Pencil beam scanning is a technique used in the proton therapy. This technique makes use of a thin beam which can irradiate each spot at millimetre precision. It is a very promising technique, especially for more radiation sensitive areas, e.g. lung carcinogenesis, as it can spare more healthy surrounding tissue compared to conventional radiation therapy due to proton’s physical property of the Bragg peak: this is the explosively release of the particles’ energy at a certain point in the beam path; a minimal energy loss is obtained before this peak and no energy is deposited after this Bragg peak. In the PBS, interplay is a concern. The interplay effect is defined as the interference of the moving beam and breathing induced tumour motion. Hence an inhomogeneous dose distribution occurs which differs from the planned dose. In the interplay effect different parameters are involved, which can be divided into beam and patient parameters. The HollandPTC developed a Quality Assurance tool for assessing the interplay effect in lung treatment plans in which a first order sinusoidal function is utilized. However, a sine function is not reflecting the daily variation in target motion and also beam delivery fluctuates over time. By implementing variations into our QA tool, a more realistic interplay assessment could be obtained. A previously done literature search provided us insufficient information regarding beam and patient parameters describing variations over time, hence we did our own research. In this thesis, an investigation was done to analyse the variation in beam and patient specific parameters. For the machine parameters, the variation in Energy Layer Switching Time (ELST) and Beam On Time (BOT) was determined for the VARIAN ProBeam 4.0. Three clinical lung plans which contained in total nine beams, were irradiated on an array of ionization chambers multiple times over multiple days. The output files were analysed regarding the ELST and BOT. For each beam 15 measurements were done, a total of 135 measurements were executed over a period of two weeks. We found variations in ELST between energy layers, but also within an energy layer variations in ELST was observed. The within day and day-to-day variations were comparable. Regarding the BOT, this variable strongly depends on the planned dose. Looking at each individual beam: variations between energies are found; no variations within an energy layer was found. By dividing the measured dose of all output files within an energy layer by the corresponding BOT, the dose rate for each energy was obtained. The dose rate was low at low energies and gradually increased towards the higher energies. Patient parameters were also investigated regarding the tumour motion pattern: the variation in amplitude, period and degree of asymmetry was investigated. In three lung patients, the breathing signal was recorded for 1.5 minutes utilizing the Anzai belt. Five measurements were done: two measurements for two patients and one measurement for one patient. The obtained signals were analysed in terms of amplitude, period and degree of asymmetry for each breathing cycle. Each cycle was fitted into the Lujan’s model, hence a value for each of the three variables were observed. For our group the amplitude variated between 6 and 12mm and the period variated between 2.5 and 4.5 seconds. The degree of asymmetry was most likely to be 1. We found significant interpatient variation, mainly for the amplitude and period. In this analysis, we found that the ELST mainly depends on the step size of the degrader and slit movement. Unfortunately, no hard conclusion regarding the variation within an energy layer could be stated, probably the data transfer systems of the beam line are involved in this variation. Developing a prediction tool for assessing the ELST seems appealing, however more data in different energy ranges should be obtained. Regarding the BOT: this time was more or less dependent on the planned dose. Variations measured for this parameter were caused by inaccuracies of our measurement tool itself. Regarding the patient parameters, significant differences are found between patients’ respiratory signal e.g. the tumour motion strongly depends on tumour characteristics. Hence, we advise to analyse the tumour motion pattern patient specifically. In this thesis report the first insights towards the fluctuations in the relevant parameters were determined. The retrieved information can be used to optimize the interplay QA tool, to get a more realistic interplay assessment in the plans.