From Protocol to TMF: Building an Integrated Data Model to Improve Operational Alignment in Clinical Research

Clinical research is known for its complexity, its constant operational changes, and the critical importance of high-quality data for patient safety. Multiple systems, documents, and data sources are used to plan and execute a study, often resulting in fragmented workflows and extensive manual effort. There is a growing need for automation and digital transformation to streamline data and operations; however, many practitioners believe that the inherent complexity of research makes full integration difficult or even impossible. This OSF project was created to present, collect, and exchange ideas on how digital transformation in clinical research can be made practical, achievable, and scientifically grounded. It aims to gather evidence, explore best practices, and develop conceptual and technical approaches that support simplification, quality improvement, and efficiency, particularly in non-commercial research environments, where resources are limited but quality expectations remain high. Objective of the Project: To establish collaboration for developing a unified, SQL-like relational data model for clinical research that links protocol design, operational workflows, TMF alignment, and budgeting logic. This model is intended to enhance operational efficiency, documentation quality, and financial transparency, while remaining compatible with modern analytical tools such as Python, R, JSON-based outputs, and standard data exchange formats commonly used in academic and non-commercial settings. A central theme of the project is exploring how the protocol, Trial Master File, operational processes, and budgeting/financial planning can be connected more directly through a structured data foundation. By examining and modeling these relationships, the project seeks to contribute to more coherent workflows, improved audit readiness, and a stronger scientific and operational basis for clinical trial conduct. The project welcomes collaborators from clinical operations, TMF management, process improvement, research administration, data modeling, SQL and analytical development, project management, and digital transformation. Materials include preprints, conceptual frameworks, structured data models, and early prototypes designed to support open collaboration and transparent methodological development.