Enhancing Chemical Adherence Testing through Pharmacokinetics and Pharmacogenetics Insights and Mass Spectrometry Advancements.

Abstract

This thesis addresses the pressing issue of medication non-adherence with a focus on hypertension. Non-adherence is common and significantly elevates the risk of hospitalisation and mortality. The study investigates chemical adherence tests to assess medication adherence, employing liquid chromatography with tandem mass spectrometry (LC-MS/MS) as a robust method. The introduction highlights the complexities of adherence measurement and outlines potential limitations, including the influence of pharmacokinetics (PK) and pharmacogenetics on medication detection and the time-consuming nature of chemical adherence testing (CAT) processes. The central hypothesis underpinning this research is that the pharmacokinetics and pharmacogenetics of antihypertensive medications do not significantly affect medication detection or, consequently, the results of CAT by LC-MS/MS. This hypothesis is explored through a series of specific aims, including establishing PK parameters for the 20 most commonly prescribed antihypertensive medications through a comprehensive literature review. Additionally, the study aims to determine whether these PK parameters have any bearing on the outcomes of CAT using LC-MS/MS. A systematic review is conducted to identify genetic polymorphisms related to the effects of cardiovascular medications within the Biology Study to Tailored Treatment in Chronic Heart Failure (BIOSTAT-CHF) cohort, and the subsequent investigation focuses on the association between genetic polymorphisms and medication detection rates in the same cohort. Furthermore, the study strives to develop and partial validate an improved and more efficient CAT method for quantitating various cardiometabolic medications using LC-QQTO MS, a crucial step in ensuring accurate adherence assessments. The findings of this research reveal several critical insights. Chapter 3, which reviews the PK parameters of commonly prescribed antihypertensive medications, demonstrates no significant correlation between these parameters and adherence scores. This observation holds for multiple parameters, including bioavailability, urine excretion, clearance, volume of distribution (VD), half-life, peak time, and peak concentrations. Logistic regression analysis confirms that PK parameters do not predict non-adherence, even when considering additional factors such as age, sex, the number of medications, and creatinine levels. In Chapter 4, the systematic review uncovers various genetic polymorphisms associated with cardiovascular medication effects in the BIOSTAT-CHF cohort. However, these genetic variations do not exhibit a substantial correlation with non-adherence to prescribed cardiovascular drugs and encompass a wide range of effects, including PK influences, adverse drug reactions, metabolic responses, therapeutic outcomes, and risk-related impacts. Additionally, a non-directed genome wide association study (GWAS) showed weak associations with some potential polymorphisms, but none met the usual threshold of significance. Chapter 5 focuses on the development and partial validation of LC-QTOF-MS methods for the quantitation of cardiometabolic medications. Due to the distinct challenges posed by the COVID-19 pandemic, the objective was modified to conduct a partial validation assessment. The analysis time was reduced by 10 times from the previous method. The optimization of conditions for both positive and negative modes of LC-QTOF-MS is detailed, covering parameters such as capillary voltage, energy settings, and mobile phase selection. The validation results underscore the importance of tailored approaches for different pharmaceutical compounds, emphasising the significance of meticulous method development and validation in pharmaceutical analysis. In conclusion, this thesis proves the central hypothesis that the pharmacokinetics and pharmacogenetics of antihypertensive medications do not significantly affect medication detection and, therefore, do not influence the outcomes of CAT by LC-MS/MS. These findings offer valuable insights into improving medication adherence assessment and management in cardiometabolic diseases, highlighting the need for a multifaceted approach that considers pharmacokinetics and pharmacogenetics. Notably, my thesis had to adapt to the challenges posed by the COVID-19 crisis. The research shifted its focus from the initial plan of conducting PK profiles of antihypertensive medications in healthy volunteers to the plan of undertaking a systematic review of genetic polymorphisms associated with various effects of cardiovascular medications within the BIOSTAT-CHF cohort study.