The dose individualisation of oral anticoagulants

Oral anticoagulants are used to treat and prevent blood clots. All anticoagulants carry the risk of bleeding if the systemic exposure is too high, while inadequate exposure will increase the risk of thrombosis. Therefore, the safe and effective use of all oral anticoagulants will require dose individualisation and monitoring. The overarching goal of this thesis is to critically evaluate and explore dose individualisation methods for warfarin and dabigatran therapy to improve patient outcomes. For warfarin, methods for predicting the maintenance dose were investigated. Specifically, Chapter 2 investigates the predictive performance of a Bayesian dose individualisation tool for warfarin. It was found that the maintenance dose was over-predicted especially in patients requiring higher daily doses and further studies into the source of bias were conducted. Chapter 3 further evaluates whether published warfarin maintenance dose prediction algorithms can accurately predict the observed maintenance dose in patients who require ≥7 mg daily (the upper quartile of dose requirements). A systematic review and meta-analysis was conducted to answer this question. It was found that all warfarin dosing algorithms included in the study under-predicted the maintenance dose in this group of patients. One common metric to measure predictive performance of a model is the mean prediction error, which is a measure of bias. The work conducted in Chapter 2 and 3 suggests that the mean prediction error may not capture non-constant bias. This is when the predictions systematically deviate away from the line of identity in one direction in relation to the observed data. Chapter 4 proposes new method to assess predictive performance to analyse non-constant systematic deviation from the line of identity. The proposed method is not specific to warfarin, but can be applied to the analysis of predictive performance in general. For dabigatran dosing, aspects of concentration monitoring as a means of determining a suitable dosing rate were explored. In Chapter 5, an assay using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was developed to measure all active entities of dabigatran concentrations in human plasma. The assay was used to measure dabigatran concentrations collected from a previous study. A de novo population pharmacokinetic model was not pursued in the first instance as the data were fairly sparse. Instead, the measured concentrations were used in Chapter 6 in a simulation based study to select an appropriate prior population pharmacokinetic model that might be used in a future Bayesian dose individualisation method for dabigatran. The overall intention of Chapter 6 was to develop a Bayesian dose individualisation method for dabigatran. In conclusion, this thesis has identified the limitations of current methods for predicting warfarin maintenance dose and has explored dabigatran concentration monitoring as a means of improving dabigatran dosing. Models for predicting warfarin maintenance dose were critically evaluated and it was found that all existing models can not accurately predict the maintenance dose in patients requiring higher daily doses. An improvement in the method to assess predictive performance was proposed. The work conducted in this thesis on dabigatran dosing provides the basis for future research to individualise dosing and monitoring using population pharmacokinetic models

The dose individualisation of oral anticoagulants

Oral anticoagulants are used to treat and prevent blood clots. All anticoagulants carry the risk of bleeding if the systemic exposure is too high, while inadequate exposure will increase the risk of thrombosis. Therefore, the safe and effective use of all oral anticoagulants will require dose individualisation and monitoring. The overarching goal of this thesis is to critically evaluate and explore dose individualisation methods for warfarin and dabigatran therapy to improve patient outcomes. For warfarin, methods for predicting the maintenance dose were investigated. Specifically, Chapter 2 investigates the predictive performance of a Bayesian dose individualisation tool for warfarin. It was found that the maintenance dose was over-predicted especially in patients requiring higher daily doses and further studies into the source of bias were conducted. Chapter 3 further evaluates whether published warfarin maintenance dose prediction algorithms can accurately predict the observed maintenance dose in patients who require ≥7 mg daily (the upper quartile of dose requirements). A systematic review and meta-analysis was conducted to answer this question. It was found that all warfarin dosing algorithms included in the study under-predicted the maintenance dose in this group of patients. One common metric to measure predictive performance of a model is the mean prediction error, which is a measure of bias. The work conducted in Chapter 2 and 3 suggests that the mean prediction error may not capture non-constant bias. This is when the predictions systematically deviate away from the line of identity in one direction in relation to the observed data. Chapter 4 proposes new method to assess predictive performance to analyse non-constant systematic deviation from the line of identity. The proposed method is not specific to warfarin, but can be applied to the analysis of predictive performance in general. For dabigatran dosing, aspects of concentration monitoring as a means of determining a suitable dosing rate were explored. In Chapter 5, an assay using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was developed to measure all active entities of dabigatran concentrations in human plasma. The assay was used to measure dabigatran concentrations collected from a previous study. A de novo population pharmacokinetic model was not pursued in the first instance as the data were fairly sparse. Instead, the measured concentrations were used in Chapter 6 in a simulation based study to select an appropriate prior population pharmacokinetic model that might be used in a future Bayesian dose individualisation method for dabigatran. The overall intention of Chapter 6 was to develop a Bayesian dose individualisation method for dabigatran. In conclusion, this thesis has identified the limitations of current methods for predicting warfarin maintenance dose and has explored dabigatran concentration monitoring as a means of improving dabigatran dosing. Models for predicting warfarin maintenance dose were critically evaluated and it was found that all existing models can not accurately predict the maintenance dose in patients requiring higher daily doses. An improvement in the method to assess predictive performance was proposed. The work conducted in this thesis on dabigatran dosing provides the basis for future research to individualise dosing and monitoring using population pharmacokinetic models

