This thesis compares the efficacy of misspecified pharmacokinetic models to mechanistically true models when optimizing discrete dose levels. The aim is to compare discrete dose predictions and the resulting drug exposure levels between these models. Dose levels are discrete in practice, and physicians often determine a patient’s dose based on variables that are easily measured, such as age or weight, rather than those directly influencing pharmacokinetics, like renal function. This study investigates how using misspecified or simplified models affect the resulting drug exposure through the predicted discrete dose.Non-linear mixed effects models are used to simulate drug concentrations in hypothetical patients. Data are simulated using the true model, followed by evaluation of both true and misspecified models at the population and individual levels. At the population level, results show that simplified or misspecified models generally produced comparable exposure levels to those of the true model, despite differences in predicted doses. At the individual level, the outcomes are even more consistent, with misspecified models yielding almost identical results to their respective true models.This study underscores the practical utility of misspecified models in pharmacokinetic simulations while highlighting the importance of context-specific evaluations.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-532092 |
| Date | January 2024 |
| Creators | Hamberg, Hanna |
| Publisher | Uppsala universitet, Statistiska institutionen |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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