P229: Digital Adoption Platforms: Enhancing Compliance, Data Integrity, and Efficiency in Life Sciences
Poster Presenter
Joan Cheung
Principal Consultant
Epista Life Science United States
Objectives
This poster shows how improving data quality and adopting cloud based regulatory platforms can support trusted, scalable submissions while helping organizations accelerate approvals and move toward more data driven regulatory approaches.
Method
A structured framework for data remediation and a cloud based regulatory approach were evaluated to address disconnected systems, inconsistent standards, and inefficiencies for core data across the product lifecycle.
Results
Many life sciences organizations continue to struggle with fragmented systems, siloed teams, and inconsistent data standards across the clinical and regulatory lifecycle. These challenges create unreliable datasets and slow down critical processes.
• Weak data governance and inconsistent metadata across systems
• Outdated integrations and limited alignment between platforms
• Heavy reliance on manual reconciliation and quality checks
• Increased pressure during inspections and regulatory submissions
At the same time, the volume of clinical and real world data continues to grow, making manual data cleaning impractical. Poor data quality has become a major barrier to adopting newer capabilities such as AI, structured submissions, and cloud based collaboration.
To address this, a structured data quality modernization framework was applied with three core steps:
1. Data Quality Assessment and Profiling
2. Intelligent Data Remediation Execution
3. Governance & Future State Enablement
This approach supports a shift from system focused thinking to a more data focused model, allowing teams to create reliable and reusable datasets across the regulatory landscape.
In parallel, cloud based regulatory platforms provide a secure environment for collaboration across sponsors, partners, and health authorities. Key capabilities include:
• Improved traceability and transparency of data and changes
• Shared access to a single source of truth
• Better version control and reduced rework
• Faster collaboration across global stakeholders
When combined with a global dossier approach, organizations can reuse core submission content across regions rather than recreating it. This reduces duplication, lowers cost, and improves submission timelines.
• Faster preparation of submission ready data
• Improved inspection readiness and auditability
• Greater scalability across global markets
Conclusion
Data quality is the foundation for modern regulatory transformation. Without consistent and trusted data, organizations cannot fully adopt cloud platforms, structured submissions, or advanced analytics.
A strong data quality framework supported by governance and ongoing monitoring allows teams to move away from reactive cleanup efforts toward a more controlled and scalable approach. This results in more consistent, traceable, and reliable data across the lifecycle.
When this foundation is combined with cloud based regulatory platforms, organizations are better positioned to collaborate with regulators, partners, and affiliates in a secure and efficient way. This supports reliance programs, reduces duplication, and simplifies global submission strategies.
Together, these changes help shorten review timelines, improve submission quality, and support faster patient access to therapies.
Overall, this represents a shift from document driven processes to more connected, data driven ways of working that deliver better outcomes for both organizations and patients.
