Mission Statement
Our mission is to advance clinical trial operations by championing cross-pharma and cross-functional collaborative research and driving statistical innovations. We are dedicated to fostering interdisciplinary progress in trial design and execution, ensuring the highest standards of study conduct. We will actively share insights, experiences, and identify gaps observed across the pharma industry to learn from one another, adopt best practices, and collectively improve clinical trial execution. Through these efforts, we aim to best represent label claims, optimize efficiency, and reduce waste, ultimately impact the clinical development process.Targeted Improvements
- Accelerate timelines for treatment availability.
- Enhance the quality and integrity of clinical trial data.
- Reduce administrative and logistical burdens on patients and investigators.
- Improve generalizability of clinical trial results.
- Lower development costs.
Objectives
Our key objectives are:
- Identify, assess, and reduce operational inefficiencies in clinical trials.
- Promote collaboration among statisticians, clinical scientists, and clinical operations experts.
- Develop statistical and predictive methodologies to improve clinical trial processes, including
- Bayesian modeling, AI/ML
- Clinical trial simulation
- Data visualization
- Real-world and clinical trial data
- Share best practices and insights through publications, workshops, and webinars.
Members
The working group will consist of 10-15 members with expertise in the following domains:
- Statisticians specializing in clinical trials.
- Clinical operations professionals experienced in site management and trial logistics.
- Data scientists with knowledge in AI/ML, predictive modeling, and real-world data.
- Clinical trial simulation experts and programming specialists.
Together, this team will collaborate to address key challenges in clinical trial execution.
Focus Areas/Activities
The working group will focus on the following key areas of improvement:
- Site Selection and Performance Assessment: Develop data-driven predictive models to enhance site selection and holistically evaluate site performance.
- Recruitment Monitoring and Forecasting: Promote real-time tracking tools and methodologies to optimize patient recruitment.
- Clinical Drug Supply Optimization: Leverage predictive analytics to streamline drug supply management.
- Patient Representation: Ensure broad patient recruitment to achieve more representative and generalizable trial results.
- Decentralized and Pragmatic Trial Settings: Explore emerging trial designs and provide recommendations for operational strategies.
- Innovative Methodologies: Apply Bayesian modeling, AI/ML, trial simulations, and data visualization for enhanced decision-making.
- Patient-Centered Approaches: Integrate participant satisfaction into operational planning to improve trial experiences.
Deliverables
The working group aims to produce the following key deliverables:
- White Papers and Journal Articles: Comprehensive documentation of methodologies, findings, and innovations for use by industry and academia.
- Case Studies and Best Practices: Practical examples that demonstrate real-world impact of improved trial efficiency.
- Workshops and Webinars: Educational sessions designed to disseminate knowledge and facilitate hands-on learning for stakeholders.
- Tools and Frameworks: Development of predictive models, dashboards, and/or decision-support tools to enhance operational efficiency.
- Guidelines and Recommendations: Clear, actionable strategies for improving trial efficiency, including site selection and patient recruitment methodologies.
Ultimately, our goal is to maximize the usability and adoption of Efficiency+ practices across the clinical research community.