Abstract
Special patient groups, such as children and pregnant women, are not regularly included in drug development programs. Changes in physiological processes in these patients affect the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. This may result in suboptimal efficacy or substantial toxicity caused by under- or overexposure to these drugs. This thesis presents how modelling and simulation can be used to optimize anticancer treatment of special patient groups. By identification of predictors or covariates that influence the clinical pharmacology of anticancer drugs, treatment may be further optimized by individualization of treatment. In addition, the developed models can be used to predict future dosing regimens, expected toxicities or outcomes and are particularly useful to extrapolate to special patient populations for which typically limited data is available.
Original language | English |
---|---|
Qualification | Doctor of Philosophy |
Awarding Institution |
|
Supervisors/Advisors |
|
Award date | 23 Apr 2020 |
Publisher | |
Print ISBNs | 978-94-6380-751-7 |
Publication status | Published - 23 Apr 2020 |
Keywords
- Cancer
- pregnancy
- children
- pharmacometrics
- pharmacokinetics
- pharmacodynamics