Alan Godfrey|Benjamin Vandendriessche|Jessie P. Bakker|Cheryl Fitzer?Attas|Ninad Gujar|Matthew Hobbs|Qi Liu|Carrie A. Northcott|Virginia Parks|William A. Wood|Vadim Zipunnikov|John A. Wagner|Elena S. Izmailova
Fit?for?Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience
Northumbria University|Case Western Reserve University|Philips (United States)|Healthcentric Advisors|Curis (United States)|Cognition Therapeutics (United States)|Center for Drug Evaluation and Research|United States Food and Drug Administration|Pfizer (United States)|Takeda (United States)|Johns Hopkins University|Foresite (United States)
biometric monitoring technologies biomets becoming increasingly common aid data collection clinical trials practice state biomets associated digitally measured biomarkers highly reminiscent field laboratory biomarkers 2 decades ago review summarized leveraged historical perspectives lessons learned laboratory biomarkers apply biomets categories share common features including goals roles biomedical research definitions many elements biomarker qualification framework also classified based underlying technology distinct features performance characteristics require bench human experimentation testing phases contrast laboratory biomarkers digitally measured biomarkers require prospective data collection purposes analytical validation human subjects lack wellestablished widely accepted performance characteristics require human factor testing many applications access raw samplelevel data novel methods handle large volumes data well security data rights requirements add complexity emerging field review highlights need common framework appropriate vocabulary standardized approaches evaluate digitally measured biomarkers including defining performance characteristics acceptance criteria additionally need human factor testing drives early patient engagement technology development finally use biomets requires relatively high degree technology literacy among study participants healthcare professionals transparency data generation need novel analytical statistical tools creates opportunities precompetitive collaborations