Dataset Information

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

ABSTRACT: Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.

SUBMITTER: Goldsack JC

PROVIDER: S-EPMC7156507 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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

Goldsack Jennifer C JC Coravos Andrea A Bakker Jessie P JP Bent Brinnae B Dowling Ariel V AV Fitzer-Attas Cheryl C Godfrey Alan A Godino Job G JG Gujar Ninad N Izmailova Elena E Manta Christine C Peterson Barry B Vandendriessche Benjamin B Wood William A WA Wang Ke Will KW Dunn Jessilyn J

NPJ digital medicine 20200414

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, a ...[more]

PMID: 32337371

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Project description:BACKGROUND: Mass spectrometry (MS) is a very sensitive and specific method for protein identification, biomarker discovery, and biomarker validation. Protein identification is commonly carried out by comparing MS data with public databases. However, with the development of high throughput and accurate genomic sequencing technology, public databases are being overwhelmed with new entries from different species every day. The application of these databases can also be problematic due to factors such as size, specificity, and unharmonized annotation of the molecules of interest. Current databases representing liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based searches focus on enzyme digestion patterns and sequence information and consequently, important functional information can be missed within the search output. Protein variants displaying similar sequence homology can interfere with database identification when only certain homologues are examined. In addition, recombinant DNA technology can result in products that may not be accurately annotated in public databases. Curated databases, which focus on the molecule of interest with clearer functional annotation and sequence information, are necessary for accurate protein identification and validation. Here, four cases of curated database application have been explored and summarized. FINDINGS: The four presented curated databases were constructed with clear goals regarding application and have proven very useful for targeted protein identification and biomarker application in different fields. They include a sheeppox virus database created for accurate identification of proteins with strong antigenicity, a custom database containing clearly annotated protein variants such as tau transcript variant 2 for accurate biomarker identification, a sheep-hamster chimeric prion protein (PrP) database constructed for assay development of prion diseases, and a custom Escherichia coli (E. coli) flagella (H antigen) database produced for MS-H, a new H-typing technique. Clearly annotating the proteins of interest was essential for highly accurate, specific, and sensitive sequence identification, and searching against public databases resulted in inaccurate identification of the sequence of interest, while combining the curated database with a public database reduced both the confidence and sequence coverage of the protein search. CONCLUSION: Curated protein sequence databases incorporating clear annotations are very useful for accurate protein identification and fit-for-purpose application through MS-based biomarker validation.

Project description:Rationale, aims and objectivesThe field of implementation science is critical for embedding research evidence into healthcare practice, benefiting individuals, organizations, governments, and the broader community. Implementation science is messy and complex, underpinned by many theories and frameworks. Efficacious interventions for older people with multiple comorbidities exist, yet many lack effectiveness evaluation relevant to pragmatic implementation within aged care practice. This article outlines the conceptualization and development of an Implementation Framework for Aged Care (IFAC), fit-for-purpose for an aged care organization, Bolton Clarke, intent on embedding evidence into practice.MethodA four-stage process was adopted to (1) explore context and relevant literature to conceptualize the IFAC; (2) identify key elements for a draft IFAC; (3) expand elements and refine the draft in consultation with experts and (4) apply the IFAC to three existing projects, identifying key learnings. A checklist to operationalize the IFAC was then developed.ResultsThe IFAC is grounded in codesign principles and encapsulated by the implementation context, from a social, cultural and political perspective. The IFAC addresses the questions of (1) why do we need to change?; (2) what do we know?; (3) who will benefit?; (4) who will make the change?; (5) what strategies will be used?; and (6) what difference are we making? Three pilot projects: early adoption of a Wellness and Reablement approach; a care worker and virtual physiotherapist-led program to prevent falls; and a therapeutic horticulture program for residential communities, highlight learnings of applying the IFAC in practice.ConclusionThis fit-for-purpose IFAC was developed for a proactive and responsive aged care provider. The simplicity of the six-question IFAC is underpinned by substantial theoretical perspectives for its elements and their connections. This complexity is then consolidated into an 18-question checklist to operationalize the IFAC, necessary to advance the translation of evidence into clinical practice.

Dataset Information

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

Publications

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

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