## Fantastic post 👍🏽 [NCA / SHAM]

Hi Nastia,

limited time (bloody bread-and-butter job). Some desultory thoughts about PK

»

Not only that (it’s a side-effect). What are we interested in? Extent of absoption (cleary AUC) and rate of absorption (k

» The distribution type of the function is also questionable (ratio of log-normal - paranormal ?).

Do you know ’Pataphysics? Seriously, László (The Younger) asked me the same question years ago, which I could not answer. Martin helped us out. It doesn’t matter: The sum/difference of two normal distributions will be normal, the same here: It will be log-normal.

»

The jury is out.

»

» order momentum (why to limit ourselves by first order? There could be second or third order as well...).

Not only physics. Statistical distributions have also moments and we can interpret the behavior of drug molecules as a stochastic process. I love moments. I general

»

Not only that. As a rule of thumb at \(\small{MRT}\) ~⅔ of the drug is eliminated. It is very useful comparing PK models with different compartments. The slowest t

More to come.

limited time (bloody bread-and-butter job). Some desultory thoughts about PK

**metrics**(more to come).»

**C**is referred sometimes to be more appropriate in BE studies than C_{max}/AUC_{max}cause it has much lower variability…Not only that (it’s a side-effect). What are we interested in? Extent of absoption (cleary AUC) and rate of absorption (k

_{a}and possibly t_{lag}). k_{a}is not easily accessible in NCA. C_{max}is a*composite*surrogate (because influenced by AUC). Easy to show: Define any PK model and vary ƒ whilst keeping k_{a}and t_{lag}constant. C_{max}will change… C_{max}/AUC is an attempt to deal with that.» The distribution type of the function is also questionable (ratio of log-normal - paranormal ?).

Do you know ’Pataphysics? Seriously, László (The Younger) asked me the same question years ago, which I could not answer. Martin helped us out. It doesn’t matter: The sum/difference of two normal distributions will be normal, the same here: It will be log-normal.

»

**pAUC**(partial AUC, truncated AUC), index of early exposure, as was discussed in the parallel thread could be more sensitive than AUC_{last}(*'pAUC was always more sensitive than C*). The question is what time should be the end time of the calculation? […] The time should be related to clinically relevant pharmacodynamic measure. What are their advantages?_{max}'^{2}The jury is out.

*E.g.*, for biphasic methylphenidate the cut-off time (FDA: 3 h fasting, 4 h fed) is based on PD indeed (at that time ~90% of patients show the maximum effect). Makes sense. The EMA it its eternal wisdom asks to set the cut-off based on PK (a trough between the two parts). Splendid. Some subjects show just a shoulder (see there) and mean curves of the innovator are completely useless.»

**AUMC**(first order momentum, the area under the curve 'Concentration*time-time'). If we'll look at the physics analogy - the first-order momentum for the plain figure is the static momentum which defines the center of mass coordinates, while the second-order momentum is moment of inertia. The definition could be generalised to the n-th» order momentum (why to limit ourselves by first order? There could be second or third order as well...).

Not only physics. Statistical distributions have also moments and we can interpret the behavior of drug molecules as a stochastic process. I love moments. I general

\(S_i=\int x^i\cdot f(x)dx\)

and in PK \(\small{i=0\ldots2}\). Hence,\(S_0=\int x^0\cdot f(x)dx = \int f(x)dx\),

\(S_1=\int x^1\cdot f(x)dx = \int x\cdot f(x)dx\),

\(S_2=\int x^2\cdot f(x)dx\),

»

**MRT**is a most common PK parameters that compels to look at the AUMC. There existed approaches^{4}to use MRT instead of T_{1/2}in order to choose the appropriate washout period.Not only that. As a rule of thumb at \(\small{MRT}\) ~⅔ of the drug is eliminated. It is very useful comparing PK models with different compartments. The slowest t

_{½}might be misleading (see there, slides 24–28). There is a big problem with it. To get a reliable estimate of AUC one has to cover 95% (!) of AUC_{0–∞}(note that I’m not taking about BE but hard-core PK). For AUMC is should be 99%. I’m quoting Les Benet. Don’t blame me.More to come.

—

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

*Dif-tor heh smusma*🖖Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

### Complete thread:

- Fantastic PK parameters and where to find them Astea 2020-06-12 14:22 [NCA / SHAM]
- Fantastic post 👍🏽Helmut 2020-06-12 16:23
- Rattleback Astea 2020-06-13 10:17
- Chatter Helmut 2020-06-13 12:28
- Reinventing the Hula-Hoop Astea 2020-06-16 01:33
- Hula-Hoop references Helmut 2020-06-16 13:07
- Prof. Keller vs. Yamaoka mittyri 2020-06-17 14:28
- SHAM(e) math Astea 2020-06-23 14:41
- SHAM(e) math Helmut 2020-06-23 15:55
- OT: Möbius strip Astea 2020-06-23 21:41
- OT: Möbius strip Helmut 2020-06-24 11:29

- OT: Möbius strip Astea 2020-06-23 21:41

- SHAM(e) math Helmut 2020-06-23 15:55

- SHAM(e) math Astea 2020-06-23 14:41

- Prof. Keller vs. Yamaoka mittyri 2020-06-17 14:28

- Hula-Hoop references Helmut 2020-06-16 13:07

- Reinventing the Hula-Hoop Astea 2020-06-16 01:33

- Chatter Helmut 2020-06-13 12:28

- Rattleback Astea 2020-06-13 10:17
- More stuff Helmut 2020-06-13 15:28
- MRT and Gravity duration mittyri 2020-06-14 22:24
- Fantastic PK parameters and where to find them ElMaestro 2020-06-16 09:46
- Cauchy distribution mittyri 2020-06-16 10:54
- Cauchy distribution Helmut 2020-06-16 13:14
- Cauchy distribution ElMaestro 2020-06-20 10:33
- noncentral normal ratio mittyri 2020-06-20 23:04

- Cauchy distribution mittyri 2020-06-16 10:54

- Fantastic post 👍🏽Helmut 2020-06-12 16:23