There is high variability in response to cancer chemotherapies among patients. Its sources are diverse: genetic, physiologic, comorbidities, concomitant medications, environment, compliance, etc. As the therapeutic window of anticancer drugs is usually narrow, such variability may have serious consequences: severe (even life-threatening) toxicities or lack of therapeutic effect. Therefore, various approaches to individually tailor treatments and dosing regimens have been developed: a priori (based on genetic information, body size, drug elimination functions, etc.) and a posteriori (that is using information of measurements of drug exposure and/or effects). Mixed-effects modelling of pharmacokinetics and pharmacodynamics (PK-PD), combined with Bayesian maximum a posteriori probability estimation of individual effects, is the method of choice for a posteriori adjustments of dosing regimens. In this thesis, a novel approach to adjust the doses on the basis of predictions, given by a model for ordered categorical observations of toxicity, was developed and investigated by computer simulations. More technical aspects concerning the estimation of individual parameters were analysed to determine the factors of good performance of the method. These works were based on the example of capecitabine-induced hand-and-foot syndrome in the treatment of colorectal cancer. Moreover, a review of pharmacodynamic models for discrete data (categorical, count, time-to-event) was performed. Finally, PK-PD analyses of hydroxyurea in the treatment of sickle cell anemia were performed and used to compare different dosing regimens and determine the optimal measures for monitoring the treatment
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00846454 |
| Date | 29 September 2011 |
| Creators | Paule, Inès |
| Publisher | Université Claude Bernard - Lyon I |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | English |
| Detected Language | English |
| Type | PhD thesis |
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