Effects of CYP3A5 Polymorphism on Rapid Progression of Chronic Kidney Disease: A Prospective, Multicentre Study

Personalised medicine is potentially useful to delay the progression of chronic kidney disease (CKD). The aim of this study was to determine the effects of CYP3A5 polymorphism in rapid CKD progression. This multicentre, observational, prospective cohort study was performed among adult CKD patients (≥18 years) with estimated glomerular filtration rate (eGFR) ≥30 mL/min/1.73 m2, who had ≥4 outpatient, non-emergency eGFR values during the three-year study period. The blood samples collected were analysed for CYP3A5*3 polymorphism. Rapid CKD progression was defined as eGFR decline of >5 mL/min/1.73 m2/year. Multiple logistic regression was then performed to identify the factors associated with rapid CKD progression. A total of 124 subjects consented to participate. The distribution of the genotypes adhered to the Hardy–Weinberg equilibrium (X2 = 0.237, p = 0.626). After adjusting for potential confounding factors via multiple logistic regression, the factors associated with rapid CKD progression were CYP3A5*3/*3 polymorphism (adjusted Odds Ratio [aOR] 4.190, 95% confidence interval [CI]: 1.268, 13.852), adjustments to antihypertensives, young age, dyslipidaemia, smoking and use of traditional/complementary medicine. CKD patients should be monitored closely for possible factors associated with rapid CKD progression to optimise clinical outcomes. The CYP3A5*3/*3 genotype could potentially be screened among CKD patients to offer more individualised management among these patients

An International Adult Guideline for Making Clozapine Titration Safer by Using Six Ancestry-Based Personalized Dosing Titrations, CRP, and Clozapine Levels

This international guideline proposes improving clozapine package inserts worldwide by using ancestry-based dosing and titration. Adverse drug reaction (ADR) databases suggest that clozapine is the third most toxic drug in the United States (US), and it produces four times higher worldwide pneumonia mortality than that by agranulocytosis or myocarditis. For trough steady-state clozapine serum concentrations, the therapeutic reference range is narrow, from 350 to 600 ng/mL with the potential for toxicity and ADRs as concentrations increase. Clozapine is mainly metabolized by CYP1A2 (female non-smokers, the lowest dose; male smokers, the highest dose). Poor metabolizer status through phenotypic conversion is associated with co-prescription of inhibitors (including oral contraceptives and valproate), obesity, or inflammation with C-reactive protein (CRP) elevations. The Asian population (Pakistan to Japan) or the Americas' original inhabitants have lower CYP1A2 activity and require lower clozapine doses to reach concentrations of 350 ng/mL. In the US, daily doses of 300-600 mg/day are recommended. Slow personalized titration may prevent early ADRs (including syncope, myocarditis, and pneumonia). This guideline defines six personalized titration schedules for inpatients: 1) ancestry from Asia or the original people from the Americas with lower metabolism (obesity or valproate) needing minimum therapeutic dosages of 75-150 mg/day, 2) ancestry from Asia or the original people from the Americas with average metabolism needing 175-300 mg/day, 3) European/Western Asian ancestry with lower metabolism (obesity or valproate) needing 100-200 mg/day, 4) European/Western Asian ancestry with average metabolism needing 250-400 mg/day, 5) in the US with ancestries other than from Asia or the original people from the Americas with lower clozapine metabolism (obesity or valproate) needing 150-300 mg/day, and 6) in the US with ancestries other than from Asia or the original people from the Americas with average clozapine metabolism needing 300-600 mg/day. Baseline and weekly CRP monitoring for at least four weeks is required to identify any inflammation, including inflammation secondary to clozapine rapid titration