Track 3: Data and Data Standards
Data science is multidimensional area that includes two major dimensions: Curation and Analysis. This track focuses on the curation dimension, which includes the structure, organization, validation, storage, extraction, and delivery of diverse types of patient data to facilitate review, analysis, and reporting in regulatory submissions. Specifically, the track will have the following as focal points:
- Structured and unstructured data sources
- Data Quality
- Data Standards
- Real World Data / Evidence
- Mobile / wearable technologies
- Informatic solutions and machine learning
- Endpoints: evolving data requirements to support new endpoints
Sessions in Data and Data Standards
Monday, June 21-Friday, June 25 | Short Courses
- #012A: Real World Evidence: The Evolving Landscape of Regulators, Data, and Integrated Use
- #014P: Data Visualization in the Life Sciences
Monday, June 28
- Machine Learning Enabled Digital Data Flow and Advanced Real-World Evidence
- Real-World Response: Harnessing Electronic Health Records to Develop Robust Clinical Endpoints in Solid Tumors
- Driving Innovation in Data Standards and Regulatory Submissions at FDA
Tuesday, June 29
- Perspectives on Real-World Data/Evidence Collection Through Expanded Access During the COVID-19 Pandemic
- Driving Change Globally: Transforming the Regulators as Early Digital Adopters
- Enabling Patient-Centric Experience Using Connected Data Hub and Wearable Technologies
Wednesday, June 30
- Towards a Patient-Focused Drug Development Ecosystem: Adoption of Core Outcome Sets
- Worldwide COVID-19 Pandemic Effects on Real-World Data: Research Can Go On
- Converge and Conquer: The Overlapping Roles of Data Management, Operations, Monitoring, and More, and What it Means for Industry
- Breaking the Document Paradigm to Digitize Study Start Up: The Digital Data Flow Initiative
- The COVID-19 Digital Response of Countries and Companies: What is Here to Stay?
Thursday, July 1
- The Data Scientist’s Handbook: ‘Good Science’ Principles in Non-Interventional Studies
- EHR Interoperability Supporting COVID-19 Critical Care and Research
- The Relationship Between Data, AI, and Bias
Who is This Track is Designed For?
DIA recommends this track and associated sessions to professionals involved in: informatics (bio and medical), data standards and quality control (and regulatory standards implementation specialists), data quality, clinical data management, clinical trial design, clinical operations, eClinical (electronic health records), submissions and global submissions, health economics outcomes research, biostatistics, medical writing, real world evidence roles, epidemiology, post-market studies, regulatory affairs and operations, and statistics.