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

• AIDS has become a chronic, potentially life-threatening, clinical condition.
• An MILP model is proposed for planning HIV drug chemotherapy in the long term.
• Real-world treatment strategies can be determined for resource-limited settings.
• The solution framework proposed can be extended to other viral pathologies.

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.