Optimizing Data Collection

The Optimizing Data Collection initiative builds on the evolution of ICH guidance and seeks to activate sponsors to highlight areas to consider in protocol design to optimize procedures and their frequencies. The initiative is building a framework of solutions with an aim to reduce unnecessary burden on patients, sites, regulators, and other stakeholders by helping sponsors critically assess what data is collected and why, while balancing scientific, operational, and regulatory demands.

Key resources

Rationale

Research conducted by the Tufts Center for the Study of Drug Development (CSDD) highlights the escalating burden imposed by protocol design on patients and sites. Yet, the complexity of protocols has surged across the industry, with a 40% increase in total procedures and a 283% increase in data points collected during Phase III pivotal trials over the past decade.1

Building on this evidence, the Optimizing Data Collection initiative conducted a collaborative study between Tufts CSDD and 14 TransCelerate BioPharma member companies. The analysis of 105 multi-therapeutic protocols quantified how core, non-core and standard or required procedures contribute to clinical study reporting and stakeholder burden (i.e., patients and site burden). Findings revealed that nearly one-third of the procedures and data collected in Phase II and III protocols are non-core or non-essential. 

These insights underscore a clear opportunity: sponsors need structured, repeatable approaches that help teams think critically about what data is collected, why it is needed, and how often it must be captured. By reducing unnecessary assessments and streamlining evidence generation, organizations can meaningfully lower burden while preserving scientific and regulatory rigor. 

TransCelerate is well-positioned to advance solutions and thereby reduce burden across patients, sites, and sponsors. The goal is to motivate sponsors to take action to support initiatives that optimize data collection via simplified protocol design.

1. Getz, K., Sharma, M., Ibrahim, S., Baykal-Caglar, E., Sam, L., Comic-Savic, S., (2024, January 31). Optimizing Study Design and Setting the Stage for Efficient Conduct through Quality by Design, [Paper presentation]. Duke-Margolis Institute for Health Policy Public Workshop 2024: Washington, DC, United States.

Solutions and Resources

Explore a suite of solutions designed to help sponsors and other interested stakeholders optimize clinical trial data collection from early development through study closeout. Our expanding set of resources supports teams in evaluating data needs, reducing unnecessary complexity, and aligning collection practices with both scientific objectives and patient/site burden. 

Insights Informing Strategies for Optimizing the Collection of Clinical Trial Data: This peer-reviewed publication, available in Therapeutic Innovation & Regulatory Science (DIA TIRS), outlines strategic approaches to improving data collection in clinical trials. 

Regulatory Landscape Assessment: Our analysis of key ICH guidelines – such as E6(R3), E8(R1), E19, and M11 – shows how they apply to the Optimizing Data Collection initiative and why they matter. 

Clinical Development Plan Framework & Considerations for Data Optimization​: A structured framework that can be used to align study objectives and endpoints to the Target Product Profile (TPP), helping teams define the evidence needed for a given indication and avoid unnecessary complexity across protocols.​ 

Protocol Considerations for Data Optimization​: A structured, question‑based resource that helps guide teams through endpoint‑guided decision‑making to map procedures, frequencies, and data needs, enabling more fit-for-purpose protocol design and data collection. 

Benefits

  • Provides considerations for sponsors to support study-level evaluation of fit-for-purpose procedural needs and downstream data collection efficiencies and effectiveness to reduce participant and site burden.
  • Improves understanding of the impact and implications of procedure and data collection decisions across the ecosystem, leading to more intentional, streamlined, and participant-centric clinical designs.

*These are potential benefits