Everything you need to know
Purity is the number the market advertises. Content is the number that fails. In the largest published analysis of third-party research peptide reports, vials that passed purity but missed their label amount outnumbered vials that failed purity by more than ten to one.
When research peptide vials fail spec, is it usually purity or content?
Content, by a wide margin. Mendias and Awan analysed 6,285 laboratory reports covering 14 peptides from 203 synthesis companies. Judged against a compounding-style standard, 32.8% of samples met the purity criterion but fell outside an acceptable range for how much peptide was actually in the vial. Only 3.0% did the reverse, meeting the label amount while failing purity. A further 3.3% failed both and 2.4% failed identity outright. Against a stricter manufactured-product standard the same pattern widened: 44.3% passed purity and missed the amount, against 8.4% the other way. The failure mode that dominates this market is quantity, and a purity-only certificate does not measure it.
What exactly did that analysis measure?
It applied two sets of thresholds to reports that had already been produced by a third-party testing service. The compounding-style model asked for 90 to 110% of label claim and purity at or above 98.0%. The manufactured-product model tightened both, to 95 to 105% of label claim and purity at or above 99.5%. Under the first, 58.4% of samples met both criteria, leaving 41.6% failing on purity, amount, or identity. Under the second, 28.9% met both. This is an analysis of someone else's laboratory reports rather than a Prodigy study, and the thresholds are the authors' choice rather than a regulatory limit. What it establishes is the shape of the problem, not a pass rate any individual vendor should be held to.
Why would purity look fine while content fails?
Purity is normally a peak area ratio from reverse-phase HPLC. It compares the target peak to everything else the detector saw. It does not weigh the vial. A vial filled with 3 mg of very clean peptide and labelled 5 mg will report an entirely accurate high purity and still be short 40% of what was paid for. Two other things inflate the gap. A peptide supplied as an acetate or trifluoroacetate salt carries counterion mass that the label may have counted as peptide, and residual moisture adds mass that is not peptide either. Content is a separate quantitative assay run against a characterised reference standard and reported as mg in the vial.
Does this mean purity testing is not worth running?
No. Purity is what flags truncated and deletion sequences, oxidised and deamidated forms, and late-eluting species that should not be there. Identity is what establishes that the compound present is the one named. The argument is not that purity is uninformative, it is that purity is the cheapest question to answer and the easiest to advertise, and on its own it leaves the dominant failure mode unmeasured. Identity, purity and content answer three different questions and a label that states a milligram amount is making a claim that only content can check.
What should I ask for on the certificate?
Ask for purity as a percentage of total peak area with the detection wavelength named, identity by a method appropriate to your use, and content in mg per vial with the reference standard identified and the calculation basis stated. If a lab sells content as an optional add-on, ask whether its reference standard is characterised for content or only for chromatographic purity, because a standard certified only for purity will bias every content result upward. At Prodigy Labs content is included from Tier 1 rather than sold separately. More on how purity and content differ.
Where can I read the underlying analysis?
Mendias CL and Awan TM, "Evaluation of Research Grade Peptides Marketed Directly to Consumers Reveals Extensive Variability in Purity and Measured Abundance", posted to Preprints.org on 24 April 2026, doi:10.20944/preprints202604.1748.v1. It is a preprint, which means it has not completed peer review at the time of writing. The dataset is drawn from one testing service's reports, so it reflects the population of vials whose owners chose to pay for testing rather than a random sample of the market.