Why do two lots from the same vendor differ by nine per cent on content?

I have both a purity figure and a content figure, which is why the discrepancy is visible.

An unexpected observation, and I would like a differential rather than reassurance.

The conditions were within what I understood to be the acceptable range, which is why I am asking.

What is the differential here, and which test discriminates between the options?

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.

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.

Put another way, if the lot was manufactured in multiple batches, testing vials from each batch separately establishes whether batch-to-batch variation is acceptable.

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.

Specifically, two vials tested from a lot of ten is very different from two vials tested from a lot of ten thousand, and most certificates do not state the lot size.

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.

Published segregation failures show that even modern automated processes sometimes produce lots with measurable vial-to-vial variation.

Sampling plans for pharmaceutical manufacturing are defined in ISO 2859 and ANSI Z1.4, and they are based on statistical sampling theory.

If testing multiple vials, state how many you tested and why you chose those vials.

Most suppliers test one vial per lot and report the result as lot homogeneity, which is sampling one item from one lot and extrapolating wildly.

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.

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 practical summary: a lot number without a sampling statement is a lot number without meaning.

edited 25 Jan 2025 by plate_count_9k — updated for the 2026 guidance change

The practical consequence is that spot-testing one vial from a new supplier is better than assuming they are all the same.

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.

The caveat is that sampling is a trade-off between cost and confidence, and neither test nor assumption is cost-free.

Assume segregation is possible, and design your sampling to catch it if it exists.

edited 8 Apr 2025 by Dr_Bram_Verhoeven — reworded for clarity after a comment