Advancing the Use of Digital Health Technologies for Data Capture & Improved Clinical Trials
The use of digital health technologies for data capture has the potential to transform clinical trials. What has been missing is a clear road map for making this vision a reality—until now.
CTTI’s Digital Health Technologies recommendations and resources address the challenges that previously hindered the use of digital health technologies in clinical trials. With this new comprehensive guide, stakeholders across the clinical trials enterprise can start to benefit from the potential advantages of using digital health technologies—including capturing “real world” data from patients, reducing barriers to participation, and lowering costs.
A Guide to Using Digital Health Technologies for Data Capture
To access the complete packet of recommendations and resources as a .zip file, please click here.
The use of mobile technologies has the potential to transform clinical trials. What has been missing is a clear road map for overcoming perceived complexities and making this vision a reality—until now.
Once a sponsor has decided to use a technology-derived outcome measure (see CTTI’s Mobile Clinical Trials: Novel Endpoints recommendations and resources), there are many decisions related to selecting the technology, capturing and handling data, and designing the protocol. CTTI has developed solutions that outline best practices for the use of mobile technologies to capture objective data—an approach that has the potential to transform the quality and efficiency of clinical trials.
Scientific and Technological Issues Surrounding the Use of Mobile Technologies in Clinical Trials (2016 – ongoing)
This is just one project within CTTI’s Mobile Clinical Trials (MCT) program. Additional work within CTTI’s MCT program includes:
The goal of CTTI’s MCT program is to provide a comprehensive, intuitive toolkit of recommendations and resources for every stakeholder using mobile technologies for data capture in clinical trials—including recommendations for conducting a complete or hybrid decentralized clinical trial.
The MCT Mobile Technologies project specifically addresses the scientific and technical considerations that follow the decision to collect technology-derived outcomes data in a clinical trial. The resulting work provides a road map for using mobile technologies to capture objective data—an approach that has the potential to transform clinical trials and improve data quality, efficiency, and patient centricity.
CTTI’s mobile technologies recommendations and resources provide stakeholders with comprehensive guidance to support the inclusion of mobile technologies for data capture in clinical trials. Ultimately, this will improve the quality and efficiency of medical product development.
CTTI conducted interviews in two phases. First, we solicited input from research sponsors and clinical investigators experienced in using mobile technologies in clinical trials. These preliminary results revealed challenges related to data management, validation, analysis, and security. Sponsors and investigators shared their approach to mobile technologies selection as well as to managing and reporting safety signals and adverse events. The preliminary results were shared in a CTTI webinar.
A second phase of interviews with technical experts (device manufacturers, data management experts, data security experts, and data analysts and biostatisticians) examined evolving best practices among sponsors and investigators and probed solutions to specific technical issues that have continued to challenge studies relying on mobile technologies for data capture.
In June 2017, CTTI convened a multi-stakeholder expert meeting to explore solutions to the scientific and technological challenges of using mobile technologies in clinical trials. Themes from the meeting included:
A meeting summary is available that highlights themes from these discussions.
CTTI also convened a Recommendations Advisory Committee, a team of clinical trials and technology experts, to provide ongoing feedback to the recommendations during development, and help shape the supporting resources—ensuring that the final solutions are useful, applicable, and impactful.
In July 2018, CTTI released the final recommendations for the use of mobile technologies for objective data capture in clinical research. The full set of evidence-based recommendations and resources includes case examples, frameworks, decision tools, flowcharts, and more, which offer practical guidance for:
Role | Name |
Affiliation![]() |
---|---|---|
Team Member | Chris Miller | AstraZeneca Pharmaceuticals LP |
Project Manager | Jen Goldsack* | Clinical Trials Transformation Initiative |
Social Science Lead | Amy Corneli | Clinical Trials Transformation Initiative |
Project Manager | Lindsay Kehoe | Clinical Trials Transformation Initiative |
Team Member | Ashish Narayan | Feinstein Institute for Medical Research |
Team Member | Aaron Coleman | Fitabase |
Team Member | Ernesto Ramirez | Fitabase |
Team Leader | Cheryl Grandinetti | Food and Drug Administration |
Team Leader | Kaveeta Vasisht | Food and Drug Administration |
Team Member | Phil Kronstein | Food and Drug Administration |
Team Member | Dharmesh Patel | Food and Drug Administration |
Team Member | Evan Wearne | Food and Drug Administration |
Team Member | Tom Switzer | Genentech - a member of the Roche Group |
Executive Committee Champion | John Hubbard | Genstar Capital |
Team Member | Jonathan Helfgott | Johns Hopkins University |
Team Leader | Phil Coran | Medidata Solutions |
Team Member | Matthew Kirchoff | National Institutes of Health |
Team Leader | Ken Babamoto* | Pfizer, Inc |
Team Leader | Christopher Dell | Pfizer, Inc |
Team Leader | Seleen Ong* | Pfizer, Inc |
Team Member | Barry Peterson | Philips Respironics |
Team Member | Jessie Bakker | Philips Respironics |
Team Member | Adam Amdur | Sleep Apnea Association |
Team Leader | Marisa Bolognese | The Life Raft Group |
Team Member | Aiden Doherty | University of Oxford |
Team Leader | Ray Dorsey | URMC |
Team Member | Drew Schiller | Validic |