During FY 2004 through 2008, as one of the projects in the first medium term plan, the Pharmaceuticals and Medical Devices Agency(PMDA)had been engaged in the research and establishment of data mining method as an operational support tool to assist staff in charge of post-marketing safety measures, with the goal to implement this tool in April 2009.
This article was written with objective to demonstrate the current operation process of data mining in PMDA.

PMDA, the Japanese regulatory agency, has worked for reinforcing and enhancing its post-marketing safety measures as stated in the second mid-term (FY 2009-2013) plan. MIHARI Project-Medical Information for Risk Assessment Initiative was started in FY 2009 to develop a new safety assessment system for post-marketing drugs using Japanese electronic healthcare data in PMDA. In the second mid-term, we examined characteristics of some electronic healthcare data available in Japan including, claims data, hospital information system data and Diagnosis Procedure Combination (DPC) data in order to make efficient use of those databases for the purpose of drug safety assessment. In addition, some pilot pharmacoepidemiological studies for risk assessment and drug utilization were conducted by use of these electronic healthcare data. Based on the accumulated findings, knowledge, and experiences from the pilot studies, we established the framework by FY 2013 to implement pharmacoepidemiology-based safety assessment in PMDA. In the third mid-term (FY 2014-2018), one of the important mission is to apply this framework into the current risk management process of drug safety. For that purpose, cooperation with other divisions of PMDA such as Office of Safety and Office of New Drug is a key. Simultaneously, we will work to establish an access to another database and novel pharmacoepidemiological methods using electronic healthcare data. A large-scale electronic health record database (MID-NET) as well as national claims database are expected to be an important database in the future activities of MIHARI Project. Furthermore, in April 2015, PMDA established new office focusing on Medical Informatics and Epidemiology for further promotion of electronic healthcare data utilization in Japan. In this article, we describe history and past activities of MIHARI Project followed by future challenges.

In these days, Japanese regulatory reform toward Real World Data (RWD) utilization in Pharmacovigilance (PV) has been carried out. One of the major changes is the amendment of “Ministerial Ordinance on Good Post-marketing Study Practice for Drugs” (No. 171, Ministry of Health, Labour and Welfare, dated December 20, 2004) implemented in April 2018. In this amendment, it clearly defines “Post-marketing database study” as one of post-marketing studies conducted by pharmaceutical companies. However, it does not mean that conventional post-marketing studies (e.g.；enrolling a few thousands patients in a single cohort study with primary data collection), can be simply replaced by the “Post-marketing database study” . The RWD utilization could be a trigger to accelerate efforts on pharmacovigilance in Japan for selecting the best method based on the issue to be addressed.

Although the recent revision of the ministerial ordinance on Good Post-marketing Study Practice (GPSP) included the utilization of medical information databases for post-marketing surveillance, there has been limited research on the validity of diagnosis codes and other outcome definitions in Japanese databases such as administrative claims (“receipt”) database. This task force proposed how to conduct good validations studies, based on the narrative review on around 100 published papers around the world. The established check list consists of ： (ⅰ) understanding the type of the database (e.g. administrative claims data, electronic health records, disease registry) ； (ii) understanding the setting of the validation study (e.g. “population-based” or not) ； (iii) defining the study outcome ； (iv) determining the way of linkage between databases ； (v) defining the gold standard ； (vi) selecting the sampling method (e.g. using the information of all patients in the database or a hospital, random sampling from all patients, random sampling from patients satisfying the outcome definition, random sampling from patients satisfying and not satisfying the outcome definition, “all possible cases” method) and sample size ； (vii) calculating the measures of validity (e.g. sensitivity, specificity, positive predictive value, negative predictive value) ； and (viii) discussing how to use the result for future studies. In current Japan, where the linkage between databases is logistically and legally difficult, most validation studies would to be conducted on a hospital basis. In such a situation, detailed description of hospital and patient characteristics is important to discuss the generalizability of the validation study result to the entire database. This report is expected to encourage and help to conduct appropriate validation studies.