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Limited inter-occasion variability in relation to inter-individual variability in chemotherapy-induced myelosuppression
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Oncology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
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2010 (English)In: Cancer Chemotherapy and Pharmacology, ISSN 0344-5704, E-ISSN 1432-0843, Vol. 65, no 5, p. 839-848Article in journal (Refereed) Published
Abstract [en]

Purpose: A previously developed semi-physiological model of chemotherapy-induced myelosuppression has shown consistent system-related parameter and inter-individual variability (IIV) estimates across drugs. A requirement for dose individualization to be useful is relatively low variability between treatment courses (IOV) in relation to IIV. The objective of this study was to evaluate and compare magnitudes of IOV and IIV in myelosuppression model parameters across six different anti-cancer drug treatments.Methods: Neutrophil counts from several treatment courses following therapy with docetaxel, paclitaxel, epirubicin-docetaxel, 5-fluorouracil-epirubicin-cyclophosphamide, topotecan and etoposide were included in the analysis. The myelosuppression model was fitted to the data using NONMEM VI. IOV in the model parameters baseline neutrophil counts (ANC0), mean transit time through the non-mitotic maturation chain (MTT) and the parameter describing the concentration-effect relationship (Slope) were evaluated for statistical significance (P < 0.001).Results: IOV in MTT was significant for all the investigated datasets, except for topotecan, and was of similar magnitude (8-16 CV %). IOV in Slope was significant for docetaxel, topotecan and etoposide (19-39 CV %). For all six investigated datasets the IOV in myelosuppression parameters was lower than the IIV. There was no indication of systematic shifts in the system- or drug sensitivity-related parameters over time across data sets.Conclusion: This study indicates that the semi-physiological model of chemotherapy-induced myelosuppression has potential to be used for prediction of the time-course of myelosuppression in future courses and is thereby a valuable step towards individually tailored anticancer drug therapy.

Place, publisher, year, edition, pages
2010. Vol. 65, no 5, p. 839-848
Keywords [en]
Hematologic toxicity, pharmacodynamics, NONMEM, inter-occasion variability, anti-cancer drugs
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
URN: urn:nbn:se:uu:diva-100507DOI: 10.1007/s00280-009-1089-3ISI: 000274655500004PubMedID: 19680655OAI: oai:DiVA.org:uu-100507DiVA, id: diva2:210445
Available from: 2009-04-02 Created: 2009-04-01 Last updated: 2018-01-13Bibliographically approved
In thesis
1. Dose Adaptation Based on Pharmacometric Models
Open this publication in new window or tab >>Dose Adaptation Based on Pharmacometric Models
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[en]
Model Based Dose Adaptation
Abstract [en]

Many drugs exhibit major variability in both pharmacokinetic (PK) and pharmacodynamic (PD) parameters that prevents the use of the same dose for all patients. Variability can occur both between patients (IIV) as well as within patients over the course of time (IOV). In a drug with narrow therapeutic range and substantial IIV, dose selection may require individual adaptation. Adaptation can either be made before (a priori) or after (a posteriori) first drug administration. The former implies basing the dose on prior information known to be influential, such as kidney function indicators, weight or concomitant medication, whereas a posteriori dose adaptations are based on post-treatment observations. Often individualization cannot be based on the clinical outcome itself. In such cases, drug concentrations or biomarkers may be valuable for dose individualisation.

In this thesis two therapeutic areas where dosing is critical have been investigated regarding the possibilities of a priori and a posteriori dose adaptation; anticancer treatment where myelosuppression is dose limiting, and tacrolimus used for immunosuppression in paediatric transplantation. In tacrolimus previously published models were found to be of little value for dose adaptation in the early critical days post-transplantation. New PK models were developed and used to suggest new dosing regimens tailored for the paediatric population, recognizing the changing pharmacokinetics in the early time post-transplantation.

For several anticancer drugs covariates were identified that partly explained IIV in myelosuppression. IOV were found to be lower than IIV which implies that individual dose adaptations a posteriori can be valuable. Dose adaptation, using Bayesian principles in order to simultaneously minimise the risk of severe toxicity or subtherapeutic levels, was evaluated using simulations. Type and amount of data needed, as well as variability parameters influential on the outcome, were evaluated. Results show drug concentrations being of little value, if neutrophil counts are available.

The models discussed in this thesis have been implemented in MS Excel macros for Bayesian forecasting, to allow widespread distribution to clinical settings without necessitating access to specific statistical software.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2009. p. 80
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 94
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-100569 (URN)978-91-554-7488-1 (ISBN)
Public defence
2009-05-15, B41, BMC, Dag Hammarsköldsväg, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2009-04-22 Created: 2009-04-02 Last updated: 2018-01-13Bibliographically approved
2. Pharmacometric Models for Biomarkers, Side Effects and Efficacy in Anticancer Drug Therapy
Open this publication in new window or tab >>Pharmacometric Models for Biomarkers, Side Effects and Efficacy in Anticancer Drug Therapy
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

New approaches quantifying the effect of treatment are needed in oncology to improve the drug development process and to enable treatment optimization for existing therapies. This thesis focuses on the development of pharmacometric models for biomarkers, side effects and efficacy in order to identify predictors of clinical response in anti-cancer drug therapy.

The variability in myelosuppression was characterized in six different cytotoxic anticancer treatments to evaluate a model-based dose individualization approach utilizing neutrophil counts as a biomarker. The estimated impact of inter-occasion variability was relatively low in relation to the inter-individual variability, indicating that myelosuppression is predictable from one treatment course to another. The approach may thereby be useful for dose optimization within an individual.

To further study and to identify predictors for the severe side effect febrile neutropenia (FN), the relationship between the shape of the myelosuppression time-course and the probability of FN was characterized. Patients with a rapid decline in neutrophil counts and high drug sensitivity were identified to have a higher probability of developing FN compared with other patients who experience grade 4 neutropenia.

Predictors of clinical response in patients receiving sunitinib for the treatment of gastro-intestinal stromal tumor (GIST) were identified by the development of an integrated modeling framework. Drug exposure, biomarkers, tumor dynamics, side effects and overall survival (OS) were linked in a unified structure, and univariate and multivariate exposure variables were tested for their predictive capacities. The soluble biomarker, sVEGFR-3 and tumor size at start of treatment were found to be promising predictors of overall survival, with decreased sVEGFR-3 levels and smaller baseline tumor size being predictive of longer OS. Also hypertension and neutropenia was identified as predictors of OS. The developed modeling framework may be useful to monitor clinical response, optimize dosing in sunitinib and to facilitate dose individualization.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2012. p. 58
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 157
Keywords
Pharmacokinetics, Pharmacodynamics, Oncology, Febrile Neutropenia, GIST, Sunitinib
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-170738 (URN)978-91-554-8312-8 (ISBN)
Public defence
2012-05-04, B42, Uppsala Biomedical Center, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2012-04-13 Created: 2012-03-12 Last updated: 2018-01-12Bibliographically approved

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Hansson, Emma K.Wallin, JohanLindman, HenrikKarlsson, Mats O.Friberg, Lena E.

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