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

Concretely: QST · 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.

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

Reconciling gross mass to label claim

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.

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.

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.

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.

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.

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

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

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 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.

Concretely, 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.

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

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

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

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.

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.

Published data on lot homogeneity from manufacturers who sample multiple vials consistently find variation below the published specifications, suggesting the sampling plans work.

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 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.

To be exact about it, batch testing establishes what can be claimed about the lot as a whole, and the sample size determines how much you can actually claim.

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.

The ICH Q3A and Q3B thresholds for reporting, identification and qualification of impurities are the framework the pharmaceutical industry works to, and they are worth reading even though nothing in the research-grade supply chain is obliged to meet them, because they tell you which numbers a competent analyst would consider worth reporting at all.

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 10 Nov 2024 by fill_volume — expanded the table to cover the lower concentration