An Analytical Methodology for Controlling Hepatitis B Virus Infection with Uncertain Patient Parameters

Chronic hepatitis B virus (HBV) infection is a severe healthcare problem from which many people around the world suffer. Although the current treatment methods may succeed in suppressing the viral load of hepatitis B, long-term viral treatment still represents a challenge. In this paper, a novel analytical controller that is based on the system dynamic model was utilized for the purpose of achieving effective treatment of HBV infection. To implement the proposed algorithm, two second-order polynomial functions for infected cells and free viruses were introduced. These functions consist of time as a single independent variable. The six polynomial coefficients were determined by satisfying the initial, mid, and final states for both uninfected cells and free virus while iterating on a single free parameter which the time between the initial and final times to achieve the cost function. Then, the proposed approach method was validated under nominal and off-nominal patient parameters using Monte-Carlo simulation method. The results show that the analytical controller is enormously able to block the new viral infection and to inhibit the viral production in the presence of patient parameters dispersion.