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Modelling a change in absorption rate?


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#1 mjons

mjons

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Posted 23 March 2021 - 04:27 PM

Hi,

I am trying to build a PK-model for an extended release formulation by combining a release model based on biorelevant dissolution testing and a PK model on an immediate release formulation.

 

-I was able to achieve a good fit for in-vitro release data and IR PK data individually

 

-Trying to combine in vitro release data with an IR PK model results in a decent curve shape and a good fit for initial plasma levels of the ER formulation, however later plasma levels are over-predicted. My interpretation is that colonic absorption is slower than absorption from the small intestines, resulting in this discrepancy.

 

-I would like to explore if the model could be improved by using different absorption characteristics (Ka) for the small intestines and the colon.

 

=>Is there a way to model a change of absorption constant (Ka) at a specific time point (or more preferably having this time point as a fitted parameter)?

 

Best regards,

/Martin



#2 kniefort

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Posted 23 March 2021 - 06:01 PM

Hi Martin,

 

This can be achieved through the “sequence” statement combined with the “sleep” statement, see the codes for an example:

 

stparm(Ka_bChangePt = tvKa_bChangePt * exp(nKa_bChangePt)) # absorption rate before

stparm(Ka_aChangePt = tvKa_aChangePt * exp(nKa_aChangePt)) # absorption rate after

stparm(TimePt_KaChange = tvTimePt_KaChange * exp(nTimePt_KaChange)) # time point where Ka changes its value

     

      # absorption rate

      double(Ka)

      sequence{

            Ka = Ka_bChangePt

              sleep(TimePt_KaChange)

            Ka = Ka_aChangePt

            }    

      



#3 mjons

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Posted 23 March 2021 - 06:27 PM

Thanks a lot!

I did some own investigating and found another solution without the sequence statement in the forum which was more intuitive to me. (I am currently investigating saturable colonic absorption, which seems to fit better with the data):

 

Ka = t < Tgit? Ka1: Kamax*Agut/(Agut50+Agut)

 

where

 

Tgit is GI transit time to colon;

Ka1 is the initial, "small intestine" Ka (from IR data);

Kamax and Agut50 are saturation model parameters (for the colonic Ka);

Agut is the amount dissolved available for absorption (from the dissolution model)

 

Tgit, Kamax and Agut50 could then be fitted from the ER PK data...






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