Brandon Tupou
Despite global use since its approval in the clinic over 60 years ago, warfarin remains a difficult anticoagulant to dose correctly. Significant interindividual variability has motivated efforts to personalise warfarin treatment that has focussed on using genetic and clinical factors to optimise warfarin dosage. However, the consensus on whether genotype/clinical-guided algorithms improve anticoagulant therapy is debated. Therefore, this project aims to investigate algorithms developed from control theory by adopting a black-box system identification approach. Namely, the classical PID (proportional-integral-derivative) and PIP-LQ (proportional-integral-plus linear quadratic) controllers are investigated. The dataset analysed contains records of 303 patients describing their INR (international normalised ratio) and corresponding dose adjustment over 14 clinical visits. The control systems are simulated in MATLAB & Simulink and are assessed against performance criteria: stability, setpoint tracking, robustness, and safety. Simulation results concluded that the PIP-LQ controller outperformed the simple PID controller against all performance metrics. These findings indicate the potential application of control systems in current warfarin management and other medical regimes. In conclusion, this project demonstrates that genotype-guided treatment is not essential to optimise warfarin treatment and that the PIP-LQ controller is robust to external disturbances and uncertainties.