# PharmPK Discussion - PK modelling - Kinetica

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• On 4 Dec 1998 at 11:13:58, Azucena Aldaz (aaldaz.-a-.unav.es) sent the message

I am working with Kinetica software from Innaphase. I have created my
own model usin the Designer optino. Now, I want to use my own weighting
scheme. I heve read the manual and it says that it is possible, but I do
not how to do it.
Is anyone working with that program? Could anyone help me to do that?
Thank you very much.

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• On 10 Dec 1998 at 11:23:19, Peter Ryan (113204.1277.aaa.compuserve.com) sent the message

Dear Dr. Aldaz,

Please find below a soft coded method that will resolve your question
regarding the user defined weighting scheme when performing PK Modeling in
Kinetica. A full template containing the structure and embedded model has
been sent to your direct email address so that you may run the example with

Please do not hesitate to contact me if you have any further questions.

Best regards,

Bertrand Roudier, Ph.D.
InnaPhase Corporation

' Two compartment model with user defined error variance.
' The W column contains the computed variance of the residuals.
' The minimised criteria will be the sum of (Yc(i)-Yobs(i))*(Yc(i)-Yobs(i))
/ W(i)
' Bertrand Roudier, December 12 1999

Dim A As Parameter
Dim alpha As Parameter
Dim B As Parameter
Dim beta As Parameter
Dim X As InputColumn
Dim Yc As ComputedColumn
Dim Yobs As ColumnToFit
dim W As ComputedWeightColumn

Sub FitTwoComp()

For i = 1 To X_count
If x_status(i) = 0 And Yobs_status(i) = 0 Then
Yc(i) = A * Exp(-alpha * X(i)) + B * Exp(-beta * X(i))
W(i) = Yc(i) * 10
End If
Next i

Yc_unit = Yobs_unit
W_unit = "(" + Yc_unit + ")^2"

End Sub

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• On 11 Dec 1998 at 10:30:29, "Nick Holford" (n.holford.aaa.auckland.ac.nz) sent the message

> Yc(i) = A * Exp(-alpha * X(i)) + B * Exp(-beta * X(i))
> W(i) = Yc(i) * 10
Huh? Why multiply by 10?

This looks like Iteratively Reweighted Least Squares.
Is W(i) supposed to be proportional to the inverse of the variance of the
residual error in Yc? If so then this model is for Poisson error. A more
common error model is the constant CV (aka proportional) model which would
use W(i)=Yc(i)*Yc(i) if the W(i) are really the inverse of the variances.
What happens if Yc is 0?
Can you estimate parameters of the W model e.g. using Extended Least
Squares?

--
Nick Holford, Dept Neurology,L226
OHSU,3181 SW Sam Jackson Park Rd,Portland,OR 97201,USA
email:n.holford.aaa.auckland.ac.nz tel:+1(503)494-7228 fax:494-7242
http://www.phm.auckland.ac.nz/Staff/NHolford/nholford.htm

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