OK, I have what is more than likely a dumb question. When is method validation required? So, if one is doing basic research and creates a method based on others, does validation need to be done?
By M. Stone on Tuesday, April 13, 2004 - 05:09 pm:
Well, if you are not in a regulatory environment it is basically a matter of what you - and your coworkers - think is necessary. I think at a minimum it would be advisable to do a few quick experiments such that you can be confident that the results you get from the method are, in fact, accurate. This may involve analyzing spike recovery samples or analysis of a sample with a known quantity of material. From these same experiments you can also get a handle on what type of precision your method is giving you. That's about the best answer I can give without knowing the details of what you're doing.
By tom jupille on Sunday, April 18, 2004 - 10:46 pm:
To expand a bit on the previous post: "validation" is basically proving that a method does what it purports to do. How stringent that proof needs to be depends on what you are doing.
In a "regulated" area (e.g., pharmaceuticals), the level of proof required is very high (for obvious reasons), and the steps involved are established by regulatory agencies. In basic research, validation can be as simple as a few quick recovery experiments, as suggested above. When you publish , your "validation" results should form part of the publication (and, as such, be subject to peer review). If you are a student, your research advisor should be able to point you in the right direction. If you are in industry, talk to others working in the same area to get a feel for what level of validation is expected.
By Anonymous on Friday, June 18, 2004 - 12:07 pm:
How do you go about validating a standard addition method? I have an OVI mehod by GC headspace. Now it needs validated for NDA. It is obviously linear, but how would you define accuracy and LOQ? Would you report precision based on only one level? What would be the best approach?
By rod on Tuesday, June 22, 2004 - 07:27 am:
Here is my opinion. It is 5 cents worth of free advice. Use with caution and discretion at your own risk. IN OTHER WORDS, don't quote me.
You should first generate a protocol of analysis and validation and then follow it exactly. Review the latest USP requirements.
First validate and show that solvent blank standards are linear and reproducible. If this is not so, then it is not likely to be so if the drug is dissolved in the solvent. If you had a water soluble drug then show that the test is linear.... R*R ¡Ý 0.99, 0.995, 0.999 ? and reproducible.... RSD ¡Ü 10%, 5%, 3%, 1% ? for each analyte of interest at the limit concentration. Determine the Limit of Quanitation using solvent blank standards as well. How? that depends on what YOU decide is the criterion. Make certain that it is acceptable to the FDA. How? Ask them.
Next show LOQ in the matrix itself.
Then do standard additions of the analyte in the drug solution, usually done by adding the analyte in the dissolution solvent with or without an internal std via GC-HS.
Show linearity and reproducibility in a drug solution matrix as you demonstrated it in the solvent blank solution.
It sounds like a lot of work but after you validate an analyte in a solvent matrix once you do not have to repeat it, just repeat the validation for each drug matrix you wish to test.
I published a linearity and reproducibility study in Analytical Chemistry in June 1997, p2221-2223 using 18 different solvents from a water/DMAc solution. Please review it for answers to many of your questions.
Accuracy at low levels can be approximated by creating a linear response regression line for larger spikes and then comparing how the lower level responses compare to that regression line.
The regression line slope of the dissolution solvent and the dissolved drug matrix may not be the same, but the line should be linear for both.
If your regression line does not pass through 'close' to zero of the X-axis, you must determine why, and you may not have a good method.
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