Monitoring of propofol in breath; pharmacokinetic modeling and design of a control system

The research work presented in this thesis discusses innovative strategies for breath propofol detection, monitoring and its pharmacokinetic modeling. Design of a breath based propofol control system is also presented. Propofol (2,6-diisopropylphenol) has become a commonly used hypnotic in total intravenous anesthesia. It has some volatility, so it can be detected in exhaled breath gas of individuals receiving intravenous propofol. Online detection and quantification of propofol bolus in breath reflect plasma propofol concentrations. The research work presented in this thesis focus on three main objectives 1. Monitoring and quantization of exhaled breath propofol using IMR-MS (Ion molecule reaction mass spectrometer) and electrochemical sensors that detects propofol from expired gas. 2. Design of a multi compartment pharmacokinetic model to describe the expired breath propofol concentrations. 3. Development of a breath based feedback control system which controls intravenous propofol application. Proof-of-concept experiments were conducted to address the principles in monitoring of breath propofol and breath based feedback control system. In the introduction Chapters 1 and 2, various principles of breath monitoring and methods used to detect propofol in breath are explained in detail. A brief introduction to the concepts of pharmacokinetic modeling (with emphasis on compartmental modeling) and anesthesia control are given. The goal is to acquaint the reader with the terminology and principles involved in breath monitoring and the mathematical model that has been proposed to describe it. In Chapter 3, the experimental methods and procedures used in the study are elaborately explained. Details about the preclinical study protocols are also given. Chapter 4 focuses on the detection of breath propofol by electrochemical sensor. The optimisation methods used in developing the sensor system are also briefly described in this chapter. In Chapter 5, monitoring of exhaled propofol using ion molecule reaction mass spectrometry (IMR-MS) and electrochemical sensor after administering propofol boli with a continuous infusion in pigs is well described. Also the characterization of breath propofol detected by both IMR-MS and electrochemical sensor is explained. Effects of changes in breath frequency, cardiac output and hemorrhagic shock on breath propofol pharmacokinetics are demonstrated. Chapter 6 focuses on design of a multi compartment pharmacokinetic model to describe expired gas propofol concentrations. This model is used as a patient simulator for the design of the feedback control system. The performance of this model is presented. Chapter 7 discusses the breath based control system design and its performance. Its performance in maintaining anesthesia is compared to results from previous studies using BIS (bi-spectral index) as the control variable.