Raman spectroscopy can provide the biomolecular fingerprint of a cell in a label-free manner. Although a variety of clinical and biomedical applications have been demonstrated, the method remains largely a niche technology. The two main problems are the complexity of data acquisition and the complexity of data analysis. Generally, Raman measurements are performed manually and require a substantial amount of time. This, on the other hand, frequently results in a low number of samples and hence with questionable statistical evaluation. Here, we propose an automated high content screening Raman spectroscopy (HCS-RS) platform, which can perform a series of experiments without human interaction, significantly increasing the number of measured samples and making the measurement more reliable. The automated image processing of bright field images in combination with automatic spectral acquisition of the molecular fingerprint of cells exposed to different physiological conditions enables label-free high content screening applications. The performance of the developed HCS-RS platform is demonstrated by investigating the effect of panitumumab on SW48 and SW480 colorectal cancer cells with wild-type and mutated K-RAS, respectively, in a series of concentrations. Our result indicates that the increased content of panitumumab prohibits the activation of the MAP kinase of the colorectal cancer cells with wild-type K-RAS strongly, whereas there is no significant effect on the K-RAS mutated cells. Moreover, the relative amount of the panitumumab content present in the cells is determined from the Raman spectral information, which could be beneficial for personalized patient treatment.