Objective: In Japan, the Guideline on Drug Interaction for Drug Development and Appropriate Provision of Information (GL) was notified in 2018. In the GL and the associated document, it was determined that package inserts of drugs which need to be categorized as precaution due to the significant degree of drug interactions by CYP3A inhibition should describe possible perpetrator drugs using designated expressions, such as “strong CYP3A inhibitor.” For contraindication, it was decided that all drugs should be described individually. In 2021, as supplementary information to the GL, a list of CYP substrates, inhibitors and inducers, classified based on interaction strength and CYP isoenzymes (i.e., the drug list), was published. In this study, we aimed to survey the information on drug interactions by CYP3A inhibition described in the package inserts based on information in the drug list, and to clarify the status and issues.Methods: The package inserts of 24 substrate drugs of CYP3A with contraindications for itraconazole, a strong CYP3A inhibitor, were examined, and the descriptions of strong, moderate, and other CYP3A inhibitors were studied.Results: The frequencies of contraindication for strong CYP3A inhibitors were cobicistat (75%), grapefruit juice (0%), ritonavir (92%), voriconazole (67%), clarithromycin (50%), ceritinib (0%), and posaconazole (33%). On the other hand, some CYP3A substrate drugs was contraindicated with moderate CYP3A inhibitors but not with these strong CYP3A inhibitors. Furthermore, 19 CYP3A inhibitors, which were not on the drug list published in 2021, were identified as contraindications for co-administration. Majority of these were protease inhibitors, and some have been discontinued or not available in Japan.Conclusion: The findings of this study imply the necessity of organizing scientific description based on the GL strength classification. Moreover, it is important to disseminate the information and precautions for drug interactions provided in the package inserts to medical practice.

To examine risk factors for shoulder injuries with or without history of the injuries using the stratification analysis for collegiate rugby players. 71 elite rugby players from one university rugby club joined in the preseason medical screening related to their shoulder joints, including basic demographics, history of injuries, and physical findings at that time. Subsequently, the occurrence of shoulder injuries was recorded during four playing seasons. Analysis was stratified with or without history of the injuries; player without the past history of injury, 47 players; player with the past history of injury, 24 players. As a result of all players with the past history, 13 players sustained the shoulder injuries. Internal rotational range of motion [IR ROM] (OR, 1.5; 95%CI, 1.13-1.96; p=0.004), external rotational range of motion [ER ROM] (OR, 1.9; 95%CI, 1.21-2.87; p=0.005), horizontal flexion range of motion [HF ROM] (OR, 1.3; 95%CI, 1.03-1.64; p=0.025), IR muscle strength (OR, 0.4; 95%CI, 0.20-0.65; p=0.001) and rugby experience (OR, 1.2; 95%CI, 1.02-1.46; p=0.032) were associated with the shoulder injuries. On the other hand, 10 players sustained injuries of the players without the past history of injury. IR muscle strength (OR, 0.3; 95%CI, 0.11-0.72; p=0.008) and rugby experience (OR, 1.4; 95%CI, 1.11-1.66; p=0.003) were associated with the shoulder injuries. This study clearly showed that IR, ER, HF ROM, IR muscle strength and rugby experience were important initial risk factors for shoulder injuries. Moreover, IR muscle strength and rugby experience were important recurrence risk factors for shoulder injuries.

Since infectious diseases heed no national borders, international research collaboration across borders must be enhanced. The Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan launched the J-GRID program in 2005, which consists of the two elements; (1) construction of collaboration centers in Asian and African countries on a reciprocal basis between a Japanese university/institution and a counterpart in the host country and (2) connecting those collaboration centers into a network and setting up its headquarters, CRNID. J-GRID initiated with 5 collaboration centers in 3 Asian countries has expanded to include 13 centers in 8 countries (6 in Asia and 2 in Africa). The aims of J-GRID include conducting high quality research on infectious diseases of regional and global importance, and advancing technologies and developing human resources in the field. In this way, J-GRID is expected to contribute to the public health of the host countries, our own country and the world. After the completion of the first start-up phase (2005–2009), J-GRID has stepped up its activity for the second phase (2010–2014). While the first phase was just like an incubation period, the second phase should be the exponential growth phase, maximizing its research activities. Indeed, J-GRID is now generating remarkable research outcomes with an increasing number of publications. The mid-term evaluation made by the MEXT in FY2012 commended J-GRID as an ideal model led by Japan, a world leader of science and technology, and highly recommended that the program be continued for years to come after 2014.

Since infectious diseases heed no national borders, international research collaboration across borders must be enhanced. The Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan launched the J-GRID program in the fiscal year (FY) 2005, which consists of the two elements; (1) the construction of collaboration centers in Asian and African countries on a reciprocal basis between a Japanese university/institution and an overseas partner university/institution and (2) the networking of those collaboration centers and setting up its headquarters at RIKEN. J-GRID initiated with 5 collaboration centers in 3 Asian countries has expanded to include 13 centers in 8 countries (6 in Asia and 2 in Africa). The aims of J-GRID include conducting high quality research on infectious diseases of regional and global importance, advancing relevant technologies and developing human resources in the field. In this way, J-GRID is expected to contribute to the public health of the host countries, Japan and the rest of the world. After the completion of the first start-up phase, Term I (2005–2009), J-GRID has stepped up its activity for the second step-up phase, Term II (2010–2014). While the first term was just like an incubation period, the second term should be the exponential growth phase, maximizing its research activities. Indeed, J-GRID is now generating remarkable research outcomes with an increasing number of publications. The mid-term evaluation made by the MEXT in FY2012 commended J-GRID as an ideal model to demonstrate Japan’s leadership, in science and technology, and strongly recommended its extension in years to come after Term II terminates in FY 2014.

Objective: Recently, the cost of medical care in Japan has increased as a result of an aging society.  In response to this reality, the Japanese government initiated a campaign to promote the use of generic drugs.  In spite of this campaign, Japanese consumers have doubts about the safety and reliability of generic drugs, resulting in lower usage of these drugs compared to usage in Europe and the US.
Methods: In order to clarify some of the factors that contribute to low rates of generic drug use, we carried out a survey of 400 pharmacies.  The survey data was analyzed using factor analysis and cluster analysis, which is a technique known as multivariate analysis.
Results: The results from factor analysis derived four factors: 1) generic drug usage related to generic drug prescription class, 2) the amount of generic drug prescriptions related to patient preferences, 3) patient willingness to use generic drug prescriptions, and 4) pharmacy willingness.  Cluster analysis was used to classify pharmacies participating in the survey.  The results of cluster analysis revealed three main pharmacy groups: a) low usage of generic drugs, b) moderate usage of generic drugs, and c) high usage of generic drugs.
Conclusion: The results of multivariate analysis showed that pharmacists are more willing to issue generic drugs unless doctors instruct them to use a brand-name drug.