vol.44, no.10, pp.1514-1523, 2021-10-01 (Released:2021-10-01)

参考文献数

57

被引用文献数

8

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Drug-induced liver injury (DILI) is a common adverse drug event. Spontaneous reporting systems such as the Japanese Adverse Event Report Database (JADER) have been used to evaluate the association between drugs and adverse drug events. However, the association of drugs with adverse drug events may be overestimated due to reporting biases. Therefore, it is important to objectively evaluate the association using liver function test values. The aim of the present study was to predict potential hepatotoxic drugs using real-world data including electronic medical records and the JADER database. A total of 70009 (2779 with DILI and 67230 without DILI) and 438515 (10235 with DILI and 428280 without DILI) Japanese adult patients were extracted from electronic medical records and the JADER database, respectively. Drugs with ≥100 DILI patients in both of the two databases were regarded as suspected drugs for DILI. We used multivariate logistic regression to evaluate the association between the suspected drugs and increased risk of DILI. Among the suspected drugs, broad-spectrum antibiotics such as meropenem, tazobactam/piperacillin and ceftriaxone were significantly associated with an increased risk of DILI, and meropenem had a greater risk of DILI in both of the two databases. Additionally, there were significant associations of mosapride and L-carbocisteine with increased risk of DILI. In addition to well-known associations between antibiotic drugs and DILI, mosapride and L-carbocisteine were found to be new potential signals of drugs causing hepatotoxicity. This study indicates potential hepatotoxic drugs that require further causality assessment.

著者

Shuji Kaneko Takuya Nagashima

出版者

The Pharmaceutical Society of Japan

雑誌

Biological and Pharmaceutical Bulletin (ISSN:09186158)

巻号頁・発行日

vol.43, no.3, pp.362-365, 2020-03-01 (Released:2020-03-01)

参考文献数

11

被引用文献数

15

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Recent pharmacological studies have been developed based on finding new disease-related genes, accompanied by the production of gene-manipulated disease model animals and high-affinity ligands for the target proteins. However, the emergence of this gene-based strategy in drug development has led to the rapid depletion of drug target molecules. To overcome this, we have attempted to utilize clinical big data to explore a novel and unexpected hypothesis of drug–drug interaction that would lead to drug repositioning. Here, we introduce our data-driven approach in which adverse event self-reports are statistically analyzed and compared in order to find and validate new drug targets. The hypotheses provided by such a data-driven approach will likely impact the style of future drug development and pharmaceutical study.