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Analysis of drug induced interstitial lung disease in non-small cell lung cancer through modelling and simulation
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Wanika, Linda (2022) Analysis of drug induced interstitial lung disease in non-small cell lung cancer through modelling and simulation. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3857775
Abstract
A class of drugs known as tyrosine kinase inhibitors (TKIs) are often used in targeted therapies for the treatment of non-small cell lung cancer (NSCLC). Approximately 1% of non-small cell cancer patients who are treated with TKIs develop interstitial lung disease (ILD) as an adverse event. ILD is a term used to describe a group of diseases which affect the pulmonary interstitium. Currently, the mechanism of TKI-induced ILD is not known. The low occurrence of this adverse event hinders the investigation of possible mechanism(s) for TKI-induced ILD. In this thesis, different approaches are introduced and applied in order to enhance the current knowledge of TKI-induced ILD. Bayesian analysis is combined with the traditional frame work of a meta-analysis in order to investigate the risk of ILD for NSCLC patients who are treated with different TKIs. Patients who were treated with the TKI crizotinib seemed to be more at risk of developing ILD than patients who were treated with alectinib, dacomitinib, gefitinib, osimertinib and vandetanib. An in-vitro pharmacokinetic/pharmacodynamic model was developed to simulate a potential pathway for TKI-induced ILD. The model was able to simulate the changes in transforming growth factor beta (TGFβ) in response to different TKIs. It is thought that an increase in TGFβ can lead to ILD as TGFβ is a promoter of pulmonary fibrosis. There is a need to identify risk factors for ILD that can be used to monitor patients without the use of specialist techniques or measurements. Moreover there is also a need to highlight whether these factors can be used to identify when a patient is likely to develop ILD. The application of machine learning as well as Bayesian analysis of baseline clinical trial data and real word evidence data (respectively) are used to identify possible factors. Low albumin and creatinine levels, high levels of glucose and longer duration between NSCLC diagnosis and treatment commencement were all associated with a higher risk of ILD. Moreover, these factors also aided in identifying the time interval over which patients were likely to develop ILD.
Item Type: | Thesis (PhD) | ||||
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Subjects: | R Medicine > RC Internal medicine R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer) |
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Library of Congress Subject Headings (LCSH): | Protein-tyrosine kinase -- Inhibitors, Protein-tyrosine kinase -- Inhibitors -- Therapeutic use, Interstitial lung diseases, Lungs -- Diseases, Lungs -- Cancer | ||||
Official Date: | February 2022 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | School of Engineering | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Chappell, M. J. (Michael J.) ; Evans, Neil D. | ||||
Sponsors: | Engineering and Physical Sciences Research Council ; AstraZeneca (Firm) | ||||
Format of File: | |||||
Extent: | xxi, 365 pages : illustrations | ||||
Language: | eng |
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