Quality generation and ethical use of digital health data in clinical studies

Owned by David Proudlock (Unlicensed)
Last updated: May 16, 2021 by Becky Upton
3 min read

Interested, who to contact:

@Paul Denny-Gouldson (Unlicensed)

@Ashley George (Unlicensed)

@Becky Upton

The problem:

The quality and quantity of evidence required to deem a product fit-for-purpose are not agreed upon by industry, patient, or government stakeholders. Currently, there is no consensus on what constitutes “evidence' or what metrics should be used to distinguish high-quality evidence from low-quality evidence.

FDA/EMA are both encouraging patients to be part of drug/device development from pre-IND through commercialization (PFDD/PFMD) The industry is not sure of the value of doing this or how to do this. This project can help the industry understand both the value and how to do this.

Proposal

Utilize an existing digital real-world data collection tool, an app/platform, to encourage data input and house and analyze the quality of the data collected and investigate the standards required for ethical use in clinical studies. To achieve broad adoption and positively impact health, digital medicine products require evidence to demonstrate that they are trustworthy.

Who will / should get involved?

The user community which can be built up through interaction with the app and engagement activities to encourage participation. Although the app is a therapeutic area agnostic, for the industry to see the value the focus will have to be therapeutic area specific. We work with the patient advocacy groups in that given area as they have a stake in getting improved treatments and participation will be encouraged through peer influence.

Objectives / proposed deliverables of the proposed demonstration project

1 - a validated process to collect data the inform patient-centered clinical trial protocols

2 - proof of the value of patient-generated data

3 - build a protocol appropriate for the chosen therapeutic area

4. Articulate a standard lexicon of digital study types

5. Define quality metrics for categorizing evidence used to designate digital tools as fit-for-purpose in a clinical application (could limit to clinical trials to constrain scope)

Any Comments Defining quality in study design and reporting will drive the field of digital medicine towards maturity by establishing consistency in the evidentiary base used to support clinical applications of digital medicine tools.

Plan / Timings

month 1 to determine appropriate app, therapeutic area;

month 2 identify and build relationships with appropriate patient advocacy groups; month 3 campaign for the usage of the app;

months 4-11 - collect data; month 12 analyze the data, where - dependent on the advocacy groups, must set up face-to-face meetings to start building relationships. Once this is done the project manager is the main point of contact. The goal of the proposed demonstration project With 8 months of RWD behavioural data, we will have an understanding of how someone lives with managing the therapeutic area. We will see that the drug or device is not at the centre of their lives. The usual reason people drop out of clinical trials is due to the difficulty in managing the protocol. With the data gathered over the 8 month period, we will be better informed about how to build a protocol that can work for both researchers and study participants, not just researchers.

Necessary expertise and/or resources for the proposed demonstration project

1 - therapeutic area agnostic app/platform

2 - knowledge of engagement initiatives to encourage app usage Proposal/Value Proposition: To develop a toolkit defining a crosswalk between the proposed evidentiary frameworks already proposed by DiMe (in press) and the study design and reporting necessary to support a tool as fit for purpose in clinical applications.