What Is Parallel Reaction Monitoring (PRM)?

Parallel reaction monitoring, or PRM, is a mass spectrometry technique that measures specific proteins or metabolites in a biological sample by capturing all the fragment ions from a target molecule at once, rather than watching for them one at a time. It emerged in the early 2010s as a more flexible alternative to selected reaction monitoring (SRM), the method that had dominated targeted quantification for years, and has since become a go-to approach in fields ranging from cancer biomarker research to drug development. What makes PRM distinctive is that it leans on high-resolution instruments to deliver selectivity that older setups struggled to match, while also simplifying the work researchers have to do before they even start collecting data.

How PRM Works in Plain Terms

To understand PRM, it helps to picture what happens inside the mass spectrometer. The instrument first isolates a molecule of interest, then breaks it apart and records the fragments. In older SRM workflows, the instrument could only watch for a handful of pre-chosen fragment ions at a time. If an interfering signal happened to fall on one of those fragments, the measurement suffered, and figuring out which fragments were clean required a round of trial and error before the real experiment could begin.

PRM sidesteps that problem. Instead of pre-selecting a few fragments, it records every fragment ion from the target molecule simultaneously in a single, high-resolution spectrum. Because the mass analyzer can distinguish fragments that differ by tiny fractions of a mass unit, chemical noise that would have overlapped with the signal on older instruments gets separated cleanly. Researchers can then pick the best fragment ions after the data is already collected, rather than guessing beforehand. This eliminates a time-consuming optimization step and makes it much harder for interfering molecules to corrupt the measurement.

The foundational idea behind PRM was described by researchers who proposed swapping the low-resolution third quadrupole of a traditional triple-quadrupole instrument with a high-resolution, accurate-mass analyzer, allowing parallel detection of all target product ions in a single analysis step.¹ That shift from monitoring a few transitions to monitoring all of them in parallel is exactly where the name comes from.

PRM Versus SRM and DIA

SRM had been the reference standard for targeted quantification for a long time, and it still works well. Head-to-head comparisons have shown that PRM and SRM produce comparable linearity, dynamic range, precision, and repeatability when quantifying proteins.² So PRM is not inherently “better” in raw performance terms. Where it pulls ahead is convenience and robustness: you do not need to hand-pick interference-free fragment ions in advance, and the high-resolution data lets you confirm the identity of what you’re measuring more confidently.³

Early work on quadrupole-orbitrap instruments also showed that PRM could achieve a wider dynamic range than SRM when the sample contained a complex background matrix, precisely because high resolution lets you separate your signal from co-eluting junk.¹ That advantage matters most when you’re looking for a needle-in-a-haystack protein in something as complicated as blood plasma.

A newer approach, data-independent acquisition (DIA), takes a broader net by fragmenting everything in wide mass windows rather than targeting specific molecules. A multi-platform comparison found that while DIA can generate reproducible quantitative data, SRM and PRM workflows showed higher accuracy and precision, especially at low concentrations.⁴ In practice, labs often use DIA for broad discovery and then switch to PRM when they need to nail down exact quantities of a short list of targets.

The Instruments Behind PRM

PRM is most commonly run on quadrupole-orbitrap and quadrupole-time-of-flight (Q-TOF) mass spectrometers. Both pair a quadrupole, which acts as a gatekeeper to select only the molecule of interest, with a high-resolution analyzer that reads out all the resulting fragments. The quadrupole-orbitrap design, benchmarked against SRM on triple-quadrupole instruments, demonstrated similar or better performance in selectivity, dynamic range, and sensitivity for targeted protein quantification in biological samples like urine.⁵ The quadrupole-orbitrap platform in particular was pivotal in establishing PRM’s credibility, largely because its mass accuracy is high enough to resolve signals that would have been indistinguishable on older hardware.

Q-TOF instruments offer their own strengths. Researchers have implemented scheduled PRM assays on Q-TOF systems using software such as Skyline to manage retention-time windows and spectral libraries.⁶ Scheduling matters because the instrument only scans for a given target during the time window when it is expected to arrive at the detector, freeing up cycle time for other targets and improving sensitivity.

