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. 2020 Dec 31;3(4):536–544. doi: 10.1093/jamiaopen/ooaa048

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© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 2. — An overview of our framework’s emulation pipeline and the underlying components. The central module is the Randomized Controlled Trial (RCT) Emulator, which orchestrates the entire process. First, the Tested Drugs Extractor identifies a list of repurposing candidates, based on the user-provided Drug Criteria. For each such candidate, using the input Study Design parameters, the Treatment & Control Cohorts Extractor assigns patients to the respective cohorts. The Confounders & Outcomes Extractor computes a baseline and follow-up attributes for patients in both cohorts. The Drug Repurposing Engine then instantiates an RCT Emulator for each candidate, which estimates its effect on disease outcomes in the treatment versus control cohorts, adjusting for the extracted confounders and using methods implemented in the Causal Inference Library.