More usefully, sampling plans exist precisely because testing everything is expensive, and they define the statistical relationship between sample size and lot-wide inference.
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.
What each test answers
| Test | Answers | Does NOT answer |
|---|
| RP-HPLC, area % | What fraction of detected material is the target | How much target is present |
| Quantified content | Milligrams of peptide per vial | What the impurities are |
| ESI-MS identity | Whether the molecular weight matches | Purity, or isomeric substitution |
| Peptide mapping | Sequence, localised to a fragment | Quantity |
| Karl Fischer | Water content of the solid | Solvent content |
| LAL endotoxin | Pyrogen load in EU/mg | Sterility |
| Sterility test | Growth in defined media over 14 days | Endotoxin, or bioburden count |
Put another way, a statement that "lot 20260412 complies with specifications" is meaningless without stating which vials from the lot were tested and how many there were.
Published data on lot homogeneity from manufacturers who sample multiple vials consistently find variation below the published specifications, suggesting the sampling plans work.
One qualification: testing more vials gives better confidence, but at some point the cost outweighs the benefit.
Assume segregation is possible, and design your sampling to catch it if it exists.
For what it is worth, my own result was within half a per cent of this. – tandem_gradient 3 months ago Any reason this would differ for a longer peptide? – n_takahashi 2 months ago add a comment