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- Abrantes, João A.
(författare)
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Pharmacometric Approaches to Improve Dose Individualization Methods in Hemophilia A
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Hemophilia A is a bleeding disorder caused by the lack of functional coagulation factor VIII (FVIII). The overall aim of this thesis was to improve dose individualization of FVIII replacement therapy in hemophilia A using pharmacometric approaches.A population pharmacokinetic (PK) model of FVIII activity following the administration of moroctocog alfa was developed based on data from a large heterogeneous cohort of moderate to severe hemophilia A patients. Body weight, age, neutralizing anti-FVIII inhibitors, race, and analytical assay were found to be significant predictors of FVIII activity PK. In addition, large inter-individual variability (IIV) and inter-occasion variability (IOV) was identified highlighting the need for dose individualization.High magnitudes of IOV are known to impair model-based therapeutic drug monitoring. Using a population PK model of FVIII activity, several approaches to handle IOV in Bayesian forecasting of individual PK parameters were assessed across a wide range of features. Considering IOV in Bayesian forecasting, but ignoring IOV in dose calculation, led to the most precise individualized doses, in particular, when sparse data was used.The dose-exposure-response relationship of FVIII replacement therapy remains unclear. A parametric repeated time-to-categorical event (RTTCE) model was developed to characterize the relationship between the dose of octocog alfa, plasma FVIII activity, bleeding frequency and severity, and covariates, using data from clinical trials. The bleeding hazard was found to decrease throughout time and to be affected by plasma FVIII activity and number of previous bleeds. Unexplained IIV in the bleeding hazard was found to be large.Bayesian forecasting based on the RTTCE model was used to predict the future occurrence of bleeds, and to contrast the predicted outcome using individual i) PK, ii) bleeding, and iii) PK, bleeding and covariate information, from data collected in clinical trials. The results support that individual bleed information can inform the optimization of prophylactic dosing regimens in severe hemophilia A patients.In summary, the pharmacometric approaches presented provide a valuable quantitative framework to improve dose individualization in hemophilia A. Furthermore, enhanced dosing has the potential to reduce bleeding frequency and to lower the high costs associated to treatment.
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| 2. |
- Netterberg, Ida, 1988-
(författare)
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Pharmacometric Evaluation of Biomarkers to Improve Treatment in Oncology
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cancer is a family of many different diseases with substantial heterogeneity also within the same cancer type. In the era of personalized medicine, it is desirable to identify an early response to treatment (i.e., a biomarker) that can predict the long-term outcome with respect to both safety and efficacy. It is however not uncommon to categorize continuous data, e.g., using tumor size data to classify patients as responders or non-responders, resulting in loss of valuable information. Pharmacometric modeling offers a way of analyzing longitudinal time-courses of different variables (e.g., biomarker and tumor size), and therefore minimizing information loss.Neutropenia is the most common dose-limiting toxicity for chemotherapeutic drugs and manifests by a low absolute neutrophil count (ANC). This thesis explored the potential of using model-based predictions together with frequent monitoring of the ANC to identify patients at risk of severe neutropenia and potential dose delay. Neutropenia may develop into febrile neutropenia (FN), a potentially life-threatening condition. Interleukin 6, an immune-related biomarker, was identified as an on-treatment predictor of FN in breast cancer patients treated with adjuvant chemotherapy. C-reactive protein, another immune-related biomarker, rather demonstrated confirmatory value to support FN diagnosis.Cancer immunotherapy is the most recent advance in anticancer treatment, with immune checkpoint inhibitors, e.g., atezolizumab, leading the breakthrough. In a pharmacometric modeling framework, the area under the curve of atezolizumab was related to tumor size changes in non-small cell lung cancer patients treated with atezolizumab. The relative change from baseline of Interleukin 18 at 21 days after start of treatment added predictive value on top of the drug effect. The tumor size time-course predicted overall survival (OS) in the same population.Circulating tumor cells (CTCs) are tumor cells that have shed from a tumor and circulate in the blood. CTCs may cause distant metastases, which is related to a poor prognosis. A novel modeling framework was developed in which the relationship between tumor size and CTC count was quantified in patients with metastatic colorectal cancer treated with chemotherapy and targeted therapy. It was also demonstrated that the CTC count was a superior predictor of OS in comparison to tumor size changes.In summary, IL-6 predicted FN, IL-18 predicted tumor size changes and tumor size changes and CTC counts predicted OS. The results in this thesis were obtained by using pharmacometrics to evaluate biomarkers to improve treatment in oncology.
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