Guidelines are not mandatory, there are so many guidlines, methods of parameter in analytical validation. Always the experts will introduce the parameters, interpretation and statistical methods of analysis based on new developments, technology,
update the methodology, tehnology to align with others
Hi senthamizh, it is clear that guidlines are not mandatory but very likely to be applied when we want to come to a global harmonization of concepts in method validation and development. One global harmonization on these concepts could make many things easier for the not only the pharmaceutical industry but also for CROs and academia
Hello Dear, As such there are not mandatory to follow guidelines. But at the same time if you are going to submit the method to approving authority or similar authority; then it will be better understood or authenticated. If these thing will be as per guidelines; none of them can arise question about authenticity of the work. Rest is upto you. Wish u all the best
Hi, for example in many validation methods the report of an ULOQ is required but many papers that report the ULOQ show concentrations above this upper limit of quantification and this obvious an contradiction. The introduction of an ULOC (upper limit of calibration) could depict the concentration of the highest calibrator and from this the ULOQ can be determined by the ULOC multiplied with a validated dilution factor.
Guidelines are always the outer frame of respective area and according to user experience, he can take input of the guidelines with sufficient justification for rational of the respective analytical work, like development or validation. To build confidence in the executed method and it should be evidance to the agency, the method is robus and rugeed.
Guidelines and validation are of course useful, there are several reasons to establish a consensus related to methodology among researchers. One of the most important is the possibility to compare the findings between independent labs under an equivalent frame. i.e. in molecular biology, there is the "MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments" by Bustinet al. 2009 that try to standardize the practice/application of RT-qPCR methodology to diminish the existing conditions variability found in the published literature that quite often makes hard to compare results and validate further conclusions.
A general comment on validation vs calibration (beyond any FDA or other practices): As a statistician I would say that the usual semantic attached to validation is that: a similar experiment would give a similar outcome. This is all very vague and calibration is probably a way forward narrowing down the concepts of validation methods as it is linked to quality concepts: given a range of variability for the input, the method is expected to give as outcome this range of variability. Hope this helps!?
I see it differently. To me, calibration is "only" connected with the questions "Do I have a reference method or reference standards", "which", "Is the method response linear (or do I need to calibrate with a more complicated curve". Once I have answered this, I have "the method", and I can try it out and estimate the errors associated with the calculated values.
After that, I need to validate it: Do I get the same accuracy when I repeat it tomorrow or in winter? Does my colleague get the same scatter and do the values agree? What about other labs, other equipment, samples or reagents of different origin etc.
This is how we use the term; getting an idea about the range where the method can be applied is only a part of calibration (and also needs to be validated - I recently had a method that seemed to be linear up to x in the first test, but later was consistently non-linear above 0.3 x...)
I accept the idea of ULOC instead of current ULOQ. I don’t think that the idea is value added, the derived ULOQ can be less than the actual / true ULOQ but this would not affect the accuracy / precision of the method.
We have conducted many validations for FDA submissions (Pharmacokinetics, TK, TD, others), and agree with most of the Olsson et al. article. We set up validation standards in 100% matrix, and dilute in buffer to match the same matrix concentration as the calibration curve (usually 10% or 1% matrix). Further dilutions are performed in the diluted matrix (10% or 1%) to lie within the calibration curve. Therefore ULOQ or ULOC is not useful to us, and we do not usually report this parameter to the FDA. If pressed, we would report it as ULOC, along with LLOQ (lower limit of quantification), the latter a much more important parameter, and is the lowest validation standard or QC that can be validated to 15% within-run and between-run (N=3) accuracy and precision using 3-6 replicate QC samples at low, mid, and high concentrations within the calibration curve, and 2-3 QC concentrations well above the calibration curve, which are diluted to lie within the curve.
Stability and Validation are separate experiments.
Any method which covers Accuracy,linearity,precision,Ruggedness,Specificity,LOQ(limit of quantification) and LOD(limit of detection) is considered as validated no extra excercise is required.
Answering to Frank and I believe in relation also to what followed. I think we do have the same semantic about the term calibration, but I was more saying that whichever response curve you may get and which can have been tuned (changing some parameters in the model/compound etc ...) to fit as much as possible a linear, cubic etc ... it is important to give also a confidence bound around the response curve (variability due repetition / winter condition etc ...) ... Probably part of the validation which is needed in calibration is to define the range of variability for the inputs: this is the "standardisation aspect of it? i.e. this is valid under/within these circumstances ... Sorry if this is maybe repeating what I already commented? (not sure now)