In clinical drug development, regulatory agencies like Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) often issue data inquiries that require many additional analyses, especially in oncology trials. These requests demand the rapid generation of multiple reports.

We propose using the R package {cards} to create Analysis Results Datasets (ARD) that standardize adverse event summary outputs. The ARD concept provides a structured, reusable format for reporting analysis results. By defining ARDs for PMDA oncology queries, we can aggregate events (e.g., all adverse events, Grade ≥3, fatal, serious, or those leading to treatment modifications) in a unified way. This standardization enables more efficient processing, easier reuse of analysis code, and improved quality control. We will introduce the ARD framework and demonstrate a new ARD-based analysis workflow using {cards}. Our results show that this approach accelerates report generation, ensures consistency across analyses, and supports future extensions of the workflow.
Shunsuke Goto | Hiroki Yamanobe | Hiro Kosako | Tomoyuki Namai | Yuichi Nakajima
Novartis | Maruho | A2 Healthcare | Chugai | GSK
Using Analysis Results Data using {cards} for PMDA Oncology inqueries
In clinical drug development, regulatory agencies like Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) often issue data inquiries that require many additional analyses, especially in oncology trials. These requests demand the rapid generation of multiple reports.  We propose using the R package  cards  to create Analysis Results Datasets (ARD) that standardize adverse event summary outputs. The ARD concept provides a structured, reusable format for reporting analysis results. By defining ARDs for PMDA oncology queries, we can aggregate events (e.g., all adverse events, Grade ≥3, fatal, serious, or those leading to treatment modifications) in a unified way. This standardization enables more efficient processing, easier reuse of analysis code, and improved quality control. We will introduce the ARD framework and demonstrate a new ARD-based analysis workflow using  cards . Our results show that this approach accelerates report generation, ensures consistency across analyses, and supports future extensions of the workflow.