Transparency Personalized Digityping
Personalized Digityping, short for personalized digital phenotyping, takes patient data collection upstream from randomized clinical trials and helps build and maintain ongoing relationships with patients before, during and after the conduct of formal clinical studies intended for regulatory review and drug approval. It is intended to provide value to patients while also building a database of potential clinical trial participants and collecting aggregated health data for a variety of scientific and health applications.
Participating patients are encouraged to continuously monitor their condition utilizing multiple mHealth devices, whether provisioned or “bring-your-own device” (BYOD). Digityping databases can provide valuable data and insights to clinical trial sponsors at the earliest stages of the patient engagement process when key design assumptions are being assessed and finalized. The digityping data allows sponsors to stratify patients and improve the clinical trial design. When combined with TLS Protocol Crowdsourcing, the Personalized Digityping data can help ensure an optimal clinical protocol and study population.
Personalized Digityping also provides an opportunity to substantively engage patient advocacy groups, foundations and disease-focused online groups to ensure greater and more diverse participation in clinical trials.
The Transparency Personalized Digityping program is currently being established. To learn more about the program and how you can participate, contact us here.
|What It Is||What It Does|
|Transparency Protocol Crowdsourcing||Web-based surveys, incentive system that recognizes outstanding participation, and data analysis methods||Turns input from patients and professionals into optimized protocols|
|Software platform, mHealth devices, and related methodology||Integrates the software systems that collect patient data outside of the clinic|
|Transparency Personalized Digityping||Software platform, mHealth devices, and data aggregation services||Aggregates mHealth data for patients’ self-monitoring and industry analysis|