One practical limitation worth knowing: on orbitrap-type analyzers, sensitivity depends heavily on how long ions are allowed to accumulate before the spectrum is read. That accumulation time tends to be the bottleneck for cycle time, which in turn determines how many targets you can monitor per run while keeping data quality high.⁷ You can also run PRM on lower-resolution instruments like linear ion traps, though you trade some of the selectivity that makes high-resolution PRM attractive.³

Adding Ion Mobility With prm-PASEF

A significant recent development is prm-PASEF, which stands for parallel reaction monitoring combined with parallel accumulation and serial fragmentation. This approach, developed on Bruker’s timsTOF Pro mass spectrometer, adds ion mobility separation as an extra dimension on top of the usual chromatographic separation and mass analysis. The result is improved proteome coverage in less analysis time, because ions are separated not only by mass and retention time but also by their shape and charge.⁸

In one demonstration of prm-PASEF’s capabilities, researchers achieved absolute quantitation of 125 plasma proteins using isotope-labeled peptide standards, measuring across a broad dynamic range and detecting signals as low as roughly 1 fmol.⁹ Separately, the technique has been scaled to quantify 782 plasma peptides in a single multiplexed assay, using shorter chromatographic gradients than traditional PRM would require.¹⁰ For labs that need to measure hundreds of proteins at once in a clinical-type setting, prm-PASEF is pushing the throughput boundaries of targeted proteomics.

Where PRM Gets Used

PRM started in proteomics, and that remains its primary home. But the applications have expanded considerably. One way to think about the landscape is by the type of biological question being asked.

In cancer biomarker research, PRM-based assays are used to verify candidate proteins that surface in discovery studies. An internal-standard triggered PRM (IS-PRM) assay, for example, was developed to quantify over 5,000 peptides representing more than 1,300 breast cancer biomarker candidates in human plasma. The assay showed a median precision below 8% coefficient of variation, linearity over four orders of magnitude, and sensitivity reaching roughly below 1 fmol. Among 893 quantified proteins, 162 candidate biomarkers were verified in at least one cancer pool and 22 were verified across all three.¹¹ That kind of throughput would have been impractical with older SRM methods, where scaling to thousands of targets was a logistical nightmare.

For rare or difficult-to-measure proteins, PRM has proven valuable as well. Researchers have used it to determine the absolute amount of dystrophin in muscle biopsies, using full-length isotope-labeled dystrophin as an internal standard.¹² Dystrophin is the protein missing or defective in Duchenne muscular dystrophy, and measuring how much of it is present in a patient’s tissue after a gene therapy or exon-skipping treatment is directly clinically relevant. Having a precise, targeted assay for that purpose matters far more than a rough estimate from a Western blot.

Measuring Protein Modifications

One of PRM’s more specialized applications is quantifying post-translational modifications, the chemical changes that happen to proteins after they are made. Phosphorylation, a common modification that acts as an on-off switch for many cellular signaling pathways, is a good example. Researchers have used PRM to determine exact phosphorylation ratios, meaning the fraction of a given protein that carries the modification at a particular site, using isotope-labeled reference peptides. In cell-culture experiments, reproducible phosphorylation ratios were measured with coefficients of variation between roughly 6% and 13%.¹³

This capability extends to preserved tissue samples. PRM has been applied to formalin-fixed, paraffin-embedded (FFPE) tissue, the standard format for archived clinical samples, to quantify phosphorylation ratios in normal brain tissue with good reproducibility. The finding that formalin fixation does not prevent accurate relative quantification of phosphorylation is important because it opens up vast hospital tissue archives for retrospective protein-modification studies.¹⁴

Beyond phosphorylation, PRM workflows using newer fragmentation approaches have quantified other modifications, including succinylation, malonylation, and acetylation, on synthetic peptides with coefficients of variation around 2% to 7%.¹⁵ These modifications are increasingly recognized as important regulators of metabolism and gene expression, and having a reliable way to measure them quantitatively is a prerequisite for understanding what they do biologically.

PRM Beyond Proteins

Although PRM was conceived for proteomics, the same logic works for smaller molecules. In metabolomics, researchers have adapted PRM to quantify metabolites and lipids on the same types of instruments. One group developed a large-scale scheduled PRM method targeting 237 metabolites involved in various metabolic pathways, using a quadrupole-orbitrap system.¹⁶ Others have built PRM workflows for targeted lipidomics on Q-TOF instruments.¹⁷

High-resolution fragment-ion data turns out to be just as useful for resolving metabolite interferences as it is for proteins. Metabolites in biological fluids often share similar masses, and relying on a single fragment for identification is risky. By collecting the full fragment spectrum, PRM gives metabolomics researchers the same post-acquisition flexibility that proteomics labs enjoy. One study highlighted the additional benefit of integrating precursor-level scans (MS1) with PRM fragment data to enable both targeted quantification and dynamic carbon-13 labeling analysis in the same run.¹⁸

Assay Validation and Standardization

A mass spectrometry assay is only useful if other labs can reproduce the results and regulatory bodies trust the data. The U.S. National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) has established tiered guidelines for characterizing targeted mass spectrometry assays. Tier 1 represents fully validated clinical-grade assays. Tier 2 assays are considered “fit for purpose,” meaning they have been shown to have sufficient precision, stability, and reproducibility for research applications like biomarker verification, even if they have not cleared every bar required for clinical diagnostics.

