Combine operations research with molecular biology to stretch pharmacogenomics and personalized medicine—A case study on HIV/AIDS

The dramatic reduction in morbidity and mortality associated with the use of highly active antiretroviral therapy has created new challenges for clinicians: AIDS has become a chronic, potentially life-threatening, condition in many clinical instances. In this paper, a novel system engineering approach based on mixed-integer linear programming (MILP) is presented to support HIV/AIDS clinicians when formulating real-world therapeutic plans for heavily treatment-experienced patients under variable settings. Our results suggest that, while current practices (standard protocols and/or subjective recommendations based on the clinician's experience) can generally provide satisfactory management of drug resistance in the short-term, optimization-based therapy planning has a far greater potential to achieve this goal over expanded time horizons thereby changing paradigms and rethinking best practices in the HIV/AIDS clinical arena. Moreover, the ability of this methodology to address other viral pathologies (e.g., hepatitis B and C virus) can make this work appeal to a broader audience.