Hypoxia is a consequence of the decrease in the oxygen reaching the tissues of the body. It is a prominent feature of most solid tumors and is known to promote malignant progression, metastatic capacity, resistance to chemotherapy, and leads to poor patient prognosis. When a cell is under hypoxic stress, a cascade of cell signals is initiated through a family of transcription factors named as hypoxia inducible factors (HIFs). During hypoxia, HIF stabilizes and enters the nucleus and binds to the DNA via the hypoxia response element (HRE) and leads to the translation of downstream genes. The decision of adaptation or cell death depends on the extent of hypoxic stress faced by the cells. Proper understanding of hypoxic stress response is critical for understanding the mechanism of tumor cell adaptation to hypoxia and to develop efficient therapeutic interventions. In this paper, we develop a Boolean network model with targeted drug intervention in a cell that mimics persistent hypoxia. This hypoxic pathway is combined with pathways that help the cell adapt to the situation or undergo cell death. It is linked to apoptosis, cell survival, and energy production via the p53/Mdm2, PI3k/Akt/mTOR, and Glycolysis/TCA cycle pathways, respectively. In this model, we have incorporated eight known anticancer drugs that target these pathways. Through simulations, we have identified drug combinations that provided overall benefits to the cell in comparison to the no intervention case. Where applicable, the behavior predicted by this model is in agreement with experimental observations from the published literature.