Chemotherapy plays an important role in the treatment of cancer. However, these drugs also cause death of non-malignant cells, resulting in severe side-effects. In addition, drug resistance may exist. Predictive tools for dose and drug selection are therefore warranted. In this thesis predictive pharmacometric models were developed for the main dose-limiting side-effect, neutropenia, and for treatment response following chemotherapy. Neutropenia is associated with a high risk for life-threatening infections and leads frequently to reduced dose delivery and thereby suboptimal treatment of the tumor. A better characterization of the dynamics of docetaxel induced neutropenia was obtained by simultaneous analysis of neutrophils and leukocytes. The fraction of neutrophils was shown to change over the time-course, hence leukocytes and neutrophil counts are not interchangeable biomarkers. Sometimes neutrophil count is reported as categorical severity of neutropenia (Grade 0-4). A method was developed that allowed analysis of these data closer to its true continuous nature. The main regulatory hormone of neutrophils is granulocyte colony stimulating factor (G-CSF). Although recombinant G-CSF is used as supportive therapy to prevent neutropenia, little is known of how the endogenous G-CSF concentrations vary in patients following chemotherapy. A prospective study was carried out and simultaneous analysis of endogenous G-CSF and neutrophils following chemotherapy enabled a more mechanistic model to be developed that also could verify the self-regulatory properties of the physiological system. Patient characteristics were investigated using a pharmacokinetic-myelosuppression model for docetaxel in patients with normal and impaired liver function. The model was a useful tool in evaluating different dosing strategies and a reduced dosing scheme was suggested in patients with poor liver function, thereby enabling docetaxel treatment in this patient population which has previously been excluded. Treatment of acute myeloid leukemia with daunorubicin and cytarabine is associated with drug resistance and high variability in pharmacokinetics, which was partly explained for daunorubicin by peripheral leukocyte count. An integrated model of the in vitro drug sensitivity and treatment response showed that in vitro drug sensitivity was predictive for treatment outcome in this patient population and may therefore be used for choice of drug. The developed pharmacometric models in this thesis may be useful in the optimization of treatments schedules for existing and new drugs as well as to assist in drug and dose selection to improve therapy in an individual patient. The models and methods presented may also facilitate pooled analysis of data and demonstrate principles which could be useful for the pharmacometric community.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-150431 |
| Date | January 2011 |
| Creators | Quartino, Angelica L |
| Publisher | Uppsala universitet, Institutionen för farmaceutisk biovetenskap, Uppsala : Acta Universitatis Upsaliensis |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, 1651-6192 ; 144 |
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