Software for labs
that quantify.
MRMpipe automates peak integration and review for targeted LC/GC-MS. ProteoCore runs your lab's proteomics pipeline and centralizes data storage.
MRMpipe
Targeted LC/GC-MS, analysed end to end
MRMpipe reads raw vendor files, picks your analyte peaks, whether metabolites, lipids, PFAS or peptides, and returns validated results. Machine learning flags the analytes that need a human eye. It remembers your molecule-specific methods and adapts to your review.
Explore MRMpipeProteoCore
The lab's proteomics pipeline, in one place
DDA, DIA and targeted runs processed automatically, results in one central database, open to the whole lab from anywhere.
Explore ProteoCoreThe problem
Peak review still happens one sample at a time.
Every analyte in every injection is integrated and checked by hand. The decision an analyst makes on one peak does not carry to the next sample, and nothing carries to the next batch. The work is the same every plate, and it depends on who is doing it.
A 900-sample cohort
3 days
reviewed by hand
3 minutes
to process with MRMpipe
The analyst then reviews only the analytes the model is unsure about. Same rules for every sample, every batch.
What changes
Robust scores, faster batches, less training.
- Every analyte is scored the same way, whoever runs the batch.
- Recurring analytes get faster: each molecule's method and your past decisions are remembered.
- Technicians skip months of learning routine review and are productive from the first batch.
Why it works
Every analyte is modelled, scored and remembered.
Manual integration varies between analysts and starts from nothing every batch. MRMpipe fits every peak with the same model, checks it against the rest of the batch, and carries each molecule's settings and your review decisions into the next run.
-
01
Detect and fit
Each peak is located and fitted with its tail, so overlapping compounds are separated and the true area is recovered.
-
02
Check across the batch
Retention time, peak shape and ion ratios are compared across all samples. Drift and outliers are flagged.
-
03
Score, flag, learn
A trained model scores each analyte and flags the uncertain ones for review. Your decisions and per-molecule settings are kept for the next batch.
Have a batch to process, or a workflow to fix?
Send a test batch and we'll return a full MRMpipe report. Or describe the system your lab is missing and we'll scope it with you.
Prefer email? contact@quantivum.com