Hiromi Sugano, PMDA

The status of electronic study data utilization for new drug review in PMDA and recent updates will be presented. In addition, the current status of our consideration of the use of open source software in NDA will be also presented.

Hajime Shimizu, ICON Clinical Research GK

The CDISC Open Rules Engine (CORE) is an open-source software currently under development by the Clinical Data Interchange Standards Consortium (CDISC). This presentation will provide an overview of CORE, detailing its objectives and background. Attendees will gain insights into how CORE can be utilized in various scenarios, along with a discussion on the potential involvement of the Japanese CDISC community in its development. By exploring experimental examples and forecasting future applications, this presentation aims to highlight the significance of CORE for CDISC users.

Takahiro Shibata, Altair Engineering

As the demand for advanced data utilization increases in the pharmaceutical industry, software modernization and linked data are playing a crucial role. Traditional legacy systems have faced challenges such as data silos and inefficient information management. However, by incorporating various cutting-edge technologies, including generative AI and knowledge graphs, these issues can be addressed, enabling more flexible and rapid data utilization. In this presentation, we will introduce Altair’s solutions for software modernization and linked data, along with case studies from the pharmaceutical industry.

Daniel Sabanés Bové, RCONIS

The focus of this presentation will be on clinical trial designs and their implementation in R. We will present rpact, which is a fully validated, open source, free-of-charge R package for the design and analysis of fixed sample size, group-sequential, and adaptive trials. We will summarize and showcase the functionality of rpact:

• Enables the design of confirmatory adaptive group sequential designs
• Provides interim data analysis including early efficacy stopping and futility analyses
• Enables sample-size reassessment with different strategies
• Enables treatment arm selection in multi-stage multi-arm (MAMS) designs
• Provides a comprehensive and reliable sample size calculator

In addition, we will also briefly present crmPack, which is an open source, free-of-charge R package for the design and analysis of dose escalation trials. Together, rpact and crmPack enable the implementation of a very wide range of clinical trials.

Hiroaki Fukuda, MSD K.K.

While the programming language R has seen an increase in usage within the pharmaceutical industry, several challenges remain in leveraging R effectively. These challenges include limited experience in developing R-based deliverables and a shortage of skilled workers in R programming. In particular, R Shiny is well known as a framework to develop web applications with great flexibility and interactivity; however, there has not been sufficient accumulation of knowledge about its effective implementation and utilization in clinical development. To address these challenges, this presentation will provide practical insights for developing an R Shiny application and examples of R Shiny usage.

Shunsuke Goto, Novartis Pharma K.K.

In recent years, the use of open source software has become increasingly active in the pharmaceutical industry. In line with this trend, there are more and more opportunities to utilize packages in statistical analysis. However, there are some important points to be considered when using packages. For example, we need to manage the version of packages to ensure the reproductivity of the analysis. In addition, we also need to assess the risk of packages to see if the packages are reliable.

Therefore, it is very important to build the process of package management that includes managing the version of packages and risk assessment. In this presentation, I will introduce the package management process at Novartis. I will show how we manage the versions of packages and assess the risk of packages.

Taku Sakaue, Chugai Pharmaceutical Co., Ltd.

Streamlit is a powerful Python library that enables the creation of interactive web applications. This presentation explores the fundamentals of Streamlit, including its installation process and provides a step-by-step walkthrough for building a simple web application.

Toshiaki Habu, SAS Japan
William Kuan, SAS Japan

Organizations face significant challenges in analyzing clinical trial and real-world data due to data silos, technological fragmentation, and variations in employees’ analytic skills. Data silos impede seamless access and integration, while disparate technologies create inefficiencies in workflows. Additionally, differences in employee proficiency with analytic tools hinder collaboration and productivity, slowing down the decision-making process. SAS Viya, as a modern analytics platform, addresses these challenges by providing a unified, cloud-native environment that enhances productivity and fosters collaboration across the entire analytics lifecycle. Its in-memory processing capabilities enable efficient handling of large datasets, while its intuitive interface democratizes analytics, making advanced techniques accessible to all team members regardless of skill level. By integrating seamlessly with both SAS and open-source technologies like R and Python, SAS Viya and SAS Viya Workbench empowers organizations to leverage the strengths of multi-language ecosystems, self-service, scalability, and faster insights in the pursuit of data-driven decisions.

Takuji Komeda, Shionogi & Co., Ltd.
Yuki Yoshida, Shionogi & Co., Ltd.
Yohei Komatsu, TIS, Inc.
Yoshitake Kitanishi, Shionogi & Co., Ltd.

Shionogi & Co., Ltd. has developed AI SAS Programmer System (AI-SAS), a system that semi-automatically creates analysis programs based on the shells of the target clinical trial. This system builds a model by learning from accumulated shells, analysis datasets, and other related materials from past clinical trial analysis tasks. AI-SAS has demonstrated a reduction of approximately 100 hours (30%) in Shionogi’s clinical trial analysis tasks.

Meanwhile, the creation of real-world evidence (RWE) from analyses using real-world data (RWD) outside of clinical trials is becoming increasingly active in the industry, highlighting the need to improve the efficiency of RWD analysis. Unlike clinical trials, RWD studies often lack third-party oversight, raising concerns about the transparency of the research process and the possibility of researchers adjusting methods to obtain desired results. Ensuring the quality of research through transparent analysis processes is therefore another challenge.

Given these challenges, we believe that improving the efficiency of RWD analysis with a transparent workflow is essential for accelerating the creation and enhancing the quality of RWE. Therefore, we are developing AI-SAS for RWE, an application of AI-SAS to RWD. This presentation will introduce our efforts in developing AI-SAS for RWE.

Ryo Nakaya, Takeda Pharmaceutical Co., Ltd.

In these two years, technology in generative AI and LLM services are growing fast with amazing speed. We need to keep catching up the latest information and foresee the future carefully since the environment surrounding us rapidly changes. In statistical programming space in drug development, automation of generating statistical deliverables including CDISC SDTM and ADaM for e-data submission, and TFLs can be a main target of process optimization utilizing generative AI technology. A challenge for the automation using LLMs will be shared as well as recent updates in generative AI topics.

Ayako Noda, Japan Programming Head Council
Miho Yuki, Japan Programming Head Council
Mika Tsujimoto, Japan Programming Head Council
Takashi Kitahara, Japan Programming Head Council
Masato Suzuki, Japan Programming Head Council
Yuichi Nakajima, Japan Programming Head Council

The Japan Programming Head Council (JPHC) was established in 2023 as a mirror organization of the Global Programming Head Council (PHC). Its members include leaders in statistical analysis and programming from domestic and international pharmaceutical companies with operations in Japan. The council serves as a platform for exchanging insights on industry challenges and envisioning the future of pharmaceutical programming and statistical analysis.

At the upcoming PharmaSUG Japan SDE, we will present an overview of JPHC’s discussions to date, highlighting key topics and challenges identified across the industry. Additionally, a panel discussion will be held with participants to explore actionable solutions and collaborative approaches to address these challenges, fostering a shared vision for the future of the pharmaceutical programming landscape.