Cancer is one of the leading causes of death around the world and the number of patients is expected to increase in the next years. Most of the cancer patients are treated with radiotherapy for at least a part of their treatment. The success of a radiation therapy treatment lies on its correct planning and the accurate prediction of dose distribution in the patient. These dose distributions are generated using treatment planning systems. Analytical algorithms are commonly used despite more accurate results can be achieved using Monte Carlo based algorithms due to the long calculation times required by them. In 2013 a new Monte Carlo based algorithm, PRIMO, was developed. In this program, based on PENELOPE, several variance reduction techniques have been included in order to speed up the calculations as well as a graphical user interface has been designed to make it user friendly. This work will help to validate the simulation code PRIMO. The validation of a treatment planning algorithm involves many different tests, among them, a basic validation of computed doses compared to measurements in water, as well as the verification of its dosimetric accuracy in complex situations. The aim of this work is to investigate the performance of the PRIMO code, in particular to study its dosimetric accuracy in complex situations such as the presence of materials different than water (lung and bone) and when computing the dose within the first millimeters of the patient. This aim was translated into a set of computational experiments performed on simple geometrical phantoms as well as on computerized tomography images. Results showed that the algorithm allows to obtain accurate results in water phantoms, as well as in regions susceptible to errors like the build up region and regions with material heterogeneities.