Targeted drug delivery is critical in pharmaceutical applications, to ensure that the right quantity of medicine is delivered to the right location. Considering the pulmonary system of the human body, oral inhalation based administration of medicine is a common method adopted in treating many ailments such as Ashtma, COPD and so on. Assessing the regional deposition of (medicinal) particles is therefore of paramount importance, in understanding the transport of the medicine inside the lung, deciding dosage of the medicine and operating conditions of the inhalation device, and estimating possibilities for side effects due to the transport of the medicine internally. This work aims to computationally study (In-Silico) the flow mechanisms and turbulence in different realisitic geometries of human mouth-throat and extra-thoracic region, under different operating conditions of an inhaler, the effect of the flow of the particle dynamics, leading to different regional deposition patterns and fractions, and the effect of other conditions such as gravity. Large Eddy Simulations (LES) are performed to obtain well resolved flow fields. A one way coupling between the flow and particles is assumed. Since the particle dynamics and trajectories are dependent of the flow field, the flow is analyzed initially, leading to an estimation of the potential particle behaviour. Based on the flow analysis, the qualitative and quantitative description of the particle deposition is presented in terms of the regional deposition patterns and the deposition fraction. These results are used to understand the influence of different factors such as geometric differences (person specific), flow rate (device and person specific), gravity, and turbulence. Understanding the influence of these factors in the estimation of particle deposition is instrumental in the study of targeted drug delivery, design of inhaler devices and deciding medication protocols. Further, the well resolved flow analysis helps to better understand the limitations of analytical/typical-path models, and how (and the scenarios when) the assumptions made in those models lead significant deviations in the estimations of particle deposition.