Pre-Conference Training

PharmaSUG China 2022

Again, we are offering four pre-conference training seminars. The cost will be is an additional fee from registration. More detailes will be released soon.

Thursday morning – 8:30 am -12:30 pm

1. The background, special considerations, and solutions of eCTD electronic submission in China By Richard Que and Jane Liang

The training will mainly focus on drug regulatory submission using electronic Common Technical Document. The topic will be interpreted from following aspects. 1) The status and evolvement of electronic Common Technical Document in global drug regulatory submission. 2) The progress of eCTD implementation in China. 3) Interpretation of regulatory guidance in China. 4) The company strategy on how to prepare eCTD package to follow China regulatory guidance.

Intended audience: Audience from industry who are interested in the progress of eCTD electronic submission in China

2. Deep Dive into Tidyverse, ggplot2 and Shiny with Real Case Applications in Drug Development - Part I: Tidyverse Advanced and ggplot2 Intermediate By John Wang and Emily Cheng

This is an overview and case practices of Tidyverse, ggplot2 and Shiny for users of clinical study community at PharmaSUG China. No prior knowledge of R, RStudio or Shiny is needed. The full-day hands-on course is composed of three parts, how to do basic data wrangling using Tidyverse, create common clinical graphs using ggplot2, and build fancy interactive apps using Shiny. CDISC formatted datasets examples will be provided for each topic. Attendees need to get their hands dirty in class and instructors will be around for assistance. If you’re passionate to explore different methods to achieve your daily goals, this course will surely have benefits and a lot of fun.

The whole course is separated into two independent parts (Part I and Part II) and attendees can join one of them or join both per need.

What's expected in Part I:
- R basics
- Get Started with Tidyverse
- Common Data Wrangling using Tidyverse vs SAS
- Supercharge your efficiency using Pipe %>%
- Get started with ggplot2
- ggplot2: Graphical elements, aesthetics, geometries
- Building a basic plot

Thursday afternoon – 01:30 pm - 05:30 pm

3. Python Programming for Reporting, Data Visualization and Machine Learning By Haiping Yu and Chengjun Lv

Python is a versatile open-source programming language which has become very popular nowadays in web development, data science and artificial intelligence, because of its active community, fueling of both academia and industry, and its unique way of simplicity and efficiency.

This seminar is intended for beginners and intermediate in Python programming. In the seminar, we will learn the Python programming features, practice tutorials in a web-based interactive development environment. After completing the seminar, we will understand “The Zen of Python”, know richness of Python packages and possibilities of Python application, and start to think about how to use Python to empower clinical research and development.

What's expected in the course:
- Get started with the Python programming environment, the JupyterLab and Jupyter Notebook
- Python programming foundations, and comparison with other languages
- Data wrangling and analysis using Pandas, and comparison with SAS
- Data plotting and choices of Python visualization libraries
- Introduction of machine learning and example of application to real world problem

4. Deep Dive into Tidyverse, ggplot2 and Shiny with Real Case Applications in Drug Development - Part II: ggplot2 Advanced and Shiny Advanced By Emily Cheng and Jerry Wang

The whole course is separated into two independent parts (Part I and Part II) and attendees can join one of them or join both per need.

What's expected in Part II:
- ggplot2: quick go-through of syntax
- Common plots in clinical trials and practices
- Get started with Shiny, Interactive visualization
- Shiny apps examples in clinical trials and practices

Biography

Richard Que Publishing Team Manager (Emerging Market, CMC and Japan), Publishing and Product License Support, Global Regulatory Operations at Pfizer. Richard joined Pfizer in 2012 as role of CSR Coordinator. In 2017, Richard was transferred to Publishing Team and appointed as PPLS manger focusing on multiple function supports including regulatory submissions publishing, publishing vendor management etc. In 2019, Richard was appointed to as the team leader directing a team which is focuses on publishing covering the Emerging Markets regulatory submissions, IMPD (Investigational Medicinal Product Dossier) CMC (Chemistry, Manufacturing and Controls) package & Japan NDA Submissions. He has profound knowledge of eCTD standards and regulatory operational experiences across markets. He also worked a Subject Matter Expert (SME) and Business Administrator for Document Management System and Regulatory tracking and publishing system for Pfizer. In addition, he also has plenty of experience on automation and BI application in regulatory operation. Richard holds master’s degree in Pharmaceutical Chemistry from Fudan University

