Targeted mass spectrometry (tMSn) traditionally is employed at the end of the biomarker discovery pipeline for small numbers of diagnostic compounds. Although tMSn produces the best quantitative data, it has had limited applicability to upstream experiments due to its low throughput.We describe a novel high-speed hybrid nominal mass platform designed for tMSn that has ~10x higher throughput for targeted peptide quantitation than triple quadrupole (QQQ) platforms.The increased performance is due to a combination of hardware/instrument control developments coupled with a real-time AdaptiveRT algorithm that adjusts for retention time shifts, allowing narrower acquisition windows. We also present a Skyline-based software plugin that streamlines instrument method creation.These advances enable large-scale tMSn with applications to translational and even discovery proteomics. Parallel ion management is used to achieve high duty cycles for ion injection and analysis, maximizing sensitivity and acquisition rates. A new long-life detector maintains stable gain while achieving single-ion detection limits. The instrument acquires nominal resolution mass spectrometry data at a rate of 65-100 Hz for peptide analysis, depending on the choice of acquisition parameters. The Skyline plugin filters transition data according to metrics like area and signal-to-background, and filters precursors by a minimum number of qualifying transitions. Precursors are scheduled for analysis with a load-balancing technique that chooses the best peptides per protein and ensures a minimum points-per-peak. The AdaptiveRT algorithm estimates retention time shifts and updates acquisitions using cross correlation-based comparisons of real-time with reference data. Large scale discovery experiments are now capable of probing the depths of the proteome in unprecedentedly short times. However, the data independent and data dependent acquisition strategies used to perform those experiments carry tradeoffs in sensitivity and selectivity, as well as instrument complexity and cost. On the other hand, targeted experiments on QQQ are more cost effective and have good sensitivity but have not traditionally been easily scalable to more than a few hundreds of peptides. The new MS platform fills the gap between the capabilities of QQQ and HRAM instruments, with a capacity to target more than 5000 peptides per hour. We present a unified workflow for creating large scale tMSn assays on the new instrument from discovery data. With a new Skyline-based software plugin, precursors are selected that have the best chance of being good quantitative targets. We present experimental use cases that include relative and absolute quantitation, as well as MS2 and MS3 acquisition modes. While the platform"s additional throughput can be used to extend the number of targeted compounds, we show that the gains can be used to shorten the gradients used with smaller numbers of targets.