PRM-based assays have been evaluated against these guidelines in multiple contexts. Multiplexed assays for glycosite-containing peptides in serum were characterized using CPTAC performance criteria to facilitate broader adoption.¹⁹ A study targeting 23 putative ovarian cancer biomarkers in serum explicitly followed nationally recognized consensus guidelines for Tier 2 assay validation.²⁰ And a large effort characterizing 53 multiplexed targeted assays for cancer cell lines demonstrated fit-for-purpose Tier 2 performance with sufficient precision, stability, and reproducibility for preclinical research.²¹

This standardization work matters because the path from a research discovery to a clinical test is littered with assays that couldn’t be reproduced outside the originating lab. Having a recognized framework for what “good enough for verification” looks like gives the proteomics community common benchmarks and helps reviewers, funders, and pharmaceutical companies evaluate whether a PRM dataset should be trusted.

Software and Data Processing

PRM generates rich, high-resolution spectra that need to be processed efficiently. The dominant software tool in the field is Skyline, an open-source program that handles everything from method design (choosing target peptides, setting retention-time schedules) to data extraction and visualization. Skyline supports PRM natively, and researchers routinely use it to import spectral libraries, set up scheduled PRM assays based on retention times from prior runs, and extract fragment-ion chromatograms for quantification.²²

Auxiliary tools have also been developed to plug into Skyline or complement it. One example is an R-based program for fitting log-normal curves to PRM chromatographic peaks, which helps improve peak integration accuracy when peaks are not perfectly symmetric.²³ The fact that Skyline is free and community-supported has been a significant factor in PRM’s adoption. Labs that might balk at the cost of another proprietary software license can set up a PRM workflow with freely available tools, which lowers the barrier to entry considerably.

The Role of Isotope-Labeled Standards

When absolute quantification is the goal, meaning you want to know the actual amount of a protein in a sample, not just whether it went up or down, PRM assays typically rely on spiking in isotope-labeled synthetic peptides that are chemically identical to the target except for a small mass shift. The labeled peptide behaves the same way during sample processing and analysis, so comparing its signal to the endogenous peptide’s signal corrects for losses and instrument variability. This strategy is common across targeted mass spectrometry, but PRM’s full-spectrum acquisition makes the comparison more robust because you can check the ratio across multiple fragment ions simultaneously, catching problems that might go unnoticed with SRM’s limited fragment view.

Choosing the right reference peptides is itself an art. Ideal peptides are unique to the target protein, stable during sample preparation, and produce clean, intense fragment spectra. Poor choices, such as peptides that are prone to chemical modification or that co-elute with interferences, can undermine the whole assay. Standardized protocols now exist that walk researchers through the selection criteria and provide guidance on how to validate that a given surrogate peptide faithfully represents its parent protein.

What PRM Cannot Do Easily

PRM is a targeted method, which means you have to decide what you’re looking for before you start. It is not a discovery tool. If you have no idea which proteins might be changing in your experiment, you need an untargeted or data-independent approach first. PRM enters the picture once you have a list of candidates and want to measure them precisely.

Multiplexing, while increasingly impressive, still has practical ceilings. The more targets you add to a single run, the less time the instrument spends accumulating ions for each one, and sensitivity drops. Scheduling helps by concentrating measurements into the windows when each target elutes, but at some point, running hundreds of targets in a short gradient pushes the instrument’s duty cycle to its limits. The IS-PRM and prm-PASEF innovations described earlier represent engineering efforts to push that ceiling higher, but the fundamental tradeoff between number of targets and sensitivity per target has not been eliminated.

Cost is another barrier. Quadrupole-orbitrap and Q-TOF instruments carry price tags that can exceed a million dollars, and synthesizing isotope-labeled standard peptides for a large panel adds significant reagent costs. For labs already equipped with triple-quadrupole instruments, the marginal benefit of switching to PRM has to be weighed against the capital investment. In many routine clinical assays, SRM on a triple quadrupole still gets the job done at lower cost and with well-established regulatory precedent. PRM’s advantages are most decisive when the sample is complex, when interferences are unpredictable, or when the target list is expected to evolve as a project matures, since adding a new target to a PRM method does not require the same re-optimization that SRM demands.