The Drug Disease Model Resources (DDMoRe) Interoperability Framework (IOF) enables pharmacometric model encoding and execution via Model Description Language (MDL) and R language, through the ddmore package. Through its components and converter plugins, the IOF can execute pharmacometric tasks using different target tools, starting from a single MDL‐encoded model. In this article, we present the WinBUGS plugin and show how its integration in the IOF enables an easy implementation of complex Bayesian workflows. We selected a published diabetes‐linked study as a real‐world example, in which two inter‐related models are used to estimate insulin secretion rate in response to a glucose stimulus from intravenous glucose tolerance test (IVGTT) data. This model was implemented following different approaches to propagate uncertainty, via diverse IOF target tools (NONMEM, WinBUGS, PsN, and Xpose). The developed software supports a plethora of pharmacokinetic/pharmacodynamic (PK/PD) modeling features. It provides solutions to reproducibility and interoperability issues in Bayesian modeling, and facilitates the difficult encoding of complex PK/PD models in WinBUGS.
Complex Bayesian Modeling Workflows Encoding and Execution Made Easy With a Novel WinBUGS Plugin of the Drug Disease Model Resources Interoperability Framework
C. Larizza,E. Borella,L. Pasotti,P. Tartaglione,Mike K. Smith,Stuart L. Moodie,P. Magni
Published 2018 in CPT: Pharmacometrics & Systems Pharmacology
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- Publication year
2018
- Venue
CPT: Pharmacometrics & Systems Pharmacology
- Publication date
2018-03-25
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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