sample handling on your end absolutely affects it. draw cleanly, ship fast, do not let it sit warm
#test-results 2025-12-17
Wednesday38 messages8 participantstimes are UTC
Highlights from this day
- lisbon_lot — does anyone log the negative results, the boring ones 20:29
- assay_not_purity — anyone had a result they think was a lab error rather than a bad vial underfill is more common than impurity. if you only test purity you are testing the less likely… 20:35
- assay_not_purity — whats the worst result anyone has logged and what happened next a result without a lot number and a purchase date is an anecdote with a pdf attached 20:49
- lyophile_liv — right so if you are testing to settle an argument you will not settle it with n of 1 22:09
- net_peptide — whats the underfill rate people are actually seeing 22:14
the honest limits: hobby chain of custody is weak and any result here should be read with that in mind
underfill is more common than impurity. if you only test purity you are testing the less likely failure, thats one data point
update from 9 months ago: retested the same supplier, result came back better, logged both, happy to be corrected
certificate said 98.6 and the independent came back 99.4, is that a problem
test it again
thats within range
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assay_not_purityunderfill is more common than impurity. if you only test purity you are testing the…
does anyone log the negative results, the boring ones
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anyone had a result they think was a lab error rather than a bad vial
underfill is more common than impurity. if you only test purity you are testing the less likely failure
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selection bias
whats the worst result anyone has logged and what happened next
a result without a lot number and a purchase date is an anecdote with a pdf attached
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how do you post a result so it is actually useful to somebody in a year
thats not great
my vial assayed under label but the purity was fine, which matters more
whats the lot
99.2 against a certificate of 96.8 is fine. the same supplier landing low four times in a row is a question
right so do the results in this channel skew because people test when suspicious
log the boring results too. a channel that only records failures produces a false picture
how do you separate batch variance from supplier variance
log the lot number
nice result
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attach the pdf
unrelated but i have never regretted spending the money on a test. i have regretted not testing twice
is it worth testing if the vial has already been through a warm transit
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how many lots do you need before you can say anything about a supplier
a single sample tells you about a single vial. that is genuinely all it tells you
one bad test does not condemn a supplier. one good test does not clear one. both halves get ignored equally
right so if you are testing to settle an argument you will not settle it with n of 1
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weigh the vial before you reconstitute. it costs nothing and catches the common failure
what interests me is when the gap goes the same direction every time. once is noise, three times is a pattern, n of 1 obviously
assay_not_puritywhats the worst result anyone has logged and what happened next a result without a lot…
if the vial has been through a bad transit you are testing the transit as much as the supplier
whats the underfill rate people are actually seeing
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the widest spread in my data is about 2.6 percentage points across five lots from one supplier
i had a result i am fairly sure was a handling error on my side and i logged it as such
is anyone tracking results over time in a way they would share
a supplier disputing a result is rare here and it has never gone well for the supplier, ill dig out the number
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sorry to jump in assay under label with good purity means you got less of the right thing. that is a fill problem, not a synthesis problem, thats one data point
coming back to this anyone tested the same lot twice at different labs
sorry to jump in the results in this channel skew because people test when they are suspicious. that is selection bias and it is real, i think