DCRI Think Tanks Demonstrate What Is PossibleTackling today’s healthcare challenges requires collaboration from every stakeholder, including patients, academic investigators, site investigators, regulatory agencies, pharmaceutical and device industry leaders, payers, technology companies and more.
DCRI Think Tanks demonstrate what is possible when you bring smart people together to tackle the biggest challenges in clinical research. From cardiovascular diabetes to the Pediatric Rule to the Modern Data Monitoring Committee, these meetings are about creating pathways to useful, focused discussions across the healthcare continuum and then moving consensus to action.
Our mission—to address the most critical gaps in clinical research by convening leaders across the healthcare industry to map the way forward in designing, conducting, and implementing high-quality, evidence-based research.
Upcoming DCRI Think Tank
January 29-30, 2020
Leveraging Artificial Intelligence and Machine Learning Methods and Approaches to Transform Clinical Trial Design, Planning, and Execution
The clinical trials landscape is rapidly evolving based upon technological and data science innovations that are enabled and facilitated by advances with Artificial Intelligence (AI) and Machine Learning (ML) techniques applied to clinical trial data and processes.
Concurrently, regulatory interest in developing a new tailored review framework for artificial intelligence-based medical devices and software algorithms intersects with the applications of AI/ML to contemporary drug discovery and drug development. As pharmaceutical companies seek to harness the potential of AI/ML for improving clinical trial design, planning, and execution and the FDA develops the organizational structure and technical expertise for appropriate oversight of AI/ML techniques utilized for health care delivery and clinical research, thoughtful consideration of the perspectives from a diverse group of stakeholders is needed to delineate the appropriate review framework and expectations. The Duke Clinical Research Institute seeks to bring academic, regulatory, and industry leaders, and AI/ML subject matter experts together to discuss key questions and topics related to the application of AI/ML techniques to enable the clinical trials of the future with appropriate quality expectations and to develop agreement on risk mitigation strategies that promote innovation and efficiency.
Key objectives of this DCRI Think Tank will include:
- Review recent experiences with AI/ML for informing and supporting clinical trials
- Delineate data, methodological, and resource needs to refine and validate AI/ML approaches that will meet quality expectations for use with clinical trials
- Determine the regulatory framework for oversight and approval of AI/ML approaches for supporting clinical trials especially for outcome classification
- Using deep learning for casual inference in observational settings for RWE
Recent DCRI Think Tank
October 2-3, 2019
Innovative Approaches to Accelerating New Drug Evaluation for Chronic Cardiometabolic Diseases - Leveraging Intermediate Non-Clinical Endpoints and Pragmatic Clinical Trials
The development of new therapies for chronic cardiometabolic diseases has become increasingly expensive and time-consuming as the pivotal clinical trials required to demonstrate safety and efficacy on clinical outcomes have gotten larger and longer in duration. This reality means that many promising new therapies for chronic cardiometabolic conditions are abandoned and never developed. One often proposed solution to this challenge is to accelerate development through pre-market clinical trials with intermediate, non-clinical “surrogate” endpoints to be followed by post-market confirmatory, pragmatic clinical trials with hard clinical outcomes.
This Think Tank focused on the question of whether and under what circumstances such an approach would be feasible and desirable. The characteristics of appropriate, intermediate, non-clinical endpoints that meet the needs of all stakeholders were reviewed and discussed. Clinical trials evaluating the effects of novel therapies on non-clinical endpoints will require subsequent confirmatory clinical trials with clinical endpoints. The design and timing of these confirmatory clinical trials were discussed with a focus on opportunities for pragmatic approaches. Not all confirmatory clinical trials will succeed. What happens when confirmatory clinical trial are not timely, adequate, or do not confirm the findings of clinical trials on non-clinical endpoints were also considered.
Key questions of this DCRI Think Tank included:
- When is accelerated development using non-clinical endpoints appropriate?
- What are the characteristics of a valid, non-clinical endpoint?
- What are the characteristics of an appropriate confirmatory clinical trial?
- When should confirmatory clinical trials be started and completed relative to regulatory review and approval?
- What is the potential for more pragmatic approaches to confirmatory clinical trials?
- What happens when confirmatory clinical trials are not conducted adequately or in a timely fashion?
- What happens when confirmatory clinical trials do not confirm the results of clinical trials with non-clinical endpoints?
- What are the perspectives of all stakeholders including drug developers, regulators, investigators, clinicians, and patients?
DCRI Think Tanks Publications
Technology-Enabled Clinical Trials
Meeting: October 3-4, 2018
Heart Failure Preserved Ejection Fraction
Meeting: June 7-8, 2017
Leveraging E.H.R. for Clinical Research Now!
Meeting: February 18-19, 2016