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You searched for subject:(Dose Individualisation). Showing records 1 – 2 of 2 total matches.

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University of New South Wales

1. Kumar, Shaun. Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes.

Degree: Medical Sciences, 2016, University of New South Wales

Dose selection is a critical part of individualising pharmacotherapy in order to ensure optimal safety and effectiveness. Population pharmacokinetic and/or pharmacodynamic modelling paired with Bayesian Forecasting is a sophisticated tool that can provide guidance for dose selection to clinicians. The overall aim of this thesis was to demonstrate the use of population modelling in three different settings and the utility of this approach for providing individualised dose selection.In the first application the aim was to demonstrate that plasma samples of ribavirin in early Hepatitis C therapy could be used to predict plasma concentrations at Week 4 (critical for toxicity). Bayesian Forecasting was shown to provide a better prediction of ribavirin concentrations than standard linear regression analysis. This work demonstrated that safer and more effective doses could be predicted early in the course of therapy allowing earlier dose individualisation.In the second application the aim was to confirm the published concentration-response relationship of imatinib in treating gastrointestinal stromal tumours. Interestingly, the data showed that patients with higher total plasma concentrations had a poorer response, opposite to what was expected. More work is needed to address this lack of concordance with the previous findings. One suggestion is that since imatinib is highly bound, unbound concentrations may be a better correlate of response than that based on total concentration.In the final application, the aim was to establish a metformin concentration-weight loss relationship in a group of overweight, non-diabetic women. A small but significant relationship between total metformin exposure and weight loss was shown. This finding is novel, as a relationship between drug concentration and weight loss has not been presented in the literature previously.Overall, the work presented in this thesis provided evidence for the value of population modelling and Bayesian Forecasting to assist in dose individualisation. Future directions for this work are: to refine the approach to dose selection in these and other important clinical areas of medicine; to establish a strong evidence base for implementation more widely; and then to pursue implementation strategies so that clinicians have access to these tools to make more appropriate dose selection. Advisors/Committee Members: Day, Richard, Clinical School - St Vincent's Hospital, Faculty of Medicine, UNSW, Williams, Kenneth, Medical Sciences, Faculty of Medicine, UNSW, Kirkpatrick, Carl, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University.

Subjects/Keywords: Population pharmacodynamics; Pharmacometrics; Population pharmacokinetics; Ribavirin; Imatinib; Metformin; Dose individualisation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kumar, S. (2016). Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55575 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:38076/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Kumar, Shaun. “Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes.” 2016. Doctoral Dissertation, University of New South Wales. Accessed August 07, 2020. http://handle.unsw.edu.au/1959.4/55575 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:38076/SOURCE02?view=true.

MLA Handbook (7th Edition):

Kumar, Shaun. “Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes.” 2016. Web. 07 Aug 2020.

Vancouver:

Kumar S. Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2020 Aug 07]. Available from: http://handle.unsw.edu.au/1959.4/55575 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:38076/SOURCE02?view=true.

Council of Science Editors:

Kumar S. Exploring the value of population pharmacokinetic and pharmacodynamic modelling: in infectious disease, cancer and diabetes. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/55575 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:38076/SOURCE02?view=true


University of Otago

2. Al-Sallami, Hesham. Optimising Patient Care by Individualising Drug Dosage .

Degree: University of Otago

Drug therapy is an important component of the treatment and prevention of diseases. A drug is administered to achieve a treatment target so it is important to quantify the drug dose and dosing regimen prior to administration in order to achieve this target. Following administration, the patient’s response to therapy is assessed and the drug dosage is adjusted accordingly in order to optimise therapy in terms of effectiveness and safety. The process of obtaining a treatment target for a particular drug, calculating a suitable dosage for an individual patient, measuring patient response, and adjusting dosage in order to optimise this response is complex and often inadequately done in clinical practice. This process often requires specialised knowledge in drug pharmacokinetics, pharmacodynamics, and model-based dose individualisation. In this thesis a treatment target for the anticoagulant drug enoxaparin was explored. The target (anti-factor Xa) was evaluated using a Bayesian dose-individualisation method and data collected retrospectively. The Bayesian forecasting method was then applied prospectively in a randomised clinical trial. Also, the analytical method used to measure enoxaparin concentration (anti-factor Xa) was evaluated in terms of accuracy, precision, stability, and performance in special conditions such as blood sample haemolysis and antithrombinaemia. The thesis also explored one of the main sources of variability in response between individuals, body composition. A model to predict fat-free mass, as a measure of structural maturation, from age, sex, height, and weight was developed and evaluated. The maturation model was then used successfully to develop a pharmacokinetic-pharmacodynamic model for the anticoagulant drug unfractionated heparin in a paediatric population. Advisors/Committee Members: Duffull, Stephen (advisor).

Subjects/Keywords: Dose Individualisation; Pharmacometrics; PKPD; Covariates; Enoxaparin; Heparin; Clinical Pharmacology; Fat-free mass; Target-concentration intervention

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Al-Sallami, H. (n.d.). Optimising Patient Care by Individualising Drug Dosage . (Doctoral Dissertation). University of Otago. Retrieved from http://hdl.handle.net/10523/5787

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Chicago Manual of Style (16th Edition):

Al-Sallami, Hesham. “Optimising Patient Care by Individualising Drug Dosage .” Doctoral Dissertation, University of Otago. Accessed August 07, 2020. http://hdl.handle.net/10523/5787.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

MLA Handbook (7th Edition):

Al-Sallami, Hesham. “Optimising Patient Care by Individualising Drug Dosage .” Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Al-Sallami H. Optimising Patient Care by Individualising Drug Dosage . [Internet] [Doctoral dissertation]. University of Otago; [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10523/5787.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Council of Science Editors:

Al-Sallami H. Optimising Patient Care by Individualising Drug Dosage . [Doctoral Dissertation]. University of Otago; Available from: http://hdl.handle.net/10523/5787

Note: this citation may be lacking information needed for this citation format:
No year of publication.

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