How do I check that two TFC lots of liraglutide agree on content assay?

Concretely: TFC · liraglutide.

I think I have a problem. I am not yet sure whether it is a real problem or a measurement artefact.

I want to know whether this is recoverable or whether the honest answer is to write it off.

Should I be treating this as a failure or as noise?

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.

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.

What each test answers

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.

I would treat a "complies with" statement without sampling details as a claim rather than as evidence.

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

edited 14 Jul 2026 by loss_on_drying — fixed an arithmetic slip in the third paragraph

It helps to be literal 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.

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.

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 limitation is that you cannot know for certain without testing every vial, and you almost never can afford to do that.

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

Stated carefully, a certificate that reports one test result on one vial extrapolates to claim that all two hundred vials in the lot are identical, which is an assumption worth questioning.

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

A statement that "lot 20260412 complies with specifications" is meaningless without stating which vials from the lot were tested and how many there were.

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

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.

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.

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

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

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.

The honest statement is that unless you have tested multiple vials or have segregation data, you are making an assumption about lot homogeneity that may not hold.

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.

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.