This work is focused on the development of new microscopy-based analysis methods with single-entity resolution and high-throughput capabilities from the cellular to the molecular level to study biomembrane-associated interactions. Currently, there is a variety of methods available for obtaining quantitative information on cellular and molecular responses to external stimuli, but many of them lack either high sensitivity or high throughput. Yet, the combination of both aspects is critical for studying the weak but often complex and multivalent interactions at the interface of biological mem-branes. These interactions include binding of pathogens such as some viruses (e.g., influenza A virus, herpes simplex virus, and SARS-CoV-2), transmembrane signaling such as ligand-based oli-gomerization processes, and transduction of mechanical forces acting on cells. The goal of this work was to overcome the shortcomings of current methods by developing and es-tablishing new methods with unprecedented levels of automation, sensitivity, and parallelization. All methods are based on the combination of optical (video) microscopy followed by highly refined data analysis to study single cellular and molecular events, allowing the detection of rare events and the identification and quantification of cellular and molecular populations that would remain hidden in ensemble-averaging approaches. This work comprises four different projects. At the cellular level, two methods have been developed for single-cell segmentation and cell-by-cell readout of fluorescence reporter systems, mainly to study binding and inhibition of binding of viruses to host cells. The method developed in the first pro-ject features a high degree of automation and automatic estimation of sufficient analysis parameters (background threshold, segmentation sensitivity, and fluorescence cutoff) to reduce the manual ef-fort required for the analysis of cell-based infection assays. This method has been used for inhibition potency screening based on the IC50 value of various virus binding inhibitors. With the method used in the second project, the sensitivity of the first method is extended by providing an estimate of the number of fluorescent nanoparticles bound to the cells. The image resolution was chosen to allow many cells to be imaged in parallel. This allowed for the quantification of cell-to-cell heterogeneity of particle binding, at the expense of resolution of the individual fluorescent nanoparticles. To account for this, a new approach was developed and validated by simulations to estimate the number of fluo-rescent nanoparticles below the diffraction limit with an accuracy of about 80 to 100 %. In the third project, an approach for the analysis and refinement of two-dimensional single-particle tracking ex-periments was presented. It focused on the quality assessment of the derived tracks by providing a guide for the selection of an appropriate maximal linking distance. This tracking approach was used in the fourth project to quantify small molecule responses to hydrodynamic shear forces with sub-nm resolution. Here, the combination of TIRF microscopy, microfluidics, and single particle tracking enabled the development of a new single molecule force spectroscopy method with high resolution and parallelization capabilities. This method was validated by quantifying the mechanical response of well-defined PEG linkers and subsequently used to study the energy barriers of dissociation of mul-tivalent biotin-NeutrAvidin complexes under low (~ 1.5 to 12 pN) static forces. In summary, with this work, the repertoire of appropriate methods for high-throughput investigation of the properties and interactions of cells, nanoparticles, and molecules at single resolution is expand-ed. In the future, the methods developed here will be used to screen for additional virus binding inhib-itors, to study the oligomerization of membrane receptors on cells and model membranes, and to quantify the mechanical response of force-bearing proteins and ligand-receptor complexes under low force conditions.