Table 1 Existing definitions of V&V or similar concepts in a selection of reference and guidance documents from disciplines contributing to digital medicine.

From: Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)

Source of guidance document IEEE (2016)43 BEST (2018)5 CTTI (2018)14 SaMD (2017)17 FDA (2002)42 NASEM (2017)44
Intended audience for document System, software, and hardware suppliers, acquirers, developers, maintainers, V&V practitioners, operators, users, and managers in both the supplier and acquirer organizations Broad stakeholder group (e.g., regulators, medical product manufacturers, patients) Biotech & pharmaceutical sponsors, contract research organizations (CROs) and outsourced electronic service vendors, such as mobile technology manufacturers International Regulatory Community • Persons subject to the medical device quality system regulation
• Persons responsible for the design, development, or production of medical device software
• Persons responsible for the design, development, production, or procurement of automated tools used for the design, development, or manufacture of medical devices or software tools used to implement the quality system itself
• FDA investigators
• FDA compliance officers
• FDA scientific reviewers
Multi-stakeholder community engaged in genetic and diagnostic testing
Are terms V&V defined?
Verification Yes No Yes In prerequisite documents Yes No
Validation Yes (does not split out analytical vs. clinical) Yes (splits out analytical vs. clinical) Yes (refers to analytical validation only) Yes (splits out analytical vs. clinical validation; also includes clinical association/scientific validity) Yes Yes (splits out analytic vs clinical validation; also includes clinical utility)
What’s the context of V&V definitions? Provides standards for V&V of software, hardware, and systems Gives definitions & examples of biomarkers and surrogate endpoints; additional focus on COA (clinical outcome assessment)— specific validation (e.g., construct, content & criterion) Advancing the use of mobile technologies for data capture & improved clinical trials Describes an approach for planning the process for clinical evaluation of a SaMD (software with a medical purpose) Describes how provisions of the medical device quality system regulation apply to software and the FDA’s approach to evaluating a software validation system Developed in the context of providing recommendations to advance the development of an adequate evidence base for genetic tests to improve patient care and treatment. Uses the CDC’s ACCE model of 44 targeted questions
What’s missing from V&V definitions? Data processing algorithm
Clinical validation
Data processing algorithm Relationship of digital metric to a meaningful clinical state or experience
Clinical care applications
Hardware (decoupled from software)
View of full data- supply chain
Hardware (decoupled from software)
View of full data supply chain
Clinical validation
Sensor hardware