Consultant RWES / HEOR, IQVIA Solutions Japan K.K., Japan
Background: After 10 years of Japanese RMP (J-RMP) implementation, understanding trends and features of J-RMP collectively over time might contribute to appropriate pharmacovigilance activities. A list of submitted J-RMPs is publicly available in portable document format (PDF) files on the webpage of the Pharmaceuticals and Medical devices Agency (PMDA), the Japanese regulatory agency. We examined the characteristics of J-RMPs through the robotic process automation (RPA) tool that extracts information automatically.
Objectives: 1. To describe summary statistics of important identified risk, important potential risk, and important missing information in J-RMPs using information extracted by the RPA tool. 2. To develop the RPA tool to extract information from RMPs automatically
Methods: The brand name, active ingredient, market authorization holder, therapeutic category, safety issues and indication are extracted using the RPA tool from J-RMPs listed in the webpage of PMDA. Since some J-RMPs did not use standardized template and could not extracted by the RPA tool, manual extraction was performed for some records.
Results: Overall, 79 J-RMPs newly submitted or updated in November 2022 were extracted. The average numbers of safety concerns addressed on each J-RMP were 4.95 (Standard deviation [SD]: 4.38) for important identified risk, 3.06 (SD: 2.30) for important potential risk, 0.48 (SD: 0.92) for important missing information, and 0.86 (SD: 1.11) for effectiveness consideration. When limited to RMPs for antineoplastic agents, the average number are 5.67 (SD: 5.03) for important identified risk, 2.90 (SD: 2.02) for important potential risk, 0.19 (SD: 0.51) for important missing information, and 0.48 (SD: 0.87) for effectiveness consideration. The liver and renal related adverse events set as important identified risk is 38.0%, and 22.8%, respectively. Effectiveness considerations were set for 51.9%, 63.4% of which included “effectiveness in actual clinical practice”. Regarding the properties RPA tool, the error rate of information extraction became less than 5 % for all items after several modifications. The extraction was completed in about one hour, which was shorted than the estimated time of four hours for manual extraction.
Conclusions: The summary statistics revealed the characteristics of the J-RMPs. Since these statistics will contribute to promoting more effective use of RMPs, it is important to establish a database that can consolidate the information such as safety concerns.
