## multiple units, lag-times [General Sta­tis­tics]

Hi Relaxation,

❝ Although I am lost regarding most of the mathematical discussion,…

You are not alone.

❝ … ASA seems to misbehave - and this information catched my exe.

❝ ❝ 100 mg ASA (actually 5 × 20 mg tablets).

I have to correct myself: 500 mg ASA (5 × 100 mg tablets; reference Bayer’s Aspirin® 100 N). Don’t know why such a high dose was chosen (sponsor’s wish ); we had another analytical method sensitive enough for 100 mg as well. It is well known that at ~200 mg we are deep in saturation…

❝ To be very brief, from my experience, a study with multiple tablets under fasted conditions always could/might (will) result in an increase in variability in particular in Cmax.

❝ To visualize, imagine all tablets reach the stomach immediately, but every tablet has an individual chance to be emtyied into the intestine.

❝ So we might see subjects with one single peak (5 tablets at once) or subjects with 5 individual peaks (blurred together) and anything in between. These subjects will then show artificially low Cmax values that will not correlate at all.

You are absolutely right in general. Below simulations (n=24) with a lag-time of 1±1 h. Lag-times simulated with a truncated normal distribution [0, 2]. V, ka, CL simulated with a lognormal. CVintra 12%, CVinter 21%, GMR 100%.

Single dose of 500 mg:

AUC  GMR (90% CI):  97.59% (74.93% – 127.11%) Cmax GMR (90% CI):  97.60% (74.92% – 127.15%)

Single dose of five units à 100 mg:

AUC  GMR (90% CI):  98.96% (87.28% – 112.22%) Cmax GMR (90% CI): 100.81% (70.93% – 143.26%)

As you rightly assumed, the intra-subject variability of Cmax substantially increases (whereas the one of AUC decreases).

❝ Looking at the individual profiles posted above I think I see at least a few "irregular profiles" even including late tmax at about 2 hours.

See a more telling plot above. Latest tmax at 1:40. But: In 4/24 subjects tmax was >50 minutes (R) and in 6/24 (T). Too stupid to simulate that.

❝ I am not saying that this is a/the solution, but this may be one aspect helping to understand, why the correlation for ASA is lousy in comparison with other APIs and drug products.

Maybe. Maybe not. There are many examples very the variability in Cmax is much higher than the one of AUC and the correlation is pretty good. Here both behave nicely (CVintra 18.3% and 11.8%). Still fail to understand why I saw such a low correlation in my study (and Astea a much higher one in hers).

Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz

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