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Basic calculations with internal standards
Posted: Wed Oct 21, 2009 11:38 pm
by keefhalek
Hello,
I'm under the gun here. Any help would be greatly appreciated.
I have been asked to work on an LC/MS project that employs the use of an internal standard. I've only ever worked with external standards and I need to find a good source for beginners and noobs. Does anyone know (or care to explain) the basic calculations for internal standard ratios and how they can be used to determine concentrations of my analyte?
Thanks!
Posted: Thu Oct 22, 2009 2:18 am
by Don_Hilton
You put a constant quantity of internal standard in each sample. You then take the ratio of the area of the analyte to the area of the internal standard to give you a normalized value for the analyte response. You can create a regression for this ratio, just like you can for an external standard.
If your problem is how to make and use the calibration in specific instrument software, identify the software and someone using that software maybe able to help you out with specifics.
Posted: Thu Oct 22, 2009 12:12 pm
by tangaloomaflyer
You can use the same calculations that you would use with an external calibration, just substitute response for response ratio (analyte response/internal standard response), and substitute concentration for concentration ratio (analyte conc./internal std. conc.).
If using linear regression, with external calibration you would find the line of best fit to your calibration data and the line would be in the form
mx + c = y
where m is the response factor, x is concentration, c is a constant (represents baseline response) and y = response
with internal standard the equation is
RRF(conc ratio) +c = response ratio
where RRF = relative response factor
However as baseline response does not affect the ratio of analyte/I.S. responses we can do away with the constant
RRF(conc ratio) = response ratio
expanding and rearranging to solve for concentration ratio:
RRF(analyte conc/IS conc.) = analyte response/I.S. response
Analyte conc = (analyte response * IS conc.) / (IS response *RRF)
With linear regression RF and c are found using linear regression and requires multiple data points to fit to.
With internal standard RRF can be calculated easily from the equation above. It can be found from one datapoint (i.e. you can do a single point calibration - just find the response ratio of a known conc. of analyte and int. std.) or it can be the average of multiple points in a calibration.
With linear regression the r2 coefficient is a measure of good fit. With relative response factors the percent deviation from the mean is a measure of fit. If using a single point calibration you may wish to veify the calibration by measuring the deviation of the single-point RRF from the multipoint average RRFs
Posted: Thu Oct 22, 2009 3:01 pm
by jclark
A couple of good articles to read: Wikipedia article on "internal standard" is very brief, but a good introduction; Journal of Chemical Education had a brief article, February 1999, vol. 76, No. 2, p. 252, by J.Magee and A. Herd. It uses a specific example from chromatography, with tabulated data that you can easily follow.
jc
Posted: Mon Oct 26, 2009 9:51 pm
by Tommy Krak
Greetings All,
If I may, allow me to suggest a book which I believe that no mass spec lab should be without. This particular book does go through a lot of the basics, though who could not use a little re-fresher in the basics. The book has a lot of references which will only help to detail what has been described in the book. The book has a fair bit on internal standards (volumetric and surrogate).
The title of the book is "Trace Quantitative Analysis by Mass Spectrometry", Authored by R.K. Boyd, C. Basic and R.A. Bethem, ISBN 978-0-470-05771-1
Good luck with using internal standards.
Tom
Posted: Tue Nov 03, 2009 4:42 pm
by chris.singleton
I'm going to second the recommendation by Tommy, Trace Quantitative Analysis by Mass Spectrometry is an excellent book. Almost all the questions I've had about standards (internal, external, standard addition) are contained in that book, and it's well referenced should you need to know more about using standards. Cheers,
Chris Singleton
DMPK
BiogenIdec