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Implementation of an automatic quality control of derived data files for NONMEM
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
2019 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

A pharmacometric analysis must be based on correct data to be valid.

Source clinical data is rarely ready to be modelled as is, but rather

needs to be reprogrammed to fit the format required by the

pharmacometric modelling software. The reprogramming steps include

selecting the subsets of data relevant for modelling, deriving new

information from the source and adjusting units and encoding.

Sometimes, the source data may also be flawed, containing vague

definitions and missing or confusing values. In either setting, the

source data needs to be reprogrammed to remedy this, followed by

extensive quality control to capture any errors or inconsistencies

produced along the way. The quality control is a lengthy task which is

often performed manually, either by the scientists conducting the

pharmacometric study or by independent reviewers. This project

presents an automatic data quality control with the purpose of aiding

the data curation process, as to minimize any potential errors that

would otherwise have to be detected by the manual quality control. The

automatic quality control is implemented as an R-package and is

specifically tailored for the needs of Pharmetheus.

Place, publisher, year, edition, pages
2019.
Series
UPTEC X ; 18 033
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-375892OAI: oai:DiVA.org:uu-375892DiVA, id: diva2:1284787
External cooperation
Pharmetheus AB
Educational program
Molecular Biotechnology Engineering Programme
Supervisors
Examiners
Available from: 2019-02-05 Created: 2019-02-01 Last updated: 2019-02-07Bibliographically approved

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CiteExportLink to record
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  • apa
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