Supporting Drug Regulators Through Simple Rapid Cycle Analyses

Main Article Content

Ximena Camacho
Margaret Wilson
Michael Paterson
Sallie Pearson
David Henry

Abstract

Introduction
Drug regulators require timely, relevant information to address questions about the safety of prescribed medicines. Some questions can be informed by initial rapid and simple analyses of linked exposure/outcome data. These analyses will establish how many individuals have received the drug, their characteristics, the availability of follow up time and the frequency of the event of interest in the exposed cohort. This approach does not enable causal inferences but establishes the need for, and feasibility of, more complex controlled analyses. Discovery that the exposure or outcome are uncommon can allay initial fears about the extent of a problem.


Objectives and Approach
A pilot network to support the Australian drug regulator (TGA, Department of Health) was established among three research institutions in Australia and Canada. Initial queries were identified and prioritised by staff at the TGA. Academic staff at the partner institutions performed a rapid feasibility assessment based on existing knowledge and expertise. Following this, initial exposure/outcome analyses were undertaken on selected queries using routinely collected data from Canada and Australia. Updates were provided to the TGA at each stage to ensure that decision-makers were fully informed and participated in decision making.


Results
To date, the network has assessed 20 queries. Seven were deemed infeasible and 4 queries were being addressed by studies that were already planned or underway; in these cases, arrangements were made to provide early results directly to the regulator. The final four queries progressed to an initial exposure/outcome analysis, and one such study was expanded to a fully adjusted controlled analysis.


Conclusion / Implications
This framework has proven to be agile and responsive and has strengthened the relationship between academia and the TGA. It may serve as a model for others who wish to engage more closely with governments or other decision makers.

Article Details

How to Cite
Camacho, X., Wilson, M., Paterson, M., Pearson, S. and Henry, D. (2020) “Supporting Drug Regulators Through Simple Rapid Cycle Analyses”, International Journal of Population Data Science, 5(5). doi: 10.23889/ijpds.v5i5.1581.

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