If improvements are to be made in tuberculosis (TB) treatment, an increased understanding of disease in the lung is needed. Studies have shown that bacteria in a less metabolically active state, which is associated with the presence of lipid bodies, are less susceptible to antibiotics, and recent results have highlighted the disparity in concentration of different compounds into lesions. Treatment success therefore depends critically on the responses of the individual bacteria that constitute the infection. We propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the level of cells, linking individual cell behaviour with the macroscopic behaviour of cell organisation and the microenvironment. The individual cells (bacteria, macrophages and T cells) are modelled using a cellular automaton (CA) approach and we have incorporated the evolution of oxygen and chemokine dynamics within this hybrid model in order to study the effects of the microenvironment in TB therapies. We allow bacteria to switch states depending on oxygen concentration, which affects how they respond to treatment. Using this multiscale model, we investigate the role of bacterial cell state and of initial bacterial location on treatment outcome. We demonstrate that when bacteria are located further away from blood vessel sources, and when the immune response is unable to contain the less metabolically active bacteria near the start of the simulations, a less favourable outcome is likely.