Statistical analysis of bioassay data with dependent replicates

dc.contributor.advisorStewart, Connie
dc.contributor.advisorStephenson, Matthew
dc.contributor.authorCann, Liam
dc.date.accessioned2025-05-20T18:35:27Z
dc.date.available2025-05-20T18:35:27Z
dc.date.issued2025-03
dc.description.abstractBioassays play a key role in ensuring that every batch of drug produced is safe and effective for release. They play a critical role in testing the potency of biologic drugs, such as vaccines or monoclonal antibodies. Due to the importance of bioassays in ensuring a safe and effective product, it is critical that the statistical methods used are appropriate. However, it is the current common practice to treat the replicate responses at each dose group as if they are independent despite the fact they are often correlated. In this research, we look at quantitatively assessing the risks of the conventional analysis methods using a simulation study to investigate the impact of correlation on the statistical analysis of bioassays. Specifically, we consider parallelism assessment, model goodness-of-fit, and relative potency estimation. We also make recommendations within the constraints of the current available commercial bioassay analysis software to provide valid statistical inference.
dc.description.copyright© Liam Cann, 2025
dc.format.extentvii, 44
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/38296
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.relationQuantics Biostatistics
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.titleStatistical analysis of bioassay data with dependent replicates
dc.typemaster report
oaire.license.conditionother
thesis.degree.disciplineMathematics and Statistics
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.

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