This is my second independent submission on material from the same supplier.
I have the document in front of me and I can read the numbers. What I cannot do is interpret them.
I am reasonably comfortable with statistics and completely uncomfortable with chromatography, or vice versa.
What does this actually establish, and what does it not?
The underlying point is that batch testing establishes what can be claimed about the lot as a whole, and the sample size determines how much you can actually claim.
Stratified sampling — testing one vial from the top, one from the middle, and one from the bottom of a shipment — is cheap insurance against segregation.
| Component | Typical share | Counted in purity? | Counted in content? |
|---|---|---|---|
| Target peptide | 88–94 % | Yes, as main peak | Yes |
| Related impurities | 1–3 % | Yes, as other peaks | No |
| Counter-ion (TFA or acetate) | 2–8 % | No | No |
| Residual water | 2–6 % | No | No |
| Bulking agent, if present | 0–40 % | No | No |
Published segregation failures show that even modern automated processes sometimes produce lots with measurable vial-to-vial variation.
Lyophilised peptide homogeneity studies show that vial-to-vial variation is usually small but occasionally large, depending on the distribution in the freeze-dryer.
The caveat is that sampling is a trade-off between cost and confidence, and neither test nor assumption is cost-free.
The practical summary: a lot number without a sampling statement is a lot number without meaning.
edited 6 Jan 2025 by j_wierzbicki — added the method parameters
Aggregated, published test results and vendor ratings built from submitted batches. Methodology stated, dataset browsable, no listing fees.
Browse resultsMost suppliers test one vial per lot and report the result as lot homogeneity, which is sampling one item from one lot and extrapolating wildly.
Acceptance Sampling by Attributes defines the number of samples you need from a lot to claim a specified quality level at a specified risk — it is in ANSI standard Z1.4.
Testing a vial that has been open in the lab for three months is testing aged material, not the fresh lot, and the result should be explicitly noted as a retest.
Worth noting that thermal excursions during shipping affect different vials differently, so the lot may not be homogeneous even if it left the factory that way.
If testing multiple vials, state how many you tested and why you chose those vials.
Start from the question: how many vials from this lot do I need to test to claim that the lot meets specification, and the answer depends on both the lot size and the acceptable risk.
If the entire lot failed qualification, a retest on a different vial is sometimes done, but reporting a retest result under the same lot number is misleading.
In practice, under AQL sampling plans, testing two vials from a fifty-vial lot gives you an operating characteristic curve that tells you what risks you are accepting.
Published data on lot homogeneity from manufacturers who sample multiple vials consistently find variation below the published specifications, suggesting the sampling plans work.
Assume segregation is possible, and design your sampling to catch it if it exists.
Sampling plans exist precisely because testing everything is expensive, and they define the statistical relationship between sample size and lot-wide inference.
If you have reason to suspect inhomogeneity — different appearance in different vials, or a long or warm shipment — testing more vials is the diagnostic move.
I would treat a "complies with" statement without sampling details as a claim rather than as evidence.
If you only pay for one test, pay for quantified content. Purity is the number everyone quotes and content is the number that changes what you do.
Put another way, the single most misleading statement on a research-grade certificate is a lot number with no statement of how many vials from that lot were tested.
The sample size determination requires choosing a confidence level and an acceptable error rate, and the smaller the error rate you want, the larger your sample must be.
Sampling plans for pharmaceutical manufacturing are defined in ISO 2859 and ANSI Z1.4, and they are based on statistical sampling theory.
The limitation is that you cannot know for certain without testing every vial, and you almost never can afford to do that.
In practice: ask for the chromatogram, check the method section, check the lot number against the vial, and set your accept threshold before you see the result rather than after.
edited 9 Dec 2024 by tobias_maartens — corrected a unit error in the worked example
Ask PeptideStack is a static archive. Posting is closed, but the norms are worth stating: answer the question that was asked, show your working, cite the trial or the certificate, and say plainly where the evidence runs out.