When you submit your paper, you will need to specify the submission section that you think your paper best fits. Here are the submission sections that have been defined for PharmaSUG 2022:

Section Descriptions

• Advanced Programming: Comprehensive explanations of sophisticated programming techniques, examples of solving programming problems, examples of specific programming solutions, integrations, and other innovative, high-level technical presentations geared for an audience of intermediate and advanced pharmaceutical and biotech industry programmers. (SAS, R, Python, and other languages/systems)
• Applications Development: Development, exploration, and demonstration of programs, system utilities, integration and productivity tools designed to assist the process of managing data and deliverables for clinical and observational trials. Including decisions, designs, and development process utilizing any programming language. (SAS, R, Python, and others).
• Artificial Intelligence (Machine Learning): Exploring how we can utilize AI approaches in machine learning, automated decision processes, knowledge representation, evolving computation algorithms, and other subfields related to AI to drive pharmaceutical and biotech industry development and better outcomes for patients.
• Data Standards: Discussions of industry data standards such as CDISC CDASH/SDTM/ADaM, compliance, controlled terminology, versioning, implementation strategies and maintaining data quality, validation and acceptance, transparency and traceability, data exchange with partners and vendors, pilots and case studies.
• Data Visualization and Reporting: Explore techniques for creating graphs and tools for effective data visualization. Demonstrate how to apply new technology to better understand and communicate data effectively. Show how to present results to people of every technical level from critical stakeholders, medical personnel, and regulatory authorities to the general public. The techniques presented within this section can be used to better understand the data and improve decision-making in pharmaceutical and biotech industry development. Large and complicated data can be presented in an understandable way.
• e-Posters: e-Posters are focused on innovative topics and practical experiences presenting graphics, source code, statistics, thought-provoking concepts, novel data management, innovative ways to implement data standards, and much more. e-Posters are available throughout the conference and are ideal for displaying high-resolution graphics and presentations without requiring a formal lecture. There are scheduled times when authors are available to answer questions.
• Leadership Skills: Discussions of issues facing programmers, statisticians, data scientists, consultants, executives and front-line supervisors in today's pharmaceutical and biotech industries. Topics include work life balance, industry trends, interpersonal interactions, career development, leadership and mentoring by helping others developing and reach their full potential, consulting and contracting, networking techniques, recruiting and retention, dealing with global teams and the distributed model of working, or other relevant subjects.
• Medical Devices: Discussions about how medical device analytics differs from traditional clinical trials. Techniques will be presented on the types of data being collected and the challenges involved in using and analyzing that data, along with handling submission requirements that may differ between regulatory agencies such as CDRH or CDER. Use cases of CDISC implementation are also encouraged.
• Quick Tips: Brief presentations of programming code, programming tips, efficiency techniques, useful algorithms, macros, utilities, undocumented/new features, and creative uses of software that makes a job easier. Perfect for beginners and experts alike to share tips and tricks that can increase efficiencies or provide time/cost savings. (SAS, R, Python, and others)
• Real World Evidence and Big Data: Discussions about software tools, analytics, visualization, summary reporting, and data mining techniques in healthcare research areas that focus on real-world and big data such as patient-reported outcomes, patient/disease registries, risk evaluation and mitigation strategies, knowledge and behavior surveys, health claims, quality-of-life measurements, call center reports, electronic health records, prescription databases, FAERS/VAERS, and other real-world assessments.
• Statistics and Analytics: The implementation of statistical methods, advanced analytics, and innovative ideas to analyze and manage the data in our industry to report results from all phases of clinical trials (PK/PD, exposure-response modeling, pharmacogenetics, etc.), public health studies, and healthcare research. (SAS, R, Python, and others)
• Strategic Implementation: Business operations content dealing with new trends in in hardware and software for managing complex clinical trial programs, strategies for deploying new technologies, programming metrics, temporary workforce challenges, training methods and programs, and effective use of support resources such as technical support, discussion forums, user groups, social networking, and discussions with management to adopt new technology through implementation, training and staffing challenges.
• Submission Standards: Discussions of global submission industry standards, best practices and implementation strategies for deliverables such as Define-XML, SDRG, ADRG and eCTD folder content, the use of metadata repositories and other tools to automate submission documentation, submission experiences, pilots and case studies for regulatory submissions.
• Hands-On Training: Interactive training on a variety of topics that provides attendees with practical "hands-on" experience using industry software tools in a classroom setting taught by seasoned experts. Speakers are by invitation only.