In this study, we systematically evaluate sample preparation strategies, data acquisition modes and data-analysis approaches for both labeled and label-free proteomics, with the explicit goal of maximizing throughput and quantitative depth using Orbitrap-based instruments operating below 50Hz scan rates and without reliance on automation. Our central objective is to define realistic, accessible proteomics workflows that can be implemented within standard cell and molecular biology laboratories, enabling high-throughput deep and dynamic proteome measurements akin to cell screening platforms. Specifically, we first assess high-throughput sample preparation strategies compatible with 96-well cell culture formats, comparing in-solution (adapted from Simplit17 i.e. Simplit2), filter-based (STrap18), and on bead aggregation (SP319) based enzymatic digestion. Next we benchmarked TMT-based approaches (MS2,SPS-MS3 and real time search assisted SPS-MS3) and DIA appraoches on three species peptide mix. Similar benchmarking of dynamic SILAC-DIA and SILAC-TMT can be found in associated submissions.