How do I trace an MKM lot number back to a synthesis date?

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

I want a method I can write down and repeat, not a rule of thumb.

I would rather over-engineer this than discover a problem later, within reason.

Concretely, what should I do, and how would I know afterwards whether I did it right?

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

The statistical foundation here is well-established, which is why sampling plans from decades ago are still valid.

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.

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

edited 30 Mar 2025 by Dr_Rosalind_Achebe — added the placebo-arm figures

Worth being precise here: 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.

For a quantitative result like content, the acceptable range determines how many vials you need to test to establish the lot complies.

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.

Lyophilised peptide homogeneity studies show that vial-to-vial variation is usually small but occasionally large, depending on the distribution in the freeze-dryer.

One qualification: testing more vials gives better confidence, but at some point the cost outweighs the benefit.

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

Sampling plans exist precisely because testing everything is expensive, and they define the statistical relationship between sample size and lot-wide inference.

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.

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.

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

Specifically, the failure mode here is publishing a result that applies to the tested vial alone while implying it applies to the entire lot.

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.

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.