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

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University of Otago

1. Vajjah, Venkata Pavan Kumar. Application of pharmacometric methods to clinical toxicology studies .

Degree: 2011, University of Otago

Risk assessment is a fundamental part of clinical toxicology. It is complicated due to a variable time course of clinical effects of drugs in clinical toxicology. Defining the time course of clinical effects of drugs in overdose will assist in accurate risk assessment and thus minimise the risk to benefit ratio for each individual patient. However assessing the time course of clinical effects of drugs is complex in overdose studies. The complexity arises from absence of accurate knowledge of the dose, the time at which the overdose was ingested and observations in the initial phase of the study after the overdose. The study designs in overdose studies are highly unbalanced which adds to the complexity. The purpose of this thesis is to apply pharmacometric methods to define the time course of clinical effects of drugs in overdose. In this thesis pharmacometric methods are applied to: 1) Quantify the effects of various decontamination procedures on pharmacokinetics of venlafaxine in overdose. 2) Quantify the effects of various decontamination procedures on pharmacodynamics of venlafaxine in overdose. 3) Develop a robust optimality criterion for designing a study to assess whether paracetamol in overdose has linear or nonlinear pharmacokinetics. In the pharmacokinetic analysis (Chapter 2), data obtained from a venlafaxine overdose study were modelled using Bayesian methodology in WinBUGS 1.4.3.The results of the analysis showed that a one-compartment model with first-order input and first-order elimination provided an adequate description of the data. Single dose activated charcoal increased the clearance of venlafaxine by 35% and a combination of single dose activated charcoal and whole bowel irrigation reduced the fraction absorbed by 29%, however the latter produced a greater reduction in maximum plasma concentration for a similar drop in area under the curve compared to single dose activate charcoal alone. In the pharmacodynamic analysis (Chapter 4), a linear logistic regression model was used to describe the influence of dose and decontamination on the probability of seizures. Simulations from the model showed that the probability of seizure increased with dose. Single dose activated charcoal and combination of single dose activated charcoal and whole bowel irrigation decreased the probability of seizure. The decrease in probability of seizure was greater with the combination when compared with single dose activated charcoal alone. A modified Gompertz model was used to define the time to first seizure using Bayesian methodology in WinBUGS 1.4.3. Simulations from the model showed that the time to 90% of first seizure was not affected by dose or decontamination procedures. The results also showed that the pharmacokinetics of venlafaxine drives the pharmacodynamics. A pharmacokinetic study of paracetamol in overdose was prospectively designed to optimally discriminate between two candidate models (Chapter 6). In this study a robust T-optimal design was developed to distinguish between two candidate models, a… Advisors/Committee Members: Duffull, Stephen (advisor).

Subjects/Keywords: Pharmacometrics; Clinical toxicology; Bayesian analysis

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

APA (6th Edition):

Vajjah, V. P. K. (2011). Application of pharmacometric methods to clinical toxicology studies . (Doctoral Dissertation). University of Otago. Retrieved from http://hdl.handle.net/10523/554

Chicago Manual of Style (16th Edition):

Vajjah, Venkata Pavan Kumar. “Application of pharmacometric methods to clinical toxicology studies .” 2011. Doctoral Dissertation, University of Otago. Accessed August 07, 2020. http://hdl.handle.net/10523/554.

MLA Handbook (7th Edition):

Vajjah, Venkata Pavan Kumar. “Application of pharmacometric methods to clinical toxicology studies .” 2011. Web. 07 Aug 2020.

Vancouver:

Vajjah VPK. Application of pharmacometric methods to clinical toxicology studies . [Internet] [Doctoral dissertation]. University of Otago; 2011. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10523/554.

Council of Science Editors:

Vajjah VPK. Application of pharmacometric methods to clinical toxicology studies . [Doctoral Dissertation]. University of Otago; 2011. Available from: http://hdl.handle.net/10523/554


University of Otago

2. Lagishetty, Chakradhar. Covariates in Pharmacometrics .

Degree: 2013, University of Otago

Understanding the variability in drug response forms an important aspect of pharmacometrics. Various biological, statistical, clinical and mathematical concepts need to be considered to reach a unified decision point to understand and quantify sources of variability. This current work involves studies on methodological and clinical exploratory evaluation of covariates in the context of pharmacometrics. Studies have been conducted using theoretic approaches on the design of pharmacokinetic (PK) studies for latent covariates, use of a reduction in random between subject variability as a covariate selection criterion and evaluated methods to handle non-ignorable nuisance covariates. Exploratory studies were also conducted in a clinical & experimental framework for identification of suitable metrics of organ function as covariates to predict drug clearance. Part I of this thesis includes methodological evaluation of covariates with Chapters 2, 3 and 4. Part II involves clinical exploratory evaluation of covariates with Chapters 5 and 6. Chapter 2 involved studies on the design of pharmacokinetic studies for latent covariates. The motivating context for this work was from a single nucleotide polymorphism (SNP) believed to influence clearance. This led to exploration of the concept of latent covariates which can have uncertainty in both their distribution and frequency. Simulation studies were conducted in both linear regression and nonlinear mixed effects modelling (NLMEM) frameworks assuming both even and uneven frequencies of the covariate. The designs for latent covariates were evaluated assuming continuous, ordinal and nominal distribution of covariates. Initially, the designs were evaluated in a theoretic framework using linear regression. Then, these were evaluated in a NLMEM framework assuming direct influence of latent covariate or indirect influence of latent covariate via another observable continuous covariate on parameter of interest. It was observed that continuous models performed better than categorical models. A covariate selection criterion was evaluated in Chapter 3. In pharmacometric analysis, a reduction in random between subject variability is used as part of standard criteria for selection of a covariate. The covariate is not selected if it failed to reduce random between subject variance (BSVR) in the model. Studies were conducted in a simulation framework to assess nested covariate models (NCM) and not nested covariate models (NNCM). Further, covariate-η interaction models were explored but were found to be marginally important. NCMs were found to be more robust to model misspecification than NNCMs which may not result in a reduction in BSVR. Chapter 4 explores analysis methods for handling nuisance covariates. The frequency with which a covariate occurs is important when interpreting its effect size. Covariates like genotypes and concomitant medication are sometimes present at low frequencies or as rare events. Due to alpha error inflation, estimates of their effect size may be false. These are… Advisors/Committee Members: Duffull, Stephen (advisor).

Subjects/Keywords: latent covariate; between subject variability; nuisance covariate; telomere length; single nucleotide polymorphisms; qPCR assay; genotyping; biological age; organ function; Pharmacometrics analysis

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

APA (6th Edition):

Lagishetty, C. (2013). Covariates in Pharmacometrics . (Doctoral Dissertation). University of Otago. Retrieved from http://hdl.handle.net/10523/4520

Chicago Manual of Style (16th Edition):

Lagishetty, Chakradhar. “Covariates in Pharmacometrics .” 2013. Doctoral Dissertation, University of Otago. Accessed August 07, 2020. http://hdl.handle.net/10523/4520.

MLA Handbook (7th Edition):

Lagishetty, Chakradhar. “Covariates in Pharmacometrics .” 2013. Web. 07 Aug 2020.

Vancouver:

Lagishetty C. Covariates in Pharmacometrics . [Internet] [Doctoral dissertation]. University of Otago; 2013. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10523/4520.

Council of Science Editors:

Lagishetty C. Covariates in Pharmacometrics . [Doctoral Dissertation]. University of Otago; 2013. Available from: http://hdl.handle.net/10523/4520

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