Washout: how long is long enough, and for what purpose — setting out what I have, and where I think it stops being reliable.
A narrow question about washout, deliberately narrow, because the broad version has been asked here four times and produced four long threads and no answer.
One question, stated units, stated method, and what I have already ruled out.
Adding a data point of agreement rather than a data point.
I had read the opposite somewhere and cannot now find where, which tells me something.
The most useful thing anyone has posted about washout in this category was a table of what had been measured and by whom. That is what I would want again.
Post #7 is right about the mechanism and I think understates the practical bit.
A note on scope: what I am saying about washout applies to the case in the first post and I would not extend it further without checking.
Everything in post #7 holds. The case it does not cover is the one I have.
What would change my mind on washout is a second dataset collected by someone with no stake in the first. Until then I hold it loosely and I would rather say so than pretend to more.
A pharmacokinetic model fitted to trial data describes the population studied. Applying it to somebody outside the enrolled range is an extrapolation, and the model will not tell you it is.
If that is already documented somewhere, ignore me and link it.
Half-life: semaglutide ≈ 165–184 hours (about a week). Tirzepatide ≈ 5 days. Liraglutide ≈ 13 hours. The half-life determines how much accumulation happens at steady state and how long it takes to clear after stopping.
It is the kind of thing that is obvious once and never again.
Everything in post #10 holds. The case it does not cover is the one I have.
I read the earlier replies on washout twice before writing this, because I had assumed the opposite and wanted to be sure I was disagreeing with what was said rather than what I expected.
Marking my place. If it changes for me I will come back and say so.
Checked the washout claim against the primary source this morning. It survives, with a narrower scope than the version quoted here. Posting the narrower scope.
The arithmetic in post #12 is right; the assumption feeding it is the part to check.
Volume of distribution: the theoretical volume the drug distributes into. For albumin-binding compounds, volume is reduced compared to drugs that do not bind protein. That is relevant to understanding how much free drug is available.
Answering the question post #14 raises rather than the one it answers.
Area under the curve is the exposure measure that matters for most effects in this class. Peak concentration matters more for tolerability.
The most useful reply I ever got about washout was a request to state my units. It sounds like pedantry and it has saved me twice.
Metabolism for peptide drugs is proteolytic rather than hepatic in the usual sense, which is why the cytochrome interaction questions that dominate small-molecule pharmacology mostly do not apply.
Offering a way to settle washout rather than another opinion about it. Two measurements, taken the same way, a fortnight apart. If the difference is within the noise, the question was not answerable at this precision.
Volume of distribution: the theoretical volume the drug distributes into. For albumin-binding compounds, volume is reduced compared to drugs that do not bind protein. That is relevant to understanding how much free drug is available.
Stating my assumptions rather than smuggling them in.
Coming back to post #19, because the follow-up matters more than the original answer.
Where I have landed on washout, having got it wrong once in public: the direction is clear, the magnitude is not, and anyone quoting a precise magnitude has borrowed it from somewhere that did not measure it.
The confident answers on washout and the well-sourced answers are not the same answers, which is the most useful thing I have learned reading this category.
A pharmacokinetic model fitted to trial data describes the population studied. Applying it to somebody outside the enrolled range is an extrapolation, and the model will not tell you it is.
Worth saying I have only my own numbers here, and n is small.
This follows post #23 rather than contradicting it.
Where two sources give different half-lives, check the study design before deciding either is wrong. Sampling duration, assay sensitivity and population all move the number.
Thank you for taking the time. That was more work than a reply usually is.
This follows post #27 rather than contradicting it.
What I would want before treating washout as settled: the method, the sample, and whether anyone tried to find the opposite result. Two of the three are usually missing.