High throughput screening holds a key role in current drug discovery research, but its impact is limited by the presence of many false positive compounds, making further pharmacological development of bioactive compounds slower and more expensive. In this study we introduced Minimal Variance Sampling Analysis, a novel approach inspired by data valuation methods to simultaneously prioritize true positive compounds and detect assay interferents in HTS data.