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Hi,
How to incorporate the weighing factor 1/x or 1/x2 in excel sheet while calculating the concentrations using y=exec.
Harsha.K.N
Associate Scientific Manager,
DMPK-Biology.
Syngene International Ltd.
Biocon Park
Plot # 2&3, Bommasandra IV Phase
Jigani Link Road, Bangalore-560099
Email: Harsha.Narasimhaiah.-a-.syngeneintl.com
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The following message was posted to: PharmPK
Dear Mr.Harsha
Do you want how to decide Weighing factor or how to incorporate?
In LCMSMS softwares,once you choose 1/x or 1/x2, concentration will
come automatically.
There is a standard procedure to analyse goodness of fit to decide
weighing factor, i could not able to understand calculating the
concentrations using y=exec.
o.k
Thank you
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The following message was posted to: PharmPK
Dear Harsha:
I am not clear why you use these weighting factors. I know they are
commonly used, but I do wonder why, and that you (and others) seem not to
take into account the actual error of the assay itself, which is the
reciprocal of the variance with which each measurement was made. You might
look at
Jelliffe RW, Schumitzky A, Van Guilder M, Liu M, Hu L, Maire P, Gomis P,
Barbaut X, and Tahani B: Individualizing Drug Dosage Regimens: Roles of
Population Pharmacokinetic and Dynamic Models, Bayesian Fitting, and
Adaptive Control. Therapeutic Drug Monitoring, 15: 380-393, 1993.
Very best regards,
Roger Jelliffe
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The following message was posted to: PharmPK
Weighting and different models used in assay calibration are applied
to minimize error associated with standard points. Indirectly and
hopefully, weighting and model selection will minimize errors
associated with QC and unknown samples as well. Assay error has at
least two components which may be resolved into accuracy |%Bias| and
precision |%CV|. Total error is the sum of these terms.
Again these terms apply to the assay performance and only by inference
to the unknowns. Most ligand assays will have a measure of precision
for unknowns but obviously no measure of accuracy, and in many LC
assays the sample is measured once- there is no precision measure
associated with the unknown.
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