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Curr Med Res Opin. 2016 Jul;32(7):1269-76. doi: 10.1185/03007995.2016.1170671. Epub 2016 Apr 21.

Risk indicator taxonomy for supervision of clinical trials on medicinal products.

Author information

1
a Centre for Health Protection , National Institute of Public Health and the Environment (R.I.V.M.) , Bilthoven , the Netherlands ;
2
b Medicines Evaluation Board , (M.E.B.) Utrecht , the Netherlands ;
3
c Division of Pharmacoepidemiology and Clinical Pharmacology , Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University , Utrecht , the Netherlands ;
4
d Healthcare Inspectorate (I.G.Z.) , Utrecht , the Netherlands.

Abstract

AIM:

To facilitate a risk-based approach for the supervision of clinical trials on medicinal products, we identified and categorized indicators that may present an elevated safety and/or ethical risk for participants, and/or for data integrity. The indicators are relevant for all stakeholders including participants, regulatory bodies, health care inspectorates, sponsors and trial sites.

METHODS:

The sources of indicators included Medline (using the search terms risk-based/-triggered/-driven oversight/monitoring/inspection), relevant documents from websites of regulatory authorities in Europe, North America and Australia, and results of a brainstorm session organized for experts working in the field. Indicators were classified according to risk area (safety and ethical, data integrity, or both).

RESULTS:

In total, we identified 69 risk indicators that were categorized into six branch-levels of the taxonomy. We visualized the taxonomy in a tree structure to clearly distinguish individual indicators. In addition to readily detectable risk indicators, more context-related aspects determine the final impact of the trial and constitute further components in risk assessment. Context-related aspects include potential high media attention, consequences for the reputation of medical research, and the socioeconomic situation in the geographic region and have to be considered on a case-by-case basis.

CONCLUSIONS:

We identified a wide array of risk indicators for clinical trials on medicinal products and we used a tree structure to incorporate the indicators identified to clearly distinguish individual indicators and to enable efficient use of the indicators. The overview of indicators may facilitate multiple stakeholders in developing structured risk assessment (identification and analysis) for supervising clinical trials on medicinal products. Stakeholders can interpret and prioritize the indicators from their own perspective.

KEYWORDS:

Clinical trial; Data integrity; Ethics; Investigational medicinal product; Risk; Risk assessment; Risk indicator; Safety; Supervision; Taxonomy

PMID:
27009363
DOI:
10.1185/03007995.2016.1170671
[Indexed for MEDLINE]

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