Jane Liang is responsible for comprehensive project management for global publishing operational initiatives to ensure alignment and execution among Publishing, Submission Management, Information Management, and Business Technology, etc. and also taking oversight of regional and global operational initiatives and a vendor sub-team in other APAC regions. She joined Pfizer in early 2017, worked for several enterprise level content management applications full covered the drug development lifecycle, and also collaborated with worldwide platform and solution providers to liaise with business and technical groups in the aiming of customize the technology into drug development process in pharma areas. She started her career in the pharmaceutical industry in 2012 at Roche. After that she worked as a Regulatory Specialist in Medline Industries, Inc. All these solid experiences gained her both with drug development and medical device registration knowledge. Jane holds Master degree in Biochemistry and Molecular Biology from Shanghai University.

John Wang Senior Director, Statistical Analysis, at dMed Biopharmaceutical Co., Ltd. He has 14+ years extensive statistical analysis experience in all phases of clinical trials and is familiar with different kinds of programming languages and system tools in clinical research. Before he joined dMed, he was the Manager of SAS Programming at Johnson & Johnson China since 2009. Prior to that, he was associate manager of SAS programming for four years at Global Research Services, LLC. He is Vice Chair and team lead for the SDTM group in C3C (China CDISC Coordinating Committee). He has very extensive experience using CDISC fundamental data standards such as CDASH, SDTM, ADaM, Controlled Terminology and define.xml. He became a CDISC authorized SDTM Instructor in early 2016.

Emily Cheng Statistical Programming Analyst at Janssen China R&D with 3 years programming experience in pharmaceutical industry supporting Oncology studies. Her expertise in R is data visualization, focusing on ggplot2. As R trainer, she delivered R base trainings to APAC programming colleagues. She also organized cross-sector R sharing seminar and facilitated workshops to build a dynamic R learning environment for R beginners. She enjoys exploring elegant solutions to create graphs, the process that taking flat data and bringing it to life.

Jerry Wang Statistical Programming Lead, at Janssen China R & D. He has 9+ years of experiences in drug development industry. He joined Janssen in 2017 and accumulated extensive statistical programming and analysis experiences spanning phase I to phase III trials, including eSub, data pooling, FDA/EMA/and other healthy authority ad-hoc requests and publication support requests. Aside from projects, Jerry is pioneer in departmental R initiatives, his key accomplishments include Shiny APP development and several pilot projects with TLFs in R static and interactive mode. Jerry is passionate in coding with various languages, particularly R package and Shiny app development are his expertise. He finds the automation using R in our daily work is not only a fancy idea and R really lights up this solution for efficiency and cross-function connections, which make this R journey very promising and evolutionary in future of industry. Prior to Janssen, he worked at Pfizer R&D as Technical Supervisor, Clinical Programming.

Haiping Yu Director, Technical Operation Lead of Clinical Data Management, at dMed Biopharmaceutical Co., Ltd. He has 15+ years of experiences in new drug R&D industry, he is enthusiastic about software development and data standards implementation in this area. He joined dMed in 2017, he and his team developed Clinical Metadata Repository (MDR) and many other programs to enable end-to-end automation of clinical data workflows. Before he joined dMed, he was Manager, Technical Process Lead of Clinical Data Management at Pfizer China R&D Center since 2009, in this position, he was working in data standards and data visualization team.

Chengjun Lv Manager, Clinical Data Management, at dMed Biopharmaceutical Co., Ltd. He has 10+ years of experiences in clinical data management, focuses on the application of clinical research-related software systems, as well as the development of automated tools, he is familiar with both SAS and Python, he has also involved in central monitoring software setups in a couple of years. He joined dMed in 2018, prior to that, he worked at Pfizer R&D China Center.