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How can we develop models for platelet aggregation to be used in the design of controllers to regulate the formation of thrombus?

Title: Intelligent control for microfloppies systems for the study of platelet aggregation.
Abstract: The proposed research involves the development of lab-on-a-chip-type platforms with advanced control systems, for the study of cardiovascular diseases in vitro. The main purpose is to provide an engineering perspective in the study of the process of human platelet aggregation. The proposed approach will make use of devices that allow the study of biological phenomena at the micro scale with remarkable precision, microfloppies, in combination with systems that drive the behaviour of such platforms towards desired results with optimum performance, control systems. Validity and interpretation of results will be done in collaboration with experts in cardiovascular research. Literature Review: The core area of study in this project is within the frame of Control Systems theory, whose aim is to find the set of required actions for a system, to obtain a desired behaviour, in the best possible way. Control System theory has been widey applied in engineering for over a century, having a strong influence in the development of communications and electronics with the introduction of the concept of feedback control [1]. Numerous works on the field have been carried out, including tools for the analysis of the stability of control systems [2-4], design of optimal control strategies [5, 6], self-regulating strategies [7], amongst others. However, fundamentals of classical control theory are mainly based on modelling of dynamical systems through sets of differential equations, and unfortunately, this is not always possible to achieve. Modern control techniques, such as intelligent systems, have overcome this impediment. These can be used for the design, optimization and control of various systems without requiring mathematical models, and typically involves many fields such as neural networks, fuzzy logic, evolutionary strategy, and genetic algorithm, and their hybrids and derivatives [8]. Application of such methodologies to complex nonlinear systems has been very successful, especially in the biomedical field [9]. On the other hand, a key area in cardiovascular research is the study of the process of platelet aggregation at sites of vascular injury. This phenomenon is vital to stop bleeding at those sites, and responsible for subsequent repairs. Nonetheless, an exaggerated response of this process can generate thrombi, which can result in cardiovascular disease states such as ischemic strokes and acute coronary syndromes [10-12]. Extensive research has been carried out on the study of thrombosis and as a result, the chemical and molecular events leading the formation of aggregates of platelets in suspension are well understood [13-15]. However, recent studies from our group have revealed the crucial importance of the blood flow dynamics within the process [16,17]. This breakthrough has opened a new approach to the study of cardiovascular diseases using micro engineered technologies. The proposal of this project is the combination of novel intelligent control systems with advanced microfloppies platforms for the study of platelet aggregation. At the frontier of the first field are the Genetic Fuzzy Systems [18], which have been proven to be effective for dealing with complex nonlinear systems with uncertainties that are otherwise difficult to model, as it is the case for platelet aggregation. These systems will be applied to novel microfloppies platforms to obtain controlled blood flow patterns [17] that will be able to reveal the main parameters driving the process of platelet aggregation. It is expected that as a result of this study, new robust and reliable tools for study and detection of blood disorders will be developed. Research Questions

1) How can we develop models for platelet aggregation to be used in the design of controllers to regulate the formation of thrombus?

2) Can we implement lab-on-a-chip platforms to demonstrate theoretical control systems for the regulation of thrombus formation?

3) How can we optimise the developed control systems so that they are robust to inter-patient variability?

4) What can we learn about blood platelet function using this controlled system?
Rationale: This project aims to provide support in the field of cardiovascular research through the development of technologies that allow a systematic detection of blood disorders. Advancement in the battle against cardiovascular diseases such as coronary heart disease and stroke is of great importance to Australia, since these are the largest cause of death, as well as the most expensive group of diseases for the health care system in the country [19]. The integration of intelligent control systems with precise micro engineered platforms will revolutionize the way detection of blood disorders is carried out, by providing reliable and cost-effective measurements the can be done in remote locations with minimum requirement of specialized personnel. If successful, this project will enable clinics to detect blood disorders through the analysis of the platelet aggregation response of blood samples from different patients. The general community will benefit of such tools by detecting blood disorders quickly, and being able to start treatments at earlier stages of the diseases, therefore, unexpectedly lowering the morbidity rates of these patients. Context in the Current Body of Knowledge: Recently, a study in collaboration with the Australian Centre for Blood Diseases produced a groundbreaking article in the understanding of platelet aggregation dynamics [16]. This work showed that the platelet aggregation response is highly dependent on the blood hydrodynamics –theology, which plays a primary role in the process of platelet aggregation. Nonetheless, the prediction of the response of the platelet aggregation is very complex, as it is influenced by a number of variables. My aim is to use fuzzy logic based tools [20] and knowledge from our previous work [17] to develop a fuzzy-logic-based mathematical model of such response and be able to predict the behaviour of the system upon certain conditions. This will address my research question, “How can a model of the function of the platelet function chip of [17] be formulated such that it would be possible to apply control algorithms such as Fuzzy Logic Control to regulate thrombus formation?” The next challenge will be exploring manipulations to some of the key variables of the process of platelet aggregation, such as shear rate. This includes the design and implementation of novel intelligent feedback control systems [21, 22] applied to our previously implemented platform [17]. Recent techniques for the rapid manipulation of micro-fluids [23, 24] will be considered for the advancement on our current platform. This will address my research questions, “Can a lab-on-a-chip platform be created that will enable the demonstration of the theoretical control system of this research question? Can this control system be used to (for example) stabilise the size of a thrombus? How robust is this control system (for example, when using rarefied platelets, platelets and red blood cells in artificial blood and ultimately whole blood)?” It is anticipated that the performance of a control system to regulate thrombus formation will face several issues: how to deal with the noise in the system, inter-patient variability, and inability to measure all process variables. This part of the project will look at typical control issues such as Robustness, Uncertainty, Stability, Optimal and Observability. The proposed method includes evolutionary strategies to identify optimum parameters in the controller implemented, and techniques to filter out noise from the measured signal for monitoring the thrombus size [25]. This involves the use of detailed mathematical models [26, 27] for the simulation of the controller’s performance. This will address my research questions, “How can we refine the detection, control algorithm and control actuation to be robust to different blood types? How can we adjust these parameters to be selective to different blood platelet types (eg. with mild and severe Von Willebrand disease)?” The ultimate goal of this study is the application of the developed framework to the detection of blood disorders, for which a reliable platform to measure the effectiveness of several blood and drug types to clotting will be realized using a fuzzy-logic-based control system [28]. This platform will be useful for testing newly developed drugs for the stopping of blood clotting, with the potential to becoming a revolutionary standard tool in the assessment of risk to thrombosis. This will address my research question, “What can we learn about blood platelet function using this controlled system?” Outcomes: The outcomes of this research will lead to novel tools for the support in the detection of blood disorders including microfloppies chips, algorithms for the control of the platform and processing of the measurements from the tests, and ultimately knowledge on the dynamics of the process of blood clotting.

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