Would you re-test cagrilintide after six weeks at room temperature, or accept the original certificate?

Details up front: cagrilintide · six weeks · room temperature.

This is a planning question. I know what my options are; I do not know how to weigh them.

What I want is the minimum viable version, which I suspect is smaller than what I would design.

How do I make this decision on evidence rather than on feel?

six weeks is 42 days, and at room temperature the ten-degree rule of thumb makes that roughly 141 refrigerated days of equivalent exposure. Room temperature is not a number, so take the pharmacopoeial 20–25 °C and its 22.5 °C midpoint: 17.5 kelvin above the 5 °C middle of a 2–8 °C refrigerator. The ten-degree rule of thumb — degradation rate roughly doubling per 10 K — puts that at about 3.4 times the refrigerated rate. It is an order-of-magnitude statement about a rate, not a shelf life, and the top of the 20–25 °C band runs about 1.4 times faster than the bottom of it. Compare that against what the certificate covers, which is the material as it left the laboratory on the date of analysis and nothing after it. That is short enough that a re-test is a stability study rather than a safety check — worth doing if you will publish the result, hard to justify if you will only reassure yourself. If you do re-test, send it for content as well as purity; the 42 days will have moved one of them further than the other.

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

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

The part that matters: 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.

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

The part that matters: if a lot has visibly segregated — some vials showing different appearance — then sampling the top and bottom of the shipment is worth doing.

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.

Worth being precise here: the statistical foundation here is well-established, which is why sampling plans from decades ago are still valid.

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

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

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

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

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.

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

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

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.

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

edited 27 Jul 2026 by tobias_maartens — corrected a unit error in the worked example

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

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.

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.

edited 7 Jul 2026 by Dr_Ilse_Vandenberg — added a caveat about sampling

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.

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.

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.

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

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.