4．Utilization of Real World Data for Post-marketing Pharmacovigilance Activity / 薬剤疫学

Good Post-Marketing Study Practice (GPSP) changed in April 2018, allows pharmaceutical companies to use a real-world data for pharmacovigilance activity. On the other hand, it is known that there are 3 major dimensions of pharmacovigilance： “Monitoring, vigilance, and science：building the best evidence” ,“Regulation, industry, and legal system：ensuring public health” and “Medicine, medicines, and uncertainty : doing good to patients” . Therefore, in this article, we consider how the change of GPSP reflects on the 3 features of pharmacovigilance.In general, it is thought that the change of GPSP contributes pharmacovigilance, considering the 3 features of pharmacovigilance. On the other hand, there are some points to improve pharmacovigilance system：1) how a safety question for pharmacovigilance should be addressed, 2) how information of routine pharmacovigilance should contribute to a safety question to be addressed, 3) how a feasibility assessment (assessment of data source before conducting a formal comparative activity) should be conducted, and 4) a necessity of a variety of methodology and data sources such as descriptive studies and disease registry. These improvements will contribute to global standardization and give us global competence.Overall, it is very difficult to consider the best safety question, data source and methodology from many options. However, it is thought that keep considering them in order to accumulate experiences is important for our ultimate goal, which is to help our patients. We expect more discussions among all the stakeholders together.

Task Force Report on the Validation of Diagnosis Codes and Other Outcome Definitions in the Japanese Receipt Data / 薬剤疫学

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.

<b>3. Contributions of Databases for Vaccines Pharmacovigilance </b> / 薬剤疫学

Pharmacovigilance for vaccines has different considerations from other drugs. In this article, contributions of databases for vaccines pharmacovigilance are discussed, such as spontaneous case reporting databases and medical information databases (claims databases and electronic health record databases). Regarding spontaneous case reporting databases, some databases such as in-house databases and Japanese Adverse Drug Event Report database (JADER) have been already established, and can be utilized for detection of a vaccination failure, a vaccine quality defect-related issue and a statistical safety signal. In the future, a pharmacovigilance activity for vaccines with spontaneous case reporting databases will be expected to become more robust by integrating data which pharmaceutical companies and regulators respectively accumulate and by compiling data from current regulatory programs. Regarding medical information databases, while there is a critical limitation that vaccination information cannot be captured, some points can be utilized, for example, to understand background incidence/trend of events or infections. Also there is a possibility that an assessment by using medical information databases can be alternative means of current regulatory programs. In the future, a paradigm shift will be expected through establishment of further medical information databases, for example, by standardization of vaccine code on the electronic medical record and by linkage of vaccine data to the medical information databases.

<b>3．For a Change of Pharmacovigilance Activities, from a Viewpoint of a Pharmaceutical Company </b> / 薬剤疫学

This article describes findings about effective utilization of electronic medical databases from a viewpoint of a pharmaceutical company, with a progress of MIHARI Project in mind. Purposes of this article are (1) to understand merits to perform a database study and a drug use result survey as an additional pharmacovigilance activity for each risk in a risk management plan, and (2) to find points to be considered when their activities are to be selected. A database study has advantages as follows: a comparison group can be set easily; a power is high as a database has many cases; and no need to consider some points such as reporting bias and recall bias. On the other hand, some issues of a technical point (e.g. understanding characteristics of each database) and a regulatory system (e.g. clarifying association to the drug reexamination system) should be considered. A drug use result survey has advantages as follows: data can be collected, even the data that databases do not have; and a drug use result survey in a specific condition can be useful. As a usual design of drug use result surveys however is hard to answer a research question on each risk, more various designs should be considered. Each pharmacovigilance activity has different points to be considered. Therefore, we have to clearly understand the purpose to perform an additional activity and select the most appropriate activity to maximize the benefit of medication users.