Optimal medication in HIV seropositive patient treatment using fuzzy cost function

This work concerns the optimization of medication doses using fuzzy relations to represent the compromise between the side-effects and therapeutic effects in the clinical treatment of HIV (human immunodeficiency virus) seropositive patients. The optimization process is carried out using a mathematical model which relates immunological variables such as the number of CD4+T helper cells (immune cells) and the viral load. The control variables used in the optimization process are the doses of reverse transcriptase inhibitor and protease inhibitor. The cost function uses fuzzy logic rules because clinical states are well expressed by linguistic variables by the medical staff. The results are illustrated with a model fitted to the actual data clinical data of an HIV seropositive patient.