No rule fits all [NCA / SHAM]

posted by mittyri – Russia, 2019-02-14 12:55 (811 d 09:41 ago) – Posting: # 19917
Views: 6,738

Hi Astea,

» Why do algorithms for inter- and extrapolation differ?

Well.. I don't think there's a simple enough solution which fits all situations.
Say we have
Data set
 Time  Conc
0          1
1          60
2          80
3          100
4          130
5          160
6          130
7          100
8          90
10         70
12         40
14         30
18         60
24         2

Something is wrong at the point 18h. Could be a good idea to exclude that point from λz estimation, right?
Now imagine we want to get AUC0-18. Since that point exists, we cannot ignore it.
Lin-up,Log-down method claims AUC0-18 = 1320.139
So far so good.
Other next goal is AUC0-17.9, but taking into account not a robust interpolation of the neighbours but intelligent loglinear regression fit given as λz:
[1] 15.0076

AUC0_17.9 = 1224.5557 :confused:

Are you feeling some PK inconsistency here? Why is AUC18 so differ from the value 0.1h before?
I think this is (only one of many I think!) the reason why the methods differ.

Regarding Cmin as a first point: there could be other situations where to use Cmin from overall dataset (not the dosing period) is not good idea. Ctaupred? OK, but what if λz is not estimable for any reason?
I don't think the default WNL NCA rules will change since it can break a lot of templates and projects. Name it as unhealthy and lazy conservatism ;-)

PS: you can ask Certara to add some new optional NCA rule.

Kind regards,

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